mergin with branch beta
This commit is contained in:
commit
2bbece2ca5
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@ -27,8 +27,8 @@ public class GraphCleaningFunctions extends CleaningFunctions {
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public static final int ORCID_LEN = 19;
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public static final String CLEANING_REGEX = "(?:\\n|\\r|\\t)";
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public static final String INVALID_AUTHOR_REGEX = ".*deactivated.*";
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public static final String TITLE_FILTER_REGEX = "[.*test.*\\W\\d]";
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public static final int TITLE_FILTER_RESIDUAL_LENGTH = 10;
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public static final String TITLE_FILTER_REGEX = "(test)|\\W|\\d";
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public static final int TITLE_FILTER_RESIDUAL_LENGTH = 5;
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public static <T extends Oaf> T fixVocabularyNames(T value) {
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if (value instanceof Datasource) {
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|
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@ -107,7 +107,7 @@
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--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
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--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
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--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
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--conf spark.sql.shuffle.partitions=2560
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--conf spark.sql.shuffle.partitions=5000
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</spark-opts>
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<arg>--inputGraphTablePath</arg><arg>${inputGraphRootPath}/publication</arg>
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<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Publication</arg>
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@ -159,7 +159,7 @@
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--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
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--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
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--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
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--conf spark.sql.shuffle.partitions=2560
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--conf spark.sql.shuffle.partitions=5000
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</spark-opts>
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<arg>--inputGraphTablePath</arg><arg>${workingDir}/publication</arg>
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<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Publication</arg>
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|
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@ -99,7 +99,7 @@
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--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
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--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
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--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
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--conf spark.sql.shuffle.partitions=2560
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--conf spark.sql.shuffle.partitions=5000
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</spark-opts>
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<arg>--inputGraphTablePath</arg><arg>${inputGraphRootPath}/relation</arg>
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<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Relation</arg>
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@ -29,6 +29,13 @@
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<goal>testCompile</goal>
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</goals>
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</execution>
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<execution>
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<id>scala-doc</id>
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<phase>process-resources</phase> <!-- or wherever -->
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<goals>
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<goal>doc</goal>
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</goals>
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</execution>
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</executions>
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<configuration>
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<scalaVersion>${scala.version}</scalaVersion>
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@ -0,0 +1,49 @@
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package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
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import java.util.Optional;
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import org.apache.spark.api.java.function.MapFunction;
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import org.apache.spark.sql.Dataset;
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import org.apache.spark.sql.Encoders;
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import org.apache.spark.sql.SparkSession;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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public class Constants {
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public static final String DOI = "doi";
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public static final String UPDATE_DATA_INFO_TYPE = "update";
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public static final String UPDATE_SUBJECT_FOS_CLASS_ID = "subject:fos";
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public static final String UPDATE_CLASS_NAME = "Inferred by OpenAIRE";
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public static final String UPDATE_MEASURE_BIP_CLASS_ID = "measure:bip";
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public static final String FOS_CLASS_ID = "FOS";
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public static final String FOS_CLASS_NAME = "Fields of Science and Technology classification";
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public static final String NULL = "NULL";
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public static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
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private Constants() {
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}
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public static Boolean isSparkSessionManaged(ArgumentApplicationParser parser) {
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return Optional
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.ofNullable(parser.get("isSparkSessionManaged"))
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.map(Boolean::valueOf)
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.orElse(Boolean.TRUE);
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}
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public static <R> Dataset<R> readPath(
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SparkSession spark, String inputPath, Class<R> clazz) {
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return spark
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.read()
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.textFile(inputPath)
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.map((MapFunction<String, R>) value -> OBJECT_MAPPER.readValue(value, clazz), Encoders.bean(clazz));
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}
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}
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@ -0,0 +1,77 @@
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package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
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import java.io.IOException;
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import java.io.InputStreamReader;
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import java.io.Serializable;
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import java.util.Objects;
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import java.util.Optional;
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import org.apache.commons.io.IOUtils;
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import org.apache.hadoop.conf.Configuration;
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import org.apache.hadoop.fs.FileSystem;
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import org.apache.hadoop.fs.Path;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.common.collection.GetCSV;
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public class GetFOSData implements Serializable {
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private static final Logger log = LoggerFactory.getLogger(GetFOSData.class);
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public static final char DEFAULT_DELIMITER = '\t';
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public static void main(final String[] args) throws Exception {
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final ArgumentApplicationParser parser = new ArgumentApplicationParser(
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IOUtils
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.toString(
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Objects
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.requireNonNull(
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GetFOSData.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/get_fos_parameters.json"))));
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parser.parseArgument(args);
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// the path where the original fos csv file is stored
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final String sourcePath = parser.get("sourcePath");
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log.info("sourcePath {}", sourcePath);
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// the path where to put the file as json
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final String outputPath = parser.get("outputPath");
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log.info("outputPath {}", outputPath);
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final String hdfsNameNode = parser.get("hdfsNameNode");
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log.info("hdfsNameNode {}", hdfsNameNode);
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final String classForName = parser.get("classForName");
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log.info("classForName {}", classForName);
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final char delimiter = Optional
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.ofNullable(parser.get("delimiter"))
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.map(s -> s.charAt(0))
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.orElse(DEFAULT_DELIMITER);
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log.info("delimiter {}", delimiter);
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Configuration conf = new Configuration();
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conf.set("fs.defaultFS", hdfsNameNode);
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FileSystem fileSystem = FileSystem.get(conf);
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new GetFOSData().doRewrite(sourcePath, outputPath, classForName, delimiter, fileSystem);
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}
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public void doRewrite(String inputPath, String outputFile, String classForName, char delimiter, FileSystem fs)
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throws IOException, ClassNotFoundException {
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// reads the csv and writes it as its json equivalent
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try (InputStreamReader reader = new InputStreamReader(fs.open(new Path(inputPath)))) {
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GetCSV.getCsv(fs, reader, outputFile, classForName, delimiter);
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}
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}
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}
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@ -0,0 +1,145 @@
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package eu.dnetlib.dhp.actionmanager.createunresolvedentities;
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import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.*;
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import static eu.dnetlib.dhp.actionmanager.createunresolvedentities.Constants.UPDATE_CLASS_NAME;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
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import java.io.Serializable;
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import java.util.List;
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import java.util.Optional;
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import java.util.stream.Collectors;
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import org.apache.commons.io.IOUtils;
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import org.apache.hadoop.hdfs.client.HdfsUtils;
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import org.apache.spark.SparkConf;
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import org.apache.spark.api.java.JavaRDD;
