merge with beta - resolved conflict in pom

This commit is contained in:
Miriam Baglioni 2021-11-15 10:52:16 +01:00
commit 4ec88c718c
273 changed files with 19141 additions and 1931 deletions

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@ -28,7 +28,7 @@ public class HdfsSupport {
* @param configuration Configuration of hadoop env * @param configuration Configuration of hadoop env
*/ */
public static boolean exists(String path, Configuration configuration) { public static boolean exists(String path, Configuration configuration) {
logger.info("Removing path: {}", path); logger.info("Checking existence for path: {}", path);
return rethrowAsRuntimeException( return rethrowAsRuntimeException(
() -> { () -> {
Path f = new Path(path); Path f = new Path(path);

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@ -85,6 +85,13 @@ public class MakeTarArchive implements Serializable {
String p_string = p.toString(); String p_string = p.toString();
if (!p_string.endsWith("_SUCCESS")) { if (!p_string.endsWith("_SUCCESS")) {
String name = p_string.substring(p_string.lastIndexOf("/") + 1); String name = p_string.substring(p_string.lastIndexOf("/") + 1);
if (name.startsWith("part-") & name.length() > 10) {
String tmp = name.substring(0, 10);
if (name.contains(".")) {
tmp += name.substring(name.indexOf("."));
}
name = tmp;
}
TarArchiveEntry entry = new TarArchiveEntry(dir_name + "/" + name); TarArchiveEntry entry = new TarArchiveEntry(dir_name + "/" + name);
entry.setSize(fileStatus.getLen()); entry.setSize(fileStatus.getLen());
current_size += fileStatus.getLen(); current_size += fileStatus.getLen();

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@ -4,19 +4,19 @@ package eu.dnetlib.dhp.utils;
import java.io.*; import java.io.*;
import java.nio.charset.StandardCharsets; import java.nio.charset.StandardCharsets;
import java.security.MessageDigest; import java.security.MessageDigest;
import java.util.List; import java.util.*;
import java.util.Map; import java.util.stream.Collectors;
import java.util.Properties;
import java.util.zip.GZIPInputStream;
import java.util.zip.GZIPOutputStream;
import org.apache.commons.codec.binary.Base64;
import org.apache.commons.codec.binary.Base64OutputStream;
import org.apache.commons.codec.binary.Hex; import org.apache.commons.codec.binary.Hex;
import org.apache.commons.io.IOUtils; import org.apache.commons.io.IOUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path; import org.apache.hadoop.fs.Path;
import org.apache.http.client.methods.CloseableHttpResponse;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;
import org.apache.spark.sql.Dataset; import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.SaveMode; import org.apache.spark.sql.SaveMode;
import org.slf4j.Logger; import org.slf4j.Logger;
@ -26,6 +26,8 @@ import com.fasterxml.jackson.databind.ObjectMapper;
import com.google.common.collect.Maps; import com.google.common.collect.Maps;
import com.jayway.jsonpath.JsonPath; import com.jayway.jsonpath.JsonPath;
import eu.dnetlib.dhp.schema.mdstore.MDStoreWithInfo;
import eu.dnetlib.dhp.schema.oaf.utils.CleaningFunctions;
import net.minidev.json.JSONArray; import net.minidev.json.JSONArray;
import scala.collection.JavaConverters; import scala.collection.JavaConverters;
import scala.collection.Seq; import scala.collection.Seq;
@ -52,10 +54,56 @@ public class DHPUtils {
} }
} }
/**
* Retrieves from the metadata store manager application the list of paths associated with mdstores characterized
* by he given format, layout, interpretation
* @param mdstoreManagerUrl the URL of the mdstore manager service
* @param format the mdstore format
* @param layout the mdstore layout
* @param interpretation the mdstore interpretation
* @param includeEmpty include Empty mdstores
* @return the set of hdfs paths
* @throws IOException in case of HTTP communication issues
*/
public static Set<String> mdstorePaths(final String mdstoreManagerUrl,
final String format,
final String layout,
final String interpretation,
boolean includeEmpty) throws IOException {
final String url = mdstoreManagerUrl + "/mdstores/";
final ObjectMapper objectMapper = new ObjectMapper();
final HttpGet req = new HttpGet(url);
try (final CloseableHttpClient client = HttpClients.createDefault()) {
try (final CloseableHttpResponse response = client.execute(req)) {
final String json = IOUtils.toString(response.getEntity().getContent());
final MDStoreWithInfo[] mdstores = objectMapper.readValue(json, MDStoreWithInfo[].class);
return Arrays
.stream(mdstores)
.filter(md -> md.getFormat().equalsIgnoreCase(format))
.filter(md -> md.getLayout().equalsIgnoreCase(layout))
.filter(md -> md.getInterpretation().equalsIgnoreCase(interpretation))
.filter(md -> StringUtils.isNotBlank(md.getHdfsPath()))
.filter(md -> StringUtils.isNotBlank(md.getCurrentVersion()))
.filter(md -> includeEmpty || md.getSize() > 0)
.map(md -> md.getHdfsPath() + "/" + md.getCurrentVersion() + "/store")
.collect(Collectors.toSet());
}
}
}
public static String generateIdentifier(final String originalId, final String nsPrefix) { public static String generateIdentifier(final String originalId, final String nsPrefix) {
return String.format("%s::%s", nsPrefix, DHPUtils.md5(originalId)); return String.format("%s::%s", nsPrefix, DHPUtils.md5(originalId));
} }
public static String generateUnresolvedIdentifier(final String pid, final String pidType) {
final String cleanedPid = CleaningFunctions.normalizePidValue(pidType, pid);
return String.format("unresolved::%s::%s", cleanedPid, pidType.toLowerCase().trim());
}
public static String getJPathString(final String jsonPath, final String json) { public static String getJPathString(final String jsonPath, final String json) {
try { try {
Object o = JsonPath.read(json, jsonPath); Object o = JsonPath.read(json, jsonPath);

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@ -0,0 +1,49 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
import java.util.Optional;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.SparkSession;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
public class Constants {
public static final String DOI = "doi";
public static final String UPDATE_DATA_INFO_TYPE = "update";
public static final String UPDATE_SUBJECT_FOS_CLASS_ID = "subject:fos";
public static final String UPDATE_CLASS_NAME = "Inferred by OpenAIRE";
public static final String UPDATE_MEASURE_BIP_CLASS_ID = "measure:bip";
public static final String FOS_CLASS_ID = "FOS";
public static final String FOS_CLASS_NAME = "Fields of Science and Technology classification";
public static final String NULL = "NULL";
public static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
private Constants() {
}
public static Boolean isSparkSessionManaged(ArgumentApplicationParser parser) {
return Optional
.ofNullable(parser.get("isSparkSessionManaged"))
.map(Boolean::valueOf)
.orElse(Boolean.TRUE);
}
public static <R> Dataset<R> readPath(
SparkSession spark, String inputPath, Class<R> clazz) {
return spark
.read()
.textFile(inputPath)
.map((MapFunction<String, R>) value -> OBJECT_MAPPER.readValue(value, clazz), Encoders.bean(clazz));
}
}

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@ -0,0 +1,77 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
import java.io.IOException;
import java.io.InputStreamReader;
import java.io.Serializable;
import java.util.Objects;
import java.util.Optional;
import org.apache.commons.io.IOUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.common.collection.GetCSV;
public class GetFOSData implements Serializable {
private static final Logger log = LoggerFactory.getLogger(GetFOSData.class);
public static final char DEFAULT_DELIMITER = '\t';
public static void main(final String[] args) throws Exception {
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
IOUtils
.toString(
Objects
.requireNonNull(
GetFOSData.class
.getResourceAsStream(
"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/get_fos_parameters.json"))));
parser.parseArgument(args);
// the path where the original fos csv file is stored
final String sourcePath = parser.get("sourcePath");
log.info("sourcePath {}", sourcePath);
// the path where to put the file as json
final String outputPath = parser.get("outputPath");
log.info("outputPath {}", outputPath);
final String hdfsNameNode = parser.get("hdfsNameNode");
log.info("hdfsNameNode {}", hdfsNameNode);
final String classForName = parser.get("classForName");
log.info("classForName {}", classForName);
final char delimiter = Optional
.ofNullable(parser.get("delimiter"))
.map(s -> s.charAt(0))
.orElse(DEFAULT_DELIMITER);
log.info("delimiter {}", delimiter);
Configuration conf = new Configuration();
conf.set("fs.defaultFS", hdfsNameNode);
FileSystem fileSystem = FileSystem.get(conf);
new GetFOSData().doRewrite(sourcePath, outputPath, classForName, delimiter, fileSystem);
}
public void doRewrite(String inputPath, String outputFile, String classForName, char delimiter, FileSystem fs)
throws IOException, ClassNotFoundException {
// reads the csv and writes it as its json equivalent
try (InputStreamReader reader = new InputStreamReader(fs.open(new Path(inputPath)))) {
GetCSV.getCsv(fs, reader, outputFile, classForName, delimiter);
}
}
}

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@ -0,0 +1,145 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.*;
import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.UPDATE_CLASS_NAME;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import java.io.Serializable;
import java.util.List;
import java.util.Optional;
import java.util.stream.Collectors;
import org.apache.commons.io.IOUtils;
import org.apache.hadoop.hdfs.client.HdfsUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.SaveMode;
import org.apache.spark.sql.SparkSession;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.BipDeserialize;
import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.BipScore;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.common.HdfsSupport;
import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.oaf.KeyValue;
import eu.dnetlib.dhp.schema.oaf.Measure;
import eu.dnetlib.dhp.schema.oaf.Result;
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
import eu.dnetlib.dhp.utils.DHPUtils;
public class PrepareBipFinder implements Serializable {
private static final Logger log = LoggerFactory.getLogger(PrepareBipFinder.class);
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
public static <I extends Result> void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
.toString(
PrepareBipFinder.class
.getResourceAsStream(
"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/prepare_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
Boolean isSparkSessionManaged = Optional
.ofNullable(parser.get("isSparkSessionManaged"))
.map(Boolean::valueOf)
.orElse(Boolean.TRUE);
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
final String sourcePath = parser.get("sourcePath");
log.info("sourcePath {}: ", sourcePath);
final String outputPath = parser.get("outputPath");
log.info("outputPath {}: ", outputPath);
SparkConf conf = new SparkConf();
runWithSparkSession(
conf,
isSparkSessionManaged,
spark -> {
HdfsSupport.remove(outputPath, spark.sparkContext().hadoopConfiguration());
prepareResults(spark, sourcePath, outputPath);
});
}
private static <I extends Result> void prepareResults(SparkSession spark, String inputPath, String outputPath) {
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
JavaRDD<BipDeserialize> bipDeserializeJavaRDD = sc
.textFile(inputPath)
.map(item -> OBJECT_MAPPER.readValue(item, BipDeserialize.class));
spark
.createDataset(bipDeserializeJavaRDD.flatMap(entry -> entry.keySet().stream().map(key -> {
BipScore bs = new BipScore();
bs.setId(key);
bs.setScoreList(entry.get(key));
return bs;
}).collect(Collectors.toList()).iterator()).rdd(), Encoders.bean(BipScore.class))
.map((MapFunction<BipScore, Result>) v -> {
Result r = new Result();
r.setId(DHPUtils.generateUnresolvedIdentifier(v.getId(), DOI));
r.setMeasures(getMeasure(v));
return r;
}, Encoders.bean(Result.class))
.write()
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.json(outputPath + "/bip");
}
private static List<Measure> getMeasure(BipScore value) {
return value
.getScoreList()
.stream()
.map(score -> {
Measure m = new Measure();
m.setId(score.getId());
m
.setUnit(
score
.getUnit()
.stream()
.map(unit -> {
KeyValue kv = new KeyValue();
kv.setValue(unit.getValue());
kv.setKey(unit.getKey());
kv
.setDataInfo(
OafMapperUtils
.dataInfo(
false,
UPDATE_DATA_INFO_TYPE,
true,
false,
OafMapperUtils
.qualifier(
UPDATE_MEASURE_BIP_CLASS_ID,
UPDATE_CLASS_NAME,
ModelConstants.DNET_PROVENANCE_ACTIONS,
ModelConstants.DNET_PROVENANCE_ACTIONS),
""));
return kv;
})
.collect(Collectors.toList()));
return m;
})
.collect(Collectors.toList());
}
}

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@ -0,0 +1,133 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.*;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import java.io.Serializable;
import java.util.*;
import java.util.stream.Collectors;
import org.apache.commons.io.IOUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.SaveMode;
import org.apache.spark.sql.SparkSession;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.FOSDataModel;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.oaf.Result;
import eu.dnetlib.dhp.schema.oaf.StructuredProperty;
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
import eu.dnetlib.dhp.utils.DHPUtils;
public class PrepareFOSSparkJob implements Serializable {
private static final Logger log = LoggerFactory.getLogger(PrepareFOSSparkJob.class);
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
.toString(
PrepareFOSSparkJob.class
.getResourceAsStream(
"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/prepare_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
String sourcePath = parser.get("sourcePath");
log.info("sourcePath: {}", sourcePath);
final String outputPath = parser.get("outputPath");
log.info("outputPath: {}", outputPath);
SparkConf conf = new SparkConf();
runWithSparkSession(
conf,
isSparkSessionManaged,
spark -> {
distributeFOSdois(
spark,
sourcePath,
outputPath);
});
}
private static void distributeFOSdois(SparkSession spark, String sourcePath, String outputPath) {
Dataset<FOSDataModel> fosDataset = readPath(spark, sourcePath, FOSDataModel.class);
fosDataset.flatMap((FlatMapFunction<FOSDataModel, FOSDataModel>) v -> {
List<FOSDataModel> fosList = new ArrayList<>();
final String level1 = v.getLevel1();
final String level2 = v.getLevel2();
final String level3 = v.getLevel3();
Arrays
.stream(v.getDoi().split("\u0002"))
.forEach(d -> fosList.add(FOSDataModel.newInstance(d, level1, level2, level3)));
return fosList.iterator();
}, Encoders.bean(FOSDataModel.class))
.map((MapFunction<FOSDataModel, Result>) value -> {
Result r = new Result();
r.setId(DHPUtils.generateUnresolvedIdentifier(value.getDoi(), DOI));
r.setSubject(getSubjects(value));
return r;
}, Encoders.bean(Result.class))
.write()
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.json(outputPath + "/fos");
}
private static List<StructuredProperty> getSubjects(FOSDataModel fos) {
return Arrays
.asList(getSubject(fos.getLevel1()), getSubject(fos.getLevel2()), getSubject(fos.getLevel3()))
.stream()
.filter(Objects::nonNull)
.collect(Collectors.toList());
}
private static StructuredProperty getSubject(String sbj) {
if (sbj.equals(NULL))
return null;
StructuredProperty sp = new StructuredProperty();
sp.setValue(sbj);
sp
.setQualifier(
OafMapperUtils
.qualifier(
FOS_CLASS_ID,
FOS_CLASS_NAME,
ModelConstants.DNET_SUBJECT_TYPOLOGIES,
ModelConstants.DNET_SUBJECT_TYPOLOGIES));
sp
.setDataInfo(
OafMapperUtils
.dataInfo(
false,
UPDATE_DATA_INFO_TYPE,
true,
false,
OafMapperUtils
.qualifier(
UPDATE_SUBJECT_FOS_CLASS_ID,
UPDATE_CLASS_NAME,
ModelConstants.DNET_PROVENANCE_ACTIONS,
ModelConstants.DNET_PROVENANCE_ACTIONS),
""));
return sp;
}
}

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@ -0,0 +1,79 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.*;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import java.io.Serializable;
import org.apache.commons.io.IOUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.api.java.function.MapGroupsFunction;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.SaveMode;
import org.apache.spark.sql.SparkSession;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.schema.oaf.Result;
public class SparkSaveUnresolved implements Serializable {
private static final Logger log = LoggerFactory.getLogger(PrepareFOSSparkJob.class);
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
.toString(
PrepareFOSSparkJob.class
.getResourceAsStream(
"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/produce_unresolved_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
String sourcePath = parser.get("sourcePath");
log.info("sourcePath: {}", sourcePath);
final String outputPath = parser.get("outputPath");
log.info("outputPath: {}", outputPath);
SparkConf conf = new SparkConf();
runWithSparkSession(
conf,
isSparkSessionManaged,
spark -> {
saveUnresolved(
spark,
sourcePath,
outputPath);
});
}
private static void saveUnresolved(SparkSession spark, String sourcePath, String outputPath) {
spark
.read()
.textFile(sourcePath + "/*")
.map(
(MapFunction<String, Result>) l -> OBJECT_MAPPER.readValue(l, Result.class),
Encoders.bean(Result.class))
.groupByKey((MapFunction<Result, String>) r -> r.getId(), Encoders.STRING())
.mapGroups((MapGroupsFunction<String, Result, Result>) (k, it) -> {
Result ret = it.next();
it.forEachRemaining(r -> ret.mergeFrom(r));
return ret;
}, Encoders.bean(Result.class))
.write()
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.json(outputPath);
}
}

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@ -0,0 +1,28 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
/**
* Class that maps the model of the bipFinder! input data.
* Only needed for deserialization purposes
*/
public class BipDeserialize extends HashMap<String, List<Score>> implements Serializable {
public BipDeserialize() {
super();
}
public List<Score> get(String key) {
if (super.get(key) == null) {
return new ArrayList<>();
}
return super.get(key);
}
}

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@ -0,0 +1,30 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
import java.io.Serializable;
import java.util.List;
/**
* Rewriting of the bipFinder input data by extracting the identifier of the result (doi)
*/
public class BipScore implements Serializable {
private String id; // doi
private List<Score> scoreList; // unit as given in the inputfile
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
public List<Score> getScoreList() {
return scoreList;
}
public void setScoreList(List<Score> scoreList) {
this.scoreList = scoreList;
}
}

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@ -0,0 +1,71 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
import java.io.Serializable;
import com.opencsv.bean.CsvBindByPosition;
public class FOSDataModel implements Serializable {
@CsvBindByPosition(position = 1)
// @CsvBindByName(column = "doi")
private String doi;
@CsvBindByPosition(position = 2)
// @CsvBindByName(column = "level1")
private String level1;
@CsvBindByPosition(position = 3)
// @CsvBindByName(column = "level2")
private String level2;
@CsvBindByPosition(position = 4)
// @CsvBindByName(column = "level3")
private String level3;
public FOSDataModel() {
}
public FOSDataModel(String doi, String level1, String level2, String level3) {
this.doi = doi;
this.level1 = level1;
this.level2 = level2;
this.level3 = level3;
}
public static FOSDataModel newInstance(String d, String level1, String level2, String level3) {
return new FOSDataModel(d, level1, level2, level3);
}
public String getDoi() {
return doi;
}
public void setDoi(String doi) {
this.doi = doi;
}
public String getLevel1() {
return level1;
}
public void setLevel1(String level1) {
this.level1 = level1;
}
public String getLevel2() {
return level2;
}
public void setLevel2(String level2) {
this.level2 = level2;
}
public String getLevel3() {
return level3;
}
public void setLevel3(String level3) {
this.level3 = level3;
}
}

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@ -0,0 +1,26 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
import java.io.Serializable;
public class KeyValue implements Serializable {
private String key;
private String value;
public String getKey() {
return key;
}
public void setKey(String key) {
this.key = key;
}
public String getValue() {
return value;
}
public void setValue(String value) {
this.value = value;
}
}

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@ -0,0 +1,30 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities.model;
import java.io.Serializable;
import java.util.List;
/**
* represents the score in the input file
*/
public class Score implements Serializable {
private String id;
private List<KeyValue> unit;
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
public List<KeyValue> getUnit() {
return unit;
}
public void setUnit(List<KeyValue> unit) {
this.unit = unit;
}
}

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@ -1,41 +0,0 @@
package eu.dnetlib.dhp.actionmanager.datacite
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.schema.oaf.Oaf
import org.apache.hadoop.io.Text
import org.apache.hadoop.io.compress.GzipCodec
import org.apache.hadoop.mapred.SequenceFileOutputFormat
import org.apache.spark.SparkConf
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
import scala.io.Source
object ExportActionSetJobNode {
val log: Logger = LoggerFactory.getLogger(ExportActionSetJobNode.getClass)
def main(args: Array[String]): Unit = {
val conf = new SparkConf
val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/actionmanager/datacite/exportDataset_parameters.json")).mkString)
parser.parseArgument(args)
val master = parser.get("master")
val sourcePath = parser.get("sourcePath")
val targetPath = parser.get("targetPath")
val spark: SparkSession = SparkSession.builder().config(conf)
.appName(ExportActionSetJobNode.getClass.getSimpleName)
.master(master)
.getOrCreate()
implicit val resEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val tEncoder:Encoder[(String,String)] = Encoders.tuple(Encoders.STRING,Encoders.STRING)
spark.read.load(sourcePath).as[Oaf]
.map(o =>DataciteToOAFTransformation.toActionSet(o))
.filter(o => o!= null)
.rdd.map(s => (new Text(s._1), new Text(s._2))).saveAsHadoopFile(s"$targetPath", classOf[Text], classOf[Text], classOf[SequenceFileOutputFormat[Text,Text]], classOf[GzipCodec])
}
}

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@ -1,46 +0,0 @@
package eu.dnetlib.dhp.actionmanager.datacite
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.mdstore.MetadataRecord
import eu.dnetlib.dhp.schema.oaf.{Oaf, Result}
import eu.dnetlib.dhp.utils.ISLookupClientFactory
import org.apache.spark.SparkConf
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
import scala.io.Source
object FilterCrossrefEntitiesSpark {
val log: Logger = LoggerFactory.getLogger(getClass.getClass)
def main(args: Array[String]): Unit = {
val conf = new SparkConf
val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/actionmanager/datacite/filter_crossref_param.json")).mkString)
parser.parseArgument(args)
val master = parser.get("master")
val sourcePath = parser.get("sourcePath")
log.info("sourcePath: {}", sourcePath)
val targetPath = parser.get("targetPath")
log.info("targetPath: {}", targetPath)
val spark: SparkSession = SparkSession.builder().config(conf)
.appName(getClass.getSimpleName)
.master(master)
.getOrCreate()
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val resEncoder: Encoder[Result] = Encoders.kryo[Result]
val d:Dataset[Oaf]= spark.read.load(sourcePath).as[Oaf]
d.filter(r => r.isInstanceOf[Result]).map(r => r.asInstanceOf[Result]).write.mode(SaveMode.Overwrite).save(targetPath)
}
}

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@ -60,14 +60,10 @@ object SparkCreateActionset {
val entities: Dataset[(String, Result)] = spark.read.load(s"$sourcePath/entities/*").as[Result].map(p => (p.getId, p))(Encoders.tuple(Encoders.STRING, resultEncoders)) val entities: Dataset[(String, Result)] = spark.read.load(s"$sourcePath/entities/*").as[Result].map(p => (p.getId, p))(Encoders.tuple(Encoders.STRING, resultEncoders))
entities.filter(r => r.isInstanceOf[Result]).map(r => r.asInstanceOf[Result])
entities entities
.joinWith(idRelation, entities("_1").equalTo(idRelation("value"))) .joinWith(idRelation, entities("_1").equalTo(idRelation("value")))
.map(p => p._1._2) .map(p => p._1._2)
.write.mode(SaveMode.Append).save(s"$workingDirFolder/actionSetOaf") .write.mode(SaveMode.Append).save(s"$workingDirFolder/actionSetOaf")
} }
} }

