Merge branch 'master' into stable_ids

This commit is contained in:
Claudio Atzori 2020-11-02 12:16:01 +01:00
commit 09e44dabff
26 changed files with 625 additions and 86 deletions

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@ -94,7 +94,13 @@ public class AuthorMerger {
if (r.getPid() == null) {
r.setPid(new ArrayList<>());
}
r.getPid().add(a._1());
// TERRIBLE HACK but for some reason when we create and Array with Arrays.asList,
// it creates of fixed size, and the add method raise UnsupportedOperationException at
// java.util.AbstractList.add
final List<StructuredProperty> tmp = new ArrayList<>(r.getPid());
tmp.add(a._1());
r.setPid(tmp);
}
}
});

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@ -39,15 +39,15 @@ public class ModelConstants {
public static final String IS_SUPPLEMENT_TO = "isSupplementTo";
public static final String IS_SUPPLEMENTED_BY = "isSupplementedBy";
public static final String PART = "part";
public static final String IS_PART_OF = "IsPartOf";
public static final String HAS_PARTS = "HasParts";
public static final String IS_PART_OF = "isPartOf";
public static final String HAS_PARTS = "hasParts";
public static final String RELATIONSHIP = "relationship";
public static final String CITATION = "citation";
public static final String CITES = "cites";
public static final String IS_CITED_BY = "IsCitedBy";
public static final String IS_CITED_BY = "isCitedBy";
public static final String REVIEW = "review";
public static final String REVIEWS = "reviews";
public static final String IS_REVIEWED_BY = "IsReviewedBy";
public static final String IS_REVIEWED_BY = "isReviewedBy";
public static final String RESULT_PROJECT = "resultProject";
public static final String OUTCOME = "outcome";