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import org.apache.spark.api.java.JavaSparkContext;
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import org.apache.spark.api.java.function.MapFunction;
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import org.apache.spark.sql.Encoders;
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import org.apache.spark.sql.SaveMode;
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import org.apache.spark.sql.SparkSession;
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import org.slf4j.Logger;
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||||
import org.slf4j.LoggerFactory;
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||||
import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.BipDeserialize;
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||||
import eu.dnetlib.dhp.actionmanager.createunresolvedentities.model.BipScore;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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||||
import eu.dnetlib.dhp.common.HdfsSupport;
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||||
import eu.dnetlib.dhp.schema.common.ModelConstants;
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||||
import eu.dnetlib.dhp.schema.oaf.KeyValue;
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||||
import eu.dnetlib.dhp.schema.oaf.Measure;
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||||
import eu.dnetlib.dhp.schema.oaf.Result;
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||||
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
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||||
import eu.dnetlib.dhp.utils.DHPUtils;
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||||
public class PrepareBipFinder implements Serializable {
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private static final Logger log = LoggerFactory.getLogger(PrepareBipFinder.class);
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||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
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||||
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||||
public static <I extends Result> void main(String[] args) throws Exception {
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||||
String jsonConfiguration = IOUtils
|
||||
.toString(
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PrepareBipFinder.class
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||||
.getResourceAsStream(
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||||
"/eu/dnetlib/dhp/actionmanager/createunresolvedentities/prepare_parameters.json"));
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||||
|
||||
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
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||||
|
||||
parser.parseArgument(args);
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|
||||
Boolean isSparkSessionManaged = Optional
|
||||
.ofNullable(parser.get("isSparkSessionManaged"))
|
||||
.map(Boolean::valueOf)
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||||
.orElse(Boolean.TRUE);
|
||||
|
||||
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
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|
||||
final String sourcePath = parser.get("sourcePath");
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||||
log.info("sourcePath {}: ", sourcePath);
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||||
|
||||
final String outputPath = parser.get("outputPath");
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||||
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());
|
||||
}
|
||||
}
|
||||
|
|
@ -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;
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -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);
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -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);
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -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;
|
||||
}
|
||||
}
|
||||
|
|
@ -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;
|
||||
}
|
||||
}
|
||||
|
|
@ -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;
|
||||
}
|
||||
}
|
||||
|
|
@ -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;
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,181 @@
|
|||
|
||||
package eu.dnetlib.dhp.actionmanager.opencitations;
|
||||
|
||||
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.io.Serializable;
|
||||
import java.util.*;
|
||||
|
||||
import org.apache.commons.cli.ParseException;
|
||||
import org.apache.commons.io.IOUtils;
|
||||
import org.apache.hadoop.io.Text;
|
||||
import org.apache.hadoop.mapred.SequenceFileOutputFormat;
|
||||
import org.apache.spark.SparkConf;
|
||||
import org.apache.spark.api.java.function.FilterFunction;
|
||||
import org.apache.spark.api.java.function.FlatMapFunction;
|
||||
import org.apache.spark.sql.Encoders;
|
||||
import org.apache.spark.sql.SparkSession;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
|
||||
import eu.dnetlib.dhp.schema.action.AtomicAction;
|
||||
import eu.dnetlib.dhp.schema.common.ModelConstants;
|
||||
import eu.dnetlib.dhp.schema.common.ModelSupport;
|
||||
import eu.dnetlib.dhp.schema.oaf.*;
|
||||
import eu.dnetlib.dhp.schema.oaf.utils.CleaningFunctions;
|
||||
import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory;
|
||||
import scala.Tuple2;
|
||||
|
||||
public class CreateActionSetSparkJob implements Serializable {
|
||||
public static final String OPENCITATIONS_CLASSID = "sysimport:crosswalk:opencitations";
|
||||
public static final String OPENCITATIONS_CLASSNAME = "Imported from OpenCitations";
|
||||
private static final String ID_PREFIX = "50|doi_________::";
|
||||
private static final String TRUST = "0.91";
|
||||
|
||||
private static final Logger log = LoggerFactory.getLogger(CreateActionSetSparkJob.class);
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
public static void main(final String[] args) throws IOException, ParseException {
|
||||
|
||||
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
|
||||
IOUtils
|
||||
.toString(
|
||||
Objects
|
||||
.requireNonNull(
|
||||
CreateActionSetSparkJob.class
|
||||
.getResourceAsStream(
|
||||
"/eu/dnetlib/dhp/actionmanager/opencitations/as_parameters.json"))));
|
||||
|
||||
parser.parseArgument(args);
|
||||
|
||||
Boolean isSparkSessionManaged = Optional
|
||||
.ofNullable(parser.get("isSparkSessionManaged"))
|
||||
.map(Boolean::valueOf)
|
||||
.orElse(Boolean.TRUE);
|
||||
|
||||
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
|
||||
|
||||
final String inputPath = parser.get("inputPath");
|
||||
log.info("inputPath {}", inputPath.toString());
|
||||
|
||||
final String outputPath = parser.get("outputPath");
|
||||
log.info("outputPath {}", outputPath);
|
||||
|
||||
final boolean shouldDuplicateRels = Optional
|
||||
.ofNullable(parser.get("shouldDuplicateRels"))
|
||||
.map(Boolean::valueOf)
|
||||
.orElse(Boolean.FALSE);
|
||||
|
||||
SparkConf conf = new SparkConf();
|
||||
runWithSparkSession(
|
||||
conf,
|
||||
isSparkSessionManaged,
|
||||
spark -> {
|
||||
extractContent(spark, inputPath, outputPath, shouldDuplicateRels);
|
||||
});
|
||||
|
||||
}
|
||||
|
||||
private static void extractContent(SparkSession spark, String inputPath, String outputPath,
|
||||
boolean shouldDuplicateRels) {
|
||||
spark
|
||||
.sqlContext()
|
||||
.createDataset(spark.sparkContext().textFile(inputPath + "/*", 6000), Encoders.STRING())
|
||||
.flatMap(
|
||||
(FlatMapFunction<String, Relation>) value -> createRelation(value, shouldDuplicateRels).iterator(),
|
||||
Encoders.bean(Relation.class))
|
||||
.filter((FilterFunction<Relation>) value -> value != null)
|
||||
.toJavaRDD()
|
||||
.map(p -> new AtomicAction(p.getClass(), p))
|
||||
.mapToPair(
|
||||
aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()),
|
||||
new Text(OBJECT_MAPPER.writeValueAsString(aa))))
|
||||
.saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class);
|
||||
|
||||
}
|
||||
|
||||
private static List<Relation> createRelation(String value, boolean duplicate) {
|
||||
String[] line = value.split(",");
|
||||
if (!line[1].startsWith("10.")) {
|
||||
return new ArrayList<>();
|
||||
}
|
||||
List<Relation> relationList = new ArrayList<>();
|
||||
|
||||
String citing = ID_PREFIX + IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", line[1]));
|
||||
final String cited = ID_PREFIX + IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", line[2]));
|
||||
|
||||
relationList
|
||||
.addAll(
|
||||
getRelations(
|
||||
citing,
|
||||
cited));
|
||||
|
||||
if (duplicate && line[1].endsWith(".refs")) {
|
||||
citing = ID_PREFIX + IdentifierFactory
|
||||
.md5(CleaningFunctions.normalizePidValue("doi", line[1].substring(0, line[1].indexOf(".refs"))));
|
||||
relationList.addAll(getRelations(citing, cited));
|
||||
}
|
||||
|
||||
return relationList;
|
||||
}
|
||||
|
||||
private static Collection<Relation> getRelations(String citing, String cited) {
|
||||
|
||||
return Arrays
|
||||
.asList(
|
||||
getRelation(citing, cited, ModelConstants.CITES),
|
||||
getRelation(cited, citing, ModelConstants.IS_CITED_BY));
|
||||
}
|
||||
|
||||
public static Relation getRelation(
|
||||
String source,
|
||||
String target,
|
||||
String relclass) {
|
||||
Relation r = new Relation();
|
||||
r.setCollectedfrom(getCollectedFrom());
|
||||
r.setSource(source);
|
||||
r.setTarget(target);
|
||||
r.setRelClass(relclass);
|
||||
r.setRelType(ModelConstants.RESULT_RESULT);
|
||||
r.setSubRelType(ModelConstants.CITATION);
|
||||
r
|
||||
.setDataInfo(
|
||||
getDataInfo());
|
||||
return r;
|
||||
}
|
||||
|
||||
public static List<KeyValue> getCollectedFrom() {
|
||||
KeyValue kv = new KeyValue();
|
||||
kv.setKey(ModelConstants.OPENOCITATIONS_ID);
|
||||
kv.setValue(ModelConstants.OPENOCITATIONS_NAME);
|
||||
|
||||
return Arrays.asList(kv);
|
||||
}
|
||||
|
||||
public static DataInfo getDataInfo() {
|
||||
DataInfo di = new DataInfo();
|
||||
di.setInferred(false);
|
||||
di.setDeletedbyinference(false);
|
||||
di.setTrust(TRUST);
|
||||
|
||||
di
|
||||
.setProvenanceaction(
|
||||
getQualifier(OPENCITATIONS_CLASSID, OPENCITATIONS_CLASSNAME, ModelConstants.DNET_PROVENANCE_ACTIONS));
|
||||
return di;
|
||||
}
|
||||
|
||||
public static Qualifier getQualifier(String class_id, String class_name,
|
||||
String qualifierSchema) {
|
||||
Qualifier pa = new Qualifier();
|
||||
pa.setClassid(class_id);
|
||||
pa.setClassname(class_name);
|
||||
pa.setSchemeid(qualifierSchema);
|
||||
pa.setSchemename(qualifierSchema);
|
||||
return pa;
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,93 @@
|
|||
|
||||
package eu.dnetlib.dhp.actionmanager.opencitations;
|
||||
|
||||
import java.io.*;
|
||||
import java.io.Serializable;
|
||||
import java.util.Objects;
|
||||
import java.util.zip.GZIPOutputStream;
|
||||
import java.util.zip.ZipEntry;
|
||||
import java.util.zip.ZipInputStream;
|
||||
|
||||
import org.apache.commons.cli.ParseException;
|
||||
import org.apache.commons.io.IOUtils;
|
||||
import org.apache.hadoop.conf.Configuration;
|
||||
import org.apache.hadoop.fs.FSDataInputStream;
|
||||
import org.apache.hadoop.fs.FSDataOutputStream;
|
||||
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;
|
||||
|
||||
public class GetOpenCitationsRefs implements Serializable {
|
||||
private static final Logger log = LoggerFactory.getLogger(GetOpenCitationsRefs.class);
|
||||
|
||||
public static void main(final String[] args) throws IOException, ParseException {
|
||||
|
||||
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
|
||||
IOUtils
|
||||
.toString(
|
||||
Objects
|
||||
.requireNonNull(
|
||||
GetOpenCitationsRefs.class
|
||||
.getResourceAsStream(
|
||||
"/eu/dnetlib/dhp/actionmanager/opencitations/input_parameters.json"))));
|
||||
|
||||
parser.parseArgument(args);
|
||||
|
||||
final String[] inputFile = parser.get("inputFile").split(";");
|
||||
log.info("inputFile {}", inputFile.toString());
|
||||
|
||||
final String workingPath = parser.get("workingPath");
|
||||
log.info("workingPath {}", workingPath);
|
||||
|
||||
final String hdfsNameNode = parser.get("hdfsNameNode");
|
||||
log.info("hdfsNameNode {}", hdfsNameNode);
|
||||
|
||||
Configuration conf = new Configuration();
|
||||
conf.set("fs.defaultFS", hdfsNameNode);
|
||||
|
||||
FileSystem fileSystem = FileSystem.get(conf);
|
||||
|
||||
GetOpenCitationsRefs ocr = new GetOpenCitationsRefs();
|
||||
|
||||
for (String file : inputFile) {
|
||||
ocr.doExtract(workingPath + "/Original/" + file, workingPath, fileSystem);
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
private void doExtract(String inputFile, String workingPath, FileSystem fileSystem)
|
||||
throws IOException {
|
||||
|
||||
final Path path = new Path(inputFile);
|
||||
|
||||
FSDataInputStream oc_zip = fileSystem.open(path);
|
||||
|
||||
int count = 1;
|
||||
try (ZipInputStream zis = new ZipInputStream(oc_zip)) {
|
||||
ZipEntry entry = null;
|
||||
while ((entry = zis.getNextEntry()) != null) {
|
||||
|
||||
if (!entry.isDirectory()) {
|
||||
String fileName = entry.getName();
|
||||
fileName = fileName.substring(0, fileName.indexOf("T")) + "_" + count;
|
||||
count++;
|
||||
try (
|
||||
FSDataOutputStream out = fileSystem
|
||||
.create(new Path(workingPath + "/COCI/" + fileName + ".gz"));
|
||||
GZIPOutputStream gzipOs = new GZIPOutputStream(new BufferedOutputStream(out))) {
|
||||
|
||||
IOUtils.copy(zis, gzipOs);
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -5,94 +5,249 @@ import java.io.Serializable;
|
|||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* This class represent an instance of Pubmed Article extracted from the native XML
|
||||
*
|
||||
* @author Sandro La Bruzzo
|
||||
*/
|
||||
|
||||
public class PMArticle implements Serializable {
|
||||
|
||||
/**
|
||||
* the Pubmed Identifier
|
||||
*/
|
||||
private String pmid;
|
||||
/**
|
||||
* the DOI
|
||||
*/
|
||||
private String doi;
|
||||
/**
|
||||
* the Pubmed Date extracted from <PubmedPubDate> Specifies a date significant to either the article's history or the citation's processing.