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@ -0,0 +1,49 @@
package eu.dnetlib.dhp.collection
import eu.dnetlib.dhp.schema.common.ModelSupport
import eu.dnetlib.dhp.schema.oaf.{Oaf, OafEntity, Relation}
object CollectionUtils {
/**
* This method in pipeline to the transformation phase,
* generates relations in both verse, typically it should be a phase of flatMap
*
* @param i input OAF
* @return
* If the input OAF is an entity -> List(i)
* If the input OAF is a relation -> List(relation, inverseRelation)
*
*/
def fixRelations(i: Oaf): List[Oaf] = {
if (i.isInstanceOf[OafEntity])
return List(i)
else {
val r: Relation = i.asInstanceOf[Relation]
val currentRel = ModelSupport.findRelation(r.getRelClass)
if (currentRel != null) {
// Cleaning relation
r.setRelType(currentRel.getRelType)
r.setSubRelType(currentRel.getSubReltype)
r.setRelClass(currentRel.getRelClass)
val inverse = new Relation
inverse.setSource(r.getTarget)
inverse.setTarget(r.getSource)
inverse.setRelType(currentRel.getRelType)
inverse.setSubRelType(currentRel.getSubReltype)
inverse.setRelClass(currentRel.getInverseRelClass)
inverse.setCollectedfrom(r.getCollectedfrom)
inverse.setDataInfo(r.getDataInfo)
inverse.setProperties(r.getProperties)
inverse.setLastupdatetimestamp(r.getLastupdatetimestamp)
inverse.setValidated(r.getValidated)
inverse.setValidationDate(r.getValidationDate)
return List(r, inverse)
}
}
List()
}
}

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@ -1,12 +1,10 @@
package eu.dnetlib.dhp.actionmanager.datacite package eu.dnetlib.dhp.datacite
import org.apache.commons.io.IOUtils import org.apache.commons.io.IOUtils
import org.apache.http.client.config.RequestConfig import org.apache.http.client.config.RequestConfig
import org.apache.http.client.methods.{HttpGet, HttpPost, HttpRequestBase, HttpUriRequest} import org.apache.http.client.methods.{HttpGet, HttpPost, HttpUriRequest}
import org.apache.http.entity.StringEntity import org.apache.http.entity.StringEntity
import org.apache.http.impl.client.{HttpClientBuilder, HttpClients} import org.apache.http.impl.client.HttpClientBuilder
import java.io.IOException
abstract class AbstractRestClient extends Iterator[String] { abstract class AbstractRestClient extends Iterator[String] {

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@ -1,7 +1,7 @@
package eu.dnetlib.dhp.actionmanager.datacite package eu.dnetlib.dhp.datacite
import org.json4s.{DefaultFormats, JValue}
import org.json4s.jackson.JsonMethods.{compact, parse, render} import org.json4s.jackson.JsonMethods.{compact, parse, render}
import org.json4s.{DefaultFormats, JValue}
class DataciteAPIImporter(timestamp: Long = 0, blocks: Long = 10, until:Long = -1) extends AbstractRestClient { class DataciteAPIImporter(timestamp: Long = 0, blocks: Long = 10, until:Long = -1) extends AbstractRestClient {

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@ -1,4 +1,4 @@
package eu.dnetlib.dhp.actionmanager.datacite package eu.dnetlib.dhp.datacite
import com.fasterxml.jackson.databind.ObjectMapper import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
@ -325,8 +325,9 @@ object DataciteToOAFTransformation {
val grantId = m.matcher(awardUri).replaceAll("$2") val grantId = m.matcher(awardUri).replaceAll("$2")
val targetId = s"$p${DHPUtils.md5(grantId)}" val targetId = s"$p${DHPUtils.md5(grantId)}"
List( List(
generateRelation(sourceId, targetId, "isProducedBy", DATACITE_COLLECTED_FROM, dataInfo), generateRelation(sourceId, targetId, "isProducedBy", DATACITE_COLLECTED_FROM, dataInfo)
generateRelation(targetId, sourceId, "produces", DATACITE_COLLECTED_FROM, dataInfo) // REMOVED INVERSE RELATION since there is a specific method that should generate later
// generateRelation(targetId, sourceId, "produces", DATACITE_COLLECTED_FROM, dataInfo)
) )
} }
else else
@ -580,11 +581,11 @@ object DataciteToOAFTransformation {
rel.setProperties(List(dateProps).asJava) rel.setProperties(List(dateProps).asJava)
rel.setSource(id) rel.setSource(id)
rel.setTarget(s"unresolved::${r.relatedIdentifier}::${r.relatedIdentifierType}") rel.setTarget(DHPUtils.generateUnresolvedIdentifier(r.relatedIdentifier,r.relatedIdentifierType))
rel.setCollectedfrom(List(DATACITE_COLLECTED_FROM).asJava) rel.setCollectedfrom(List(DATACITE_COLLECTED_FROM).asJava)
rel.getCollectedfrom.asScala.map(c => c.getValue)(collection.breakOut) rel.getCollectedfrom.asScala.map(c => c.getValue).toList
rel rel
})(collection breakOut) }).toList
} }
def generateDataInfo(trust: String): DataInfo = { def generateDataInfo(trust: String): DataInfo = {

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@ -1,9 +1,14 @@
package eu.dnetlib.dhp.actionmanager.datacite package eu.dnetlib.dhp.datacite
import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.application.ArgumentApplicationParser import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.collection.CollectionUtils.fixRelations
import eu.dnetlib.dhp.common.Constants.MDSTORE_DATA_PATH
import eu.dnetlib.dhp.common.Constants.MDSTORE_SIZE_PATH
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.mdstore.MetadataRecord import eu.dnetlib.dhp.schema.mdstore.{MDStoreVersion, MetadataRecord}
import eu.dnetlib.dhp.schema.oaf.Oaf import eu.dnetlib.dhp.schema.oaf.Oaf
import eu.dnetlib.dhp.utils.DHPUtils.writeHdfsFile
import eu.dnetlib.dhp.utils.ISLookupClientFactory import eu.dnetlib.dhp.utils.ISLookupClientFactory
import org.apache.spark.SparkConf import org.apache.spark.SparkConf
import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession} import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
@ -17,11 +22,10 @@ object GenerateDataciteDatasetSpark {
def main(args: Array[String]): Unit = { def main(args: Array[String]): Unit = {
val conf = new SparkConf val conf = new SparkConf
val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/actionmanager/datacite/generate_dataset_params.json")).mkString) val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/datacite/generate_dataset_params.json")).mkString)
parser.parseArgument(args) parser.parseArgument(args)
val master = parser.get("master") val master = parser.get("master")
val sourcePath = parser.get("sourcePath") val sourcePath = parser.get("sourcePath")
val targetPath = parser.get("targetPath")
val exportLinks = "true".equalsIgnoreCase(parser.get("exportLinks")) val exportLinks = "true".equalsIgnoreCase(parser.get("exportLinks"))
val isLookupUrl: String = parser.get("isLookupUrl") val isLookupUrl: String = parser.get("isLookupUrl")
log.info("isLookupUrl: {}", isLookupUrl) log.info("isLookupUrl: {}", isLookupUrl)
@ -33,16 +37,28 @@ object GenerateDataciteDatasetSpark {
.master(master) .master(master)
.getOrCreate() .getOrCreate()
import spark.implicits._
implicit val mrEncoder: Encoder[MetadataRecord] = Encoders.kryo[MetadataRecord] implicit val mrEncoder: Encoder[MetadataRecord] = Encoders.kryo[MetadataRecord]
implicit val resEncoder: Encoder[Oaf] = Encoders.kryo[Oaf] implicit val resEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
import spark.implicits._ val mdstoreOutputVersion = parser.get("mdstoreOutputVersion")
val mapper = new ObjectMapper()
val cleanedMdStoreVersion = mapper.readValue(mdstoreOutputVersion, classOf[MDStoreVersion])
val outputBasePath = cleanedMdStoreVersion.getHdfsPath
log.info("outputBasePath: {}", outputBasePath)
val targetPath = s"$outputBasePath/$MDSTORE_DATA_PATH"
spark.read.load(sourcePath).as[DataciteType] spark.read.load(sourcePath).as[DataciteType]
.filter(d => d.isActive) .filter(d => d.isActive)
.flatMap(d => DataciteToOAFTransformation.generateOAF(d.json, d.timestamp, d.timestamp, vocabularies, exportLinks)) .flatMap(d => DataciteToOAFTransformation.generateOAF(d.json, d.timestamp, d.timestamp, vocabularies, exportLinks))
.filter(d => d != null) .filter(d => d != null)
.flatMap(i => fixRelations(i)).filter(i => i != null)
.write.mode(SaveMode.Overwrite).save(targetPath) .write.mode(SaveMode.Overwrite).save(targetPath)
val total_items = spark.read.load(targetPath).as[Oaf].count()
writeHdfsFile(spark.sparkContext.hadoopConfiguration, s"$total_items", outputBasePath + MDSTORE_SIZE_PATH)
} }
} }

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@ -1,6 +1,5 @@
package eu.dnetlib.dhp.actionmanager.datacite package eu.dnetlib.dhp.datacite
import eu.dnetlib.dhp.actionmanager.datacite.DataciteToOAFTransformation.df_it
import eu.dnetlib.dhp.application.ArgumentApplicationParser import eu.dnetlib.dhp.application.ArgumentApplicationParser
import org.apache.hadoop.conf.Configuration import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.{FileSystem, LocalFileSystem, Path} import org.apache.hadoop.fs.{FileSystem, LocalFileSystem, Path}
@ -9,14 +8,14 @@ import org.apache.hadoop.io.{IntWritable, SequenceFile, Text}
import org.apache.spark.SparkContext import org.apache.spark.SparkContext
import org.apache.spark.rdd.RDD import org.apache.spark.rdd.RDD
import org.apache.spark.sql.expressions.Aggregator import org.apache.spark.sql.expressions.Aggregator
import org.apache.spark.sql.functions.max
import org.apache.spark.sql.{Dataset, Encoder, SaveMode, SparkSession} import org.apache.spark.sql.{Dataset, Encoder, SaveMode, SparkSession}
import org.json4s.DefaultFormats import org.json4s.DefaultFormats
import org.json4s.jackson.JsonMethods.parse import org.json4s.jackson.JsonMethods.parse
import org.apache.spark.sql.functions.max
import org.slf4j.{Logger, LoggerFactory} import org.slf4j.{Logger, LoggerFactory}
import java.time.format.DateTimeFormatter._ import java.time.format.DateTimeFormatter.ISO_DATE_TIME
import java.time.{LocalDate, LocalDateTime, ZoneOffset} import java.time.{LocalDateTime, ZoneOffset}
import scala.io.Source import scala.io.Source
object ImportDatacite { object ImportDatacite {

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@ -0,0 +1,49 @@
package eu.dnetlib.dhp.datacite
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.schema.oaf.{Oaf, Result}
import org.apache.spark.SparkConf
import org.apache.spark.sql.functions.max
import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
import java.text.SimpleDateFormat
import java.util.Locale
import scala.io.Source
object SparkDownloadUpdateDatacite {
val log: Logger = LoggerFactory.getLogger(getClass)
def main(args: Array[String]): Unit = {
val conf = new SparkConf
val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/datacite/generate_dataset_params.json")).mkString)
parser.parseArgument(args)
val master = parser.get("master")
val sourcePath = parser.get("sourcePath")
val workingPath = parser.get("workingPath")
val hdfsuri = parser.get("namenode")
log.info(s"namenode is $hdfsuri")
val spark: SparkSession = SparkSession.builder().config(conf)
.appName(getClass.getSimpleName)
.master(master)
.getOrCreate()
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val resEncoder: Encoder[Result] = Encoders.kryo[Result]
import spark.implicits._
val maxDate: String = spark.read.load(workingPath).as[Oaf].filter(s => s.isInstanceOf[Result]).map(r => r.asInstanceOf[Result].getDateofcollection).select(max("value")).first().getString(0)
val ISO8601FORMAT = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ssZ", Locale.US)
val string_to_date = ISO8601FORMAT.parse(maxDate)
val ts = string_to_date.getTime
}
}

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@ -1,14 +1,12 @@
package eu.dnetlib.dhp.sx.graph.bio package eu.dnetlib.dhp.sx.bio
import eu.dnetlib.dhp.schema.common.ModelConstants import eu.dnetlib.dhp.schema.common.ModelConstants
import eu.dnetlib.dhp.schema.oaf.utils.{GraphCleaningFunctions, OafMapperUtils} import eu.dnetlib.dhp.schema.oaf.utils.{GraphCleaningFunctions, OafMapperUtils}
import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Dataset, Instance, KeyValue, Oaf, Relation, StructuredProperty} import eu.dnetlib.dhp.schema.oaf._
import org.json4s.DefaultFormats import org.json4s.DefaultFormats
import org.json4s.JsonAST.{JField, JObject, JString} import org.json4s.JsonAST.{JField, JObject, JString}
import org.json4s.jackson.JsonMethods.{compact, parse, render} import org.json4s.jackson.JsonMethods.{compact, parse, render}
import collection.JavaConverters._
import scala.collection.JavaConverters._
object BioDBToOAF { object BioDBToOAF {
case class EBILinkItem(id: Long, links: String) {} case class EBILinkItem(id: Long, links: String) {}
@ -231,7 +229,6 @@ object BioDBToOAF {
} }
def generate_unresolved_id(pid: String, pidType: String): String = { def generate_unresolved_id(pid: String, pidType: String): String = {
s"unresolved::$pid::$pidType" s"unresolved::$pid::$pidType"
} }

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@ -1,8 +1,9 @@
package eu.dnetlib.dhp.sx.graph.bio package eu.dnetlib.dhp.sx.bio
import eu.dnetlib.dhp.application.ArgumentApplicationParser import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.schema.oaf.{Oaf, Result} import eu.dnetlib.dhp.schema.oaf.Oaf
import BioDBToOAF.ScholixResolved import BioDBToOAF.ScholixResolved
import eu.dnetlib.dhp.collection.CollectionUtils
import org.apache.commons.io.IOUtils import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf import org.apache.spark.SparkConf
import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession} import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
@ -13,7 +14,7 @@ object SparkTransformBioDatabaseToOAF {
def main(args: Array[String]): Unit = { def main(args: Array[String]): Unit = {
val conf: SparkConf = new SparkConf() val conf: SparkConf = new SparkConf()
val log: Logger = LoggerFactory.getLogger(getClass) val log: Logger = LoggerFactory.getLogger(getClass)
val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/bio/bio_to_oaf_params.json"))) val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/bio/ebi/bio_to_oaf_params.json")))
parser.parseArgument(args) parser.parseArgument(args)
val database: String = parser.get("database") val database: String = parser.get("database")
log.info("database: {}", database) log.info("database: {}", database)
@ -33,16 +34,15 @@ object SparkTransformBioDatabaseToOAF {
implicit val resultEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf]) implicit val resultEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
import spark.implicits._ import spark.implicits._
database.toUpperCase() match { database.toUpperCase() match {
case "UNIPROT" => case "UNIPROT" =>
spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.uniprotToOAF(i))).write.mode(SaveMode.Overwrite).save(targetPath) spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.uniprotToOAF(i))).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
case "PDB" => case "PDB" =>
spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.pdbTOOaf(i))).write.mode(SaveMode.Overwrite).save(targetPath) spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.pdbTOOaf(i))).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
case "SCHOLIX" => case "SCHOLIX" =>
spark.read.load(dbPath).as[ScholixResolved].map(i => BioDBToOAF.scholixResolvedToOAF(i)).write.mode(SaveMode.Overwrite).save(targetPath) spark.read.load(dbPath).as[ScholixResolved].map(i => BioDBToOAF.scholixResolvedToOAF(i)).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
case "CROSSREF_LINKS" => case "CROSSREF_LINKS" =>
spark.createDataset(sc.textFile(dbPath).map(i => BioDBToOAF.crossrefLinksToOaf(i))).write.mode(SaveMode.Overwrite).save(targetPath) spark.createDataset(sc.textFile(dbPath).map(i => BioDBToOAF.crossrefLinksToOaf(i))).flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
} }
} }

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@ -0,0 +1,200 @@
package eu.dnetlib.dhp.sx.bio.ebi
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.oaf.Result
import eu.dnetlib.dhp.sx.bio.pubmed.{PMArticle, PMAuthor, PMJournal, PMParser, PubMedToOaf}
import eu.dnetlib.dhp.utils.ISLookupClientFactory
import org.apache.commons.io.IOUtils
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.{FSDataOutputStream, FileSystem, Path}
import org.apache.http.client.config.RequestConfig
import org.apache.http.client.methods.HttpGet
import org.apache.http.impl.client.HttpClientBuilder
import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.expressions.Aggregator
import org.apache.spark.sql._
import org.slf4j.{Logger, LoggerFactory}
import java.io.InputStream
import scala.io.Source
import scala.xml.pull.XMLEventReader
object SparkCreateBaselineDataFrame {
def requestBaseLineUpdatePage(maxFile: String): List[(String, String)] = {
val data = requestPage("https://ftp.ncbi.nlm.nih.gov/pubmed/updatefiles/")
val result = data.lines.filter(l => l.startsWith("<a href=")).map { l =>
val end = l.lastIndexOf("\">")
val start = l.indexOf("<a href=\"")
if (start >= 0 && end > start)
l.substring(start + 9, end - start)
else
""
}.filter(s => s.endsWith(".gz")).filter(s => s > maxFile).map(s => (s, s"https://ftp.ncbi.nlm.nih.gov/pubmed/updatefiles/$s")).toList
result
}
def downloadBaselinePart(url: String): InputStream = {
val r = new HttpGet(url)
val timeout = 60; // seconds
val config = RequestConfig.custom()
.setConnectTimeout(timeout * 1000)
.setConnectionRequestTimeout(timeout * 1000)
.setSocketTimeout(timeout * 1000).build()
val client = HttpClientBuilder.create().setDefaultRequestConfig(config).build()
val response = client.execute(r)
println(s"get response with status${response.getStatusLine.getStatusCode}")
response.getEntity.getContent
}
def requestPage(url: String): String = {
val r = new HttpGet(url)
val timeout = 60; // seconds
val config = RequestConfig.custom()
.setConnectTimeout(timeout * 1000)
.setConnectionRequestTimeout(timeout * 1000)
.setSocketTimeout(timeout * 1000).build()
val client = HttpClientBuilder.create().setDefaultRequestConfig(config).build()
try {
var tries = 4
while (tries > 0) {
println(s"requesting ${r.getURI}")
try {
val response = client.execute(r)
println(s"get response with status${response.getStatusLine.getStatusCode}")
if (response.getStatusLine.getStatusCode > 400) {
tries -= 1
}
else
return IOUtils.toString(response.getEntity.getContent)
} catch {
case e: Throwable =>
println(s"Error on requesting ${r.getURI}")
e.printStackTrace()
tries -= 1
}
}
""
} finally {
if (client != null)
client.close()
}
}
def downloadBaseLineUpdate(baselinePath: String, hdfsServerUri: String): Unit = {
val conf = new Configuration
conf.set("fs.defaultFS", hdfsServerUri)
val fs = FileSystem.get(conf)
val p = new Path(baselinePath)
val files = fs.listFiles(p, false)
var max_file = ""
while (files.hasNext) {
val c = files.next()
val data = c.getPath.toString
val fileName = data.substring(data.lastIndexOf("/") + 1)
if (fileName > max_file)
max_file = fileName
}
val files_to_download = requestBaseLineUpdatePage(max_file)
files_to_download.foreach { u =>
val hdfsWritePath: Path = new Path(s"$baselinePath/${u._1}")
val fsDataOutputStream: FSDataOutputStream = fs.create(hdfsWritePath, true)
val i = downloadBaselinePart(u._2)
IOUtils.copy(i, fsDataOutputStream)
println(s"Downloaded ${u._2} into $baselinePath/${u._1}")
fsDataOutputStream.close()
}
}
val pmArticleAggregator: Aggregator[(String, PMArticle), PMArticle, PMArticle] = new Aggregator[(String, PMArticle), PMArticle, PMArticle] with Serializable {
override def zero: PMArticle = new PMArticle
override def reduce(b: PMArticle, a: (String, PMArticle)): PMArticle = {
if (b != null && b.getPmid != null) b else a._2
}
override def merge(b1: PMArticle, b2: PMArticle): PMArticle = {
if (b1 != null && b1.getPmid != null) b1 else b2
}
override def finish(reduction: PMArticle): PMArticle = reduction
override def bufferEncoder: Encoder[PMArticle] = Encoders.kryo[PMArticle]
override def outputEncoder: Encoder[PMArticle] = Encoders.kryo[PMArticle]
}
def main(args: Array[String]): Unit = {
val conf: SparkConf = new SparkConf()
val log: Logger = LoggerFactory.getLogger(getClass)
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkEBILinksToOaf.getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/bio/ebi/baseline_to_oaf_params.json")))
parser.parseArgument(args)
val isLookupUrl: String = parser.get("isLookupUrl")
log.info("isLookupUrl: {}", isLookupUrl)
val workingPath = parser.get("workingPath")
log.info("workingPath: {}", workingPath)
val targetPath = parser.get("targetPath")
log.info("targetPath: {}", targetPath)
val hdfsServerUri = parser.get("hdfsServerUri")
log.info("hdfsServerUri: {}", targetPath)
val skipUpdate = parser.get("skipUpdate")
log.info("skipUpdate: {}", skipUpdate)
val isLookupService = ISLookupClientFactory.getLookUpService(isLookupUrl)
val vocabularies = VocabularyGroup.loadVocsFromIS(isLookupService)
val spark: SparkSession =
SparkSession
.builder()
.config(conf)
.appName(SparkEBILinksToOaf.getClass.getSimpleName)
.master(parser.get("master")).getOrCreate()
val sc = spark.sparkContext
import spark.implicits._
implicit val PMEncoder: Encoder[PMArticle] = Encoders.kryo(classOf[PMArticle])
implicit val PMJEncoder: Encoder[PMJournal] = Encoders.kryo(classOf[PMJournal])
implicit val PMAEncoder: Encoder[PMAuthor] = Encoders.kryo(classOf[PMAuthor])
implicit val resultEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
if (!"true".equalsIgnoreCase(skipUpdate)) {
downloadBaseLineUpdate(s"$workingPath/baseline", hdfsServerUri)
val k: RDD[(String, String)] = sc.wholeTextFiles(s"$workingPath/baseline", 2000)
val ds: Dataset[PMArticle] = spark.createDataset(k.filter(i => i._1.endsWith(".gz")).flatMap(i => {
val xml = new XMLEventReader(Source.fromBytes(i._2.getBytes()))
new PMParser(xml)
}))
ds.map(p => (p.getPmid, p))(Encoders.tuple(Encoders.STRING, PMEncoder)).groupByKey(_._1)
.agg(pmArticleAggregator.toColumn)
.map(p => p._2).write.mode(SaveMode.Overwrite).save(s"$workingPath/baseline_dataset")
}
val exported_dataset = spark.read.load(s"$workingPath/baseline_dataset").as[PMArticle]
exported_dataset
.map(a => PubMedToOaf.convert(a, vocabularies)).as[Result]
.filter(p => p != null)
.write.mode(SaveMode.Overwrite).save(targetPath)
}
}