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@ -4,6 +4,7 @@ package eu.dnetlib.dhp.actionmanager.project;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Optional;
@ -11,6 +12,7 @@ import org.apache.commons.io.IOUtils;
import org.apache.commons.lang3.StringUtils;
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.*;
import org.slf4j.Logger;
@ -175,43 +177,54 @@ public class PrepareProgramme {
return csvProgramme;
});
prepareClassification(h2020Programmes);
// prepareClassification(h2020Programmes);
h2020Programmes
.map(csvProgramme -> OBJECT_MAPPER.writeValueAsString(csvProgramme))
JavaSparkContext jsc = new JavaSparkContext(spark.sparkContext());
JavaRDD<CSVProgramme> rdd = jsc.parallelize(prepareClassification(h2020Programmes), 1);
rdd
.map(csvProgramme -> {
String tmp = OBJECT_MAPPER.writeValueAsString(csvProgramme);
return tmp;
})
.saveAsTextFile(outputPath);
}
private static void prepareClassification(JavaRDD<CSVProgramme> h2020Programmes) {
private static List<CSVProgramme> prepareClassification(JavaRDD<CSVProgramme> h2020Programmes) {
Object[] codedescription = h2020Programmes
.map(value -> new Tuple2<>(value.getCode(), value.getTitle()))
.map(
value -> new Tuple2<>(value.getCode(),
new Tuple2<String, String>(value.getTitle(), value.getShortTitle())))
.collect()
.toArray();
for (int i = 0; i < codedescription.length - 1; i++) {
for (int j = i + 1; j < codedescription.length; j++) {
Tuple2<String, String> t2i = (Tuple2<String, String>) codedescription[i];
Tuple2<String, String> t2j = (Tuple2<String, String>) codedescription[j];
Tuple2<String, Tuple2<String, String>> t2i = (Tuple2<String, Tuple2<String, String>>) codedescription[i];
Tuple2<String, Tuple2<String, String>> t2j = (Tuple2<String, Tuple2<String, String>>) codedescription[j];
if (t2i._1().compareTo(t2j._1()) > 0) {
Tuple2<String, String> temp = t2i;
Tuple2<String, Tuple2<String, String>> temp = t2i;
codedescription[i] = t2j;
codedescription[j] = temp;
}
}
}
Map<String, String> map = new HashMap<>();
Map<String, Tuple2<String, String>> map = new HashMap<>();
for (int j = 0; j < codedescription.length; j++) {
Tuple2<String, String> entry = (Tuple2<String, String>) codedescription[j];
Tuple2<String, Tuple2<String, String>> entry = (Tuple2<String, Tuple2<String, String>>) codedescription[j];
String ent = entry._1();
if (ent.contains("Euratom-")) {
ent = ent.replace("-Euratom-", ".Euratom.");
}
String[] tmp = ent.split("\\.");
if (tmp.length <= 2) {
map.put(entry._1(), entry._2());
if (StringUtils.isEmpty(entry._2()._2())) {
map.put(entry._1(), new Tuple2<String, String>(entry._2()._1(), entry._2()._1()));
} else {
map.put(entry._1(), entry._2());
}
} else {
if (ent.endsWith(".")) {
ent = ent.substring(0, ent.length() - 1);
@ -224,14 +237,14 @@ public class PrepareProgramme {
key = key.substring(0, key.length() - 1);
}
}
String current = entry._2();
String current = entry._2()._1();
if (!ent.contains("Euratom")) {
String parent;
String tmp_key = tmp[0] + ".";
for (int i = 1; i < tmp.length - 1; i++) {
tmp_key += tmp[i] + ".";
parent = map.get(tmp_key).toLowerCase().trim();
parent = map.get(tmp_key)._1().toLowerCase().trim();
if (parent.contains("|")) {
parent = parent.substring(parent.lastIndexOf("|") + 1).trim();
}
@ -246,18 +259,29 @@ public class PrepareProgramme {
}
}
map.put(ent + ".", map.get(key) + " | " + current);
String shortTitle = entry._2()._2();
if (StringUtils.isEmpty(shortTitle)) {
shortTitle = current;
}
Tuple2<String, String> newEntry = new Tuple2<>(map.get(key)._1() + " | " + current,
map.get(key)._2() + " | " + shortTitle);
map.put(ent + ".", newEntry);
}
}
h2020Programmes.foreach(csvProgramme -> {
if (!csvProgramme.getCode().endsWith(".") && !csvProgramme.getCode().contains("Euratom")
&& !csvProgramme.getCode().equals("H2020-EC"))
csvProgramme.setClassification(map.get(csvProgramme.getCode() + "."));
else
csvProgramme.setClassification(map.get(csvProgramme.getCode()));
});
return h2020Programmes.map(csvProgramme -> {
String code = csvProgramme.getCode();
if (!code.endsWith(".") && !code.contains("Euratom")
&& !code.equals("H2020-EC"))
code += ".";
csvProgramme.setClassification(map.get(code)._1());
csvProgramme.setClassification_short(map.get(code)._2());
return csvProgramme;
}).collect();
}
public static <R> Dataset<R> readPath(

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@ -9,7 +9,6 @@ import java.util.Objects;
import java.util.Optional;
import org.apache.commons.io.IOUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.SequenceFileOutputFormat;
import org.apache.spark.SparkConf;
@ -138,7 +137,8 @@ public class SparkAtomicActionJob {
pm.setCode(csvProject.getProgramme());
h2020classification.setClassification(ocsvProgramme.get().getClassification());
h2020classification.setH2020Programme(pm);
setLevelsAndProgramme(h2020classification, ocsvProgramme.get().getClassification());
setLevelsandProgramme(h2020classification, ocsvProgramme.get().getClassification_short());
// setProgramme(h2020classification, ocsvProgramme.get().getClassification());
pp.setH2020classification(Arrays.asList(h2020classification));
return pp;
@ -177,8 +177,8 @@ public class SparkAtomicActionJob {
}
private static void setLevelsAndProgramme(H2020Classification h2020Classification, String classification) {
String[] tmp = classification.split(" \\| ");
private static void setLevelsandProgramme(H2020Classification h2020Classification, String classification_short) {
String[] tmp = classification_short.split(" \\| ");
h2020Classification.setLevel1(tmp[0]);
if (tmp.length > 1) {
h2020Classification.setLevel2(tmp[1]);
@ -189,6 +189,12 @@ public class SparkAtomicActionJob {
h2020Classification.getH2020Programme().setDescription(tmp[tmp.length - 1]);
}
// private static void setProgramme(H2020Classification h2020Classification, String classification) {
// String[] tmp = classification.split(" \\| ");
//
// h2020Classification.getH2020Programme().setDescription(tmp[tmp.length - 1]);
// }
public static <R> Dataset<R> readPath(
SparkSession spark, String inputPath, Class<R> clazz) {
return spark