|
||||
* All <History> dates will have a <Year>, <Month>, and <Day> elements. Some may have an <Hour>, <Minute>, and <Second> element(s).
|
||||
*/
|
||||
private String date;
|
||||
/**
|
||||
* This is an 'envelop' element that contains various elements describing the journal cited; i.e., ISSN, Volume, Issue, and PubDate and author name(s), however, it does not contain data itself.
|
||||
*/
|
||||
private PMJournal journal;
|
||||
/**
|
||||
* The full journal title (taken from NLM cataloging data following NLM rules for how to compile a serial name) is exported in this element. Some characters that are not part of the NLM MEDLINE/PubMed Character Set reside in a relatively small number of full journal titles. The NLM journal title abbreviation is exported in the <MedlineTA> element.
|
||||
*/
|
||||
private String title;
|
||||
/**
|
||||
* English-language abstracts are taken directly from the published article.
|
||||
* If the article does not have a published abstract, the National Library of Medicine does not create one,
|
||||
* thus the record lacks the <Abstract> and <AbstractText> elements. However, in the absence of a formally
|
||||
* labeled abstract in the published article, text from a substantive "summary", "summary and conclusions" or "conclusions and summary" may be used.
|
||||
*/
|
||||
private String description;
|
||||
/**
|
||||
* the language in which an article was published is recorded in <Language>.
|
||||
* All entries are three letter abbreviations stored in lower case, such as eng, fre, ger, jpn, etc. When a single
|
||||
* record contains more than one language value the XML export program extracts the languages in alphabetic order by the 3-letter language value.
|
||||
* Some records provided by collaborating data producers may contain the value und to identify articles whose language is undetermined.
|
||||
*/
|
||||
private String language;
|
||||
|
||||
/**
|
||||
* NLM controlled vocabulary, Medical Subject Headings (MeSH®), is used to characterize the content of the articles represented by MEDLINE citations. *
|
||||
*/
|
||||
private final List<PMSubject> subjects = new ArrayList<>();
|
||||
/**
|
||||
* This element is used to identify the type of article indexed for MEDLINE;
|
||||
* it characterizes the nature of the information or the manner in which it is conveyed as well as the type of
|
||||
* research support received (e.g., Review, Letter, Retracted Publication, Clinical Conference, Research Support, N.I.H., Extramural).
|
||||
*/
|
||||
private final List<PMSubject> publicationTypes = new ArrayList<>();
|
||||
/**
|
||||
* Personal and collective (corporate) author names published with the article are found in <AuthorList>.
|
||||
*/
|
||||
private List<PMAuthor> authors = new ArrayList<>();
|
||||
|
||||
public List<PMSubject> getPublicationTypes() {
|
||||
return publicationTypes;
|
||||
}
|
||||
|
||||
/**
|
||||
* <GrantID> contains the research grant or contract number (or both) that designates financial support by any agency of the United States Public Health Service
|
||||
* or any institute of the National Institutes of Health. Additionally, beginning in late 2005, grant numbers are included for many other US and non-US funding agencies and organizations.
|
||||
*/
|
||||
private final List<PMGrant> grants = new ArrayList<>();
|
||||
|
||||
public List<PMGrant> getGrants() {
|
||||
return grants;
|
||||
}
|
||||
|
||||
/**
|
||||
* get the DOI
|
||||
* @return a DOI
|
||||
*/
|
||||
public String getDoi() {
|
||||
return doi;
|
||||
}
|
||||
|
||||
/**
|
||||
* Set the DOI
|
||||
* @param doi a DOI
|
||||
*/
|
||||
public void setDoi(String doi) {
|
||||
this.doi = doi;
|
||||
}
|
||||
|
||||
/**
|
||||
* get the Pubmed Identifier
|
||||
* @return the PMID
|
||||
*/
|
||||
public String getPmid() {
|
||||
return pmid;
|
||||
}
|
||||
|
||||
/**
|
||||
* set the Pubmed Identifier
|
||||
* @param pmid the Pubmed Identifier
|
||||
*/
|
||||
public void setPmid(String pmid) {
|
||||
this.pmid = pmid;
|
||||
}
|
||||
|
||||
/**
|
||||
* the Pubmed Date extracted from <PubmedPubDate> Specifies a date significant to either the article's history or the citation's processing.
|
||||
* All <History> dates will have a <Year>, <Month>, and <Day> elements. Some may have an <Hour>, <Minute>, and <Second> element(s).
|
||||
*
|
||||
* @return the Pubmed Date
|
||||
*/
|
||||
public String getDate() {
|
||||
return date;
|
||||
}
|
||||
|
||||
/**
|
||||
* Set the pubmed Date
|
||||
* @param date
|
||||
*/
|
||||
public void setDate(String date) {
|
||||
this.date = date;
|
||||
}
|
||||
|
||||
/**
|
||||
* The full journal title (taken from NLM cataloging data following NLM rules for how to compile a serial name) is exported in this element.
|
||||
* Some characters that are not part of the NLM MEDLINE/PubMed Character Set reside in a relatively small number of full journal titles.
|
||||
* The NLM journal title abbreviation is exported in the <MedlineTA> element.
|
||||
*
|
||||
* @return the pubmed Journal Extracted
|
||||
*/
|
||||
public PMJournal getJournal() {
|
||||
return journal;
|
||||
}
|
||||
|
||||
/**
|
||||
* Set the mapped pubmed Journal
|
||||
* @param journal
|
||||
*/
|
||||
public void setJournal(PMJournal journal) {
|
||||
this.journal = journal;
|
||||
}
|
||||
|
||||
/**
|
||||
* English-language abstracts are taken directly from the published article.
|
||||
* If the article does not have a published abstract, the National Library of Medicine does not create one,
|
||||
* thus the record lacks the <Abstract> and <AbstractText> elements. However, in the absence of a formally
|
||||
* labeled abstract in the published article, text from a substantive "summary", "summary and conclusions" or "conclusions and summary" may be used.
|
||||
*
|
||||
* @return the extracted pubmed Title
|
||||
*/
|
||||
public String getTitle() {
|
||||
return title;
|
||||
}
|
||||
|
||||
/**
|
||||
* set the pubmed title
|
||||
* @param title
|
||||
*/
|
||||
public void setTitle(String title) {
|
||||
this.title = title;
|
||||
}
|
||||
|
||||
/**
|
||||
* English-language abstracts are taken directly from the published article.
|
||||
* If the article does not have a published abstract, the National Library of Medicine does not create one,
|
||||
* thus the record lacks the <Abstract> and <AbstractText> elements. However, in the absence of a formally
|
||||
* labeled abstract in the published article, text from a substantive "summary", "summary and conclusions" or "conclusions and summary" may be used.
|
||||
*
|
||||
* @return the Mapped Pubmed Article Abstracts
|
||||
*/
|
||||
public String getDescription() {
|
||||
return description;
|
||||
}
|
||||
|
||||
/**
|
||||
* Set the Mapped Pubmed Article Abstracts
|
||||
* @param description
|
||||
*/
|
||||
public void setDescription(String description) {
|
||||
this.description = description;
|
||||
}
|
||||
|
||||
/**
|
||||
* Personal and collective (corporate) author names published with the article are found in <AuthorList>.
|
||||
*
|
||||
* @return get the Mapped Authors lists
|
||||
*/
|
||||
public List<PMAuthor> getAuthors() {
|
||||
return authors;
|
||||
}
|
||||
|
||||
/**
|
||||
* Set the Mapped Authors lists
|
||||
* @param authors
|
||||
*/
|
||||
public void setAuthors(List<PMAuthor> authors) {
|
||||
this.authors = authors;
|
||||
}
|
||||
|
||||
/**
|
||||
* This element is used to identify the type of article indexed for MEDLINE;
|
||||
* it characterizes the nature of the information or the manner in which it is conveyed as well as the type of
|
||||
* research support received (e.g., Review, Letter, Retracted Publication, Clinical Conference, Research Support, N.I.H., Extramural).
|
||||
*
|
||||
* @return the mapped Subjects
|
||||
*/
|
||||
public List<PMSubject> getSubjects() {
|
||||
return subjects;
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
* the language in which an article was published is recorded in <Language>.
|
||||
* All entries are three letter abbreviations stored in lower case, such as eng, fre, ger, jpn, etc. When a single
|
||||
* record contains more than one language value the XML export program extracts the languages in alphabetic order by the 3-letter language value.
|
||||
* Some records provided by collaborating data producers may contain the value und to identify articles whose language is undetermined.
|
||||
*
|
||||
* @return The mapped Language
|
||||
*/
|
||||
public String getLanguage() {
|
||||
return language;
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
* Set The mapped Language
|
||||
*
|
||||
* @param language the mapped Language
|
||||
*/
|
||||
public void setLanguage(String language) {
|
||||
this.language = language;
|
||||
}
|
||||
|
||||
/**
|
||||
* This element is used to identify the type of article indexed for MEDLINE;
|
||||
* it characterizes the nature of the information or the manner in which it is conveyed as well as the type of
|
||||
* research support received (e.g., Review, Letter, Retracted Publication, Clinical Conference, Research Support, N.I.H., Extramural).
|
||||
*
|
||||
* @return the mapped Publication Type
|
||||
*/
|
||||
public List<PMSubject> getPublicationTypes() {
|
||||
return publicationTypes;
|
||||
}
|
||||
|
||||
/**
|
||||
* <GrantID> contains the research grant or contract number (or both) that designates financial support by any agency of the United States Public Health Service
|
||||
* or any institute of the National Institutes of Health. Additionally, beginning in late 2005, grant numbers are included for many other US and non-US funding agencies and organizations.