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@ -0,0 +1,118 @@
package eu.dnetlib.dhp.sx.bio.ebi
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.sx.bio.pubmed.{PMArticle, PMAuthor, PMJournal}
import eu.dnetlib.dhp.sx.bio.BioDBToOAF.EBILinkItem
import eu.dnetlib.dhp.sx.bio.pubmed.PMJournal
import org.apache.commons.io.IOUtils
import org.apache.http.client.config.RequestConfig
import org.apache.http.client.methods.HttpGet
import org.apache.http.impl.client.HttpClientBuilder
import org.apache.spark.SparkConf
import org.apache.spark.sql.functions.max
import org.apache.spark.sql._
import org.slf4j.{Logger, LoggerFactory}
object SparkDownloadEBILinks {
def createEBILinks(pmid: Long): EBILinkItem = {
val res = requestLinks(pmid)
if (res != null)
return EBILinkItem(pmid, res)
null
}
def requestPage(url: String): String = {
val r = new HttpGet(url)
val timeout = 60; // seconds
val config = RequestConfig.custom()
.setConnectTimeout(timeout * 1000)
.setConnectionRequestTimeout(timeout * 1000)
.setSocketTimeout(timeout * 1000).build()
val client = HttpClientBuilder.create().setDefaultRequestConfig(config).build()
try {
var tries = 4
while (tries > 0) {
println(s"requesting ${r.getURI}")
try {
val response = client.execute(r)
println(s"get response with status${response.getStatusLine.getStatusCode}")
if (response.getStatusLine.getStatusCode > 400) {
tries -= 1
}
else
return IOUtils.toString(response.getEntity.getContent)
} catch {
case e: Throwable =>
println(s"Error on requesting ${r.getURI}")
e.printStackTrace()
tries -= 1
}
}
""
} finally {
if (client != null)
client.close()
}
}
def requestLinks(PMID: Long): String = {
requestPage(s"https://www.ebi.ac.uk/europepmc/webservices/rest/MED/$PMID/datalinks?format=json")
}
def main(args: Array[String]): Unit = {
val log: Logger = LoggerFactory.getLogger(getClass)
val MAX_ITEM_PER_PARTITION = 20000
val conf: SparkConf = new SparkConf()
val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/bio/ebi/ebi_download_update.json")))
parser.parseArgument(args)
val spark: SparkSession =
SparkSession
.builder()
.config(conf)
.appName(SparkEBILinksToOaf.getClass.getSimpleName)
.master(parser.get("master")).getOrCreate()
import spark.implicits._
implicit val PMEncoder: Encoder[PMArticle] = Encoders.kryo(classOf[PMArticle])
implicit val PMJEncoder: Encoder[PMJournal] = Encoders.kryo(classOf[PMJournal])
implicit val PMAEncoder: Encoder[PMAuthor] = Encoders.kryo(classOf[PMAuthor])
val sourcePath = parser.get("sourcePath")
log.info(s"sourcePath -> $sourcePath")
val workingPath = parser.get("workingPath")
log.info(s"workingPath -> $workingPath")
log.info("Getting max pubmedId where the links have already requested")
val links: Dataset[EBILinkItem] = spark.read.load(s"$sourcePath/ebi_links_dataset").as[EBILinkItem]
val lastPMIDRequested = links.map(l => l.id).select(max("value")).first.getLong(0)
log.info("Retrieving PMID to request links")
val pubmed = spark.read.load(s"$sourcePath/baseline_dataset").as[PMArticle]
pubmed.map(p => p.getPmid.toLong).where(s"value > $lastPMIDRequested").write.mode(SaveMode.Overwrite).save(s"$workingPath/id_to_request")
val pmidToReq: Dataset[Long] = spark.read.load(s"$workingPath/id_to_request").as[Long]
val total = pmidToReq.count()
spark.createDataset(pmidToReq.rdd.repartition((total / MAX_ITEM_PER_PARTITION).toInt).map(pmid => createEBILinks(pmid)).filter(l => l != null)).write.mode(SaveMode.Overwrite).save(s"$workingPath/links_update")
val updates: Dataset[EBILinkItem] = spark.read.load(s"$workingPath/links_update").as[EBILinkItem]
links.union(updates).groupByKey(_.id)
.reduceGroups { (x, y) =>
if (x == null || x.links == null)
y
if (y == null || y.links == null)
x
if (x.links.length > y.links.length)
x
else
y
}.map(_._2).write.mode(SaveMode.Overwrite).save(s"$workingPath/links_final")
}
}

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@ -1,21 +1,22 @@
package eu.dnetlib.dhp.sx.graph.ebi package eu.dnetlib.dhp.sx.bio.ebi
import eu.dnetlib.dhp.application.ArgumentApplicationParser import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.schema.oaf.Oaf import eu.dnetlib.dhp.schema.oaf.Oaf
import eu.dnetlib.dhp.sx.graph.bio import eu.dnetlib.dhp.sx.bio.BioDBToOAF
import eu.dnetlib.dhp.sx.graph.bio.BioDBToOAF import eu.dnetlib.dhp.sx.bio.BioDBToOAF.EBILinkItem
import eu.dnetlib.dhp.sx.graph.bio.BioDBToOAF.EBILinkItem import BioDBToOAF.EBILinkItem
import eu.dnetlib.dhp.collection.CollectionUtils
import org.apache.commons.io.IOUtils import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD import org.apache.spark.sql._
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory} import org.slf4j.{Logger, LoggerFactory}
object SparkEBILinksToOaf { object SparkEBILinksToOaf {
def main(args: Array[String]): Unit = { def main(args: Array[String]): Unit = {
val log: Logger = LoggerFactory.getLogger(getClass) val log: Logger = LoggerFactory.getLogger(getClass)
val conf: SparkConf = new SparkConf() val conf: SparkConf = new SparkConf()
val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/ebi/ebi_to_df_params.json"))) val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/bio/ebi/ebi_to_df_params.json")))
parser.parseArgument(args) parser.parseArgument(args)
val spark: SparkSession = val spark: SparkSession =
SparkSession SparkSession
@ -24,24 +25,20 @@ object SparkEBILinksToOaf {
.appName(SparkEBILinksToOaf.getClass.getSimpleName) .appName(SparkEBILinksToOaf.getClass.getSimpleName)
.master(parser.get("master")).getOrCreate() .master(parser.get("master")).getOrCreate()
import spark.implicits._
val sourcePath = parser.get("sourcePath") val sourcePath = parser.get("sourcePath")
log.info(s"sourcePath -> $sourcePath") log.info(s"sourcePath -> $sourcePath")
val targetPath = parser.get("targetPath") val targetPath = parser.get("targetPath")
log.info(s"targetPath -> $targetPath") log.info(s"targetPath -> $targetPath")
import spark.implicits._
implicit val PMEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf]) implicit val PMEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
val ebi_rdd:Dataset[EBILinkItem] = spark.createDataset(spark.sparkContext.textFile(sourcePath).map(s => BioDBToOAF.extractEBILinksFromDump(s))).as[EBILinkItem] val ebLinks: Dataset[EBILinkItem] = spark.read.load(sourcePath).as[EBILinkItem].filter(l => l.links != null && l.links.startsWith("{"))
ebi_rdd.write.mode(SaveMode.Overwrite).save(s"${sourcePath}_dataset")
val ebLinks:Dataset[EBILinkItem] = spark.read.load(s"${sourcePath}_dataset").as[EBILinkItem].filter(l => l.links!= null)
ebLinks.flatMap(j => BioDBToOAF.parse_ebi_links(j.links)) ebLinks.flatMap(j => BioDBToOAF.parse_ebi_links(j.links))
.repartition(4000)
.filter(p => BioDBToOAF.EBITargetLinksFilter(p)) .filter(p => BioDBToOAF.EBITargetLinksFilter(p))
.flatMap(p => BioDBToOAF.convertEBILinksToOaf(p)) .flatMap(p => BioDBToOAF.convertEBILinksToOaf(p))
.flatMap(i=> CollectionUtils.fixRelations(i)).filter(i => i != null)
.write.mode(SaveMode.Overwrite).save(targetPath) .write.mode(SaveMode.Overwrite).save(targetPath)
} }
} }

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@ -1,5 +1,5 @@
package eu.dnetlib.dhp.sx.graph.bio.pubmed; package eu.dnetlib.dhp.sx.bio.pubmed;
import java.io.Serializable; import java.io.Serializable;
import java.util.ArrayList; import java.util.ArrayList;

View File

@ -1,5 +1,5 @@
package eu.dnetlib.dhp.sx.graph.bio.pubmed; package eu.dnetlib.dhp.sx.bio.pubmed;
import java.io.Serializable; import java.io.Serializable;

View File

@ -1,5 +1,5 @@
package eu.dnetlib.dhp.sx.graph.bio.pubmed; package eu.dnetlib.dhp.sx.bio.pubmed;
public class PMGrant { public class PMGrant {

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@ -1,5 +1,5 @@
package eu.dnetlib.dhp.sx.graph.bio.pubmed; package eu.dnetlib.dhp.sx.bio.pubmed;
import java.io.Serializable; import java.io.Serializable;

View File

@ -1,4 +1,4 @@
package eu.dnetlib.dhp.sx.graph.bio.pubmed package eu.dnetlib.dhp.sx.bio.pubmed
import scala.xml.MetaData import scala.xml.MetaData
import scala.xml.pull.{EvElemEnd, EvElemStart, EvText, XMLEventReader} import scala.xml.pull.{EvElemEnd, EvElemStart, EvText, XMLEventReader}

View File

@ -1,5 +1,5 @@
package eu.dnetlib.dhp.sx.graph.bio.pubmed; package eu.dnetlib.dhp.sx.bio.pubmed;
public class PMSubject { public class PMSubject {
private String value; private String value;

View File

@ -1,11 +1,12 @@
package eu.dnetlib.dhp.sx.graph.bio.pubmed package eu.dnetlib.dhp.sx.bio.pubmed
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.common.ModelConstants import eu.dnetlib.dhp.schema.common.ModelConstants
import eu.dnetlib.dhp.schema.oaf._
import eu.dnetlib.dhp.schema.oaf.utils.{GraphCleaningFunctions, IdentifierFactory, OafMapperUtils, PidType} import eu.dnetlib.dhp.schema.oaf.utils.{GraphCleaningFunctions, IdentifierFactory, OafMapperUtils, PidType}
import eu.dnetlib.dhp.schema.oaf._
import scala.collection.JavaConverters._
import java.util.regex.Pattern import java.util.regex.Pattern
import scala.collection.JavaConverters._
object PubMedToOaf { object PubMedToOaf {
@ -71,7 +72,7 @@ object PubMedToOaf {
if (article.getPublicationTypes == null) if (article.getPublicationTypes == null)
return null return null
val i = new Instance val i = new Instance
var pidList: List[StructuredProperty] = List(OafMapperUtils.structuredProperty(article.getPmid, PidType.pmid.toString, PidType.pmid.toString, ModelConstants.DNET_PID_TYPES, ModelConstants.DNET_PID_TYPES, dataInfo)) val pidList: List[StructuredProperty] = List(OafMapperUtils.structuredProperty(article.getPmid, PidType.pmid.toString, PidType.pmid.toString, ModelConstants.DNET_PID_TYPES, ModelConstants.DNET_PID_TYPES, dataInfo))
if (pidList == null) if (pidList == null)
return null return null
@ -105,7 +106,7 @@ object PubMedToOaf {
if (alternateIdentifier != null) if (alternateIdentifier != null)
i.setAlternateIdentifier(List(alternateIdentifier).asJava) i.setAlternateIdentifier(List(alternateIdentifier).asJava)
result.setInstance(List(i).asJava) result.setInstance(List(i).asJava)
i.getPid.asScala.filter(p => "pmid".equalsIgnoreCase(p.getQualifier.getClassid)).map(p => p.getValue)(collection breakOut) i.getPid.asScala.filter(p => "pmid".equalsIgnoreCase(p.getQualifier.getClassid)).map(p => p.getValue)(collection.breakOut)
val urlLists: List[String] = pidList val urlLists: List[String] = pidList
.map(s => (urlMap.getOrElse(s.getQualifier.getClassid, ""), s.getValue)) .map(s => (urlMap.getOrElse(s.getQualifier.getClassid, ""), s.getValue))
.filter(t => t._1.nonEmpty) .filter(t => t._1.nonEmpty)
@ -136,7 +137,7 @@ object PubMedToOaf {
} }
val subjects: List[StructuredProperty] = article.getSubjects.asScala.map(s => OafMapperUtils.structuredProperty(s.getValue, SUBJ_CLASS, SUBJ_CLASS, ModelConstants.DNET_SUBJECT_TYPOLOGIES, ModelConstants.DNET_SUBJECT_TYPOLOGIES, dataInfo))(collection breakOut) val subjects: List[StructuredProperty] = article.getSubjects.asScala.map(s => OafMapperUtils.structuredProperty(s.getValue, SUBJ_CLASS, SUBJ_CLASS, ModelConstants.DNET_SUBJECT_TYPOLOGIES, ModelConstants.DNET_SUBJECT_TYPOLOGIES, dataInfo))(collection.breakOut)
if (subjects != null) if (subjects != null)
result.setSubject(subjects.asJava) result.setSubject(subjects.asJava)
@ -148,7 +149,7 @@ object PubMedToOaf {
author.setFullname(a.getFullName) author.setFullname(a.getFullName)
author.setRank(index + 1) author.setRank(index + 1)
author author
}(collection breakOut) }(collection.breakOut)
if (authors != null && authors.nonEmpty) if (authors != null && authors.nonEmpty)

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@ -0,0 +1,33 @@
[
{
"paramName":"s",
"paramLongName":"sourcePath",
"paramDescription": "the path of the sequencial file to read",
"paramRequired": true
},
{
"paramName":"out",
"paramLongName":"outputPath",
"paramDescription": "the output path",
"paramRequired": true
},
{
"paramName": "ssm",
"paramLongName": "isSparkSessionManaged",
"paramDescription": "true if the spark session is managed, false otherwise",
"paramRequired": false
},
{
"paramName": "hnn",
"paramLongName": "hdfsNameNode",
"paramDescription": "the path used to store the HostedByMap",
"paramRequired": true
},
{
"paramName": "cfn",
"paramLongName": "classForName",
"paramDescription": "the path used to store the HostedByMap",
"paramRequired": true
}
]

View File

@ -0,0 +1,30 @@
<configuration>
<property>
<name>jobTracker</name>
<value>yarnRM</value>
</property>
<property>
<name>nameNode</name>
<value>hdfs://nameservice1</value>
</property>
<property>
<name>oozie.use.system.libpath</name>
<value>true</value>
</property>
<property>
<name>hiveMetastoreUris</name>
<value>thrift://iis-cdh5-test-m3.ocean.icm.edu.pl:9083</value>
</property>
<property>
<name>hiveJdbcUrl</name>
<value>jdbc:hive2://iis-cdh5-test-m3.ocean.icm.edu.pl:10000</value>
</property>
<property>
<name>hiveDbName</name>
<value>openaire</value>
</property>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>

View File

@ -0,0 +1,174 @@
<workflow-app name="UnresolvedEntities" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>fosPath</name>
<description>the input path of the resources to be extended</description>
</property>
<property>
<name>bipScorePath</name>
<description>the path where to find the bipFinder scores</description>
</property>
<property>
<name>outputPath</name>
<description>the path where to store the actionset</description>
</property>
<property>
<name>sparkDriverMemory</name>
<description>memory for driver process</description>
</property>
<property>
<name>sparkExecutorMemory</name>
<description>memory for individual executor</description>
</property>
<property>
<name>sparkExecutorCores</name>
<description>number of cores used by single executor</description>
</property>
<property>
<name>oozieActionShareLibForSpark2</name>
<description>oozie action sharelib for spark 2.*</description>
</property>
<property>
<name>spark2ExtraListeners</name>
<value>com.cloudera.spark.lineage.NavigatorAppListener</value>
<description>spark 2.* extra listeners classname</description>
</property>
<property>
<name>spark2SqlQueryExecutionListeners</name>
<value>com.cloudera.spark.lineage.NavigatorQueryListener</value>
<description>spark 2.* sql query execution listeners classname</description>
</property>
<property>
<name>spark2YarnHistoryServerAddress</name>
<description>spark 2.* yarn history server address</description>
</property>
<property>
<name>spark2EventLogDir</name>
<description>spark 2.* event log dir location</description>
</property>
</parameters>
<global>
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<configuration>
<property>
<name>mapreduce.job.queuename</name>
<value>${queueName}</value>
</property>
<property>
<name>oozie.launcher.mapred.job.queue.name</name>
<value>${oozieLauncherQueueName}</value>
</property>
<property>
<name>oozie.action.sharelib.for.spark</name>
<value>${oozieActionShareLibForSpark2}</value>
</property>
</configuration>
</global>
<start to="prepareInfo"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<fork name="prepareInfo">
<path start="prepareBip"/>
<path start="getFOS"/>
</fork>
<action name="prepareBip">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Produces the unresolved from bip finder!</name>
<class>eu.dnetlib.dhp.actionmanager.createunresolvedentities.PrepareBipFinder</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${bipScorePath}</arg>
<arg>--outputPath</arg><arg>${workingDir}/prepared</arg>
</spark>
<ok to="join"/>
<error to="Kill"/>
</action>
<action name="getFOS">
<java>
<main-class>eu.dnetlib.dhp.actionmanager.createunresolvedentities.GetFOSData</main-class>
<arg>--hdfsNameNode</arg><arg>${nameNode}</arg>
<arg>--sourcePath</arg><arg>${fosPath}</arg>
<arg>--outputPath</arg><arg>${workingDir}/input/fos</arg>
<arg>--classForName</arg><arg>eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.FOSDataModel</arg>
</java>
<ok to="prepareFos"/>
<error to="Kill"/>
</action>
<action name="prepareFos">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Produces the unresolved from FOS!</name>
<class>eu.dnetlib.dhp.actionmanager.createunresolvedentities.PrepareFOSSparkJob</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${workingDir}/input/fos</arg>
<arg>--outputPath</arg><arg>${workingDir}/prepared</arg>
</spark>
<ok to="join"/>
<error to="Kill"/>
</action>
<join name="join" to="produceUnresolved"/>
<action name="produceUnresolved">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Saves the result produced for bip and fos by grouping results with the same id</name>
<class>eu.dnetlib.dhp.actionmanager.createunresolvedentities.SparkSaveUnresolved</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${workingDir}/prepared</arg>
<arg>--outputPath</arg><arg>${outputPath}</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

View File

@ -0,0 +1,20 @@
[
{
"paramName": "issm",
"paramLongName": "isSparkSessionManaged",
"paramDescription": "when true will stop SparkSession after job execution",
"paramRequired": false
},
{
"paramName": "sp",
"paramLongName": "sourcePath",
"paramDescription": "the URL from where to get the programme file",
"paramRequired": true
},
{
"paramName": "o",
"paramLongName": "outputPath",
"paramDescription": "the path of the new ActionSet",
"paramRequired": true
}
]

View File

@ -0,0 +1,20 @@
[
{
"paramName": "issm",
"paramLongName": "isSparkSessionManaged",
"paramDescription": "when true will stop SparkSession after job execution",
"paramRequired": false
},
{
"paramName": "sp",
"paramLongName": "sourcePath",
"paramDescription": "the URL from where to get the programme file",
"paramRequired": true
},
{
"paramName": "o",
"paramLongName": "outputPath",
"paramDescription": "the path of the new ActionSet",
"paramRequired": true
}
]

View File

@ -1,81 +0,0 @@
<workflow-app name="Import_Datacite_and_transform_to_OAF" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>mainPath</name>
<description>the working path of Datacite stores</description>
</property>
<property>
<name>isLookupUrl</name>
<description>The IS lookUp service endopoint</description>
</property>
<property>
<name>blocksize</name>
<value>100</value>
<description>The request block size</description>
</property>
</parameters>
<start to="ImportDatacite"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="ImportDatacite">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>ImportDatacite</name>
<class>eu.dnetlib.dhp.actionmanager.datacite.ImportDatacite</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--targetPath</arg><arg>${mainPath}/datacite_update</arg>
<arg>--dataciteDumpPath</arg><arg>${mainPath}/datacite_dump</arg>
<arg>--namenode</arg><arg>${nameNode}</arg>
<arg>--master</arg><arg>yarn-cluster</arg>
<arg>--blocksize</arg><arg>${blocksize}</arg>
</spark>
<ok to="TransformJob"/>
<error to="Kill"/>
</action>
<action name="TransformJob">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>TransformJob</name>
<class>eu.dnetlib.dhp.actionmanager.datacite.GenerateDataciteDatasetSpark</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${mainPath}/datacite_dump</arg>
<arg>--targetPath</arg><arg>${mainPath}/datacite_oaf</arg>
<arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
<arg>--exportLinks</arg><arg>false</arg>
<arg>--master</arg><arg>yarn-cluster</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

View File

@ -1,84 +0,0 @@
<workflow-app name="Generate_Datacite_and_Crossref_dump_for_Scholexplorer" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>datacitePath</name>
<description>the path of Datacite spark dataset</description>
</property>
<property>
<name>isLookupUrl</name>
<description>The IS lookUp service endopoint</description>
</property>
<property>
<name>crossrefPath</name>
<description>the path of Crossref spark dataset</description>
</property>
<property>
<name>targetPath</name>
<description>the path of Crossref spark dataset</description>
</property>
</parameters>
<start to="ImportDatacite"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="ImportDatacite">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>ImportDatacite</name>
<class>eu.dnetlib.dhp.actionmanager.datacite.GenerateDataciteDatasetSpark</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${datacitePath}</arg>
<arg>--targetPath</arg><arg>${targetPath}/datacite_oaf</arg>
<arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
<arg>--exportLinks</arg><arg>true</arg>
<arg>--master</arg><arg>yarn-cluster</arg>
</spark>
<ok to="FilterCrossrefEntities"/>
<error to="Kill"/>
</action>
<action name="FilterCrossrefEntities">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>FilterCrossrefEntities</name>
<class>eu.dnetlib.dhp.actionmanager.datacite.FilterCrossrefEntitiesSpark</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${crossrefPath}</arg>
<arg>--targetPath</arg><arg>${targetPath}/crossref_oaf</arg>
<arg>--master</arg><arg>yarn-cluster</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

View File

@ -1,46 +1,52 @@
<workflow-app name="Datacite_to_ActionSet_Workflow" xmlns="uri:oozie:workflow:0.5"> <workflow-app name="Collect_Datacite" xmlns="uri:oozie:workflow:0.5">
<parameters> <parameters>
<property> <property>
<name>sourcePath</name> <name>mainPath</name>
<description>the working path of Datacite stores</description> <description>the working path of Datacite stores</description>
</property> </property>
<property> <property>
<name>outputPath</name> <name>isLookupUrl</name>
<description>the path of Datacite ActionSet</description> <description>The IS lookUp service endopoint</description>
</property> </property>
<property>
<name>blocksize</name>
<value>100</value>
<description>The request block size</description>
</property>
</parameters> </parameters>
<start to="ExportDataset"/> <start to="ImportDatacite"/>
<kill name="Kill"> <kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message> <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill> </kill>
<action name="ExportDataset"> <action name="ImportDatacite">
<spark xmlns="uri:oozie:spark-action:0.2"> <spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master> <master>yarn-cluster</master>
<mode>cluster</mode> <mode>cluster</mode>
<name>ExportDataset</name> <name>ImportDatacite</name>
<class>eu.dnetlib.dhp.actionmanager.datacite.ExportActionSetJobNode</class> <class>eu.dnetlib.dhp.datacite.ImportDatacite</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar> <jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts> <spark-opts>
--executor-memory=${sparkExecutorMemory} --executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840
--conf spark.extraListeners=${spark2ExtraListeners} --conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--sourcePath</arg><arg>${sourcePath}</arg> <arg>--targetPath</arg><arg>${mainPath}/datacite_update</arg>
<arg>--targetPath</arg><arg>${outputPath}</arg> <arg>--dataciteDumpPath</arg><arg>${mainPath}/datacite_dump</arg>
<arg>--namenode</arg><arg>${nameNode}</arg>
<arg>--master</arg><arg>yarn-cluster</arg> <arg>--master</arg><arg>yarn-cluster</arg>
<arg>--blocksize</arg><arg>${blocksize}</arg>
</spark> </spark>
<ok to="End"/> <ok to="End"/>
<error to="Kill"/> <error to="Kill"/>
</action> </action>
<end name="End"/> <end name="End"/>
</workflow-app> </workflow-app>