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@ -22,6 +22,15 @@ public class CSVProgramme implements Serializable {
private String shortTitle;
private String language;
private String classification;
private String classification_short;
public String getClassification_short() {
return classification_short;
}
public void setClassification_short(String classification_short) {
this.classification_short = classification_short;
}
public String getClassification() {
return classification;

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@ -9,12 +9,14 @@ import java.util.List;
import org.apache.poi.openxml4j.exceptions.InvalidFormatException;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Disabled;
import org.junit.jupiter.api.Test;
import eu.dnetlib.dhp.actionmanager.project.httpconnector.CollectorServiceException;
import eu.dnetlib.dhp.actionmanager.project.httpconnector.HttpConnector;
import eu.dnetlib.dhp.actionmanager.project.utils.EXCELParser;
@Disabled
public class EXCELParserTest {
private static Path workingDir;

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@ -92,6 +92,8 @@ public class PrepareH2020ProgrammeTest {
Assertions.assertEquals(0, verificationDataset.filter("classification = ''").count());
// tmp.foreach(csvProgramme -> System.out.println(OBJECT_MAPPER.writeValueAsString(csvProgramme)));
Assertions
.assertEquals(
"Societal challenges | Smart, Green And Integrated Transport | CLEANSKY2 | IADP Fast Rotorcraft",

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@ -78,7 +78,7 @@ public class SparkUpdateProjectTest {
"-programmePath",
getClass()
.getResource(
"/eu/dnetlib/dhp/actionmanager/project/preparedProgramme_classification_whole.json.gz")
"/eu/dnetlib/dhp/actionmanager/project/preparedProgramme_whole.json.gz")
.getPath(),
"-projectPath",
getClass().getResource("/eu/dnetlib/dhp/actionmanager/project/prepared_projects.json").getPath(),
@ -124,7 +124,7 @@ public class SparkUpdateProjectTest {
.getString(0));
Assertions
.assertEquals(
"Societal challenges",
"Societal Challenges",
execverification
.filter("id = '40|corda__h2020::2c7298913008865ba784e5c1350a0aa5'")
.select("classification.level1")
@ -133,7 +133,7 @@ public class SparkUpdateProjectTest {
.getString(0));
Assertions
.assertEquals(
"Smart, Green And Integrated Transport",
"Transport",
execverification
.filter("id = '40|corda__h2020::2c7298913008865ba784e5c1350a0aa5'")
.select("classification.level2")
@ -188,7 +188,7 @@ public class SparkUpdateProjectTest {
.getString(0));
Assertions
.assertEquals(
"Nurturing excellence by means of cross-border and cross-sector mobility",
"MSCA Mobility",
execverification
.filter("id = '40|corda__h2020::1a1f235fdd06ef14790baec159aa1202'")
.select("classification.h2020Programme.description")
@ -197,7 +197,7 @@ public class SparkUpdateProjectTest {
.getString(0));
Assertions
.assertEquals(
"Excellent science",
"Excellent Science",
execverification
.filter("id = '40|corda__h2020::1a1f235fdd06ef14790baec159aa1202'")
.select("classification.level1")
@ -206,7 +206,7 @@ public class SparkUpdateProjectTest {
.getString(0));
Assertions
.assertEquals(
"Marie Skłodowska-Curie Actions",
"Marie-Sklodowska-Curie Actions",
execverification
.filter("id = '40|corda__h2020::1a1f235fdd06ef14790baec159aa1202'")
.select("classification.level2")
@ -215,7 +215,7 @@ public class SparkUpdateProjectTest {
.getString(0));
Assertions
.assertEquals(
"Nurturing excellence by means of cross-border and cross-sector mobility",
"MSCA Mobility",
execverification
.filter("id = '40|corda__h2020::1a1f235fdd06ef14790baec159aa1202'")
.select("classification.level3")

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@ -6,8 +6,11 @@ import org.apache.commons.logging.LogFactory;
import org.apache.http.conn.ssl.SSLConnectionSocketFactory;
import org.apache.http.ssl.SSLContextBuilder;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Disabled;
import org.junit.jupiter.api.Test;
@Disabled
public class HttpConnectorTest {
private static final Log log = LogFactory.getLog(HttpConnectorTest.class);