|
||||
* @return the mapped grants
|
||||
*/
|
||||
|
||||
public List<PMGrant> getGrants() {
|
||||
return grants;
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -3,27 +3,57 @@ package eu.dnetlib.dhp.sx.bio.pubmed;
|
|||
|
||||
import java.io.Serializable;
|
||||
|
||||
/**
|
||||
* The type Pubmed author.
|
||||
*
|
||||
* @author Sandro La Bruzzo
|
||||
*/
|
||||
public class PMAuthor implements Serializable {
|
||||
|
||||
private String lastName;
|
||||
private String foreName;
|
||||
|
||||
/**
|
||||
* Gets last name.
|
||||
*
|
||||
* @return the last name
|
||||
*/
|
||||
public String getLastName() {
|
||||
return lastName;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets last name.
|
||||
*
|
||||
* @param lastName the last name
|
||||
*/
|
||||
public void setLastName(String lastName) {
|
||||
this.lastName = lastName;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets fore name.
|
||||
*
|
||||
* @return the fore name
|
||||
*/
|
||||
public String getForeName() {
|
||||
return foreName;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets fore name.
|
||||
*
|
||||
* @param foreName the fore name
|
||||
*/
|
||||
public void setForeName(String foreName) {
|
||||
this.foreName = foreName;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets full name.
|
||||
*
|
||||
* @return the full name
|
||||
*/
|
||||
public String getFullName() {
|
||||
return String
|
||||
.format("%s, %s", this.foreName != null ? this.foreName : "", this.lastName != null ? this.lastName : "");
|
||||
|
|
|
|||
|
|
@ -1,41 +1,86 @@
|
|||
|
||||
package eu.dnetlib.dhp.sx.bio.pubmed;
|
||||
|
||||
/**
|
||||
* The type Pm grant.
|
||||
*
|
||||
* @author Sandro La Bruzzo
|
||||
*/
|
||||
public class PMGrant {
|
||||
|
||||
private String grantID;
|
||||
private String agency;
|
||||
private String country;
|
||||
|
||||
/**
|
||||
* Instantiates a new Pm grant.
|
||||
*/
|
||||
public PMGrant() {
|
||||
}
|
||||
|
||||
/**
|
||||
* Instantiates a new Pm grant.
|
||||
*
|
||||
* @param grantID the grant id
|
||||
* @param agency the agency
|
||||
* @param country the country
|
||||
*/
|
||||
public PMGrant(String grantID, String agency, String country) {
|
||||
this.grantID = grantID;
|
||||
this.agency = agency;
|
||||
this.country = country;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets grant id.
|
||||
*
|
||||
* @return the grant id
|
||||
*/
|
||||
public String getGrantID() {
|
||||
return grantID;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets grant id.
|
||||
*
|
||||
* @param grantID the grant id
|
||||
*/
|
||||
public void setGrantID(String grantID) {
|
||||
this.grantID = grantID;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets agency.
|
||||
*
|
||||
* @return the agency
|
||||
*/
|
||||
public String getAgency() {
|
||||
return agency;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets agency.
|
||||
*
|
||||
* @param agency the agency
|
||||
*/
|
||||
public void setAgency(String agency) {
|
||||
this.agency = agency;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets country.
|
||||
*
|
||||
* @return the country
|
||||
*/
|
||||
public String getCountry() {
|
||||
return country;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets country.
|
||||
*
|
||||
* @param country the country
|
||||
*/
|
||||
public void setCountry(String country) {
|
||||
this.country = country;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -3,6 +3,11 @@ package eu.dnetlib.dhp.sx.bio.pubmed;
|
|||
|
||||
import java.io.Serializable;
|
||||
|
||||
/**
|
||||
* The type Pm journal.
|
||||
*
|
||||
* @author Sandro La Bruzzo
|
||||
*/
|
||||
public class PMJournal implements Serializable {
|
||||
|
||||
private String issn;
|
||||
|
|
@ -11,42 +16,92 @@ public class PMJournal implements Serializable {
|
|||
private String date;
|
||||
private String title;
|
||||
|
||||
/**
|
||||
* Gets issn.
|
||||
*
|
||||
* @return the issn
|
||||
*/
|
||||
public String getIssn() {
|
||||
return issn;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets issn.
|
||||
*
|
||||
* @param issn the issn
|
||||
*/
|
||||
public void setIssn(String issn) {
|
||||
this.issn = issn;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets volume.
|
||||
*
|
||||
* @return the volume
|
||||
*/
|
||||
public String getVolume() {
|
||||
return volume;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets volume.
|
||||
*
|
||||
* @param volume the volume
|
||||
*/
|
||||
public void setVolume(String volume) {
|
||||
this.volume = volume;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets issue.
|
||||
*
|
||||
* @return the issue
|
||||
*/
|
||||
public String getIssue() {
|
||||
return issue;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets issue.
|
||||
*
|
||||
* @param issue the issue
|
||||
*/
|
||||
public void setIssue(String issue) {
|
||||
this.issue = issue;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets date.
|
||||
*
|
||||
* @return the date
|
||||
*/
|
||||
public String getDate() {
|
||||
return date;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets date.
|
||||
*
|
||||
* @param date the date
|
||||
*/
|
||||
public void setDate(String date) {
|
||||
this.date = date;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets title.
|
||||
*
|
||||
* @return the title
|
||||
*/
|
||||
public String getTitle() {
|
||||
return title;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets title.
|
||||
*
|
||||
* @param title the title
|
||||
*/
|
||||
public void setTitle(String title) {
|
||||
this.title = title;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -2,6 +2,12 @@ package eu.dnetlib.dhp.sx.bio.pubmed
|
|||
|
||||
import scala.xml.MetaData
|
||||
import scala.xml.pull.{EvElemEnd, EvElemStart, EvText, XMLEventReader}
|
||||
|
||||
|
||||
/**
|
||||
*
|
||||
* @param xml
|
||||
*/
|
||||
class PMParser(xml:XMLEventReader) extends Iterator[PMArticle] {
|
||||
|
||||
var currentArticle:PMArticle = generateNextArticle()
|
||||
|
|
|
|||
|
|
@ -1,40 +1,83 @@
|
|||
|
||||
package eu.dnetlib.dhp.sx.bio.pubmed;
|
||||
|
||||
/**
|
||||
* The type Pubmed subject.
|
||||
*/
|
||||
public class PMSubject {
|
||||
private String value;
|
||||
private String meshId;
|
||||
private String registryNumber;
|
||||
|
||||
/**
|
||||
* Instantiates a new Pm subject.
|
||||
*/
|
||||
public PMSubject() {
|
||||
}
|
||||
|
||||
/**
|
||||
* Instantiates a new Pm subject.
|
||||
*
|
||||
* @param value the value
|
||||
* @param meshId the mesh id
|
||||
* @param registryNumber the registry number
|
||||
*/
|
||||
public PMSubject(String value, String meshId, String registryNumber) {
|
||||
this.value = value;
|
||||
this.meshId = meshId;
|
||||
this.registryNumber = registryNumber;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets value.
|
||||
*
|
||||
* @return the value
|
||||
*/
|
||||
public String getValue() {
|
||||
return value;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets value.
|
||||
*
|
||||
* @param value the value
|
||||
*/
|
||||
public void setValue(String value) {
|
||||
this.value = value;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets mesh id.
|
||||
*
|
||||
* @return the mesh id
|
||||
*/
|
||||
public String getMeshId() {
|
||||
return meshId;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets mesh id.
|
||||
*
|
||||
* @param meshId the mesh id
|
||||
*/
|
||||
public void setMeshId(String meshId) {
|
||||
this.meshId = meshId;
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets registry number.
|
||||
*
|
||||
* @return the registry number
|
||||
*/
|
||||
public String getRegistryNumber() {
|
||||
return registryNumber;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets registry number.