View File

@ -7,8 +7,8 @@
}, },
{ {
"paramName": "t", "paramName": "mo",
"paramLongName": "targetPath", "paramLongName": "mdstoreOutputVersion",
"paramDescription": "the target mdstore path", "paramDescription": "the target mdstore path",
"paramRequired": true "paramRequired": true
}, },

View File

@ -0,0 +1,126 @@
<workflow-app name="transform_Datacite" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>mainPath</name>
<description>the working path of Datacite stores</description>
</property>
<property>
<name>isLookupUrl</name>
<description>The IS lookUp service endopoint</description>
</property>
<property>
<name>mdStoreOutputId</name>
<description>the identifier of the cleaned MDStore</description>
</property>
<property>
<name>mdStoreManagerURI</name>
<description>the path of the cleaned mdstore</description>
</property>
</parameters>
<start to="StartTransaction"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="StartTransaction">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>NEW_VERSION</arg>
<arg>--mdStoreID</arg><arg>${mdStoreOutputId}</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
<capture-output/>
</java>
<ok to="TransformJob"/>
<error to="EndReadRollBack"/>
</action>
<action name="TransformJob">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>TransformJob</name>
<class>eu.dnetlib.dhp.datacite.GenerateDataciteDatasetSpark</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${mainPath}/datacite_dump</arg>
<arg>--mdstoreOutputVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
<arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
<arg>--exportLinks</arg><arg>true</arg>
<arg>--master</arg><arg>yarn-cluster</arg>
</spark>
<ok to="CommitVersion"/>
<error to="Kill"/>
</action>
<action name="CommitVersion">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>COMMIT</arg>
<arg>--namenode</arg><arg>${nameNode}</arg>
<arg>--mdStoreVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
</java>
<ok to="End"/>
<error to="Kill"/>
</action>
<action name="EndReadRollBack">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>READ_UNLOCK</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
<arg>--readMDStoreId</arg><arg>${wf:actionData('BeginRead')['mdStoreReadLockVersion']}</arg>
<capture-output/>
</java>
<ok to="RollBack"/>
<error to="Kill"/>
</action>
<action name="RollBack">
<java>
<configuration>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>
<main-class>eu.dnetlib.dhp.aggregation.mdstore.MDStoreActionNode</main-class>
<arg>--action</arg><arg>ROLLBACK</arg>
<arg>--mdStoreVersion</arg><arg>${wf:actionData('StartTransaction')['mdStoreVersion']}</arg>
<arg>--mdStoreManagerURI</arg><arg>${mdStoreManagerURI}</arg>
</java>
<ok to="Kill"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

View File

@ -1,42 +1,33 @@
<workflow-app name="Create EBI Dataset" xmlns="uri:oozie:workflow:0.5"> <workflow-app name="Transform_BioEntity_Workflow" xmlns="uri:oozie:workflow:0.5">
<parameters> <parameters>
<property> <property>
<name>sourcePath</name> <name>sourcePath</name>
<description>the Working Path</description> <description>the PDB Database Working Path</description>
</property> </property>
<property> <property>
<name>workingPath</name> <name>database</name>
<description>the Working Path</description> <description>the PDB Database Working Path</description>
</property> </property>
<property> <property>
<name>sparkDriverMemory</name> <name>targetPath</name>
<description>memory for driver process</description> <description>the Target Working dir path</description>
</property>
<property>
<name>sparkExecutorMemory</name>
<description>memory for individual executor</description>
</property>
<property>
<name>sparkExecutorCores</name>
<description>number of cores used by single executor</description>
</property> </property>
</parameters> </parameters>
<start to="DownloadEBILinks"/> <start to="ConvertDB"/>
<kill name="Kill"> <kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message> <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill> </kill>
<action name="ConvertDB">
<action name="DownloadEBILinks">
<spark xmlns="uri:oozie:spark-action:0.2"> <spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master> <master>yarn</master>
<mode>cluster</mode> <mode>cluster</mode>
<name>Incremental Download EBI Links</name> <name>Convert Bio DB to OAF Dataset</name>
<class>eu.dnetlib.dhp.sx.graph.ebi.SparkDownloadEBILinks</class> <class>eu.dnetlib.dhp.sx.bio.SparkTransformBioDatabaseToOAF</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar> <jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts> <spark-opts>
--executor-memory=${sparkExecutorMemory} --executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
@ -47,13 +38,14 @@
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--sourcePath</arg><arg>${sourcePath}</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>--master</arg><arg>yarn</arg> <arg>--master</arg><arg>yarn</arg>
<arg>--dbPath</arg><arg>${sourcePath}</arg>
<arg>--database</arg><arg>${database}</arg>
<arg>--targetPath</arg><arg>${targetPath}</arg>
</spark> </spark>
<ok to="End"/> <ok to="End"/>
<error to="Kill"/> <error to="Kill"/>
</action> </action>
<end name="End"/> <end name="End"/>
</workflow-app> </workflow-app>

View File

@ -0,0 +1,8 @@
[
{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
{"paramName":"i", "paramLongName":"isLookupUrl", "paramDescription": "isLookupUrl", "paramRequired": true},
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the path of the sequencial file to read", "paramRequired": true},
{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the oaf path ", "paramRequired": true},
{"paramName":"s", "paramLongName":"skipUpdate", "paramDescription": "skip update ", "paramRequired": false},
{"paramName":"h", "paramLongName":"hdfsServerUri", "paramDescription": "the working path ", "paramRequired": true}
]

View File

@ -0,0 +1,5 @@
[
{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the source Path", "paramRequired": true},
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the working path ", "paramRequired": true}
]

View File

@ -0,0 +1,105 @@
<workflow-app name="Create EBI Dataset" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>sourcePath</name>
<description>the Working Path</description>
</property>
<property>
<name>workingPath</name>
<description>the Working Path</description>
</property>
<property>
<name>targetPath</name>
<description>the OAF MDStore Path</description>
</property>
<property>
<name>sparkDriverMemory</name>
<description>memory for driver process</description>
</property>
<property>
<name>sparkExecutorMemory</name>
<description>memory for individual executor</description>
</property>
<property>
<name>sparkExecutorCores</name>
<description>number of cores used by single executor</description>
</property>
<property>
<name>resumeFrom</name>
<value>DownloadEBILinks</value>
<description>node to start</description>
</property>
</parameters>
<start to="resume_from"/>
<decision name="resume_from">
<switch>
<case to="DownloadEBILinks">${wf:conf('resumeFrom') eq 'DownloadEBILinks'}</case>
<case to="CreateEBIDataSet">${wf:conf('resumeFrom') eq 'CreateEBIDataSet'}</case>
<default to="DownloadEBILinks"/>
</switch>
</decision>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="DownloadEBILinks">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Incremental Download EBI Links</name>
<class>eu.dnetlib.dhp.sx.bio.ebi.SparkDownloadEBILinks</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.shuffle.partitions=2000
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${sourcePath}</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>--master</arg><arg>yarn</arg>
</spark>
<ok to="OverrideFolders"/>
<error to="Kill"/>
</action>
<action name="OverrideFolders">
<fs>
<delete path="${sourcePath}/ebi_links_dataset_old"/>
<move source="${sourcePath}/ebi_links_dataset" target="${sourcePath}/ebi_links_dataset_old"/>
<move source="${workingPath}/links_final" target="${sourcePath}/ebi_links_dataset"/>
</fs>
<ok to="CreateEBIDataSet"/>
<error to="Kill"/>
</action>
<action name="CreateEBIDataSet">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Create OAF DataSet</name>
<class>eu.dnetlib.dhp.sx.bio.ebi.SparkEBILinksToOaf</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=2000
${sparkExtraOPT}
</spark-opts>
<arg>--sourcePath</arg><arg>${sourcePath}/ebi_links_dataset</arg>
<arg>--targetPath</arg><arg>${targetPath}</arg>
<arg>--master</arg><arg>yarn</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

View File

@ -1,17 +1,22 @@
<workflow-app name="Transform_Pubmed_Workflow" xmlns="uri:oozie:workflow:0.5"> <workflow-app name="Download_Transform_Pubmed_Workflow" xmlns="uri:oozie:workflow:0.5">
<parameters> <parameters>
<property> <property>
<name>baselineWorkingPath</name> <name>baselineWorkingPath</name>
<description>the Baseline Working Path</description> <description>the Baseline Working Path</description>
</property> </property>
<property>
<name>targetPath</name>
<description>the Target Path</description>
</property>
<property> <property>
<name>isLookupUrl</name> <name>isLookupUrl</name>
<description>The IS lookUp service endopoint</description> <description>The IS lookUp service endopoint</description>
</property> </property>
<property>
<name>targetPath</name>
<description>The target path</description>
</property>
<property>
<name>skipUpdate</name>
<value>false</value>
<description>The request block size</description>
</property>
</parameters> </parameters>
<start to="ConvertDataset"/> <start to="ConvertDataset"/>
@ -24,9 +29,9 @@
<spark xmlns="uri:oozie:spark-action:0.2"> <spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master> <master>yarn</master>
<mode>cluster</mode> <mode>cluster</mode>
<name>Convert Baseline to Dataset</name> <name>Convert Baseline to OAF Dataset</name>
<class>eu.dnetlib.dhp.sx.graph.ebi.SparkCreateBaselineDataFrame</class> <class>eu.dnetlib.dhp.sx.bio.ebi.SparkCreateBaselineDataFrame</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar> <jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts> <spark-opts>
--executor-memory=${sparkExecutorMemory} --executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
@ -41,6 +46,8 @@
<arg>--targetPath</arg><arg>${targetPath}</arg> <arg>--targetPath</arg><arg>${targetPath}</arg>
<arg>--master</arg><arg>yarn</arg> <arg>--master</arg><arg>yarn</arg>
<arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg> <arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
<arg>--hdfsServerUri</arg><arg>${nameNode}</arg>
<arg>--skipUpdate</arg><arg>${skipUpdate}</arg>
</spark> </spark>
<ok to="End"/> <ok to="End"/>
<error to="Kill"/> <error to="Kill"/>

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@ -0,0 +1,250 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
import static org.junit.jupiter.api.Assertions.*;
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.stream.Collectors;
import org.apache.commons.io.FileUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocalFileSystem;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.SparkSession;
import org.junit.jupiter.api.AfterAll;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Test;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.FOSDataModel;
import eu.dnetlib.dhp.common.collection.CollectorException;
import eu.dnetlib.dhp.schema.oaf.Result;
public class PrepareTest {
private static final Logger log = LoggerFactory.getLogger(ProduceTest.class);
private static Path workingDir;
private static SparkSession spark;
private static LocalFileSystem fs;
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
@BeforeAll
public static void beforeAll() throws IOException {
workingDir = Files.createTempDirectory(PrepareTest.class.getSimpleName());
fs = FileSystem.getLocal(new Configuration());
log.info("using work dir {}", workingDir);
SparkConf conf = new SparkConf();
conf.setAppName(ProduceTest.class.getSimpleName());
conf.setMaster("local[*]");
conf.set("spark.driver.host", "localhost");
conf.set("hive.metastore.local", "true");
conf.set("spark.ui.enabled", "false");
conf.set("spark.sql.warehouse.dir", workingDir.toString());
conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString());
spark = SparkSession
.builder()
.appName(PrepareTest.class.getSimpleName())
.config(conf)
.getOrCreate();
}
@AfterAll
public static void afterAll() throws IOException {
FileUtils.deleteDirectory(workingDir.toFile());
spark.stop();
}
@Test
void bipPrepareTest() throws Exception {
final String sourcePath = getClass()
.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/bip/bip.json")
.getPath();
PrepareBipFinder
.main(
new String[] {
"--isSparkSessionManaged", Boolean.FALSE.toString(),
"--sourcePath", sourcePath,
"--outputPath", workingDir.toString() + "/work"
});
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
JavaRDD<Result> tmp = sc
.textFile(workingDir.toString() + "/work/bip")
.map(item -> OBJECT_MAPPER.readValue(item, Result.class));
Assertions.assertEquals(86, tmp.count());
String doi1 = "unresolved::10.0000/096020199389707::doi";
Assertions.assertEquals(1, tmp.filter(r -> r.getId().equals(doi1)).count());
Assertions.assertEquals(3, tmp.filter(r -> r.getId().equals(doi1)).collect().get(0).getMeasures().size());
Assertions
.assertEquals(
"6.34596412687e-09", tmp
.filter(r -> r.getId().equals(doi1))
.collect()
.get(0)
.getMeasures()
.stream()
.filter(sl -> sl.getId().equals("influence"))
.collect(Collectors.toList())
.get(0)
.getUnit()
.get(0)
.getValue());
Assertions
.assertEquals(
"0.641151896994", tmp
.filter(r -> r.getId().equals(doi1))
.collect()
.get(0)
.getMeasures()
.stream()
.filter(sl -> sl.getId().equals("popularity_alt"))
.collect(Collectors.toList())
.get(0)
.getUnit()
.get(0)
.getValue());
Assertions
.assertEquals(
"2.33375102921e-09", tmp
.filter(r -> r.getId().equals(doi1))
.collect()
.get(0)
.getMeasures()
.stream()
.filter(sl -> sl.getId().equals("popularity"))
.collect(Collectors.toList())
.get(0)
.getUnit()
.get(0)
.getValue());
}
@Test
void getFOSFileTest() throws IOException, ClassNotFoundException {
final String sourcePath = getClass()
.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/fos/h2020_fos_sbs.csv")
.getPath();
final String outputPath = workingDir.toString() + "/fos.json";
new GetFOSData()
.doRewrite(
sourcePath, outputPath, "eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.FOSDataModel",
'\t', fs);
BufferedReader in = new BufferedReader(
new InputStreamReader(fs.open(new org.apache.hadoop.fs.Path(outputPath))));
String line;
int count = 0;
while ((line = in.readLine()) != null) {
FOSDataModel fos = new ObjectMapper().readValue(line, FOSDataModel.class);
System.out.println(new ObjectMapper().writeValueAsString(fos));
count += 1;
}
assertEquals(38, count);
}
@Test
void fosPrepareTest() throws Exception {
final String sourcePath = getClass()
.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/fos/fos.json")
.getPath();
PrepareFOSSparkJob
.main(
new String[] {
"--isSparkSessionManaged", Boolean.FALSE.toString(),
"--sourcePath", sourcePath,
"-outputPath", workingDir.toString() + "/work"
});
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
JavaRDD<Result> tmp = sc
.textFile(workingDir.toString() + "/work/fos")
.map(item -> OBJECT_MAPPER.readValue(item, Result.class));
String doi1 = "unresolved::10.3390/s18072310::doi";
assertEquals(50, tmp.count());
assertEquals(1, tmp.filter(row -> row.getId().equals(doi1)).count());
assertTrue(
tmp
.filter(r -> r.getId().equals(doi1))
.flatMap(r -> r.getSubject().iterator())
.map(sbj -> sbj.getValue())
.collect()
.contains("engineering and technology"));
assertTrue(
tmp
.filter(r -> r.getId().equals(doi1))
.flatMap(r -> r.getSubject().iterator())
.map(sbj -> sbj.getValue())
.collect()
.contains("nano-technology"));
assertTrue(
tmp
.filter(r -> r.getId().equals(doi1))
.flatMap(r -> r.getSubject().iterator())
.map(sbj -> sbj.getValue())
.collect()
.contains("nanoscience & nanotechnology"));
String doi = "unresolved::10.1111/1365-2656.12831::doi";
assertEquals(1, tmp.filter(row -> row.getId().equals(doi)).count());
assertTrue(
tmp
.filter(r -> r.getId().equals(doi))
.flatMap(r -> r.getSubject().iterator())
.map(sbj -> sbj.getValue())
.collect()
.contains("psychology and cognitive sciences"));
assertTrue(
tmp
.filter(r -> r.getId().equals(doi))
.flatMap(r -> r.getSubject().iterator())
.map(sbj -> sbj.getValue())
.collect()
.contains("social sciences"));
assertFalse(
tmp
.filter(r -> r.getId().equals(doi))
.flatMap(r -> r.getSubject().iterator())
.map(sbj -> sbj.getValue())
.collect()
.contains("NULL"));
}
}

View File

@ -0,0 +1,234 @@
package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.List;
import java.util.stream.Collectors;
import org.apache.commons.io.FileUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocalFileSystem;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.SparkSession;
import org.junit.jupiter.api.AfterAll;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Test;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.oaf.*;
public class ProduceTest {
private static final Logger log = LoggerFactory.getLogger(ProduceTest.class);
private static Path workingDir;
private static SparkSession spark;
private static LocalFileSystem fs;
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
private static final String ID_PREFIX = "50|doi_________";
@BeforeAll
public static void beforeAll() throws IOException {
workingDir = Files.createTempDirectory(ProduceTest.class.getSimpleName());
fs = FileSystem.getLocal(new Configuration());
log.info("using work dir {}", workingDir);
SparkConf conf = new SparkConf();
conf.setAppName(ProduceTest.class.getSimpleName());
conf.setMaster("local[*]");
conf.set("spark.driver.host", "localhost");
conf.set("hive.metastore.local", "true");
conf.set("spark.ui.enabled", "false");
conf.set("spark.sql.warehouse.dir", workingDir.toString());
conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString());
spark = SparkSession
.builder()
.appName(ProduceTest.class.getSimpleName())
.config(conf)
.getOrCreate();
}
@AfterAll
public static void afterAll() throws IOException {
FileUtils.deleteDirectory(workingDir.toFile());
spark.stop();
}
@Test
void produceTest() throws Exception {
final String bipPath = getClass()
.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/bip/bip.json")
.getPath();
PrepareBipFinder
.main(
new String[] {
"--isSparkSessionManaged", Boolean.FALSE.toString(),
"--sourcePath", bipPath,
"--outputPath", workingDir.toString() + "/work"
});
final String fosPath = getClass()
.getResource("/eu/dnetlib/dhp/actionmanager/createunresolvedentities/fos/fos.json")
.getPath();
PrepareFOSSparkJob
.main(
new String[] {
"--isSparkSessionManaged", Boolean.FALSE.toString(),
"--sourcePath", fosPath,
"-outputPath", workingDir.toString() + "/work"
});
SparkSaveUnresolved.main(new String[] {
"--isSparkSessionManaged", Boolean.FALSE.toString(),
"--sourcePath", workingDir.toString() + "/work",
"-outputPath", workingDir.toString() + "/unresolved"
});
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
JavaRDD<Result> tmp = sc
.textFile(workingDir.toString() + "/unresolved")
.map(item -> OBJECT_MAPPER.readValue(item, Result.class));
Assertions.assertEquals(135, tmp.count());
Assertions.assertEquals(1, tmp.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi")).count());
Assertions
.assertEquals(
3, tmp
.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi"))
.collect()
.get(0)
.getSubject()
.size());
Assertions
.assertEquals(
3, tmp
.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi"))
.collect()
.get(0)
.getMeasures()
.size());
List<StructuredProperty> sbjs = tmp
.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi"))
.flatMap(row -> row.getSubject().iterator())
.collect();
sbjs.forEach(sbj -> Assertions.assertEquals("FOS", sbj.getQualifier().getClassid()));
sbjs
.forEach(
sbj -> Assertions
.assertEquals(
"Fields of Science and Technology classification", sbj.getQualifier().getClassname()));
sbjs
.forEach(
sbj -> Assertions
.assertEquals(ModelConstants.DNET_SUBJECT_TYPOLOGIES, sbj.getQualifier().getSchemeid()));
sbjs
.forEach(
sbj -> Assertions
.assertEquals(ModelConstants.DNET_SUBJECT_TYPOLOGIES, sbj.getQualifier().getSchemename()));
sbjs.forEach(sbj -> Assertions.assertEquals(false, sbj.getDataInfo().getDeletedbyinference()));
sbjs.forEach(sbj -> Assertions.assertEquals(true, sbj.getDataInfo().getInferred()));
sbjs.forEach(sbj -> Assertions.assertEquals(false, sbj.getDataInfo().getInvisible()));
sbjs.forEach(sbj -> Assertions.assertEquals("", sbj.getDataInfo().getTrust()));
sbjs.forEach(sbj -> Assertions.assertEquals("update", sbj.getDataInfo().getInferenceprovenance()));
sbjs
.forEach(
sbj -> Assertions.assertEquals("subject:fos", sbj.getDataInfo().getProvenanceaction().getClassid()));
sbjs
.forEach(
sbj -> Assertions
.assertEquals("Inferred by OpenAIRE", sbj.getDataInfo().getProvenanceaction().getClassname()));
sbjs
.forEach(
sbj -> Assertions
.assertEquals(
ModelConstants.DNET_PROVENANCE_ACTIONS, sbj.getDataInfo().getProvenanceaction().getSchemeid()));
sbjs
.forEach(
sbj -> Assertions
.assertEquals(
ModelConstants.DNET_PROVENANCE_ACTIONS,
sbj.getDataInfo().getProvenanceaction().getSchemename()));
sbjs.stream().anyMatch(sbj -> sbj.getValue().equals("engineering and technology"));
sbjs.stream().anyMatch(sbj -> sbj.getValue().equals("nano-technology"));
sbjs.stream().anyMatch(sbj -> sbj.getValue().equals("nanoscience & nanotechnology"));
List<Measure> measures = tmp
.filter(row -> row.getId().equals("unresolved::10.3390/s18072310::doi"))
.flatMap(row -> row.getMeasures().iterator())
.collect();
Assertions
.assertEquals(
"7.5597134689e-09", measures
.stream()
.filter(mes -> mes.getId().equals("influence"))
.collect(Collectors.toList())
.get(0)
.getUnit()
.get(0)
.getValue());
Assertions
.assertEquals(
"4.903880192", measures
.stream()
.filter(mes -> mes.getId().equals("popularity_alt"))
.collect(Collectors.toList())
.get(0)
.getUnit()
.get(0)
.getValue());
Assertions
.assertEquals(
"1.17977512835e-08", measures
.stream()
.filter(mes -> mes.getId().equals("popularity"))
.collect(Collectors.toList())
.get(0)
.getUnit()
.get(0)
.getValue());
Assertions
.assertEquals(
49, tmp
.filter(row -> !row.getId().equals("unresolved::10.3390/s18072310::doi"))
.filter(row -> row.getSubject() != null)
.count());
Assertions
.assertEquals(
85,
tmp
.filter(row -> !row.getId().equals("unresolved::10.3390/s18072310::doi"))
.filter(r -> r.getMeasures() != null)
.count());
}
}

View File

@ -1,8 +1,7 @@
package eu.dnetlib.dhp.actionmanager.datacite package eu.dnetlib.dhp.datacite
import com.fasterxml.jackson.databind.ObjectMapper import com.fasterxml.jackson.databind.{ObjectMapper, SerializationFeature}
import com.fasterxml.jackson.databind.SerializationFeature
import eu.dnetlib.dhp.aggregation.AbstractVocabularyTest import eu.dnetlib.dhp.aggregation.AbstractVocabularyTest
import eu.dnetlib.dhp.schema.oaf.Oaf import eu.dnetlib.dhp.schema.oaf.Oaf
import org.junit.jupiter.api.extension.ExtendWith import org.junit.jupiter.api.extension.ExtendWith