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@ -1,13 +1,15 @@
package eu.dnetlib.doiboost
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.schema.oaf.{Publication, Relation, Dataset => OafDataset, Organization}
import eu.dnetlib.dhp.oa.merge.AuthorMerger
import eu.dnetlib.dhp.schema.oaf.{Organization, Publication, Relation, Dataset => OafDataset}
import eu.dnetlib.doiboost.mag.ConversionUtil
import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf
import org.apache.spark.sql.functions.col
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
import scala.collection.JavaConverters._
object SparkGenerateDoiBoost {
@ -49,6 +51,7 @@ object SparkGenerateDoiBoost {
val otherPub = item._2._2
if (otherPub != null) {
crossrefPub.mergeFrom(otherPub)
crossrefPub.setAuthor(AuthorMerger.mergeAuthor(crossrefPub.getAuthor, otherPub.getAuthor))
}
}
crossrefPub

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@ -38,6 +38,8 @@ class QueryTest {
def myQuery(spark:SparkSession, sc:SparkContext): Unit = {
implicit val mapEncoderPub: Encoder[Publication] = Encoders.kryo[Publication]
val mapper = new ObjectMapper()
mapper.getSerializationConfig.enable(SerializationConfig.Feature.INDENT_OUTPUT)

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@ -4,7 +4,6 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.schema.oaf.{Oaf, Relation}
import eu.dnetlib.dhp.schema.scholexplorer.{DLIDataset, DLIPublication, DLIUnknown}
import eu.dnetlib.dhp.sx.ebi.EBIAggregator
import eu.dnetlib.dhp.sx.ebi.model.{PMArticle, PMAuthor, PMJournal}
import org.apache.commons.io.IOUtils
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.LoggerFactory
@ -18,38 +17,38 @@ object SparkSplitOafTODLIEntities {
}
def main(args: Array[String]): Unit = {
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkSplitOafTODLIEntities.getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/argumentparser/input_extract_entities_parameters.json")))
val logger = LoggerFactory.getLogger(SparkSplitOafTODLIEntities.getClass)
parser.parseArgument(args)
val workingPath: String = parser.get("workingPath")
logger.info(s"Working dir path = $workingPath")
def extract_dataset(spark:SparkSession, workingPath:String) :Unit = {
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val datEncoder: Encoder[DLIDataset] = Encoders.kryo[DLIDataset]
val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf].repartition(4000)
val ebi_dataset:Dataset[DLIDataset] = spark.read.load(s"$workingPath/ebi/baseline_dataset_ebi").as[DLIDataset].repartition(1000)
OAFDataset
.filter(s => s != null && s.isInstanceOf[DLIDataset])
.map(s =>s.asInstanceOf[DLIDataset])
.union(ebi_dataset)
.map(d => (d.getId, d))(Encoders.tuple(Encoders.STRING, datEncoder))
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getDLIDatasetAggregator().toColumn)
.map(p => p._2)
.repartition(2000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/dataset")
}
def extract_publication(spark:SparkSession, workingPath:String) :Unit = {
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val pubEncoder: Encoder[DLIPublication] = Encoders.kryo[DLIPublication]
implicit val datEncoder: Encoder[DLIDataset] = Encoders.kryo[DLIDataset]
implicit val unkEncoder: Encoder[DLIUnknown] = Encoders.kryo[DLIUnknown]
implicit val relEncoder: Encoder[Relation] = Encoders.kryo[Relation]
val spark:SparkSession = SparkSession
.builder()
.appName(SparkSplitOafTODLIEntities.getClass.getSimpleName)
.config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
.master(parser.get("master"))
.getOrCreate()
val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf]
val ebi_dataset:Dataset[DLIDataset] = spark.read.load(s"$workingPath/ebi/baseline_dataset_ebi").as[DLIDataset]
val ebi_publication:Dataset[DLIPublication] = spark.read.load(s"$workingPath/ebi/baseline_publication_ebi").as[DLIPublication]
val ebi_relation:Dataset[Relation] = spark.read.load(s"$workingPath/ebi/baseline_relation_ebi").as[Relation]
val ebi_publication:Dataset[DLIPublication] = spark.read.load(s"$workingPath/ebi/baseline_publication_ebi").as[DLIPublication].repartition(1000)
OAFDataset
@ -60,20 +59,17 @@ object SparkSplitOafTODLIEntities {
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getDLIPublicationAggregator().toColumn)
.map(p => p._2)
.repartition(1000)
.repartition(2000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/publication")
OAFDataset
.filter(s => s != null && s.isInstanceOf[DLIDataset])
.map(s =>s.asInstanceOf[DLIDataset])
.union(ebi_dataset)
.map(d => (d.getId, d))(Encoders.tuple(Encoders.STRING, datEncoder))
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getDLIDatasetAggregator().toColumn)
.map(p => p._2)
.repartition(1000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/dataset")
}
def extract_unknown(spark:SparkSession, workingPath:String) :Unit = {
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val unkEncoder: Encoder[DLIUnknown] = Encoders.kryo[DLIUnknown]
val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf]
OAFDataset
.filter(s => s != null && s.isInstanceOf[DLIUnknown])
@ -82,9 +78,18 @@ object SparkSplitOafTODLIEntities {
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getDLIUnknownAggregator().toColumn)
.map(p => p._2)
.repartition(1000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/unknown")
}
def extract_relations(spark:SparkSession, workingPath:String) :Unit = {
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val relEncoder: Encoder[Relation] = Encoders.kryo[Relation]
val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf]
val ebi_relation:Dataset[Relation] = spark.read.load(s"$workingPath/ebi/baseline_relation_ebi").as[Relation].repartition(2000)
OAFDataset
.filter(s => s != null && s.isInstanceOf[Relation])
@ -94,9 +99,35 @@ object SparkSplitOafTODLIEntities {
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getRelationAggregator().toColumn)
.map(p => p._2)
.repartition(1000)
.repartition(4000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/relation")
}
def main(args: Array[String]): Unit = {
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkSplitOafTODLIEntities.getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/argumentparser/input_extract_entities_parameters.json")))
val logger = LoggerFactory.getLogger(SparkSplitOafTODLIEntities.getClass)
parser.parseArgument(args)
val workingPath: String = parser.get("workingPath")
val entity:String = parser.get("entity")
logger.info(s"Working dir path = $workingPath")
val spark:SparkSession = SparkSession
.builder()
.appName(SparkSplitOafTODLIEntities.getClass.getSimpleName)
.config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
.master(parser.get("master"))
.getOrCreate()
entity match {
case "publication" => extract_publication(spark, workingPath)
case "dataset" => extract_dataset(spark,workingPath)
case "relation" => extract_relations(spark, workingPath)
case "unknown" => extract_unknown(spark, workingPath)
}