|
||||
*
|
||||
* @param registryNumber the registry number
|
||||
*/
|
||||
public void setRegistryNumber(String registryNumber) {
|
||||
this.registryNumber = registryNumber;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -8,6 +8,9 @@ import scala.collection.JavaConverters._
|
|||
|
||||
import java.util.regex.Pattern
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
object PubMedToOaf {
|
||||
|
||||
val SUBJ_CLASS = "keywords"
|
||||
|
|
@ -15,7 +18,17 @@ object PubMedToOaf {
|
|||
"pmid" -> "https://pubmed.ncbi.nlm.nih.gov/",
|
||||
"doi" -> "https://dx.doi.org/"
|
||||
)
|
||||
val dataInfo: DataInfo = OafMapperUtils.dataInfo(false, null, false, false, ModelConstants.PROVENANCE_ACTION_SET_QUALIFIER, "0.9")
|
||||
val collectedFrom: KeyValue = OafMapperUtils.keyValue(ModelConstants.EUROPE_PUBMED_CENTRAL_ID, "Europe PubMed Central")
|
||||
|
||||
|
||||
|
||||
/**
|
||||
* Cleaning the DOI Applying regex in order to
|
||||
* remove doi starting with URL
|
||||
* @param doi input DOI
|
||||
* @return cleaned DOI
|
||||
*/
|
||||
def cleanDoi(doi: String): String = {
|
||||
|
||||
val regex = "^10.\\d{4,9}\\/[\\[\\]\\-\\<\\>._;()\\/:A-Z0-9]+$"
|
||||
|
|
@ -30,6 +43,15 @@ object PubMedToOaf {
|
|||
null
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
* Create an instance of class extends Result
|
||||
* starting from OAF instanceType value
|
||||
*
|
||||
* @param cobjQualifier OAF instance type
|
||||
* @param vocabularies All dnet vocabularies
|
||||
* @return the correct instance
|
||||
*/
|
||||
def createResult(cobjQualifier: Qualifier, vocabularies: VocabularyGroup): Result = {
|
||||
val result_typologies = getVocabularyTerm(ModelConstants.DNET_RESULT_TYPOLOGIES, vocabularies, cobjQualifier.getClassid)
|
||||
result_typologies.getClassid match {
|
||||
|
|
@ -42,6 +64,12 @@ object PubMedToOaf {
|
|||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Mapping the Pubmedjournal info into the OAF Journale
|
||||
*
|
||||
* @param j the pubmedJournal
|
||||
* @return the OAF Journal
|
||||
*/
|
||||
def mapJournal(j: PMJournal): Journal = {
|
||||
if (j == null)
|
||||
return null
|
||||
|
|
@ -49,6 +77,7 @@ object PubMedToOaf {
|
|||
|
||||
journal.setDataInfo(dataInfo)
|
||||
journal.setName(j.getTitle)
|
||||
journal.setConferencedate(j.getDate)
|
||||
journal.setVol(j.getVolume)
|
||||
journal.setIssnPrinted(j.getIssn)
|
||||
journal.setIss(j.getIssue)
|
||||
|
|
@ -57,25 +86,43 @@ object PubMedToOaf {
|
|||
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
*
|
||||
* Find vocabulary term into synonyms and term in the vocabulary
|
||||
*
|
||||
* @param vocabularyName the input vocabulary name
|
||||
* @param vocabularies all the vocabularies
|
||||
* @param term the term to find
|
||||
*
|
||||
* @return the cleaned term value
|
||||
*/
|
||||
def getVocabularyTerm(vocabularyName: String, vocabularies: VocabularyGroup, term: String): Qualifier = {
|
||||
val a = vocabularies.getSynonymAsQualifier(vocabularyName, term)
|
||||
val b = vocabularies.getTermAsQualifier(vocabularyName, term)
|
||||
if (a == null) b else a
|
||||
}
|
||||
|
||||
val dataInfo: DataInfo = OafMapperUtils.dataInfo(false, null, false, false, ModelConstants.PROVENANCE_ACTION_SET_QUALIFIER, "0.9")
|
||||
val collectedFrom: KeyValue = OafMapperUtils.keyValue(ModelConstants.EUROPE_PUBMED_CENTRAL_ID, "Europe PubMed Central")
|
||||
|
||||
/**
|
||||
* Map the Pubmed Article into the OAF instance
|
||||
*
|
||||
*
|
||||
* @param article the pubmed articles
|
||||
* @param vocabularies the vocabularies
|
||||
* @return The OAF instance if the mapping did not fail
|
||||
*/
|
||||
def convert(article: PMArticle, vocabularies: VocabularyGroup): Result = {
|
||||
|
||||
if (article.getPublicationTypes == null)
|
||||
return null
|
||||
val i = new Instance
|
||||
|
||||
|
||||
// MAP PMID into pid with classid = classname = pmid
|
||||
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)
|
||||
return null
|
||||
|
||||
// MAP //ArticleId[./@IdType="doi"] into alternateIdentifier with classid = classname = doi
|
||||
var alternateIdentifier: StructuredProperty = null
|
||||
if (article.getDoi != null) {
|
||||
val normalizedPid = cleanDoi(article.getDoi)
|
||||
|
|
@ -83,43 +130,64 @@ object PubMedToOaf {
|
|||
alternateIdentifier = OafMapperUtils.structuredProperty(normalizedPid, PidType.doi.toString, PidType.doi.toString, ModelConstants.DNET_PID_TYPES, ModelConstants.DNET_PID_TYPES, dataInfo)
|
||||
}
|
||||
|
||||
// INSTANCE MAPPING
|
||||
//--------------------------------------------------------------------------------------
|
||||
|
||||
// If the article contains the typology Journal Article then we apply this type
|
||||
//else We have to find a terms that match the vocabulary otherwise we discard it
|
||||
val ja = article.getPublicationTypes.asScala.find(s => "Journal Article".equalsIgnoreCase(s.getValue))
|
||||
val pubmedInstance = new Instance
|
||||
if (ja.isDefined) {
|
||||
val cojbCategory = getVocabularyTerm(ModelConstants.DNET_PUBLICATION_RESOURCE, vocabularies, ja.get.getValue)
|
||||
i.setInstancetype(cojbCategory)
|
||||
pubmedInstance.setInstancetype(cojbCategory)
|
||||
} else {
|
||||
val i_type = article.getPublicationTypes.asScala
|
||||
.map(s => getVocabularyTerm(ModelConstants.DNET_PUBLICATION_RESOURCE, vocabularies, s.getValue))
|
||||
.find(q => q != null)
|
||||
if (i_type.isDefined)
|
||||
i.setInstancetype(i_type.get)
|
||||
pubmedInstance.setInstancetype(i_type.get)
|
||||
else
|
||||
return null
|
||||
}
|
||||
val result = createResult(i.getInstancetype, vocabularies)
|
||||
val result = createResult(pubmedInstance.getInstancetype, vocabularies)
|
||||
if (result == null)
|
||||
return result
|
||||
result.setDataInfo(dataInfo)
|
||||
i.setPid(pidList.asJava)
|
||||
pubmedInstance.setPid(pidList.asJava)
|
||||
if (alternateIdentifier != null)
|
||||
i.setAlternateIdentifier(List(alternateIdentifier).asJava)
|
||||
result.setInstance(List(i).asJava)
|
||||
i.getPid.asScala.filter(p => "pmid".equalsIgnoreCase(p.getQualifier.getClassid)).map(p => p.getValue)(collection.breakOut)
|
||||
pubmedInstance.setAlternateIdentifier(List(alternateIdentifier).asJava)
|
||||
result.setInstance(List(pubmedInstance).asJava)
|
||||
pubmedInstance.getPid.asScala.filter(p => "pmid".equalsIgnoreCase(p.getQualifier.getClassid)).map(p => p.getValue)(collection.breakOut)
|
||||
//CREATE URL From pmid
|
||||
val urlLists: List[String] = pidList
|
||||
.map(s => (urlMap.getOrElse(s.getQualifier.getClassid, ""), s.getValue))
|
||||
.filter(t => t._1.nonEmpty)
|
||||
.map(t => t._1 + t._2)
|
||||
if (urlLists != null)
|
||||
i.setUrl(urlLists.asJava)
|
||||
i.setDateofacceptance(OafMapperUtils.field(GraphCleaningFunctions.cleanDate(article.getDate), dataInfo))
|
||||
i.setCollectedfrom(collectedFrom)
|
||||
pubmedInstance.setUrl(urlLists.asJava)
|
||||
|
||||
//ASSIGN DateofAcceptance
|
||||
pubmedInstance.setDateofacceptance(OafMapperUtils.field(GraphCleaningFunctions.cleanDate(article.getDate), dataInfo))
|
||||
//ASSIGN COLLECTEDFROM
|
||||
pubmedInstance.setCollectedfrom(collectedFrom)
|
||||
result.setPid(pidList.asJava)
|
||||
|
||||
//END INSTANCE MAPPING
|
||||
//--------------------------------------------------------------------------------------
|
||||
|
||||
|
||||
// JOURNAL MAPPING
|
||||
//--------------------------------------------------------------------------------------
|
||||
if (article.getJournal != null && result.isInstanceOf[Publication])
|
||||
result.asInstanceOf[Publication].setJournal(mapJournal(article.getJournal))
|
||||
result.setCollectedfrom(List(collectedFrom).asJava)
|
||||
//END JOURNAL MAPPING
|
||||
//--------------------------------------------------------------------------------------
|
||||
|
||||
|
||||
|
||||
// RESULT MAPPING
|
||||
//--------------------------------------------------------------------------------------
|
||||
result.setDateofacceptance(OafMapperUtils.field(GraphCleaningFunctions.cleanDate(article.getDate), dataInfo))
|
||||
|
||||
if (article.getTitle == null || article.getTitle.isEmpty)
|
||||
|
|
@ -159,6 +227,9 @@ object PubMedToOaf {
|
|||
|
||||
result.setId(article.getPmid)
|
||||
|
||||
|
||||
// END RESULT MAPPING
|
||||
//--------------------------------------------------------------------------------------
|
||||
val id = IdentifierFactory.createIdentifier(result)
|
||||
if (article.getPmid.equalsIgnoreCase(id))
|
||||
return null
|
||||
|
|
|
|||
|
|
@ -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
|
||||
}
|
||||
]
|
||||
|
|
@ -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>
|
||||
|
|
@ -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>
|
||||
|
|
@ -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
|
||||
}
|
||||
]
|
||||
|
|
@ -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
|
||||
}
|
||||
]
|
||||
|
|
@ -0,0 +1,25 @@
|
|||
[
|
||||
{
|
||||
"paramName": "ip",
|
||||
"paramLongName": "inputPath",
|
||||
"paramDescription": "the zipped opencitations file",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "op",
|
||||
"paramLongName": "outputPath",
|
||||
"paramDescription": "the working path",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "issm",
|
||||
"paramLongName": "isSparkSessionManaged",
|
||||
"paramDescription": "the hdfs name node",
|
||||
"paramRequired": false
|
||||
}, {
|
||||
"paramName": "sdr",
|
||||