View File

@ -1,12 +1,10 @@
package eu.dnetlib.dhp.sx.graph.bio.pubmed package eu.dnetlib.dhp.sx.bio
import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper, SerializationFeature} import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper, SerializationFeature}
import eu.dnetlib.dhp.schema.common.ModelConstants import eu.dnetlib.dhp.aggregation.AbstractVocabularyTest
import eu.dnetlib.dhp.schema.oaf.utils.{CleaningFunctions, OafMapperUtils, PidType}
import eu.dnetlib.dhp.schema.oaf.{Oaf, Relation, Result} import eu.dnetlib.dhp.schema.oaf.{Oaf, Relation, Result}
import eu.dnetlib.dhp.sx.graph.bio.BioDBToOAF.ScholixResolved import eu.dnetlib.dhp.sx.bio.BioDBToOAF.ScholixResolved
import eu.dnetlib.dhp.sx.graph.bio.BioDBToOAF import eu.dnetlib.dhp.sx.bio.pubmed.{PMArticle, PMParser, PubMedToOaf}
import eu.dnetlib.dhp.sx.graph.bio.pubmed.PubMedToOaf.dataInfo
import org.json4s.DefaultFormats import org.json4s.DefaultFormats
import org.json4s.JsonAST.{JField, JObject, JString} import org.json4s.JsonAST.{JField, JObject, JString}
import org.json4s.jackson.JsonMethods.parse import org.json4s.jackson.JsonMethods.parse
@ -50,9 +48,11 @@ class BioScholixTest extends AbstractVocabularyTest{
} }
@Test @Test
def testEBIData() = { def testEBIData() = {
val inputXML = Source.fromInputStream(getClass.getResourceAsStream("pubmed.xml")).mkString val inputXML = Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/bio/pubmed.xml")).mkString
val xml = new XMLEventReader(Source.fromBytes(inputXML.getBytes())) val xml = new XMLEventReader(Source.fromBytes(inputXML.getBytes()))
new PMParser(xml).foreach(s =>println(mapper.writeValueAsString(s))) new PMParser(xml).foreach(s =>println(mapper.writeValueAsString(s)))
} }
@ -62,7 +62,7 @@ class BioScholixTest extends AbstractVocabularyTest{
def testPubmedToOaf(): Unit = { def testPubmedToOaf(): Unit = {
assertNotNull(vocabularies) assertNotNull(vocabularies)
assertTrue(vocabularies.vocabularyExists("dnet:publication_resource")) assertTrue(vocabularies.vocabularyExists("dnet:publication_resource"))
val records:String =Source.fromInputStream(getClass.getResourceAsStream("pubmed_dump")).mkString val records:String =Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/bio/pubmed_dump")).mkString
val r:List[Oaf] = records.lines.toList.map(s=>mapper.readValue(s, classOf[PMArticle])).map(a => PubMedToOaf.convert(a, vocabularies)) val r:List[Oaf] = records.lines.toList.map(s=>mapper.readValue(s, classOf[PMArticle])).map(a => PubMedToOaf.convert(a, vocabularies))
assertEquals(10, r.size) assertEquals(10, r.size)
assertTrue(r.map(p => p.asInstanceOf[Result]).flatMap(p => p.getInstance().asScala.map(i => i.getInstancetype.getClassid)).exists(p => "0037".equalsIgnoreCase(p))) assertTrue(r.map(p => p.asInstanceOf[Result]).flatMap(p => p.getInstance().asScala.map(i => i.getInstancetype.getClassid)).exists(p => "0037".equalsIgnoreCase(p)))

View File

@ -0,0 +1,86 @@
{"10.3390/s18072310": [{"id": "influence", "unit": [{"value": "7.5597134689e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "4.903880192", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "1.17977512835e-08", "key": "score"}]}]}
{"10.0000/096020199389707": [{"id": "influence", "unit": [{"value": "6.34596412687e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.641151896994", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "2.33375102921e-09", "key": "score"}]}]}
{"10.00000/jpmc.2017.106": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "5.39172290649e-09", "key": "score"}]}]}
{"10.0000/9781845416881": [{"id": "influence", "unit": [{"value": "5.96492048955e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "1.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "1.12641925838e-08", "key": "score"}]}]}
{"10.0000/anziamj.v0i0.266": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.76260934675e-10", "key": "score"}]}]}
{"10.0000/anziamj.v48i0.79": [{"id": "influence", "unit": [{"value": "6.93311506443e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.002176782336", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "1.7668105708e-09", "key": "score"}]}]}
{"10.0000/anziamj.v50i0.1472": [{"id": "influence", "unit": [{"value": "6.26777280882e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.406656", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.39745193285e-09", "key": "score"}]}]}
{"10.0000/cja5553": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
{"10.0000/czastest.16": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
{"10.0000/czastest.17": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.47956715615e-09", "key": "score"}]}]}
{"10.0000/czastest.18": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.47956715615e-09", "key": "score"}]}]}
{"10.0000/czastest.20": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.01810569717e-09", "key": "score"}]}]}
{"10.0000/czastest.21": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.47956715615e-09", "key": "score"}]}]}
{"10.0000/czastest.28": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "3.47956715615e-09", "key": "score"}]}]}
{"10.0000/czastest.60": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "4.65008652949e-09", "key": "score"}]}]}
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{"10.0000/hoplos.v4i7.42830": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
{"10.0000/hoplos.v4i7.42861": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}
{"10.0000/hoplos.v4i7.43096": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.48190886761e-09", "key": "score"}]}]}

View File

@ -0,0 +1,38 @@
{"doi":"10.3390/s18072310","level1":"engineering and technology","level2":"nano-technology","level3":"nanoscience & nanotechnology"}
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{"doi":"10.1109/ted.2018.2813542","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"electrical & electronic engineering"}
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{"doi":"10.1038/ng.3667\u000210.1038/ng.3667.\u000210.17615/tct6-4m26\u000210.17863/cam.15649","level1":"medical and health sciences","level2":"health sciences","level3":"genetics & heredity"}
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{"doi":"10.1111/pce.13392","level1":"agricultural and veterinary sciences","level2":"agriculture, forestry, and fisheries","level3":"agronomy & agriculture"}

View File

@ -0,0 +1,38 @@
dedup_wf_001::ddcc7a56fa13e49bcc59c6bdd19ad26c 10.3390/s18072310 engineering and technology nano-technology nanoscience & nanotechnology
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16 dedup_wf_001::e414c1dec599521a9635a60de0f6755b 10.21468/scipostphys.3.1.001 natural sciences physical sciences NULL
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19 dedup_wf_001::313ae1cd083ae1696d12dd1909f97df8 10.1016/j.expthermflusci.2019.10999410.17863/cam.46212 engineering and technology mechanical engineering mechanical engineering & transports
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21 doiboost____::5b79bd7bd9f87361b4a4abc3cbb2df75 10.1002/mma.6622 natural sciences mathematics numerical & computational mathematics
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25 dedup_wf_001::dd06ee7974730e7b09a4f03c83b3f9bd 10.6084/m9.figshare.991261410.6084/m9.figshare.9912614.v110.1080/00268976.2019.1665199 natural sciences chemical sciences physical chemistry
26 dedup_wf_001::027c78bef6f972b5e26dfea55d30fbe3 10.1175/jpo-d-17-0239.1 natural sciences biological sciences marine biology & hydrobiology
27 dedup_wf_001::43edc179aa9e1fbaf582c5203b18b519 10.1007/s13218-020-00674-7 engineering and technology industrial biotechnology industrial engineering & automation
28 dedup_wf_001::e7770e11cd6eb514bb52c07b5a8a80f0 10.1016/j.psyneuen.2016.02.00310.1016/j.psyneuen.2016.02.00310.7892/boris.7888610.7892/boris.78886 medical and health sciences basic medicine NULL
29 dedup_wf_001::80bc15d69bdc589149631f3439dde5aa 10.1109/ted.2018.2813542 engineering and technology electrical engineering, electronic engineering, information engineering electrical & electronic engineering
30 dedup_wf_001::42c1cfa33e7872944b920cff90f4d99e 10.3989/scimar.04739.25a natural sciences biological sciences NULL
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32 dedup_wf_001::59e43d3527dcfecb6097fbd5740c8950 10.1016/j.ccell.2018.08.017 medical and health sciences basic medicine biochemistry & molecular biology
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35 dedup_wf_001::83737ab4205bae751571bb3b166efa18 10.5281/zenodo.369655710.5281/zenodo.369655610.1109/jsac.2016.2545384 engineering and technology electrical engineering, electronic engineering, information engineering networking & telecommunications
36 dedup_wf_001::e3f892db413a689e572dd256acad55fe 10.1038/ng.366710.1038/ng.3667.10.17615/tct6-4m2610.17863/cam.15649 medical and health sciences health sciences genetics & heredity
37 dedup_wf_001::14ba594e8fd081847bc3f50f56335003 10.1016/j.jclepro.2019.119065 engineering and technology other engineering and technologies building & construction
38 dedup_wf_001::08ac7b33a41bcea2d055ecd8585d632e 10.1111/pce.13392 agricultural and veterinary sciences agriculture, forestry, and fisheries agronomy & agriculture

View File

@ -91,8 +91,8 @@ public class ReadBlacklistFromDB implements Closeable {
String encoding = rs.getString("relationship"); String encoding = rs.getString("relationship");
RelationInverse ri = ModelSupport.relationInverseMap.get(encoding); RelationInverse ri = ModelSupport.relationInverseMap.get(encoding);
direct.setRelClass(ri.getRelation()); direct.setRelClass(ri.getRelClass());
inverse.setRelClass(ri.getInverse()); inverse.setRelClass(ri.getInverseRelClass());
direct.setRelType(ri.getRelType()); direct.setRelType(ri.getRelType());
inverse.setRelType(ri.getRelType()); inverse.setRelType(ri.getRelType());
direct.setSubRelType(ri.getSubReltype()); direct.setSubRelType(ri.getSubReltype());

View File

@ -0,0 +1,154 @@
package eu.dnetlib.dhp.oa.dedup;
import java.io.IOException;
import java.util.Optional;
import org.apache.commons.io.IOUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.SaveMode;
import org.apache.spark.sql.SparkSession;
import org.dom4j.DocumentException;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.xml.sax.SAXException;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.schema.oaf.DataInfo;
import eu.dnetlib.dhp.schema.oaf.Relation;
import eu.dnetlib.dhp.utils.ISLookupClientFactory;
import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpException;
import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
import eu.dnetlib.pace.config.DedupConfig;
import eu.dnetlib.pace.model.MapDocument;
import eu.dnetlib.pace.util.MapDocumentUtil;
import scala.Tuple2;
public class SparkWhitelistSimRels extends AbstractSparkAction {
private static final Logger log = LoggerFactory.getLogger(SparkCreateSimRels.class);
private static final String WHITELIST_SEPARATOR = "####";
public SparkWhitelistSimRels(ArgumentApplicationParser parser, SparkSession spark) {
super(parser, spark);
}
public static void main(String[] args) throws Exception {
ArgumentApplicationParser parser = new ArgumentApplicationParser(
IOUtils
.toString(
SparkCreateSimRels.class
.getResourceAsStream(
"/eu/dnetlib/dhp/oa/dedup/whitelistSimRels_parameters.json")));
parser.parseArgument(args);
SparkConf conf = new SparkConf();
new SparkWhitelistSimRels(parser, getSparkSession(conf))
.run(ISLookupClientFactory.getLookUpService(parser.get("isLookUpUrl")));
}
@Override
public void run(ISLookUpService isLookUpService)
throws DocumentException, IOException, ISLookUpException, SAXException {
// read oozie parameters
final String graphBasePath = parser.get("graphBasePath");
final String isLookUpUrl = parser.get("isLookUpUrl");
final String actionSetId = parser.get("actionSetId");
final String workingPath = parser.get("workingPath");
final int numPartitions = Optional
.ofNullable(parser.get("numPartitions"))
.map(Integer::valueOf)
.orElse(NUM_PARTITIONS);
final String whiteListPath = parser.get("whiteListPath");
log.info("numPartitions: '{}'", numPartitions);
log.info("graphBasePath: '{}'", graphBasePath);
log.info("isLookUpUrl: '{}'", isLookUpUrl);
log.info("actionSetId: '{}'", actionSetId);
log.info("workingPath: '{}'", workingPath);
log.info("whiteListPath: '{}'", whiteListPath);
JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
// file format: source####target
Dataset<Tuple2<String, String>> whiteListRels = spark
.createDataset(
sc
.textFile(whiteListPath)
// check if the line is in the correct format: id1####id2
.filter(s -> s.contains(WHITELIST_SEPARATOR) && s.split(WHITELIST_SEPARATOR).length == 2)
.map(s -> new Tuple2<>(s.split(WHITELIST_SEPARATOR)[0], s.split(WHITELIST_SEPARATOR)[1]))
.rdd(),
Encoders.tuple(Encoders.STRING(), Encoders.STRING()));
// for each dedup configuration
for (DedupConfig dedupConf : getConfigurations(isLookUpService, actionSetId)) {
final String entity = dedupConf.getWf().getEntityType();
final String subEntity = dedupConf.getWf().getSubEntityValue();
log.info("Adding whitelist simrels for: '{}'", subEntity);
final String outputPath = DedupUtility.createSimRelPath(workingPath, actionSetId, subEntity);
Dataset<Tuple2<String, String>> entities = spark
.createDataset(
sc
.textFile(DedupUtility.createEntityPath(graphBasePath, subEntity))
.repartition(numPartitions)
.mapToPair(
(PairFunction<String, String, String>) s -> {
MapDocument d = MapDocumentUtil.asMapDocumentWithJPath(dedupConf, s);
return new Tuple2<>(d.getIdentifier(), "present");
})
.rdd(),
Encoders.tuple(Encoders.STRING(), Encoders.STRING()));
Dataset<Tuple2<String, String>> whiteListRels1 = whiteListRels
.joinWith(entities, whiteListRels.col("_1").equalTo(entities.col("_1")), "inner")
.map(
(MapFunction<Tuple2<Tuple2<String, String>, Tuple2<String, String>>, Tuple2<String, String>>) Tuple2::_1,
Encoders.tuple(Encoders.STRING(), Encoders.STRING()));
Dataset<Tuple2<String, String>> whiteListRels2 = whiteListRels1
.joinWith(entities, whiteListRels1.col("_2").equalTo(entities.col("_1")), "inner")
.map(
(MapFunction<Tuple2<Tuple2<String, String>, Tuple2<String, String>>, Tuple2<String, String>>) Tuple2::_1,
Encoders.tuple(Encoders.STRING(), Encoders.STRING()));
Dataset<Relation> whiteListSimRels = whiteListRels2
.map(
(MapFunction<Tuple2<String, String>, Relation>) r -> createSimRel(r._1(), r._2(), entity),
Encoders.bean(Relation.class));
saveParquet(whiteListSimRels, outputPath, SaveMode.Append);
}
}
private Relation createSimRel(String source, String target, String entity) {
final Relation r = new Relation();
r.setSource(source);
r.setTarget(target);
r.setSubRelType("dedupSimilarity");
r.setRelClass("isSimilarTo");
r.setDataInfo(new DataInfo());
switch (entity) {
case "result":
r.setRelType("resultResult");
break;
case "organization":
r.setRelType("organizationOrganization");
break;
default:
throw new IllegalArgumentException("unmanaged entity type: " + entity);
}
return r;
}
}

View File

@ -0,0 +1,117 @@
package eu.dnetlib.dhp.oa.dedup;
import java.util.concurrent.TimeUnit;
import org.apache.commons.io.IOUtils;
import org.apache.http.client.methods.CloseableHttpResponse;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
public class UpdateOpenorgsJob {
private static final Logger log = LoggerFactory.getLogger(UpdateOpenorgsJob.class);
public static void main(String[] args) throws Exception {
ArgumentApplicationParser parser = new ArgumentApplicationParser(
IOUtils
.toString(
SparkCreateSimRels.class
.getResourceAsStream("/eu/dnetlib/dhp/oa/dedup/updateOpenorgsJob_parameters.json")));
parser.parseArgument(args);
final String apiUrl = parser.get("apiUrl");
final int delay = Integer.parseInt(parser.get("delay"));
log.info("apiUrl: '{}'", apiUrl);
log.info("delay: '{}'", delay);
APIResponse res = httpCall(apiUrl);
while (res != null && res.getStatus().equals(ImportStatus.RUNNING)) {
TimeUnit.MINUTES.sleep(delay);
res = httpCall(apiUrl + "/status");
}
if (res == null) {
log.error("Openorgs Update FAILED: No response");
throw new RuntimeException("Openorgs Update FAILED: No response");
}
if (res.getStatus() == null || !res.getStatus().equals(ImportStatus.SUCCESS)) {
log.error("Openorgs Update FAILED: '{}' - '{}'", res.getStatus(), res.getMessage());
throw new RuntimeException(res.getMessage());
}
}
private static APIResponse httpCall(final String url) throws Exception {
final HttpGet req = new HttpGet(url);
try (final CloseableHttpClient client = HttpClients.createDefault()) {
try (final CloseableHttpResponse response = client.execute(req)) {
final String s = IOUtils.toString(response.getEntity().getContent());
return (new ObjectMapper()).readValue(s, APIResponse.class);
}
}
}
}
class APIResponse {
private String id;
private Long dateStart;
private Long dateEnd;
private ImportStatus status;
private String message;
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
public Long getDateStart() {
return dateStart;
}
public void setDateStart(Long dateStart) {
this.dateStart = dateStart;
}
public Long getDateEnd() {
return dateEnd;
}
public void setDateEnd(Long dateEnd) {
this.dateEnd = dateEnd;
}
public ImportStatus getStatus() {
return status;
}
public void setStatus(ImportStatus status) {
this.status = status;
}
public String getMessage() {
return message;
}
public void setMessage(String message) {
this.message = message;
}
}
enum ImportStatus {
SUCCESS, FAILED, RUNNING, NOT_LAUNCHED, NOT_YET_STARTED
}

View File

@ -28,6 +28,11 @@
<name>dbPwd</name> <name>dbPwd</name>
<description>password to access the OpenOrgs database</description> <description>password to access the OpenOrgs database</description>
</property> </property>
<property>
<name>dbConnections</name>
<value>10</value>
<description>number of connections to the postgres db</description>
</property>
<property> <property>
<name>workingPath</name> <name>workingPath</name>
<description>path for the working directory</description> <description>path for the working directory</description>
@ -223,7 +228,7 @@
<arg>--dbTable</arg><arg>${dbTable}</arg> <arg>--dbTable</arg><arg>${dbTable}</arg>
<arg>--dbUser</arg><arg>${dbUser}</arg> <arg>--dbUser</arg><arg>${dbUser}</arg>
<arg>--dbPwd</arg><arg>${dbPwd}</arg> <arg>--dbPwd</arg><arg>${dbPwd}</arg>
<arg>--numConnections</arg><arg>20</arg> <arg>--numConnections</arg><arg>${dbConnections}</arg>
</spark> </spark>
<ok to="PrepareNewOrgs"/> <ok to="PrepareNewOrgs"/>
<error to="Kill"/> <error to="Kill"/>
@ -254,19 +259,24 @@
<arg>--dbTable</arg><arg>${dbTable}</arg> <arg>--dbTable</arg><arg>${dbTable}</arg>
<arg>--dbUser</arg><arg>${dbUser}</arg> <arg>--dbUser</arg><arg>${dbUser}</arg>
<arg>--dbPwd</arg><arg>${dbPwd}</arg> <arg>--dbPwd</arg><arg>${dbPwd}</arg>
<arg>--numConnections</arg><arg>20</arg> <arg>--numConnections</arg><arg>${dbConnections}</arg>
</spark> </spark>
<ok to="update_openorgs"/> <ok to="update_openorgs"/>
<error to="Kill"/> <error to="Kill"/>
</action> </action>
<action name="update_openorgs"> <action name="update_openorgs">
<shell xmlns="uri:oozie:shell-action:0.1"> <java>
<job-tracker>${jobTracker}</job-tracker> <configuration>
<name-node>${nameNode}</name-node> <property>
<exec>/usr/bin/curl</exec> <name>oozie.launcher.mapreduce.user.classpath.first</name>
<argument>${apiUrl}</argument> <value>true</value>
</shell> </property>
</configuration>
<main-class>eu.dnetlib.dhp.oa.dedup.UpdateOpenorgsJob</main-class>
<arg>--apiUrl</arg><arg>${apiUrl}</arg>
<arg>--delay</arg><arg>5</arg>
</java>
<ok to="End"/> <ok to="End"/>
<error to="Kill"/> <error to="Kill"/>
</action> </action>

View File

@ -20,6 +20,10 @@
<name>workingPath</name> <name>workingPath</name>
<description>path for the working directory</description> <description>path for the working directory</description>
</property> </property>
<property>
<name>whiteListPath</name>
<description>path for the whitelist of similarity relations</description>
</property>
<property> <property>
<name>dedupGraphPath</name> <name>dedupGraphPath</name>
<description>path for the output graph</description> <description>path for the output graph</description>
@ -130,6 +134,34 @@
<arg>--workingPath</arg><arg>${workingPath}</arg> <arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>--numPartitions</arg><arg>8000</arg> <arg>--numPartitions</arg><arg>8000</arg>
</spark> </spark>
<ok to="WhitelistSimRels"/>
<error to="Kill"/>
</action>
<action name="WhitelistSimRels">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Add Whitelist Similarity Relations</name>
<class>eu.dnetlib.dhp.oa.dedup.SparkWhitelistSimRels</class>
<jar>dhp-dedup-openaire-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.shuffle.partitions=3840
</spark-opts>
<arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
<arg>--isLookUpUrl</arg><arg>${isLookUpUrl}</arg>
<arg>--actionSetId</arg><arg>${actionSetId}</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>--whiteListPath</arg><arg>${whiteListPath}</arg>
<arg>--numPartitions</arg><arg>8000</arg>
</spark>
<ok to="CreateMergeRel"/> <ok to="CreateMergeRel"/>
<error to="Kill"/> <error to="Kill"/>
</action> </action>

View File

@ -0,0 +1,14 @@
[
{
"paramName": "api",
"paramLongName": "apiUrl",
"paramDescription": "the url of the API",
"paramRequired": true
},
{
"paramName": "d",
"paramLongName": "delay",
"paramDescription": "delay for the HTTP call in minutes",
"paramRequired": true
}
]

View File

@ -0,0 +1,38 @@
[
{
"paramName": "la",
"paramLongName": "isLookUpUrl",
"paramDescription": "address for the LookUp",
"paramRequired": true
},
{
"paramName": "asi",
"paramLongName": "actionSetId",
"paramDescription": "action set identifier (name of the orchestrator)",
"paramRequired": true
},
{
"paramName": "i",
"paramLongName": "graphBasePath",
"paramDescription": "the base path of the raw graph",
"paramRequired": true
},
{
"paramName": "w",
"paramLongName": "workingPath",
"paramDescription": "path of the working directory",
"paramRequired": true
},
{
"paramName": "np",
"paramLongName": "numPartitions",
"paramDescription": "number of partitions for the similarity relations intermediate phases",
"paramRequired": false
},
{
"paramName": "wl",
"paramLongName": "whiteListPath",
"paramDescription": "whitelist file path for the addition of custom simrels",
"paramRequired": true
}
]