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@ -1,4 +1,5 @@
[
{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the work dir path", "paramRequired": true}
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the work dir path", "paramRequired": true},
{"paramName":"e", "paramLongName":"entity", "paramDescription": "the work dir path", "paramRequired": true}
]

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@ -14,30 +14,103 @@
</property>
</parameters>
<start to="ExtractDLIEntities"/>
<start to="ExtractDLIPublication"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="ExtractDLIEntities">
<action name="ExtractDLIPublication">
<spark xmlns="uri:oozie:spark-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Extract DLI Entities</name>
<name>Extract DLI Entities (Publication)</name>
<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory ${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840
--conf spark.sql.shuffle.partitions=5000
${sparkExtraOPT}
</spark-opts>
<arg>-mt</arg> <arg>yarn-cluster</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>-e</arg><arg>publication</arg>
</spark>
<ok to="ExtractDLIDataset"/>
<error to="Kill"/>
</action>
<action name="ExtractDLIDataset">
<spark xmlns="uri:oozie:spark-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Extract DLI Entities (Dataset)</name>
<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory ${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=5000
${sparkExtraOPT}
</spark-opts>
<arg>-mt</arg> <arg>yarn-cluster</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>-e</arg><arg>dataset</arg>
</spark>
<ok to="ExtractDLIUnknown"/>
<error to="Kill"/>
</action>
<action name="ExtractDLIUnknown">
<spark xmlns="uri:oozie:spark-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Extract DLI Entities (Unknown)</name>
<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory ${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=5000
${sparkExtraOPT}
</spark-opts>
<arg>-mt</arg> <arg>yarn-cluster</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>-e</arg><arg>unknown</arg>
</spark>
<ok to="ExtractDLIRelation"/>
<error to="Kill"/>
</action>
<action name="ExtractDLIRelation">
<spark xmlns="uri:oozie:spark-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Extract DLI Entities (Relation)</name>
<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory ${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=5000
${sparkExtraOPT}
</spark-opts>
<arg>-mt</arg> <arg>yarn-cluster</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>-e</arg><arg>relation</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>