"paramLongName": "shouldDuplicateRels",
|
||||
"paramDescription": "the hdfs name node",
|
||||
"paramRequired": false
|
||||
}
|
||||
]
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
[
|
||||
{
|
||||
"paramName": "if",
|
||||
"paramLongName": "inputFile",
|
||||
"paramDescription": "the zipped opencitations file",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "wp",
|
||||
"paramLongName": "workingPath",
|
||||
"paramDescription": "the working path",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "hnn",
|
||||
"paramLongName": "hdfsNameNode",
|
||||
"paramDescription": "the hdfs name node",
|
||||
"paramRequired": true
|
||||
}
|
||||
]
|
||||
|
|
@ -0,0 +1,58 @@
|
|||
<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>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>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>
|
||||
<property>
|
||||
<name>sparkExecutorNumber</name>
|
||||
<value>4</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>spark2EventLogDir</name>
|
||||
<value>/user/spark/spark2ApplicationHistory</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>sparkDriverMemory</name>
|
||||
<value>15G</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>sparkExecutorMemory</name>
|
||||
<value>6G</value>
|
||||
</property>
|
||||
<property>
|
||||
<name>sparkExecutorCores</name>
|
||||
<value>1</value>
|
||||
</property>
|
||||
</configuration>
|
||||
|
|
@ -0,0 +1,2 @@
|
|||
#!/bin/bash
|
||||
for file in $(echo $1 | tr ";" "\n"); do curl -L $(echo $file | cut -d '@' -f 1 ) | hdfs dfs -put - $2/$(echo $file | cut -d '@' -f 2) ; done;
|
||||
|
|
@ -0,0 +1,91 @@
|
|||
<workflow-app name="OpenCitations Integration" xmlns="uri:oozie:workflow:0.5">
|
||||
|
||||
<global>
|
||||
<job-tracker>${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="resume_from"/>
|
||||
|
||||
<decision name="resume_from">
|
||||
<switch>
|
||||
<case to="download">${wf:conf('resumeFrom') eq 'DownloadDump'}</case>
|
||||
<case to="extract">${wf:conf('resumeFrom') eq 'ExtractContent'}</case>
|
||||
<default to="create_actionset"/> <!-- first action to be done when downloadDump is to be performed -->
|
||||
</switch>
|
||||
</decision>
|
||||
|
||||
<kill name="Kill">
|
||||
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
|
||||
</kill>
|
||||
<action name="download">
|
||||
<shell xmlns="uri:oozie:shell-action:0.2">
|
||||
<job-tracker>${jobTracker}</job-tracker>
|
||||
<name-node>${nameNode}</name-node>
|
||||
<configuration>
|
||||
<property>
|
||||
<name>mapred.job.queue.name</name>
|
||||
<value>${queueName}</value>
|
||||
</property>
|
||||
</configuration>
|
||||
<exec>download.sh</exec>
|
||||
<argument>${filelist}</argument>
|
||||
<argument>${workingPath}/Original</argument>
|
||||
<env-var>HADOOP_USER_NAME=${wf:user()}</env-var>
|
||||
<file>download.sh</file>
|
||||
<capture-output/>
|
||||
</shell>
|
||||
<ok to="extract"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
<action name="extract">
|
||||
<java>
|
||||
<main-class>eu.dnetlib.dhp.actionmanager.opencitations.GetOpenCitationsRefs</main-class>
|
||||
<arg>--hdfsNameNode</arg><arg>${nameNode}</arg>
|
||||
<arg>--inputFile</arg><arg>${inputFile}</arg>
|
||||
<arg>--workingPath</arg><arg>${workingPath}</arg>
|
||||
</java>
|
||||
<ok to="create_actionset"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
<action name="create_actionset">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
<name>Produces the AS for OC</name>
|
||||
<class>eu.dnetlib.dhp.actionmanager.opencitations.CreateActionSetSparkJob</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>--inputPath</arg><arg>${workingPath}/COCI</arg>
|
||||
<arg>--outputPath</arg><arg>${outputPath}</arg>
|
||||
</spark>
|
||||
<ok to="End"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
<end name="End"/>
|
||||
</workflow-app>
|
||||
|
|
@ -0,0 +1,8 @@
|
|||
[
|
||||
{"paramName":"n", "paramLongName":"hdfsServerUri", "paramDescription": "the server uri", "paramRequired": true},
|
||||
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the default work path", "paramRequired": true},
|
||||
{"paramName":"f", "paramLongName":"opencitationFile", "paramDescription": "the name of the file", "paramRequired": true},
|
||||
{"paramName":"issm", "paramLongName":"isSparkSessionManaged", "paramDescription": "the name of the activities orcid file", "paramRequired": false},
|
||||
{"paramName":"o", "paramLongName":"outputPath", "paramDescription": "the name of the activities orcid file", "paramRequired": true}
|
||||
|
||||
]
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
##DHP-Aggregation
|
||||
|
||||
This module defines a set of oozie workflows for the **collection** and **transformation** of metadata records.
|
||||
|
||||
Both workflows interact with the Metadata Store Manager (MdSM) to handle the logical transactions required to ensure
|
||||
the consistency of the read/write operations on the data as the MdSM in fact keeps track of the logical-physical mapping
|
||||
of each MDStore.
|
||||
|
||||
It defines [mappings](mappings.md) for transformation of different datasource (See mapping section).
|
||||
|
|
@ -0,0 +1,7 @@
|
|||
##DHP-Aggregation
|
||||
|
||||
This module defines a set of oozie workflows for the **collection** and **transformation** of metadata records.
|
||||
|
||||
Both workflows interact with the Metadata Store Manager (MdSM) to handle the logical transactions required to ensure
|
||||
the consistency of the read/write operations on the data as the MdSM in fact keeps track of the logical-physical mapping
|
||||
of each MDStore.
|
||||
|
|
@ -0,0 +1,18 @@
|
|||
DHP Aggregation
|
||||
===============
|
||||
|
||||
DHP-Aggregations contains different mappings from original data format into OAF Data Format,
|
||||
which converge in the graph in different ways:
|
||||
|
||||
- Via Action Manager
|
||||
- Direct in the MdStore on Hadoop
|
||||
|
||||
Below the list of the implemented mapping
|
||||
|
||||
|
||||
Mappings
|
||||
=======
|
||||
|
||||
1. [PubMed](pubmed.md)
|
||||
2. [Datacite](datacite.md)
|
||||
|
||||
|
|
@ -0,0 +1,62 @@
|
|||
#Pubmed Mapping
|
||||
This section describes the mapping implemented for [MEDLINE/PubMed](https://pubmed.ncbi.nlm.nih.gov/).
|
||||
|
||||
Collection
|
||||
---------
|
||||
The native data is collected from [ftp baseline](https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/) containing XML with
|
||||
the following [shcema](https://www.nlm.nih.gov/bsd/licensee/elements_descriptions.html)
|
||||
|
||||
|
||||
Parsing
|
||||
-------
|
||||
The resposible class of parsing is [PMParser](./scaladocs/#eu.dnetlib.dhp.sx.bio.pubmed.PMParser) that generates
|
||||
an intermediate mapping of PubMed Article defined [here](/apidocs/eu/dnetlib/dhp/sx/bio/pubmed/package-summary.html)
|
||||
|
||||
|
||||
Mapping
|
||||
-------
|
||||
|
||||
The table below describes the mapping from the XML Native to the OAF mapping
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
| Xpath Source | Oaf Field | Notes |
|
||||
| ----------- | ----------- | ----------- |
|
||||
| //PMID | pid | classid = classname = pmid
|
||||
| | **Instance Mapping** | |
|
||||
|//PublicationType | InstanceType | If the article contains the typology **Journal Article** then we apply this type else We have to find a terms that match the vocabulary otherwise we discard it
|
||||
|//PMID | instance/PID | Map the pmid also in the pid in the instance |
|
||||
| //ArticleId[./@IdType="doi" | instance/alternateIdentifier |classid = classname = doi
|
||||
|//PMID | instance/URL | prepend to the PMId the base url https://pubmed.ncbi.nlm.nih.gov/
|
||||
| //PubmedPubDate | instance/Dateofacceptance | apply the function GraphCleaningFunctions.cleanDate before assign it
|
||||
| FOR ALL INSTANCE | CollectedFrom | datasourceName: *Europe PubMed Central* DatasourceId:
|
||||
| | **Journal Mapping** | |
|
||||
|//Journal/PubDate| Journal/Conferencedate | map the date of the Journal
|
||||
|//Journal/Title| Journal/Name | |
|
||||
|//Journal/Volume| Journal/Vol | |
|
||||
|//Journal/ISSN| Journal/issPrinted | |
|
||||
|//Journal/Issue| Journal/Iss | |
|
||||
| | **Publication Mapping** | |
|
||||
| //PubmedPubDate | Dateofacceptance | apply the function GraphCleaningFunctions.cleanDate before assign it
|
||||
| //Title | title | with qualifier ModelConstants.MAIN_TITLE_QUALIFIER
|
||||
| //AbstractText | Description ||
|
||||
|//Language| Language| cleaning vocabulary -> dnet:languages
|
||||
|//DescriptorName| Subject | classId, className = keyword
|
||||
| | **Author Mapping** | |
|
||||
|//Author/LastName| author.Surname| |
|
||||
|//Author/ForeName| author.Forename| |
|
||||
|//Author/FullName| author.Forename| Concatenation of forname + lastName if exist |
|
||||
|FOR ALL AUTHOR | author.rank| sequential number starting from 1|
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 21 KiB |
|
|
@ -0,0 +1,32 @@
|
|||
<?xml version="1.0" encoding="ISO-8859-1"?>
|
||||
<project xmlns="http://maven.apache.org/DECORATION/1.8.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/DECORATION/1.8.0 https://maven.apache.org/xsd/decoration-1.8.0.xsd"
|
||||
name="DHP-Aggregation">
|
||||
<skin>
|
||||
<groupId>org.apache.maven.skins</groupId>
|
||||
<artifactId>maven-fluido-skin</artifactId>
|
||||
<version>1.8</version>
|
||||
</skin>
|
||||
<poweredBy>
|
||||
<logo name="OpenAIRE Research Graph" href="https://graph.openaire.eu/"