View File

@ -5,13 +5,16 @@ import static java.nio.file.Files.createTempDirectory;
import static org.apache.spark.sql.functions.count; import static org.apache.spark.sql.functions.count;
import static org.junit.jupiter.api.Assertions.assertEquals; import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertTrue;
import static org.mockito.Mockito.lenient; import static org.mockito.Mockito.lenient;
import java.io.File; import java.io.File;
import java.io.FileReader;
import java.io.IOException; import java.io.IOException;
import java.io.Serializable; import java.io.Serializable;
import java.net.URISyntaxException; import java.net.URISyntaxException;
import java.nio.file.Paths; import java.nio.file.Paths;
import java.util.List;
import org.apache.commons.io.FileUtils; import org.apache.commons.io.FileUtils;
import org.apache.commons.io.IOUtils; import org.apache.commons.io.IOUtils;
@ -55,6 +58,10 @@ public class SparkDedupTest implements Serializable {
private static String testOutputBasePath; private static String testOutputBasePath;
private static String testDedupGraphBasePath; private static String testDedupGraphBasePath;
private static final String testActionSetId = "test-orchestrator"; private static final String testActionSetId = "test-orchestrator";
private static String whitelistPath;
private static List<String> whiteList;
private static String WHITELIST_SEPARATOR = "####";
@BeforeAll @BeforeAll
public static void cleanUp() throws IOException, URISyntaxException { public static void cleanUp() throws IOException, URISyntaxException {
@ -71,6 +78,12 @@ public class SparkDedupTest implements Serializable {
.toAbsolutePath() .toAbsolutePath()
.toString(); .toString();
whitelistPath = Paths
.get(SparkDedupTest.class.getResource("/eu/dnetlib/dhp/dedup/whitelist.simrels.txt").toURI())
.toFile()
.getAbsolutePath();
whiteList = IOUtils.readLines(new FileReader(whitelistPath));
FileUtils.deleteDirectory(new File(testOutputBasePath)); FileUtils.deleteDirectory(new File(testOutputBasePath));
FileUtils.deleteDirectory(new File(testDedupGraphBasePath)); FileUtils.deleteDirectory(new File(testDedupGraphBasePath));
@ -202,6 +215,84 @@ public class SparkDedupTest implements Serializable {
@Test @Test
@Order(2) @Order(2)
void whitelistSimRelsTest() throws Exception {
ArgumentApplicationParser parser = new ArgumentApplicationParser(
IOUtils
.toString(
SparkWhitelistSimRels.class
.getResourceAsStream(
"/eu/dnetlib/dhp/oa/dedup/whitelistSimRels_parameters.json")));
parser
.parseArgument(
new String[] {
"-i", testGraphBasePath,
"-asi", testActionSetId,
"-la", "lookupurl",
"-w", testOutputBasePath,
"-np", "50",
"-wl", whitelistPath
});
new SparkWhitelistSimRels(parser, spark).run(isLookUpService);
long orgs_simrel = spark
.read()
.load(DedupUtility.createSimRelPath(testOutputBasePath, testActionSetId, "organization"))
.count();
long pubs_simrel = spark
.read()
.load(DedupUtility.createSimRelPath(testOutputBasePath, testActionSetId, "publication"))
.count();
long ds_simrel = spark
.read()
.load(DedupUtility.createSimRelPath(testOutputBasePath, testActionSetId, "dataset"))
.count();
long orp_simrel = spark
.read()
.load(DedupUtility.createSimRelPath(testOutputBasePath, testActionSetId, "otherresearchproduct"))
.count();
// entities simrels supposed to be equal to the number of previous step (no rels in whitelist)
assertEquals(3082, orgs_simrel);
assertEquals(7036, pubs_simrel);
assertEquals(442, ds_simrel);
assertEquals(6750, orp_simrel);
// entities simrels to be different from the number of previous step (new simrels in the whitelist)
Dataset<Row> sw_simrel = spark
.read()
.load(DedupUtility.createSimRelPath(testOutputBasePath, testActionSetId, "software"));
// check if the first relation in the whitelist exists
assertTrue(
sw_simrel
.as(Encoders.bean(Relation.class))
.toJavaRDD()
.filter(
rel -> rel.getSource().equalsIgnoreCase(whiteList.get(0).split(WHITELIST_SEPARATOR)[0])
&& rel.getTarget().equalsIgnoreCase(whiteList.get(0).split(WHITELIST_SEPARATOR)[1]))
.count() > 0);
// check if the second relation in the whitelist exists
assertTrue(
sw_simrel
.as(Encoders.bean(Relation.class))
.toJavaRDD()
.filter(
rel -> rel.getSource().equalsIgnoreCase(whiteList.get(1).split(WHITELIST_SEPARATOR)[0])
&& rel.getTarget().equalsIgnoreCase(whiteList.get(1).split(WHITELIST_SEPARATOR)[1]))
.count() > 0);
assertEquals(338, sw_simrel.count());
}
@Test
@Order(3)
void cutMergeRelsTest() throws Exception { void cutMergeRelsTest() throws Exception {
ArgumentApplicationParser parser = new ArgumentApplicationParser( ArgumentApplicationParser parser = new ArgumentApplicationParser(
@ -297,7 +388,7 @@ public class SparkDedupTest implements Serializable {
} }
@Test @Test
@Order(3) @Order(4)
void createMergeRelsTest() throws Exception { void createMergeRelsTest() throws Exception {
ArgumentApplicationParser parser = new ArgumentApplicationParser( ArgumentApplicationParser parser = new ArgumentApplicationParser(
@ -353,7 +444,7 @@ public class SparkDedupTest implements Serializable {
} }
@Test @Test
@Order(4) @Order(5)
void createDedupRecordTest() throws Exception { void createDedupRecordTest() throws Exception {
ArgumentApplicationParser parser = new ArgumentApplicationParser( ArgumentApplicationParser parser = new ArgumentApplicationParser(
@ -394,13 +485,13 @@ public class SparkDedupTest implements Serializable {
assertEquals(85, orgs_deduprecord); assertEquals(85, orgs_deduprecord);
assertEquals(65, pubs_deduprecord); assertEquals(65, pubs_deduprecord);
assertEquals(51, sw_deduprecord); assertEquals(49, sw_deduprecord);
assertEquals(97, ds_deduprecord); assertEquals(97, ds_deduprecord);
assertEquals(89, orp_deduprecord); assertEquals(89, orp_deduprecord);
} }
@Test @Test
@Order(5) @Order(6)
void updateEntityTest() throws Exception { void updateEntityTest() throws Exception {
ArgumentApplicationParser parser = new ArgumentApplicationParser( ArgumentApplicationParser parser = new ArgumentApplicationParser(
@ -479,7 +570,7 @@ public class SparkDedupTest implements Serializable {
assertEquals(838, organizations); assertEquals(838, organizations);
assertEquals(100, projects); assertEquals(100, projects);
assertEquals(100, datasource); assertEquals(100, datasource);
assertEquals(200, softwares); assertEquals(198, softwares);
assertEquals(389, dataset); assertEquals(389, dataset);
assertEquals(517, otherresearchproduct); assertEquals(517, otherresearchproduct);
@ -516,7 +607,7 @@ public class SparkDedupTest implements Serializable {
} }
@Test @Test
@Order(6) @Order(7)
void propagateRelationTest() throws Exception { void propagateRelationTest() throws Exception {
ArgumentApplicationParser parser = new ArgumentApplicationParser( ArgumentApplicationParser parser = new ArgumentApplicationParser(
@ -566,7 +657,7 @@ public class SparkDedupTest implements Serializable {
} }
@Test @Test
@Order(7) @Order(8)
void testRelations() throws Exception { void testRelations() throws Exception {
testUniqueness("/eu/dnetlib/dhp/dedup/test/relation_1.json", 12, 10); testUniqueness("/eu/dnetlib/dhp/dedup/test/relation_1.json", 12, 10);
testUniqueness("/eu/dnetlib/dhp/dedup/test/relation_2.json", 10, 2); testUniqueness("/eu/dnetlib/dhp/dedup/test/relation_2.json", 10, 2);

View File

@ -0,0 +1,2 @@
50|r37b0ad08687::f645b9729d1e1025a72c57883f0f2cac####50|r37b0ad08687::4c55b436743b5c49fa32cd582fd9e1aa
50|datacite____::a90f49f9fde5393c00633bea6e4e374a####50|datacite____::5f55cdee77303ba8a2bf9996c32a330c

View File

@ -13,10 +13,30 @@ import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory} import org.slf4j.{Logger, LoggerFactory}
import scala.collection.JavaConverters._ import scala.collection.JavaConverters._
import org.json4s.DefaultFormats
import org.json4s.JsonAST.{JField, JObject, JString,JArray}
import org.json4s.jackson.JsonMethods.parse
object SparkGenerateDoiBoost { object SparkGenerateDoiBoost {
def extractIdGRID(input:String):List[(String,String)] = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
lazy val json: org.json4s.JValue = parse(input)
val id:String = (json \ "id").extract[String]
val grids:List[String] = for {
JObject(pid) <- json \ "pid"
JField("qualifier", JObject(qualifier)) <- pid
JField("classid", JString(classid)) <-qualifier
JField("value", JString(vl)) <- pid
if classid == "GRID"
} yield vl
grids.map(g => (id, s"unresolved::grid::${g.toLowerCase}"))(collection.breakOut)
}
def main(args: Array[String]): Unit = { def main(args: Array[String]): Unit = {
@ -36,6 +56,7 @@ object SparkGenerateDoiBoost {
val hostedByMapPath = parser.get("hostedByMapPath") val hostedByMapPath = parser.get("hostedByMapPath")
val workingDirPath = parser.get("workingPath") val workingDirPath = parser.get("workingPath")
val openaireOrganizationPath = parser.get("openaireOrganizationPath")
val crossrefAggregator = new Aggregator[(String, Publication), Publication, Publication] with Serializable { val crossrefAggregator = new Aggregator[(String, Publication), Publication, Publication] with Serializable {
override def zero: Publication = new Publication override def zero: Publication = new Publication
@ -156,7 +177,7 @@ object SparkGenerateDoiBoost {
magPubs.joinWith(a,magPubs("_1").equalTo(a("PaperId"))).flatMap(item => { magPubs.joinWith(a,magPubs("_1").equalTo(a("PaperId"))).flatMap(item => {
val pub:Publication = item._1._2 val pub:Publication = item._1._2
val affiliation = item._2 val affiliation = item._2
val affId:String = if (affiliation.GridId.isDefined) DoiBoostMappingUtil.generateGridAffiliationId(affiliation.GridId.get) else DoiBoostMappingUtil.generateMAGAffiliationId(affiliation.AffiliationId.toString) val affId:String = if (affiliation.GridId.isDefined) s"unresolved::grid::${affiliation.GridId.get.toLowerCase}" else DoiBoostMappingUtil.generateMAGAffiliationId(affiliation.AffiliationId.toString)
val r:Relation = new Relation val r:Relation = new Relation
r.setSource(pub.getId) r.setSource(pub.getId)
r.setTarget(affId) r.setTarget(affId)
@ -174,9 +195,35 @@ object SparkGenerateDoiBoost {
r1.setDataInfo(pub.getDataInfo) r1.setDataInfo(pub.getDataInfo)
r1.setCollectedfrom(List(DoiBoostMappingUtil.createMAGCollectedFrom()).asJava) r1.setCollectedfrom(List(DoiBoostMappingUtil.createMAGCollectedFrom()).asJava)
List(r, r1) List(r, r1)
})(mapEncoderRel).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublicationAffiliation") })(mapEncoderRel).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublicationAffiliation_unresolved")
val unresolvedRels:Dataset[(String, Relation)] = spark.read.load(s"$workingDirPath/doiBoostPublicationAffiliation_unresolved").as[Relation].map(r => {
if (r.getSource.startsWith("unresolved"))
(r.getSource, r)
else if (r.getTarget.startsWith("unresolved"))
(r.getTarget,r)
else
("resolved", r)
})(Encoders.tuple(Encoders.STRING, mapEncoderRel))
val openaireOrganization:Dataset[(String,String)] = spark.read.text(openaireOrganizationPath).as[String].flatMap(s => extractIdGRID(s)).groupByKey(_._2).reduceGroups((x,y) => if (x != null) x else y ).map(_._2)
unresolvedRels.joinWith(openaireOrganization,unresolvedRels("_1").equalTo(openaireOrganization("_2")))
.map { x =>
val currentRels = x._1._2
val currentOrgs = x._2
if (currentOrgs!= null)
if(currentRels.getSource.startsWith("unresolved"))
currentRels.setSource(currentOrgs._1)
else
currentRels.setTarget(currentOrgs._1)
currentRels
}.filter(r=> !r.getSource.startsWith("unresolved") && !r.getTarget.startsWith("unresolved")).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/doiBoostPublicationAffiliation")
magPubs.joinWith(a,magPubs("_1").equalTo(a("PaperId"))).map( item => { magPubs.joinWith(a,magPubs("_1").equalTo(a("PaperId"))).map( item => {
val affiliation = item._2 val affiliation = item._2
if (affiliation.GridId.isEmpty) { if (affiliation.GridId.isEmpty) {

View File

@ -70,7 +70,7 @@ case object Crossref2Oaf {
"reference-book" -> "0002 Book", "reference-book" -> "0002 Book",
"monograph" -> "0002 Book", "monograph" -> "0002 Book",
"journal-article" -> "0001 Article", "journal-article" -> "0001 Article",
"dissertation" -> "0006 Doctoral thesis", "dissertation" -> "0044 Thesis",
"other" -> "0038 Other literature type", "other" -> "0038 Other literature type",
"peer-review" -> "0015 Review", "peer-review" -> "0015 Review",
"proceedings" -> "0004 Conference object", "proceedings" -> "0004 Conference object",
@ -206,11 +206,16 @@ case object Crossref2Oaf {
else { else {
instance.setDateofacceptance(asField(createdDate.getValue)) instance.setDateofacceptance(asField(createdDate.getValue))
} }
val s: String = (json \ "URL").extract[String] val s: List[String] = List("https://doi.org/" + doi)
val links: List[String] = ((for {JString(url) <- json \ "link" \ "URL"} yield url) ::: List(s)).filter(p => p != null).distinct // val links: List[String] = ((for {JString(url) <- json \ "link" \ "URL"} yield url) ::: List(s)).filter(p => p != null && p.toLowerCase().contains(doi.toLowerCase())).distinct
if (links.nonEmpty) { // if (links.nonEmpty) {
instance.setUrl(links.asJava) // instance.setUrl(links.asJava)
// }
if(s.nonEmpty)
{
instance.setUrl(s.asJava)
} }
result.setInstance(List(instance).asJava) result.setInstance(List(instance).asJava)
//IMPORTANT //IMPORTANT

View File

@ -111,26 +111,9 @@ object SparkProcessMAG {
.map(item => ConversionUtil.updatePubsWithConferenceInfo(item)) .map(item => ConversionUtil.updatePubsWithConferenceInfo(item))
.write .write
.mode(SaveMode.Overwrite) .mode(SaveMode.Overwrite)
.save(s"$workingPath/merge_step_2_conference")
magPubs= spark.read.load(s"$workingPath/merge_step_2_conference").as[Publication]
.map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
val paperUrlDataset = spark.read.load(s"$sourcePath/PaperUrls").as[MagPaperUrl].groupBy("PaperId").agg(collect_list(struct("sourceUrl")).as("instances")).as[MagUrl]
logger.info("Phase 5) enrich publication with URL and Instances")
magPubs.joinWith(paperUrlDataset, col("_1").equalTo(paperUrlDataset("PaperId")), "left")
.map { a: ((String, Publication), MagUrl) => ConversionUtil.addInstances((a._1._2, a._2)) }
.write.mode(SaveMode.Overwrite)
.save(s"$workingPath/merge_step_3") .save(s"$workingPath/merge_step_3")
// logger.info("Phase 6) Enrich Publication with description")
// val pa = spark.read.load(s"${parser.get("sourcePath")}/PaperAbstractsInvertedIndex").as[MagPaperAbstract]
// pa.map(ConversionUtil.transformPaperAbstract).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/PaperAbstract")
val paperAbstract = spark.read.load((s"$workingPath/PaperAbstract")).as[MagPaperAbstract] val paperAbstract = spark.read.load((s"$workingPath/PaperAbstract")).as[MagPaperAbstract]
@ -162,12 +145,14 @@ object SparkProcessMAG {
.write.mode(SaveMode.Overwrite) .write.mode(SaveMode.Overwrite)
.save(s"$workingPath/mag_publication") .save(s"$workingPath/mag_publication")
spark.read.load(s"$workingPath/mag_publication").as[Publication]
val s:RDD[Publication] = spark.read.load(s"$workingPath/mag_publication").as[Publication] .filter(p => p.getId == null)
.map(p=>Tuple2(p.getId, p)).rdd.reduceByKey((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b)) .groupByKey(p => p.getId)
.reduceGroups((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
.map(_._2) .map(_._2)
.write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
spark.createDataset(s).as[Publication].write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
} }
} }

View File

@ -1,6 +1,7 @@
[ [
{"paramName": "m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true}, {"paramName": "m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true},
{"paramName": "hb", "paramLongName":"hostedByMapPath", "paramDescription": "the hosted By Map Path", "paramRequired": true}, {"paramName": "hb", "paramLongName":"hostedByMapPath", "paramDescription": "the hosted By Map Path", "paramRequired": true},
{"paramName": "oo", "paramLongName":"openaireOrganizationPath", "paramDescription": "the openaire Organization Path", "paramRequired": true},
{"paramName": "ap", "paramLongName":"affiliationPath", "paramDescription": "the Affliation Path", "paramRequired": true}, {"paramName": "ap", "paramLongName":"affiliationPath", "paramDescription": "the Affliation Path", "paramRequired": true},
{"paramName": "pa", "paramLongName":"paperAffiliationPath", "paramDescription": "the paperAffiliation Path", "paramRequired": true}, {"paramName": "pa", "paramLongName":"paperAffiliationPath", "paramDescription": "the paperAffiliation Path", "paramRequired": true},
{"paramName": "w", "paramLongName":"workingPath", "paramDescription": "the Working Path", "paramRequired": true} {"paramName": "w", "paramLongName":"workingPath", "paramDescription": "the Working Path", "paramRequired": true}

View File

@ -107,7 +107,6 @@
<action name="ResetMagWorkingPath"> <action name="ResetMagWorkingPath">
<fs> <fs>
<delete path="${inputPathMAG}/dataset"/> <delete path="${inputPathMAG}/dataset"/>
<delete path="${inputPathMAG}/process"/>
</fs> </fs>
<ok to="ConvertMagToDataset"/> <ok to="ConvertMagToDataset"/>
<error to="Kill"/> <error to="Kill"/>

View File

@ -27,6 +27,12 @@
<name>hostedByMapPath</name> <name>hostedByMapPath</name>
<description>the hostedByMap Path</description> <description>the hostedByMap Path</description>
</property> </property>
<property>
<name>openaireOrganizationPath</name>
<description>the OpenAire Organizations Path</description>
</property>
<property> <property>
<name>outputPath</name> <name>outputPath</name>
<description>the Path of the sequence file action set</description> <description>the Path of the sequence file action set</description>
@ -42,7 +48,7 @@
<!-- MAG Parameters --> <!-- MAG Parameters -->
<property> <property>
<name>inputPathMAG</name> <name>inputPathMAG</name>
<description>the MAG working path</description> <description>the MAG input path</description>
</property> </property>
@ -132,7 +138,7 @@
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--sourcePath</arg><arg>${inputPathMAG}/dataset</arg> <arg>--sourcePath</arg><arg>${inputPathMAG}/dataset</arg>
<arg>--workingPath</arg><arg>${inputPathMAG}/process_p</arg> <arg>--workingPath</arg><arg>${workingPath}/MAG</arg>
<arg>--targetPath</arg><arg>${workingPath}</arg> <arg>--targetPath</arg><arg>${workingPath}</arg>
<arg>--master</arg><arg>yarn-cluster</arg> <arg>--master</arg><arg>yarn-cluster</arg>
</spark> </spark>
@ -214,6 +220,7 @@
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts> </spark-opts>
<arg>--hostedByMapPath</arg><arg>${hostedByMapPath}</arg> <arg>--hostedByMapPath</arg><arg>${hostedByMapPath}</arg>
<arg>--openaireOrganizationPath</arg><arg>${openaireOrganizationPath}</arg>
<arg>--affiliationPath</arg><arg>${inputPathMAG}/dataset/Affiliations</arg> <arg>--affiliationPath</arg><arg>${inputPathMAG}/dataset/Affiliations</arg>
<arg>--paperAffiliationPath</arg><arg>${inputPathMAG}/dataset/PaperAuthorAffiliations</arg> <arg>--paperAffiliationPath</arg><arg>${inputPathMAG}/dataset/PaperAuthorAffiliations</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg> <arg>--workingPath</arg><arg>${workingPath}</arg>

View File

@ -612,4 +612,26 @@ class CrossrefMappingTest {
} }
@Test
def testMultipleURLs() :Unit = {
val json = Source.fromInputStream(getClass.getResourceAsStream("multiple_urls.json")).mkString
assertNotNull(json)
assertFalse(json.isEmpty);
val resultList: List[Oaf] = Crossref2Oaf.convert(json)
assertTrue(resultList.nonEmpty)
val item : Result = resultList.filter(p => p.isInstanceOf[Result]).head.asInstanceOf[Result]
assertEquals(1, item.getInstance().size())
assertEquals(1, item.getInstance().get(0).getUrl().size())
assertEquals("https://doi.org/10.1016/j.jas.2019.105013", item.getInstance().get(0).getUrl().get(0))
//println(mapper.writeValueAsString(item))
}
} }