View File

@ -30,7 +30,7 @@ class SparkScholexplorerAggregationTest {
implicit val pubEncoder: Encoder[DLIPublication] = Encoders.kryo[DLIPublication]
val spark: SparkSession = SparkSession.builder().appName("Test").master("local[*]").getOrCreate()
val spark: SparkSession = SparkSession.builder().appName("Test").master("local[*]").config("spark.driver.bindAddress", "127.0.0.1").getOrCreate()
val ds: Dataset[DLIPublication] = spark.createDataset(spark.sparkContext.parallelize(s)).as[DLIPublication]

View File

@ -62,6 +62,10 @@
<artifactId>dhp-schemas</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.httpcomponents</groupId>
<artifactId>httpmime</artifactId>
</dependency>
<dependency>
<groupId>org.elasticsearch</groupId>

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@ -0,0 +1,111 @@
package eu.dnetlib.dhp.export.zenodo;
import java.io.*;
import org.apache.commons.compress.archivers.tar.TarArchiveEntry;
import org.apache.commons.compress.archivers.tar.TarArchiveOutputStream;
import org.apache.commons.io.IOUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.*;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
public class MakeTar implements Serializable {
private static final Logger log = LoggerFactory.getLogger(MakeTar.class);
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
.toString(
MakeTar.class
.getResourceAsStream(
"/eu/dnetlib/dhp/export/input_maketar_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
final String outputPath = parser.get("targetPath");
log.info("hdfsPath: {}", outputPath);
final String hdfsNameNode = parser.get("nameNode");
log.info("nameNode: {}", hdfsNameNode);
final String inputPath = parser.get("sourcePath");
log.info("input path : {}", inputPath);
Configuration conf = new Configuration();
conf.set("fs.defaultFS", hdfsNameNode);
FileSystem fileSystem = FileSystem.get(conf);
makeTArArchive(fileSystem, inputPath, outputPath);
}
public static void makeTArArchive(FileSystem fileSystem, String inputPath, String outputPath) throws IOException {
RemoteIterator<LocatedFileStatus> dir_iterator = fileSystem.listLocatedStatus(new Path(inputPath));
while (dir_iterator.hasNext()) {
LocatedFileStatus fileStatus = dir_iterator.next();
Path p = fileStatus.getPath();
String p_string = p.toString();
String entity = p_string.substring(p_string.lastIndexOf("/") + 1);
write(fileSystem, p_string, outputPath + "/" + entity + ".tar", entity);
}
}
private static void write(FileSystem fileSystem, String inputPath, String outputPath, String dir_name)
throws IOException {
Path hdfsWritePath = new Path(outputPath);
FSDataOutputStream fsDataOutputStream = null;
if (fileSystem.exists(hdfsWritePath)) {
fileSystem.delete(hdfsWritePath, true);
}
fsDataOutputStream = fileSystem.create(hdfsWritePath);
TarArchiveOutputStream ar = new TarArchiveOutputStream(fsDataOutputStream.getWrappedStream());
RemoteIterator<LocatedFileStatus> fileStatusListIterator = fileSystem
.listFiles(
new Path(inputPath), true);
while (fileStatusListIterator.hasNext()) {
LocatedFileStatus fileStatus = fileStatusListIterator.next();
Path p = fileStatus.getPath();
String p_string = p.toString();
if (!p_string.endsWith("_SUCCESS")) {
String name = p_string.substring(p_string.lastIndexOf("/") + 1);
TarArchiveEntry entry = new TarArchiveEntry(dir_name + "/" + name + ".json.gz");
entry.setSize(fileStatus.getLen());
ar.putArchiveEntry(entry);
InputStream is = fileSystem.open(fileStatus.getPath());
BufferedInputStream bis = new BufferedInputStream(is);
int count;
byte data[] = new byte[1024];
while ((count = bis.read(data, 0, data.length)) != -1) {
ar.write(data, 0, count);
}
bis.close();
ar.closeArchiveEntry();
}
}
ar.close();
}
}