|
||||
img="https://graph.openaire.eu/assets/common-assets/logo-large-graph.png"/>
|
||||
</poweredBy>
|
||||
<body>
|
||||
<links>
|
||||
<item name="Code" href="https://code-repo.d4science.org/" />
|
||||
</links>
|
||||
<menu name="Documentation">
|
||||
<item name="Mappings" href="mappings.html" collapse="true">
|
||||
<item name="Pubmed" href="pubmed.html"/>
|
||||
<item name="Datacite" href="datacite.html"/>
|
||||
</item>
|
||||
<item name="Release Notes" href="release-notes.html" />
|
||||
<item name="General Information" href="about.html"/>
|
||||
|
||||
<item name="JavaDoc" href="apidocs/" />
|
||||
<item name="ScalaDoc" href="scaladocs/" />
|
||||
|
||||
</menu>
|
||||
<menu ref="reports"/>
|
||||
</body>
|
||||
</project>
|
||||
|
|
@ -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"));
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -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());
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,335 @@
|
|||
|
||||
package eu.dnetlib.dhp.actionmanager.opencitations;
|
||||
|
||||
import static org.junit.jupiter.api.Assertions.assertEquals;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.nio.file.Files;
|
||||
import java.nio.file.Path;
|
||||
|
||||
import org.apache.commons.io.FileUtils;
|
||||
import org.apache.hadoop.io.Text;
|
||||
import org.apache.spark.SparkConf;
|
||||
import org.apache.spark.api.java.JavaRDD;
|
||||
import org.apache.spark.api.java.JavaSparkContext;
|
||||
import org.apache.spark.sql.Dataset;
|
||||
import org.apache.spark.sql.Encoders;
|
||||
import org.apache.spark.sql.Row;
|
||||
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.action.AtomicAction;
|
||||
import eu.dnetlib.dhp.schema.common.ModelConstants;
|
||||
import eu.dnetlib.dhp.schema.oaf.Publication;
|
||||
import eu.dnetlib.dhp.schema.oaf.Relation;
|
||||
import eu.dnetlib.dhp.schema.oaf.utils.CleaningFunctions;
|
||||
import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory;
|
||||
|
||||
public class CreateOpenCitationsASTest {
|
||||
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
private static SparkSession spark;
|
||||
|
||||
private static Path workingDir;
|
||||
private static final Logger log = LoggerFactory
|
||||
.getLogger(CreateOpenCitationsASTest.class);
|
||||
|
||||
@BeforeAll
|
||||
public static void beforeAll() throws IOException {
|
||||
workingDir = Files
|
||||
.createTempDirectory(CreateOpenCitationsASTest.class.getSimpleName());
|
||||
log.info("using work dir {}", workingDir);
|
||||
|
||||
SparkConf conf = new SparkConf();
|
||||
conf.setAppName(CreateOpenCitationsASTest.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(CreateOpenCitationsASTest.class.getSimpleName())
|
||||
.config(conf)
|
||||
.getOrCreate();
|
||||
}
|
||||
|
||||
@AfterAll
|
||||
public static void afterAll() throws IOException {
|
||||
FileUtils.deleteDirectory(workingDir.toFile());
|
||||
spark.stop();
|
||||
}
|
||||
|
||||
@Test
|
||||
void testNumberofRelations() throws Exception {
|
||||
|
||||
String inputPath = getClass()
|
||||
.getResource(
|
||||
"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
|
||||
.getPath();
|
||||
|
||||
CreateActionSetSparkJob
|
||||
.main(
|
||||
new String[] {
|
||||
"-isSparkSessionManaged",
|
||||
Boolean.FALSE.toString(),
|
||||
"-shouldDuplicateRels",
|
||||
Boolean.TRUE.toString(),
|
||||
"-inputPath",
|
||||
inputPath,
|
||||
"-outputPath",
|
||||
workingDir.toString() + "/actionSet"
|
||||
});
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
|
||||
JavaRDD<Relation> tmp = sc
|
||||
.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
|
||||
.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
|
||||
.map(aa -> ((Relation) aa.getPayload()));
|
||||
|
||||
assertEquals(60, tmp.count());
|
||||
|
||||
// tmp.foreach(r -> System.out.println(OBJECT_MAPPER.writeValueAsString(r)));
|
||||
|
||||
}
|
||||
|
||||
@Test
|
||||
void testNumberofRelations2() throws Exception {
|
||||
|
||||
String inputPath = getClass()
|
||||
.getResource(
|
||||
"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
|
||||
.getPath();
|
||||
|
||||
CreateActionSetSparkJob
|
||||
.main(
|
||||
new String[] {
|
||||
"-isSparkSessionManaged",
|
||||
Boolean.FALSE.toString(),
|
||||
"-inputPath",
|
||||
inputPath,
|
||||
"-outputPath",
|
||||
workingDir.toString() + "/actionSet"
|
||||
});
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
|
||||
JavaRDD<Relation> tmp = sc
|
||||
.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
|
||||
.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
|
||||
.map(aa -> ((Relation) aa.getPayload()));
|
||||
|
||||
assertEquals(44, tmp.count());
|
||||
|
||||
// tmp.foreach(r -> System.out.println(OBJECT_MAPPER.writeValueAsString(r)));
|
||||
|
||||
}
|
||||
|
||||
@Test
|
||||
void testRelationsCollectedFrom() throws Exception {
|
||||
|
||||
String inputPath = getClass()
|
||||
.getResource(
|
||||
"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
|
||||
.getPath();
|
||||
|
||||
CreateActionSetSparkJob
|
||||
.main(
|
||||
new String[] {
|
||||
"-isSparkSessionManaged",
|
||||
Boolean.FALSE.toString(),
|
||||
"-inputPath",
|
||||
inputPath,
|
||||
"-outputPath",
|
||||
workingDir.toString() + "/actionSet"
|
||||
});
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
|
||||
JavaRDD<Relation> tmp = sc
|
||||
.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
|
||||
.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
|
||||
.map(aa -> ((Relation) aa.getPayload()));
|
||||
|
||||
tmp.foreach(r -> {
|
||||
assertEquals(ModelConstants.OPENOCITATIONS_NAME, r.getCollectedfrom().get(0).getValue());
|
||||
assertEquals(ModelConstants.OPENOCITATIONS_ID, r.getCollectedfrom().get(0).getKey());
|
||||
});
|
||||
|
||||
}
|
||||
|
||||
@Test
|
||||
void testRelationsDataInfo() throws Exception {
|
||||
|
||||
String inputPath = getClass()
|
||||
.getResource(
|
||||
"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
|
||||
.getPath();
|
||||
|
||||
CreateActionSetSparkJob
|
||||
.main(
|
||||
new String[] {
|
||||
"-isSparkSessionManaged",
|
||||
Boolean.FALSE.toString(),
|
||||
"-inputPath",
|
||||
inputPath,
|
||||
"-outputPath",
|
||||
workingDir.toString() + "/actionSet"
|
||||
});
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
|
||||
JavaRDD<Relation> tmp = sc
|
||||
.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
|
||||
.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
|
||||
.map(aa -> ((Relation) aa.getPayload()));
|
||||
|
||||
tmp.foreach(r -> {
|
||||
assertEquals(false, r.getDataInfo().getInferred());
|
||||
assertEquals(false, r.getDataInfo().getDeletedbyinference());
|
||||
assertEquals("0.91", r.getDataInfo().getTrust());
|
||||
assertEquals(
|
||||
CreateActionSetSparkJob.OPENCITATIONS_CLASSID, r.getDataInfo().getProvenanceaction().getClassid());
|
||||
assertEquals(
|
||||
CreateActionSetSparkJob.OPENCITATIONS_CLASSNAME, r.getDataInfo().getProvenanceaction().getClassname());
|
||||
assertEquals(ModelConstants.DNET_PROVENANCE_ACTIONS, r.getDataInfo().getProvenanceaction().getSchemeid());
|
||||
assertEquals(ModelConstants.DNET_PROVENANCE_ACTIONS, r.getDataInfo().getProvenanceaction().getSchemename());
|
||||
});
|
||||
|
||||
}
|
||||
|
||||
@Test
|
||||
void testRelationsSemantics() throws Exception {
|
||||
|
||||
String inputPath = getClass()
|
||||
.getResource(
|
||||
"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
|
||||
.getPath();
|
||||
|
||||
CreateActionSetSparkJob
|
||||
.main(
|
||||
new String[] {
|
||||
"-isSparkSessionManaged",
|
||||
Boolean.FALSE.toString(),
|
||||
"-inputPath",
|
||||
inputPath,
|
||||
"-outputPath",
|
||||
workingDir.toString() + "/actionSet"
|
||||
});
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
|
||||
JavaRDD<Relation> tmp = sc
|
||||
.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
|
||||
.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
|
||||
.map(aa -> ((Relation) aa.getPayload()));
|
||||
|
||||
tmp.foreach(r -> {
|
||||
assertEquals("citation", r.getSubRelType());
|
||||
assertEquals("resultResult", r.getRelType());
|
||||
});
|
||||
assertEquals(22, tmp.filter(r -> r.getRelClass().equals("Cites")).count());
|
||||
assertEquals(22, tmp.filter(r -> r.getRelClass().equals("IsCitedBy")).count());
|
||||
|
||||
}
|
||||
|
||||
@Test
|
||||
void testRelationsSourceTargetPrefix() throws Exception {
|
||||
|
||||
String inputPath = getClass()
|
||||
.getResource(
|
||||
"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
|
||||
.getPath();
|
||||
|
||||
CreateActionSetSparkJob
|
||||
.main(
|
||||
new String[] {
|
||||
"-isSparkSessionManaged",
|
||||
Boolean.FALSE.toString(),
|
||||
"-inputPath",
|
||||
inputPath,
|
||||
"-outputPath",
|
||||
workingDir.toString() + "/actionSet"
|
||||
});
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
|
||||
JavaRDD<Relation> tmp = sc
|
||||
.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
|
||||
.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
|
||||
.map(aa -> ((Relation) aa.getPayload()));
|
||||
|
||||
tmp.foreach(r -> {
|
||||
assertEquals("50|doi_________::", r.getSource().substring(0, 17));
|
||||
assertEquals("50|doi_________::", r.getTarget().substring(0, 17));
|
||||
});
|
||||
|
||||
}
|
||||
|
||||
@Test
|
||||
void testRelationsSourceTargetCouple() throws Exception {
|
||||
final String doi1 = "50|doi_________::"
|