View File

@ -0,0 +1,614 @@
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"volume": "10",
"author": "Agapiou",
"year": "2017",
"journal-title": "Int. J. Digit. Earth"
},
{
"key": "10.1016/j.jas.2019.105013_bib2",
"series-title": "Extracting Meaning from Ploughsoil Assemblages",
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"year": "2000"
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"key": "10.1016/j.jas.2019.105013_bib3",
"series-title": "Side-by-Side Survey. Comparative Regional Studies in the Mediterranean World",
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"key": "10.1016/j.jas.2019.105013_bib4",
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"article-title": "Local indicators of spatial association—LISA",
"volume": "27",
"author": "Anselin",
"year": "1995",
"journal-title": "Geogr. Anal."
},
{
"key": "10.1016/j.jas.2019.105013_bib5",
"series-title": "Archaeological Survey",
"author": "Banning",
"year": "2002"
},
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"key": "10.1016/j.jas.2019.105013_bib6",
"doi-asserted-by": "crossref",
"first-page": "123",
"DOI": "10.2307/3181488",
"article-title": "GIS, archaeological survey and landscape archaeology on the island of Kythera, Greece",
"volume": "29",
"author": "Bevan",
"year": "2004",
"journal-title": "J. Field Archaeol."
},
{
"issue": "1",
"key": "10.1016/j.jas.2019.105013_bib8",
"doi-asserted-by": "crossref",
"first-page": "5",
"DOI": "10.1023/A:1010933404324",
"article-title": "Random forests",
"volume": "45",
"author": "Breiman",
"year": "2001",
"journal-title": "Mach. Learn."
},
{
"key": "10.1016/j.jas.2019.105013_bib9",
"series-title": "Sampling in Contemporary British Archaeology",
"author": "Cherry",
"year": "1978"
},
{
"issue": "3",
"key": "10.1016/j.jas.2019.105013_bib10",
"doi-asserted-by": "crossref",
"first-page": "273",
"DOI": "10.1016/0734-189X(84)90197-X",
"article-title": "Segmentation of a high-resolution urban scene using texture operators",
"volume": "25",
"author": "Conners",
"year": "1984",
"journal-title": "Comput. Vis. Graph Image Process"
},
{
"key": "10.1016/j.jas.2019.105013_bib11",
"first-page": "31",
"article-title": "Old land surfaces and modern ploughsoil: implications of recent work at Maxey, Cambridgeshire",
"volume": "2",
"author": "Crowther",
"year": "1983",
"journal-title": "Scott. Archaeol. Rev."
},
{
"key": "10.1016/j.jas.2019.105013_bib12",
"series-title": "Settlement Pattern Studies in the Americas: Fifty Years since Virú",
"first-page": "203",
"article-title": "Conclusions: the settlement pattern concept from an Americanist perspective",
"author": "Fish",
"year": "1999"
},
{
"key": "10.1016/j.jas.2019.105013_bib13",
"doi-asserted-by": "crossref",
"first-page": "21",
"DOI": "10.3390/geosciences9010021",
"article-title": "Remote sensing and historical morphodynamics of alluvial plains. The 1909 indus flood and the city of Dera Gazhi Khan (province of Punjab, Pakistan)",
"volume": "9",
"author": "Garcia",
"year": "2019",
"journal-title": "Geosciences"
},
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"key": "10.1016/j.jas.2019.105013_bib14",
"unstructured": "Georgiadis, M.; Garcia-Molsosa, A.; Orengo, H.A.; Kefalidou, E. and Kallintzi, K. In Preparation. APAX Project 2015-2018: A Preliminary Report. (Hesperia)."
},
{
"key": "10.1016/j.jas.2019.105013_bib15",
"series-title": "Geographical Information Systems and Landscape Archaeology",
"first-page": "35",
"article-title": "Regional survey and GIS: the boeotia project",
"author": "Gillings",
"year": "1999"
},
{
"key": "10.1016/j.jas.2019.105013_bib16",
"doi-asserted-by": "crossref",
"first-page": "18",
"DOI": "10.1016/j.rse.2017.06.031",
"article-title": "Google Earth engine: planetary-scale geospatial analysis for everyone",
"volume": "202",
"author": "Gorelick",
"year": "2017",
"journal-title": "Remote Sens. Environ."
},
{
"issue": "107",
"key": "10.1016/j.jas.2019.105013_bib17",
"doi-asserted-by": "crossref",
"first-page": "177",
"DOI": "10.1111/j.0031-868X.2004.00278.x",
"article-title": "Photogrammetric reconstruction of the great buddha of Bamiyan, Afghanistan",
"volume": "19",
"author": "Grün",
"year": "2004",
"journal-title": "Photogramm. Rec."
},
{
"issue": "6",
"key": "10.1016/j.jas.2019.105013_bib18",
"doi-asserted-by": "crossref",
"first-page": "610",
"DOI": "10.1109/TSMC.1973.4309314",
"article-title": "Textural features for image classification",
"author": "Haralick",
"year": "1973",
"journal-title": "IEEE Trans. Syst., Man, Cybernet., SMC-3"
},
{
"key": "10.1016/j.jas.2019.105013_bib19",
"doi-asserted-by": "crossref",
"first-page": "76",
"DOI": "10.1558/jmea.v14i1.76",
"article-title": "Excavating to excess? Implications of the last decade of archaeology in Israel",
"volume": "14",
"author": "Kletter",
"year": "2001",
"journal-title": "J. Mediterr. Archaeol."
},
{
"key": "10.1016/j.jas.2019.105013_bib20",
"first-page": "299",
"article-title": "Testing Google Earth Engine for the automatic identification and vectorization of archaeological features: a case study from Faynan, Jordan",
"volume": "15",
"author": "Liss",
"year": "2017",
"journal-title": "J. Archaeol. Sci.: Report"
},
{
"key": "10.1016/j.jas.2019.105013_bib21",
"series-title": "Geographical Information Systems and Landscape Archaeology",
"first-page": "55",
"article-title": "Towards a methodology for modelling surface survey data: the sangro valley project",
"author": "Lock",
"year": "1999"
},
{
"key": "10.1016/j.jas.2019.105013_bib22",
"series-title": "Extracting Meaning from Ploughsoil Assemblages",
"first-page": "5",
"article-title": "Methods of collection recording and quantification",
"author": "Mattingly",
"year": "2000"
},
{
"issue": "14",
"key": "10.1016/j.jas.2019.105013_bib23",
"doi-asserted-by": "crossref",
"first-page": "E778",
"DOI": "10.1073/pnas.1115472109",
"article-title": "Mapping patterns of long-term settlement in Northern Mesopotamia at a large scale",
"volume": "109",
"author": "Menze",
"year": "2012",
"journal-title": "Proc. Natl. Acad. Sci."
},
{
"key": "10.1016/j.jas.2019.105013_bib24",
"doi-asserted-by": "crossref",
"first-page": "80",
"DOI": "10.1016/j.jas.2015.04.002",
"article-title": "A supervised machine-learning approach towards geochemical predictive modelling in archaeology",
"volume": "59",
"author": "Oonk",
"year": "2015",
"journal-title": "J. Archaeol. Sci."
},
{
"key": "10.1016/j.jas.2019.105013_bib25",
"doi-asserted-by": "crossref",
"first-page": "49",
"DOI": "10.1016/j.isprsjprs.2012.07.005",
"article-title": "Combining terrestrial stereophotogrammetry, DGPS and GIS-based 3D voxel modelling in the volumetric recording of archaeological features",
"volume": "76",
"author": "Orengo",
"year": "2013",
"journal-title": "ISPRS J. Photogrammetry Remote Sens."
},
{
"key": "10.1016/j.jas.2019.105013_bib26",
"doi-asserted-by": "crossref",
"first-page": "100",
"DOI": "10.1016/j.jas.2015.10.008",
"article-title": "Photogrammetric re-discovery of the Eastern Thessalian hidden long-term landscapes",
"volume": "64",
"author": "Orengo",
"year": "2015",
"journal-title": "J. Archaeol. Sci."
},
{
"issue": "3",
"key": "10.1016/j.jas.2019.105013_bib27",
"doi-asserted-by": "crossref",
"first-page": "479",
"DOI": "10.3764/aja.122.3.0479",
"article-title": "Towards a definition of Minoan agro-pastoral landscapes: results of the survey at Palaikastro (Crete)",
"volume": "122",
"author": "Orengo",
"year": "2018",
"journal-title": "Am. J. Archaeol."
},
{
"issue": "7",
"key": "10.1016/j.jas.2019.105013_bib28",
"doi-asserted-by": "crossref",
"first-page": "735",
"DOI": "10.3390/rs9070735",
"article-title": "Large-scale, multi-temporal remote sensing of palaeo-river networks: a case study from Northwest India and its implications for the Indus civilisation",
"volume": "9",
"author": "Orengo",
"year": "2017",
"journal-title": "Remote Sens."
},
{
"key": "10.1016/j.jas.2019.105013_bib29",
"doi-asserted-by": "crossref",
"first-page": "1361",
"DOI": "10.1002/esp.4317",
"article-title": "Multi-scale relief model (MSRM): a new algorithm for the visualization of subtle topographic change of variable size in digital elevation models",
"volume": "43",
"author": "Orengo",
"year": "2018",
"journal-title": "Earth Surf. Process. Landforms"
},
{
"key": "10.1016/j.jas.2019.105013_bib30",
"series-title": "Submitted to Proceedings of the National Academy of Sciences",
"article-title": "Living on the edge of the desert: automated detection of archaeological mounds in Cholistan (Pakistan) using machine learning classification of multi-sensor multi-temporal satellite data",
"author": "Orengo",
"year": "2019"
},
{
"key": "10.1016/j.jas.2019.105013_bib31",
"first-page": "154",
"article-title": "How many trees in a random forest?",
"volume": "vol. 7376",
"author": "Oshiro",
"year": "2012"
},
{
"key": "10.1016/j.jas.2019.105013_bib32",
"article-title": "Decision-making in modern surveys",
"volume": "ume 1",
"author": "Plog",
"year": "1978"
},
{
"issue": "4",
"key": "10.1016/j.jas.2019.105013_bib33",
"doi-asserted-by": "crossref",
"first-page": "100",
"DOI": "10.3390/geosciences7040100",
"article-title": "From above and on the ground: geospatial methods for recording endangered archaeology in the Middle East and north africa",
"volume": "7",
"author": "Rayne",
"year": "2017",
"journal-title": "Geosciences"
},
{
"issue": "1",
"key": "10.1016/j.jas.2019.105013_bib34",
"doi-asserted-by": "crossref",
"first-page": "1",
"DOI": "10.1080/00438243.1978.9979712",
"article-title": "The design of archaeological surveys",
"volume": "10",
"author": "Schiffer",
"year": "1978",
"journal-title": "World Archaeol."
},
{
"key": "10.1016/j.jas.2019.105013_bib35",
"series-title": "Experiments in the Collection and Analysis of Archaeological Survey Data: the East Hampshire Survey",
"author": "Shennan",
"year": "1985"
},
{
"key": "10.1016/j.jas.2019.105013_bib36",
"doi-asserted-by": "crossref",
"first-page": "1066",
"DOI": "10.1016/j.culher.2016.06.006",
"article-title": "Drones over Mediterranean landscapes. The potential of small UAV's (drones) for site detection and heritage management in archaeological survey projects: a case study from Le Pianelle in the Tappino Valley, Molise (Italy)",
"volume": "22",
"author": "Stek",
"year": "2016",
"journal-title": "J. Cult. Herit."
},
{
"key": "10.1016/j.jas.2019.105013_bib37",
"series-title": "Side-by-Side Survey. Comparative Regional Studies in the Mediterranean World",
"first-page": "65",
"article-title": "Side-by-side and back to front: exploring intra-regional latitudinal and longitudinal comparability in survey data. Three case studies from Metaponto, southern Italy",
"author": "Thomson",
"year": "2004"
},
{
"key": "10.1016/j.jas.2019.105013_bib38",
"series-title": "Digital Discovery. Exploring New Frontiers in Human Heritage. Computer Applications and Quantitative Methods in Archaeology",
"article-title": "Computer vision and machine learning for archaeology",
"author": "van der Maaten",
"year": "2007"
},
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"key": "10.1016/j.jas.2019.105013_bib39",
"doi-asserted-by": "crossref",
"first-page": "1114",
"DOI": "10.1111/j.1475-4754.2012.00667.x",
"article-title": "Computer vision-based orthophoto mapping of complex archaeological sites: the ancient quarry of Pitaranha (Portugal-Spain)",
"volume": "54",
"author": "Verhoeven",
"year": "2012",
"journal-title": "Archaeometry"
},
{
"key": "10.1016/j.jas.2019.105013_bib40",
"series-title": "A Guide for Salvage Archeology",
"author": "Wendorf",
"year": "1962"
}
],
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},
"ISSN": [
"0305-4403"
],
"issn-type": [
{
"value": "0305-4403",
"type": "print"
}
],
"subject": [
"Archaeology",
"Archaeology"
],
"published": {
"date-parts": [
[
2019,
12
]
]
},
"assertion": [
{
"value": "Elsevier",
"name": "publisher",
"label": "This article is maintained by"
},
{
"value": "A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery",
"name": "articletitle",
"label": "Article Title"
},
{
"value": "Journal of Archaeological Science",
"name": "journaltitle",
"label": "Journal Title"
},
{
"value": "https://doi.org/10.1016/j.jas.2019.105013",
"name": "articlelink",
"label": "CrossRef DOI link to publisher maintained version"
},
{
"value": "article",
"name": "content_type",
"label": "Content Type"
},
{
"value": "© 2019 The Authors. Published by Elsevier Ltd.",
"name": "copyright",
"label": "Copyright"
}
],
"article-number": "105013"
}

View File

@ -25,6 +25,24 @@ public class PropagationConstant {
private PropagationConstant() { private PropagationConstant() {
} }
public static final String DOI = "doi";
public static final String REF_DOI = ".refs";
public static final String UPDATE_DATA_INFO_TYPE = "update";
public static final String UPDATE_SUBJECT_FOS_CLASS_ID = "subject:fos";
public static final String UPDATE_CLASS_NAME = "Inferred by OpenAIRE";
public static final String UPDATE_MEASURE_BIP_CLASS_ID = "measure:bip";
public static final String FOS_CLASS_ID = "FOS";
public static final String FOS_CLASS_NAME = "Fields of Science and Technology classification";
public static final String OPENCITATIONS_CLASSID = "sysimport:crosswalk:opencitations";
public static final String OPENCITATIONS_CLASSNAME = "Imported from OpenCitations";
public static final String ID_PREFIX = "50|doi_________::";
public static final String OC_TRUST = "0.91";
public final static String NULL = "NULL";
public static final String INSTITUTIONAL_REPO_TYPE = "pubsrepository::institutional"; public static final String INSTITUTIONAL_REPO_TYPE = "pubsrepository::institutional";
public static final String PROPAGATION_DATA_INFO_TYPE = "propagation"; public static final String PROPAGATION_DATA_INFO_TYPE = "propagation";
@ -75,10 +93,25 @@ public class PropagationConstant {
public static DataInfo getDataInfo( public static DataInfo getDataInfo(
String inference_provenance, String inference_class_id, String inference_class_name, String qualifierSchema) { String inference_provenance, String inference_class_id, String inference_class_name, String qualifierSchema) {
return getDataInfo(inference_provenance, inference_class_id, inference_class_name, qualifierSchema, "0.85");
}
public static DataInfo getDataInfo(
String inference_provenance, String inference_class_id, String inference_class_name, String qualifierSchema,
String trust) {
return getDataInfo(
inference_provenance, inference_class_id, inference_class_name, qualifierSchema, trust, true);
}
public static DataInfo getDataInfo(
String inference_provenance, String inference_class_id, String inference_class_name, String qualifierSchema,
String trust, boolean inferred) {
DataInfo di = new DataInfo(); DataInfo di = new DataInfo();
di.setInferred(true); di.setInferred(inferred);
di.setDeletedbyinference(false); di.setDeletedbyinference(false);
di.setTrust("0.85"); di.setTrust(trust);
di.setInferenceprovenance(inference_provenance); di.setInferenceprovenance(inference_provenance);
di.setProvenanceaction(getQualifier(inference_class_id, inference_class_name, qualifierSchema)); di.setProvenanceaction(getQualifier(inference_class_id, inference_class_name, qualifierSchema));
return di; return di;

View File

@ -5,37 +5,40 @@ import java.util.Map;
import com.google.common.collect.Maps; import com.google.common.collect.Maps;
import eu.dnetlib.dhp.schema.common.ModelConstants;
public class Constants { public class Constants {
public static final Map<String, String> accessRightsCoarMap = Maps.newHashMap(); protected static final Map<String, String> accessRightsCoarMap = Maps.newHashMap();
public static final Map<String, String> coarCodeLabelMap = Maps.newHashMap(); protected static final Map<String, String> coarCodeLabelMap = Maps.newHashMap();
public static final String INFERRED = "Inferred by OpenAIRE"; public static final String INFERRED = "Inferred by OpenAIRE";
public static final String CABF2 = "c_abf2";
public static final String HARVESTED = "Harvested"; public static final String HARVESTED = "Harvested";
public static final String DEFAULT_TRUST = "0.9"; public static final String DEFAULT_TRUST = "0.9";
public static final String USER_CLAIM = "Linked by user"; public static final String USER_CLAIM = "Linked by user";
public static String COAR_ACCESS_RIGHT_SCHEMA = "http://vocabularies.coar-repositories.org/documentation/access_rights/"; public static final String COAR_ACCESS_RIGHT_SCHEMA = "http://vocabularies.coar-repositories.org/documentation/access_rights/";
public static String ZENODO_COMMUNITY_PREFIX = "https://zenodo.org/communities/"; public static final String ZENODO_COMMUNITY_PREFIX = "https://zenodo.org/communities/";
public static String RESEARCH_COMMUNITY = "Research Community"; public static final String RESEARCH_COMMUNITY = "Research Community";
public static String RESEARCH_INFRASTRUCTURE = "Research Infrastructure/Initiative"; public static final String RESEARCH_INFRASTRUCTURE = "Research Infrastructure/Initiative";
static { static {
accessRightsCoarMap.put("OPEN", "c_abf2"); accessRightsCoarMap.put(ModelConstants.ACCESS_RIGHT_OPEN, CABF2);
accessRightsCoarMap.put("RESTRICTED", "c_16ec"); accessRightsCoarMap.put("RESTRICTED", "c_16ec");
accessRightsCoarMap.put("OPEN SOURCE", "c_abf2"); accessRightsCoarMap.put("OPEN SOURCE", CABF2);
accessRightsCoarMap.put("CLOSED", "c_14cb"); accessRightsCoarMap.put(ModelConstants.ACCESS_RIGHT_CLOSED, "c_14cb");
accessRightsCoarMap.put("EMBARGO", "c_f1cf"); accessRightsCoarMap.put(ModelConstants.ACCESS_RIGHT_EMBARGO, "c_f1cf");
} }
static { static {
coarCodeLabelMap.put("c_abf2", "OPEN"); coarCodeLabelMap.put(CABF2, ModelConstants.ACCESS_RIGHT_OPEN);
coarCodeLabelMap.put("c_16ec", "RESTRICTED"); coarCodeLabelMap.put("c_16ec", "RESTRICTED");
coarCodeLabelMap.put("c_14cb", "CLOSED"); coarCodeLabelMap.put("c_14cb", ModelConstants.ACCESS_RIGHT_CLOSED);
coarCodeLabelMap.put("c_f1cf", "EMBARGO"); coarCodeLabelMap.put("c_f1cf", "EMBARGO");
} }

View File

@ -11,12 +11,14 @@ import java.util.Set;
import java.util.stream.Collectors; import java.util.stream.Collectors;
import org.apache.spark.SparkConf; import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FilterFunction;
import org.apache.spark.api.java.function.MapFunction; import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.sql.Encoders; import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.SaveMode; import org.apache.spark.sql.SaveMode;
import org.apache.spark.sql.SparkSession; import org.apache.spark.sql.SparkSession;
import eu.dnetlib.dhp.oa.graph.dump.community.CommunityMap; import eu.dnetlib.dhp.oa.graph.dump.community.CommunityMap;
import eu.dnetlib.dhp.oa.graph.dump.exceptions.NoAvailableEntityTypeException;
import eu.dnetlib.dhp.schema.oaf.*; import eu.dnetlib.dhp.schema.oaf.*;
/** /**
@ -37,7 +39,8 @@ public class DumpProducts implements Serializable {
isSparkSessionManaged, isSparkSessionManaged,
spark -> { spark -> {
Utils.removeOutputDir(spark, outputPath); Utils.removeOutputDir(spark, outputPath);
execDump(spark, inputPath, outputPath, communityMapPath, inputClazz, outputClazz, dumpType); execDump(
spark, inputPath, outputPath, communityMapPath, inputClazz, outputClazz, dumpType);
}); });
} }
@ -55,7 +58,7 @@ public class DumpProducts implements Serializable {
Utils Utils
.readPath(spark, inputPath, inputClazz) .readPath(spark, inputPath, inputClazz)
.map((MapFunction<I, O>) value -> execMap(value, communityMap, dumpType), Encoders.bean(outputClazz)) .map((MapFunction<I, O>) value -> execMap(value, communityMap, dumpType), Encoders.bean(outputClazz))
.filter(Objects::nonNull) .filter((FilterFunction<O>) value -> value != null)
.write() .write()
.mode(SaveMode.Overwrite) .mode(SaveMode.Overwrite)
.option("compression", "gzip") .option("compression", "gzip")
@ -65,7 +68,7 @@ public class DumpProducts implements Serializable {
private static <I extends OafEntity, O extends eu.dnetlib.dhp.schema.dump.oaf.Result> O execMap(I value, private static <I extends OafEntity, O extends eu.dnetlib.dhp.schema.dump.oaf.Result> O execMap(I value,
CommunityMap communityMap, CommunityMap communityMap,
String dumpType) { String dumpType) throws NoAvailableEntityTypeException {
Optional<DataInfo> odInfo = Optional.ofNullable(value.getDataInfo()); Optional<DataInfo> odInfo = Optional.ofNullable(value.getDataInfo());
if (odInfo.isPresent()) { if (odInfo.isPresent()) {
@ -89,11 +92,11 @@ public class DumpProducts implements Serializable {
return c.getId(); return c.getId();
} }
if (c.getId().contains("::") && communities.contains(c.getId().substring(0, c.getId().indexOf("::")))) { if (c.getId().contains("::") && communities.contains(c.getId().substring(0, c.getId().indexOf("::")))) {
return c.getId().substring(0, 3); return c.getId().substring(0, c.getId().indexOf("::"));
} }
return null; return null;
}).filter(Objects::nonNull).collect(Collectors.toList()); }).filter(Objects::nonNull).collect(Collectors.toList());
if (toDumpFor.size() == 0) { if (toDumpFor.isEmpty()) {
return null; return null;
} }
} }

View File

@ -57,16 +57,16 @@ public class MakeTar implements Serializable {
public static void makeTArArchive(FileSystem fileSystem, String inputPath, String outputPath, int gBperSplit) public static void makeTArArchive(FileSystem fileSystem, String inputPath, String outputPath, int gBperSplit)
throws IOException { throws IOException {
RemoteIterator<LocatedFileStatus> dir_iterator = fileSystem.listLocatedStatus(new Path(inputPath)); RemoteIterator<LocatedFileStatus> dirIterator = fileSystem.listLocatedStatus(new Path(inputPath));
while (dir_iterator.hasNext()) { while (dirIterator.hasNext()) {
LocatedFileStatus fileStatus = dir_iterator.next(); LocatedFileStatus fileStatus = dirIterator.next();
Path p = fileStatus.getPath(); Path p = fileStatus.getPath();
String p_string = p.toString(); String pathString = p.toString();
String entity = p_string.substring(p_string.lastIndexOf("/") + 1); String entity = pathString.substring(pathString.lastIndexOf("/") + 1);
MakeTarArchive.tarMaxSize(fileSystem, p_string, outputPath + "/" + entity, entity, gBperSplit); MakeTarArchive.tarMaxSize(fileSystem, pathString, outputPath + "/" + entity, entity, gBperSplit);
} }
} }

View File

@ -18,10 +18,10 @@ public class QueryInformationSystem {
private ISLookUpService isLookUp; private ISLookUpService isLookUp;
private static final String XQUERY = "for $x in collection('/db/DRIVER/ContextDSResources/ContextDSResourceType') " private static final String XQUERY_ALL = "for $x in collection('/db/DRIVER/ContextDSResources/ContextDSResourceType') "
+ +
" where $x//CONFIGURATION/context[./@type='community' or ./@type='ri'] " + " where $x//CONFIGURATION/context[./@type='community' or ./@type='ri'] " +
" and ($x//context/param[./@name = 'status']/text() = 'manager' or $x//context/param[./@name = 'status']/text() = 'all') " " and ($x//context/param[./@name = 'status']/text() = 'all') "
+ +
" return " + " return " +
"<community> " + "<community> " +
@ -29,9 +29,22 @@ public class QueryInformationSystem {
"{$x//CONFIGURATION/context/@label}" + "{$x//CONFIGURATION/context/@label}" +
"</community>"; "</community>";
public CommunityMap getCommunityMap() private static final String XQUERY_CI = "for $x in collection('/db/DRIVER/ContextDSResources/ContextDSResourceType') "
+
" where $x//CONFIGURATION/context[./@type='community' or ./@type='ri'] " +
" and $x//CONFIGURATION/context[./@id=%s] "
+
" return " +
"<community> " +
"{$x//CONFIGURATION/context/@id}" +
"{$x//CONFIGURATION/context/@label}" +
"</community>";
public CommunityMap getCommunityMap(boolean singleCommunity, String communityId)
throws ISLookUpException, DocumentException, SAXException { throws ISLookUpException, DocumentException, SAXException {
return getMap(isLookUp.quickSearchProfile(XQUERY)); if (singleCommunity)
return getMap(isLookUp.quickSearchProfile(XQUERY_CI.replace("%s", "'" + communityId + "'")));
return getMap(isLookUp.quickSearchProfile(XQUERY_ALL));
} }