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@ -0,0 +1,80 @@
package eu.dnetlib.dhp.export.zenodo;
import java.io.Serializable;
import java.util.Optional;
import org.apache.commons.io.IOUtils;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.*;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.common.api.MissingConceptDoiException;
import eu.dnetlib.dhp.common.api.ZenodoAPIClient;
public class SendToZenodoHDFS implements Serializable {
private static final Log log = LogFactory.getLog(SendToZenodoHDFS.class);
public static void main(final String[] args) throws Exception, MissingConceptDoiException {
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
IOUtils
.toString(
SendToZenodoHDFS.class
.getResourceAsStream(
"/eu/dnetlib/dhp/export/upload_zenodo.json")));
parser.parseArgument(args);
final String hdfsPath = parser.get("hdfsPath");
final String hdfsNameNode = parser.get("nameNode");
final String access_token = parser.get("accessToken");
final String connection_url = parser.get("connectionUrl");
final String metadata = parser.get("metadata");
final Boolean newDeposition = Boolean.valueOf(parser.get("newDeposition"));
final String concept_rec_id = Optional
.ofNullable(parser.get("conceptRecordId"))
.orElse(null);
Configuration conf = new Configuration();
conf.set("fs.defaultFS", hdfsNameNode);
FileSystem fileSystem = FileSystem.get(conf);
RemoteIterator<LocatedFileStatus> fileStatusListIterator = fileSystem
.listFiles(
new Path(hdfsPath), true);
ZenodoAPIClient zenodoApiClient = new ZenodoAPIClient(connection_url, access_token);
if (newDeposition) {
zenodoApiClient.newDeposition();
} else {
if (concept_rec_id == null) {
throw new MissingConceptDoiException("No concept record id has been provided");
}
zenodoApiClient.newVersion(concept_rec_id);
}
while (fileStatusListIterator.hasNext()) {
LocatedFileStatus fileStatus = fileStatusListIterator.next();
Path p = fileStatus.getPath();
String p_string = p.toString();
if (!p_string.endsWith("_SUCCESS")) {
// String tmp = p_string.substring(0, p_string.lastIndexOf("/"));
String name = p_string.substring(p_string.lastIndexOf("/") + 1);
log.info("Sending information for community: " + name);
FSDataInputStream inputStream = fileSystem.open(p);
zenodoApiClient.uploadIS(inputStream, name, fileStatus.getLen());
}
}
zenodoApiClient.sendMretadata(metadata);
zenodoApiClient.publish();
}
}

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@ -0,0 +1,20 @@
[
{
"paramName": "n",
"paramLongName": "nameNode",
"paramDescription": "the Name Node",
"paramRequired": true
},
{
"paramName": "s",
"paramLongName": "sourcePath",
"paramDescription": "the source path",
"paramRequired": true
},
{
"paramName": "t",
"paramLongName": "targetPath",
"paramDescription": "the target path",
"paramRequired": true
}
]

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@ -0,0 +1,45 @@
[
{
"paramName":"nd",
"paramLongName":"newDeposition",
"paramDescription": "if it is a new deposition (true) or a new version (false)",
"paramRequired": true
},
{
"paramName":"cri",
"paramLongName":"conceptRecordId",
"paramDescription": "The id of the concept record for a new version",
"paramRequired": false
},
{
"paramName":"hdfsp",
"paramLongName":"hdfsPath",
"paramDescription": "the path of the folder tofind files to send to Zenodo",
"paramRequired": true
},
{
"paramName": "nn",
"paramLongName": "nameNode",
"paramDescription": "the name node",
"paramRequired": true
},
{
"paramName": "at",
"paramLongName": "accessToken",
"paramDescription": "the access token for the deposition",
"paramRequired": false
},
{
"paramName":"cu",
"paramLongName":"connectionUrl",
"paramDescription": "the url to connect to deposit",
"paramRequired": false
},
{
"paramName":"m",
"paramLongName":"metadata",
"paramDescription": "metadata associated to the deposition",
"paramRequired": false
}
]