View File

@ -7,21 +7,28 @@ import java.util.stream.Collectors;
import org.apache.commons.lang3.StringUtils; import org.apache.commons.lang3.StringUtils;
import eu.dnetlib.dhp.oa.graph.dump.exceptions.NoAvailableEntityTypeException;
import eu.dnetlib.dhp.schema.common.ModelConstants; import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.dump.oaf.*; import eu.dnetlib.dhp.schema.dump.oaf.*;
import eu.dnetlib.dhp.schema.dump.oaf.AccessRight;
import eu.dnetlib.dhp.schema.dump.oaf.Author;
import eu.dnetlib.dhp.schema.dump.oaf.Country;
import eu.dnetlib.dhp.schema.dump.oaf.GeoLocation;
import eu.dnetlib.dhp.schema.dump.oaf.Instance;
import eu.dnetlib.dhp.schema.dump.oaf.KeyValue;
import eu.dnetlib.dhp.schema.dump.oaf.OpenAccessRoute;
import eu.dnetlib.dhp.schema.dump.oaf.Qualifier;
import eu.dnetlib.dhp.schema.dump.oaf.Result;
import eu.dnetlib.dhp.schema.dump.oaf.community.CommunityInstance; import eu.dnetlib.dhp.schema.dump.oaf.community.CommunityInstance;
import eu.dnetlib.dhp.schema.dump.oaf.community.CommunityResult; import eu.dnetlib.dhp.schema.dump.oaf.community.CommunityResult;
import eu.dnetlib.dhp.schema.dump.oaf.community.Context; import eu.dnetlib.dhp.schema.dump.oaf.community.Context;
import eu.dnetlib.dhp.schema.dump.oaf.graph.GraphResult; import eu.dnetlib.dhp.schema.dump.oaf.graph.GraphResult;
import eu.dnetlib.dhp.schema.oaf.DataInfo; import eu.dnetlib.dhp.schema.oaf.*;
import eu.dnetlib.dhp.schema.oaf.Field;
import eu.dnetlib.dhp.schema.oaf.Journal;
import eu.dnetlib.dhp.schema.oaf.StructuredProperty;
public class ResultMapper implements Serializable { public class ResultMapper implements Serializable {
public static <E extends eu.dnetlib.dhp.schema.oaf.OafEntity> Result map( public static <E extends eu.dnetlib.dhp.schema.oaf.OafEntity> Result map(
E in, Map<String, String> communityMap, String dumpType) { E in, Map<String, String> communityMap, String dumpType) throws NoAvailableEntityTypeException {
Result out; Result out;
if (Constants.DUMPTYPE.COMPLETE.getType().equals(dumpType)) { if (Constants.DUMPTYPE.COMPLETE.getType().equals(dumpType)) {
@ -33,101 +40,17 @@ public class ResultMapper implements Serializable {
eu.dnetlib.dhp.schema.oaf.Result input = (eu.dnetlib.dhp.schema.oaf.Result) in; eu.dnetlib.dhp.schema.oaf.Result input = (eu.dnetlib.dhp.schema.oaf.Result) in;
Optional<eu.dnetlib.dhp.schema.oaf.Qualifier> ort = Optional.ofNullable(input.getResulttype()); Optional<eu.dnetlib.dhp.schema.oaf.Qualifier> ort = Optional.ofNullable(input.getResulttype());
if (ort.isPresent()) { if (ort.isPresent()) {
switch (ort.get().getClassid()) { try {
case "publication":
Optional<Journal> journal = Optional
.ofNullable(((eu.dnetlib.dhp.schema.oaf.Publication) input).getJournal());
if (journal.isPresent()) {
Journal j = journal.get();
Container c = new Container();
c.setConferencedate(j.getConferencedate());
c.setConferenceplace(j.getConferenceplace());
c.setEdition(j.getEdition());
c.setEp(j.getEp());
c.setIss(j.getIss());
c.setIssnLinking(j.getIssnLinking());
c.setIssnOnline(j.getIssnOnline());
c.setIssnPrinted(j.getIssnPrinted());
c.setName(j.getName());
c.setSp(j.getSp());
c.setVol(j.getVol());
out.setContainer(c);
out.setType(ModelConstants.PUBLICATION_DEFAULT_RESULTTYPE.getClassname());
}
break;
case "dataset":
eu.dnetlib.dhp.schema.oaf.Dataset id = (eu.dnetlib.dhp.schema.oaf.Dataset) input;
Optional.ofNullable(id.getSize()).ifPresent(v -> out.setSize(v.getValue()));
Optional.ofNullable(id.getVersion()).ifPresent(v -> out.setVersion(v.getValue()));
out addTypeSpecificInformation(out, input, ort);
.setGeolocation( Optional<List<Measure>> mes = Optional.ofNullable(input.getMeasures());
Optional if (mes.isPresent()) {
.ofNullable(id.getGeolocation()) List<KeyValue> measure = new ArrayList<>();
.map( mes
igl -> igl .get()
.stream() .forEach(
.filter(Objects::nonNull) m -> m.getUnit().forEach(u -> measure.add(KeyValue.newInstance(m.getId(), u.getValue()))));
.map(gli -> { out.setMeasures(measure);
GeoLocation gl = new GeoLocation();
gl.setBox(gli.getBox());
gl.setPlace(gli.getPlace());
gl.setPoint(gli.getPoint());
return gl;
})
.collect(Collectors.toList()))
.orElse(null));
out.setType(ModelConstants.DATASET_DEFAULT_RESULTTYPE.getClassname());
break;
case "software":
eu.dnetlib.dhp.schema.oaf.Software is = (eu.dnetlib.dhp.schema.oaf.Software) input;
Optional
.ofNullable(is.getCodeRepositoryUrl())
.ifPresent(value -> out.setCodeRepositoryUrl(value.getValue()));
Optional
.ofNullable(is.getDocumentationUrl())
.ifPresent(
value -> out
.setDocumentationUrl(
value
.stream()
.map(Field::getValue)
.collect(Collectors.toList())));
Optional
.ofNullable(is.getProgrammingLanguage())
.ifPresent(value -> out.setProgrammingLanguage(value.getClassid()));
out.setType(ModelConstants.SOFTWARE_DEFAULT_RESULTTYPE.getClassname());
break;
case "other":
eu.dnetlib.dhp.schema.oaf.OtherResearchProduct ir = (eu.dnetlib.dhp.schema.oaf.OtherResearchProduct) input;
out
.setContactgroup(
Optional
.ofNullable(ir.getContactgroup())
.map(value -> value.stream().map(Field::getValue).collect(Collectors.toList()))
.orElse(null));
out
.setContactperson(
Optional
.ofNullable(ir.getContactperson())
.map(value -> value.stream().map(Field::getValue).collect(Collectors.toList()))
.orElse(null));
out
.setTool(
Optional
.ofNullable(ir.getTool())
.map(value -> value.stream().map(Field::getValue).collect(Collectors.toList()))
.orElse(null));
out.setType(ModelConstants.ORP_DEFAULT_RESULTTYPE.getClassname());
break;
} }
Optional Optional
@ -138,8 +61,7 @@ public class ResultMapper implements Serializable {
// I do not map Access Right UNKNOWN or OTHER // I do not map Access Right UNKNOWN or OTHER
Optional<eu.dnetlib.dhp.schema.oaf.Qualifier> oar = Optional.ofNullable(input.getBestaccessright()); Optional<eu.dnetlib.dhp.schema.oaf.Qualifier> oar = Optional.ofNullable(input.getBestaccessright());
if (oar.isPresent()) { if (oar.isPresent() && Constants.accessRightsCoarMap.containsKey(oar.get().getClassid())) {
if (Constants.accessRightsCoarMap.containsKey(oar.get().getClassid())) {
String code = Constants.accessRightsCoarMap.get(oar.get().getClassid()); String code = Constants.accessRightsCoarMap.get(oar.get().getClassid());
out out
.setBestaccessright( .setBestaccessright(
@ -149,7 +71,6 @@ public class ResultMapper implements Serializable {
Constants.coarCodeLabelMap.get(code), Constants.coarCodeLabelMap.get(code),
Constants.COAR_ACCESS_RIGHT_SCHEMA)); Constants.COAR_ACCESS_RIGHT_SCHEMA));
} }
}
final List<String> contributorList = new ArrayList<>(); final List<String> contributorList = new ArrayList<>();
Optional Optional
@ -225,7 +146,11 @@ public class ResultMapper implements Serializable {
} else { } else {
((CommunityResult) out) ((CommunityResult) out)
.setInstance( .setInstance(
oInst.get().stream().map(ResultMapper::getCommunityInstance).collect(Collectors.toList())); oInst
.get()
.stream()
.map(ResultMapper::getCommunityInstance)
.collect(Collectors.toList()));
} }
} }
@ -245,7 +170,7 @@ public class ResultMapper implements Serializable {
.stream() .stream()
.filter(t -> t.getQualifier().getClassid().equalsIgnoreCase("main title")) .filter(t -> t.getQualifier().getClassid().equalsIgnoreCase("main title"))
.collect(Collectors.toList()); .collect(Collectors.toList());
if (iTitle.size() > 0) { if (!iTitle.isEmpty()) {
out.setMaintitle(iTitle.get(0).getValue()); out.setMaintitle(iTitle.get(0).getValue());
} }
@ -254,24 +179,24 @@ public class ResultMapper implements Serializable {
.stream() .stream()
.filter(t -> t.getQualifier().getClassid().equalsIgnoreCase("subtitle")) .filter(t -> t.getQualifier().getClassid().equalsIgnoreCase("subtitle"))
.collect(Collectors.toList()); .collect(Collectors.toList());
if (iTitle.size() > 0) { if (!iTitle.isEmpty()) {
out.setSubtitle(iTitle.get(0).getValue()); out.setSubtitle(iTitle.get(0).getValue());
} }
} }
List<ControlledField> pids = new ArrayList<>();
Optional Optional
.ofNullable(input.getPid()) .ofNullable(input.getPid())
.ifPresent( .ifPresent(
value -> value value -> out
.setPid(
value
.stream() .stream()
.forEach( .map(
p -> pids p -> ControlledField
.add( .newInstance(p.getQualifier().getClassid(), p.getValue()))
ControlledField .collect(Collectors.toList())));
.newInstance(p.getQualifier().getClassid(), p.getValue()))));
out.setPid(pids);
oStr = Optional.ofNullable(input.getDateofacceptance()); oStr = Optional.ofNullable(input.getDateofacceptance());
if (oStr.isPresent()) { if (oStr.isPresent()) {
out.setPublicationdate(oStr.get().getValue()); out.setPublicationdate(oStr.get().getValue());
@ -281,11 +206,11 @@ public class ResultMapper implements Serializable {
out.setPublisher(oStr.get().getValue()); out.setPublisher(oStr.get().getValue());
} }
List<String> sourceList = new ArrayList<>();
Optional Optional
.ofNullable(input.getSource()) .ofNullable(input.getSource())
.ifPresent(value -> value.stream().forEach(s -> sourceList.add(s.getValue()))); .ifPresent(
// out.setSource(input.getSource().stream().map(s -> s.getValue()).collect(Collectors.toList())); value -> out.setSource(value.stream().map(Field::getValue).collect(Collectors.toList())));
List<Subject> subjectList = new ArrayList<>(); List<Subject> subjectList = new ArrayList<>();
Optional Optional
.ofNullable(input.getSubject()) .ofNullable(input.getSubject())
@ -296,7 +221,6 @@ public class ResultMapper implements Serializable {
out.setSubjects(subjectList); out.setSubjects(subjectList);
out.setType(input.getResulttype().getClassid()); out.setType(input.getResulttype().getClassid());
}
if (!Constants.DUMPTYPE.COMPLETE.getType().equals(dumpType)) { if (!Constants.DUMPTYPE.COMPLETE.getType().equals(dumpType)) {
((CommunityResult) out) ((CommunityResult) out)
@ -316,14 +240,14 @@ public class ResultMapper implements Serializable {
value -> value value -> value
.stream() .stream()
.map(c -> { .map(c -> {
String community_id = c.getId(); String communityId = c.getId();
if (community_id.indexOf("::") > 0) { if (communityId.contains("::")) {
community_id = community_id.substring(0, community_id.indexOf("::")); communityId = communityId.substring(0, communityId.indexOf("::"));
} }
if (communities.contains(community_id)) { if (communities.contains(communityId)) {
Context context = new Context(); Context context = new Context();
context.setCode(community_id); context.setCode(communityId);
context.setLabel(communityMap.get(community_id)); context.setLabel(communityMap.get(communityId));
Optional<List<DataInfo>> dataInfo = Optional.ofNullable(c.getDataInfo()); Optional<List<DataInfo>> dataInfo = Optional.ofNullable(c.getDataInfo());
if (dataInfo.isPresent()) { if (dataInfo.isPresent()) {
List<Provenance> provenance = new ArrayList<>(); List<Provenance> provenance = new ArrayList<>();
@ -338,12 +262,17 @@ public class ResultMapper implements Serializable {
.map( .map(
provenanceaction -> Provenance provenanceaction -> Provenance
.newInstance( .newInstance(
provenanceaction.getClassname(), di.getTrust())) provenanceaction.getClassname(),
di.getTrust()))
.orElse(null)) .orElse(null))
.filter(Objects::nonNull) .filter(Objects::nonNull)
.collect(Collectors.toSet())); .collect(Collectors.toSet()));
try {
context.setProvenance(getUniqueProvenance(provenance)); context.setProvenance(getUniqueProvenance(provenance));
} catch (NoAvailableEntityTypeException e) {
e.printStackTrace();
}
} }
return context; return context;
} }
@ -353,7 +282,7 @@ public class ResultMapper implements Serializable {
.collect(Collectors.toList())) .collect(Collectors.toList()))
.orElse(new ArrayList<>()); .orElse(new ArrayList<>());
if (contextList.size() > 0) { if (!contextList.isEmpty()) {
Set<Integer> hashValue = new HashSet<>(); Set<Integer> hashValue = new HashSet<>();
List<Context> remainigContext = new ArrayList<>(); List<Context> remainigContext = new ArrayList<>();
contextList.forEach(c -> { contextList.forEach(c -> {
@ -365,10 +294,117 @@ public class ResultMapper implements Serializable {
((CommunityResult) out).setContext(remainigContext); ((CommunityResult) out).setContext(remainigContext);
} }
} }
} catch (ClassCastException cce) {
return out;
}
}
return out; return out;
} }
private static void addTypeSpecificInformation(Result out, eu.dnetlib.dhp.schema.oaf.Result input,
Optional<eu.dnetlib.dhp.schema.oaf.Qualifier> ort) throws NoAvailableEntityTypeException {
switch (ort.get().getClassid()) {
case "publication":
Optional<Journal> journal = Optional
.ofNullable(((Publication) input).getJournal());
if (journal.isPresent()) {
Journal j = journal.get();
Container c = new Container();
c.setConferencedate(j.getConferencedate());
c.setConferenceplace(j.getConferenceplace());
c.setEdition(j.getEdition());
c.setEp(j.getEp());
c.setIss(j.getIss());
c.setIssnLinking(j.getIssnLinking());
c.setIssnOnline(j.getIssnOnline());
c.setIssnPrinted(j.getIssnPrinted());
c.setName(j.getName());
c.setSp(j.getSp());
c.setVol(j.getVol());
out.setContainer(c);
out.setType(ModelConstants.PUBLICATION_DEFAULT_RESULTTYPE.getClassname());
}
break;
case "dataset":
Dataset id = (Dataset) input;
Optional.ofNullable(id.getSize()).ifPresent(v -> out.setSize(v.getValue()));
Optional.ofNullable(id.getVersion()).ifPresent(v -> out.setVersion(v.getValue()));
out
.setGeolocation(
Optional
.ofNullable(id.getGeolocation())
.map(
igl -> igl
.stream()
.filter(Objects::nonNull)
.map(gli -> {
GeoLocation gl = new GeoLocation();
gl.setBox(gli.getBox());
gl.setPlace(gli.getPlace());
gl.setPoint(gli.getPoint());
return gl;
})
.collect(Collectors.toList()))
.orElse(null));
out.setType(ModelConstants.DATASET_DEFAULT_RESULTTYPE.getClassname());
break;
case "software":
Software is = (Software) input;
Optional
.ofNullable(is.getCodeRepositoryUrl())
.ifPresent(value -> out.setCodeRepositoryUrl(value.getValue()));
Optional
.ofNullable(is.getDocumentationUrl())
.ifPresent(
value -> out
.setDocumentationUrl(
value
.stream()
.map(Field::getValue)
.collect(Collectors.toList())));
Optional
.ofNullable(is.getProgrammingLanguage())
.ifPresent(value -> out.setProgrammingLanguage(value.getClassid()));
out.setType(ModelConstants.SOFTWARE_DEFAULT_RESULTTYPE.getClassname());
break;
case "other":
OtherResearchProduct ir = (OtherResearchProduct) input;
out
.setContactgroup(
Optional
.ofNullable(ir.getContactgroup())
.map(value -> value.stream().map(Field::getValue).collect(Collectors.toList()))
.orElse(null));
out
.setContactperson(
Optional
.ofNullable(ir.getContactperson())
.map(value -> value.stream().map(Field::getValue).collect(Collectors.toList()))
.orElse(null));
out
.setTool(
Optional
.ofNullable(ir.getTool())
.map(value -> value.stream().map(Field::getValue).collect(Collectors.toList()))
.orElse(null));
out.setType(ModelConstants.ORP_DEFAULT_RESULTTYPE.getClassname());
break;
default:
throw new NoAvailableEntityTypeException();
}
}
private static Instance getGraphInstance(eu.dnetlib.dhp.schema.oaf.Instance i) { private static Instance getGraphInstance(eu.dnetlib.dhp.schema.oaf.Instance i) {
Instance instance = new Instance(); Instance instance = new Instance();
@ -397,11 +433,11 @@ public class ResultMapper implements Serializable {
} }
private static <I extends Instance> void setCommonValue(eu.dnetlib.dhp.schema.oaf.Instance i, I instance) { private static <I extends Instance> void setCommonValue(eu.dnetlib.dhp.schema.oaf.Instance i, I instance) {
Optional<eu.dnetlib.dhp.schema.oaf.Qualifier> opAr = Optional Optional<eu.dnetlib.dhp.schema.oaf.AccessRight> opAr = Optional.ofNullable(i.getAccessright());
.ofNullable(i.getAccessright());
if (opAr.isPresent()) { if (opAr.isPresent() && Constants.accessRightsCoarMap.containsKey(opAr.get().getClassid())) {
if (Constants.accessRightsCoarMap.containsKey(opAr.get().getClassid())) {
String code = Constants.accessRightsCoarMap.get(opAr.get().getClassid()); String code = Constants.accessRightsCoarMap.get(opAr.get().getClassid());
instance instance
.setAccessright( .setAccessright(
AccessRight AccessRight
@ -409,9 +445,46 @@ public class ResultMapper implements Serializable {
code, code,
Constants.coarCodeLabelMap.get(code), Constants.coarCodeLabelMap.get(code),
Constants.COAR_ACCESS_RIGHT_SCHEMA)); Constants.COAR_ACCESS_RIGHT_SCHEMA));
if (opAr.get().getOpenAccessRoute() != null) {
switch (opAr.get().getOpenAccessRoute()) {
case hybrid:
instance.getAccessright().setOpenAccessRoute(OpenAccessRoute.hybrid);
break;
case gold:
instance.getAccessright().setOpenAccessRoute(OpenAccessRoute.gold);
break;
case green:
instance.getAccessright().setOpenAccessRoute(OpenAccessRoute.green);
break;
case bronze:
instance.getAccessright().setOpenAccessRoute(OpenAccessRoute.bronze);
break;
} }
} }
}
Optional
.ofNullable(i.getPid())
.ifPresent(
pid -> instance
.setPid(
pid
.stream()
.map(p -> ControlledField.newInstance(p.getQualifier().getClassid(), p.getValue()))
.collect(Collectors.toList())));
Optional
.ofNullable(i.getAlternateIdentifier())
.ifPresent(
ai -> instance
.setAlternateIdentifier(
ai
.stream()
.map(p -> ControlledField.newInstance(p.getQualifier().getClassid(), p.getValue()))
.collect(Collectors.toList())));
Optional Optional
.ofNullable(i.getLicense()) .ofNullable(i.getLicense())
.ifPresent(value -> instance.setLicense(value.getValue())); .ifPresent(value -> instance.setLicense(value.getValue()));
@ -424,11 +497,26 @@ public class ResultMapper implements Serializable {
Optional Optional
.ofNullable(i.getInstancetype()) .ofNullable(i.getInstancetype())
.ifPresent(value -> instance.setType(value.getClassname())); .ifPresent(value -> instance.setType(value.getClassname()));
Optional.ofNullable(i.getUrl()).ifPresent(value -> instance.setUrl(value));
Optional<Field<String>> oPca = Optional.ofNullable(i.getProcessingchargeamount());
Optional<Field<String>> oPcc = Optional.ofNullable(i.getProcessingchargecurrency());
if (oPca.isPresent() && oPcc.isPresent()) {
Field<String> pca = oPca.get();
Field<String> pcc = oPcc.get();
if (!pca.getValue().trim().equals("") && !pcc.getValue().trim().equals("")) {
APC apc = new APC();
apc.setCurrency(oPcc.get().getValue());
apc.setAmount(oPca.get().getValue());
instance.setArticleprocessingcharge(apc);
}
}
Optional.ofNullable(i.getUrl()).ifPresent(instance::setUrl); Optional.ofNullable(i.getUrl()).ifPresent(instance::setUrl);
} }
private static List<Provenance> getUniqueProvenance(List<Provenance> provenance) { private static List<Provenance> getUniqueProvenance(List<Provenance> provenance)
throws NoAvailableEntityTypeException {
Provenance iProv = new Provenance(); Provenance iProv = new Provenance();
Provenance hProv = new Provenance(); Provenance hProv = new Provenance();
@ -450,6 +538,8 @@ public class ResultMapper implements Serializable {
case Constants.USER_CLAIM: case Constants.USER_CLAIM:
lProv = getHighestTrust(lProv, p); lProv = getHighestTrust(lProv, p);
break; break;
default:
throw new NoAvailableEntityTypeException();
} }
} }
@ -503,9 +593,7 @@ public class ResultMapper implements Serializable {
return a; return a;
} }
private static Pid getOrcid(List<StructuredProperty> p) { private static Pid getAuthorPid(StructuredProperty pid) {
for (StructuredProperty pid : p) {
if (pid.getQualifier().getClassid().equals(ModelConstants.ORCID)) {
Optional<DataInfo> di = Optional.ofNullable(pid.getDataInfo()); Optional<DataInfo> di = Optional.ofNullable(pid.getDataInfo());
if (di.isPresent()) { if (di.isPresent()) {
return Pid return Pid
@ -528,9 +616,44 @@ public class ResultMapper implements Serializable {
); );
} }
}
private static Pid getOrcid(List<StructuredProperty> p) {
List<StructuredProperty> pidList = p.stream().map(pid -> {
if (pid.getQualifier().getClassid().equals(ModelConstants.ORCID) ||
(pid.getQualifier().getClassid().equals(ModelConstants.ORCID_PENDING))) {
return pid;
} }
return null;
}).filter(Objects::nonNull).collect(Collectors.toList());
if (pidList.size() == 1) {
return getAuthorPid(pidList.get(0));
} }
List<StructuredProperty> orcid = pidList
.stream()
.filter(
ap -> ap
.getQualifier()
.getClassid()
.equals(ModelConstants.ORCID))
.collect(Collectors.toList());
if (orcid.size() == 1) {
return getAuthorPid(orcid.get(0));
}
orcid = pidList
.stream()
.filter(
ap -> ap
.getQualifier()
.getClassid()
.equals(ModelConstants.ORCID_PENDING))
.collect(Collectors.toList());
if (orcid.size() == 1) {
return getAuthorPid(orcid.get(0));
}
return null; return null;
} }

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