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@ -0,0 +1,48 @@
<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>oozie.action.sharelib.for.spark</name>
<value>spark2</value>
</property>
<property>
<name>oozie.wf.rerun.failnodes</name>
<value>false</value>
</property>
<property>
<name>hive_metastore_uris</name>
<value>thrift://iis-cdh5-test-m3.ocean.icm.edu.pl:9083</value>
</property>
<property>
<name>spark2YarnHistoryServerAddress</name>
<value>http://iis-cdh5-test-gw.ocean.icm.edu.pl:18089</value>
</property>
<property>
<name>spark2EventLogDir</name>
<value>/user/spark/spark2ApplicationHistory</value>
</property>
<property>
<name>spark2ExtraListeners</name>
<value>"com.cloudera.spark.lineage.NavigatorAppListener"</value>
</property>
<property>
<name>spark2SqlQueryExecutionListeners</name>
<value>"com.cloudera.spark.lineage.NavigatorQueryListener"</value>
</property>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>

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@ -0,0 +1,53 @@
<workflow-app name="Send Dump to Zenodo" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>sourcePath</name>
<description>the source path</description>
</property>
<property>
<name>targetPath</name>
<description>the target path</description>
</property>
<property>
<name>metadata</name>
<description>the metadata</description>
</property>
</parameters>
<start to="send_zenodo"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="MakeTar">
<java>
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<main-class>eu.dnetlib.dhp.export.zenodo.MakeTar</main-class>
<arg>-t</arg><arg>${targetPath}</arg>
<arg>-n</arg><arg>${nameNode}</arg>
<arg>-s</arg><arg>${sourcePath}</arg>
</java>
<ok to="End"/>
<error to="Kill"/>
</action>
<action name="send_zenodo">
<java>
<main-class>eu.dnetlib.dhp.export.zenodo.SendToZenodoHDFS</main-class>
<arg>--hdfsPath</arg><arg>/user/dnet.scholexplorer/scholix/provision/scholix.tar/scholix-2020-10-16.tar</arg>
<arg>--nameNode</arg><arg>${nameNode}</arg>
<arg>--accessToken</arg><arg>b6ddrY6b77WxcDEevn9gqVE5sL5sDNjdUijt75W3o7cQo5vpFFI48dMiu8Gv</arg>
<arg>--connectionUrl</arg><arg>https://zenodo.org/api/deposit/depositions</arg>
<arg>--metadata</arg><arg>${metadata}</arg>
<arg>--conceptRecordId</arg><arg>1200252</arg>
<arg>--newDeposition</arg><arg>false</arg>
</java>
<ok to="End"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

View File

@ -3,14 +3,15 @@ package eu.dnetlib.dhp.export
import java.time.LocalDateTime
import java.time.format.DateTimeFormatter
import eu.dnetlib.dhp.provision.scholix.Scholix
import eu.dnetlib.dhp.provision.scholix.summary.ScholixSummary
import eu.dnetlib.dhp.schema.oaf.Relation
import eu.dnetlib.dhp.schema.scholexplorer.{DLIDataset, DLIPublication}
import org.codehaus.jackson.map.{ObjectMapper, SerializationConfig}
import org.junit.jupiter.api.Test
import scala.io.Source
import scala.collection.JavaConverters._
class ExportDLITOOAFTest {
val mapper = new ObjectMapper()
@ -22,12 +23,27 @@ class ExportDLITOOAFTest {
}
def extractDatasources(s:Scholix):List[String]= {
s.getTarget.getCollectedFrom.asScala.map(c => c.getProvider.getName)(collection.breakOut)
}
def extractDatasources(s:ScholixSummary):List[String] = {
s.getDatasources.asScala.map(c => c.getDatasourceName)(collection.breakOut)
}
@Test
def testMappingRele():Unit = {
val r:Relation = new Relation
r.setSource("60|fbff1d424e045eecf24151a5fe3aa738")
r.setTarget("50|dedup_wf_001::ec409f09e63347d4e834087fe1483877")
r.setRelType("IsReferencedBy")
val r1 =DLIToOAF.convertDLIRelation(r)
println(r1.getSource, r1.getTarget)