||||
+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1007/s10854-015-3684-x"));
|
||||
final String doi2 = "50|doi_________::"
|
||||
+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1111/j.1551-2916.2008.02408.x"));
|
||||
final String doi3 = "50|doi_________::"
|
||||
+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1007/s10854-014-2114-9"));
|
||||
final String doi4 = "50|doi_________::"
|
||||
+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1016/j.ceramint.2013.09.069"));
|
||||
final String doi5 = "50|doi_________::"
|
||||
+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1007/s10854-009-9913-4"));
|
||||
final String doi6 = "50|doi_________::"
|
||||
+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", "10.1016/0038-1098(72)90370-5"));
|
||||
|
||||
String inputPath = getClass()
|
||||
.getResource(
|
||||
"/eu/dnetlib/dhp/actionmanager/opencitations/inputFiles")
|
||||
.getPath();
|
||||
|
||||
CreateActionSetSparkJob
|
||||
.main(
|
||||
new String[] {
|
||||
"-isSparkSessionManaged",
|
||||
Boolean.FALSE.toString(),
|
||||
"-inputPath",
|
||||
inputPath,
|
||||
"-outputPath",
|
||||
workingDir.toString() + "/actionSet"
|
||||
});
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
|
||||
JavaRDD<Relation> tmp = sc
|
||||
.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
|
||||
.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
|
||||
.map(aa -> ((Relation) aa.getPayload()));
|
||||
|
||||
JavaRDD<Relation> check = tmp.filter(r -> r.getSource().equals(doi1) || r.getTarget().equals(doi1));
|
||||
|
||||
assertEquals(10, check.count());
|
||||
|
||||
check.foreach(r -> {
|
||||
if (r.getSource().equals(doi2) || r.getSource().equals(doi3) || r.getSource().equals(doi4) ||
|
||||
r.getSource().equals(doi5) || r.getSource().equals(doi6)) {
|
||||
assertEquals(ModelConstants.IS_CITED_BY, r.getRelClass());
|
||||
assertEquals(doi1, r.getTarget());
|
||||
}
|
||||
});
|
||||
|
||||
assertEquals(5, check.filter(r -> r.getSource().equals(doi1)).count());
|
||||
check.filter(r -> r.getSource().equals(doi1)).foreach(r -> assertEquals(ModelConstants.CITES, r.getRelClass()));
|
||||
|
||||
}
|
||||
}
|
||||
|
|
@ -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"}]}]}
|
||||
{"10.0000/czt.2019.1.2.15": [{"id": "influence", "unit": [{"value": "5.91019644836e-09", "key": "score"}]}, {"id": "popularity_alt", "unit": [{"value": "0.0", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "7.28336930301e-09", "key": "score"}]}]}
|
||||
{"10.0000/geoekonomi.v4i02.36": [{"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/geoekonomi.v4i02.37": [{"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/geoekonomi.v4i02.38": [{"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/geoekonomi.v5i01.32": [{"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/geoekonomi.v6i01.24": [{"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"}]}]}
|
||||
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@ -0,0 +1,38 @@
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{"doi":"10.3390/s18072310","level1":"engineering and technology","level2":"nano-technology","level3":"nanoscience & nanotechnology"}
|
||||
{"doi":"10.1111/1365-2656.12831\u000210.17863/cam.24369","level1":"social sciences","level2":"psychology and cognitive sciences","level3":"NULL"}
|
||||
{"doi":"10.3929/ethz-b-000187584\u000210.1002/chem.201701644","level1":"natural sciences","level2":"NULL","level3":"NULL"}
|
||||
{"doi":"10.1080/01913123.2017.1367361","level1":"medical and health sciences","level2":"clinical medicine","level3":"oncology & carcinogenesis"}
|
||||
{"doi":"10.1051/e3sconf/20199207011","level1":"natural sciences","level2":"earth and related environmental sciences","level3":"environmental sciences"}
|
||||
{"doi":"10.1038/onc.2015.333","level1":"medical and health sciences","level2":"clinical medicine","level3":"oncology & carcinogenesis"}
|
||||
{"doi":"10.1093/mnras/staa256","level1":"natural sciences","level2":"physical sciences","level3":"NULL"}
|
||||
{"doi":"10.1016/j.jclepro.2018.07.166","level1":"engineering and technology","level2":"other engineering and technologies","level3":"building & construction"}
|
||||
{"doi":"10.1103/physrevlett.125.037403","level1":"natural sciences","level2":"physical sciences","level3":"nuclear & particles physics"}
|
||||
{"doi":"10.1080/03602532.2017.1316285","level1":"natural sciences","level2":"NULL","level3":"NULL"}
|
||||
{"doi":"10.1001/jamanetworkopen.2019.1868","level1":"medical and health sciences","level2":"other medical science","level3":"health policy & services"}
|
||||
{"doi":"10.1128/mra.00874-18","level1":"natural sciences","level2":"biological sciences","level3":"plant biology & botany"}
|
||||
{"doi":"10.1016/j.nancom.2018.03.001","level1":"engineering and technology","level2":"NULL","level3":"NULL"}
|
||||
{"doi":"10.1112/topo.12174","level1":"natural sciences","level2":"NULL","level3":"NULL"}
|
||||
{"doi":"10.12688/wellcomeopenres.15846.1","level1":"medical and health sciences","level2":"health sciences","level3":"NULL"}
|
||||
{"doi":"10.21468/scipostphys.3.1.001","level1":"natural sciences","level2":"physical sciences","level3":"NULL"}
|
||||
{"doi":"10.1088/1741-4326/ab6c77","level1":"natural sciences","level2":"physical sciences","level3":"nuclear & particles physics"}
|
||||
{"doi":"10.1109/tpwrs.2019.2944747","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"electrical & electronic engineering"}
|
||||
{"doi":"10.1016/j.expthermflusci.2019.109994\u000210.17863/cam.46212","level1":"engineering and technology","level2":"mechanical engineering","level3":"mechanical engineering & transports"}
|
||||
{"doi":"10.1109/tc.2018.2860012","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"computer hardware & architecture"}
|
||||
{"doi":"10.1002/mma.6622","level1":"natural sciences","level2":"mathematics","level3":"numerical & computational mathematics"}
|
||||
{"doi":"10.1051/radiopro/2020020","level1":"natural sciences","level2":"chemical sciences","level3":"NULL"}
|
||||
{"doi":"10.1007/s12268-019-1003-4","level1":"medical and health sciences","level2":"basic medicine","level3":"NULL"}
|
||||
{"doi":"10.3390/cancers12010236","level1":"medical and health sciences","level2":"health sciences","level3":"biochemistry & molecular biology"}
|
||||
{"doi":"10.6084/m9.figshare.9912614\u000210.6084/m9.figshare.9912614.v1\u000210.1080/00268976.2019.1665199","level1":"natural sciences","level2":"chemical sciences","level3":"physical chemistry"}
|
||||
{"doi":"10.1175/jpo-d-17-0239.1","level1":"natural sciences","level2":"biological sciences","level3":"marine biology & hydrobiology"}
|
||||
{"doi":"10.1007/s13218-020-00674-7","level1":"engineering and technology","level2":"industrial biotechnology","level3":"industrial engineering & automation"}
|
||||
{"doi":"10.1016/j.psyneuen.2016.02.003\u000210.1016/j.psyneuen.2016.02.00310.7892/boris.78886\u000210.7892/boris.78886","level1":"medical and health sciences","level2":"basic medicine","level3":"NULL"}
|
||||
{"doi":"10.1109/ted.2018.2813542","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"electrical & electronic engineering"}
|
||||
{"doi":"10.3989/scimar.04739.25a","level1":"natural sciences","level2":"biological sciences","level3":"NULL"}
|
||||
{"doi":"10.3390/su12187503","level1":"natural sciences","level2":"earth and related environmental sciences","level3":"NULL"}
|
||||
{"doi":"10.1016/j.ccell.2018.08.017","level1":"medical and health sciences","level2":"basic medicine","level3":"biochemistry & molecular biology"}
|
||||
{"doi":"10.1103/physrevresearch.2.023322","level1":"natural sciences","level2":"physical sciences","level3":"nuclear & particles physics"}
|
||||
{"doi":"10.1039/c8cp03234c","level1":"natural sciences","level2":"NULL","level3":"NULL"}
|
||||
{"doi":"10.5281/zenodo.3696557\u000210.5281/zenodo.3696556\u000210.1109/jsac.2016.2545384","level1":"engineering and technology","level2":"electrical engineering, electronic engineering, information engineering","level3":"networking & telecommunications"}
|
||||
{"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"}
|
||||
{"doi":"10.1016/j.jclepro.2019.119065","level1":"engineering and technology","level2":"other engineering and technologies","level3":"building & construction"}
|
||||
{"doi":"10.1111/pce.13392","level1":"agricultural and veterinary sciences","level2":"agriculture, forestry, and fisheries","level3":"agronomy & agriculture"}
|
||||
|
|
@ -0,0 +1,38 @@
|
|||
dedup_wf_001::ddcc7a56fa13e49bcc59c6bdd19ad26c 10.3390/s18072310 engineering and technology nano-technology nanoscience & nanotechnology
|
||||
dedup_wf_001::b76062d56e28224eac56111a4e1e5ecf 10.1111/1365-2656.1283110.17863/cam.24369 social sciences psychology and cognitive sciences NULL
|
||||
dedup_wf_001::bb752acb8f403a25fa7851a302f7b7ac 10.3929/ethz-b-00018758410.1002/chem.201701644 natural sciences NULL NULL
|
||||
dedup_wf_001::2f1435a9201ecf5cbbcb12c9b2d971cd 10.1080/01913123.2017.1367361 medical and health sciences clinical medicine oncology & carcinogenesis
|
||||
dedup_wf_001::fc9e47ec16c67b101724320d4b030514 10.1051/e3sconf/20199207011 natural sciences earth and related environmental sciences environmental sciences
|
||||
dedup_wf_001::caa1e5b4de387cb31751552f4f0f5d72 10.1038/onc.2015.333 medical and health sciences clinical medicine oncology & carcinogenesis
|
||||
dedup_wf_001::c2a98df5637d69bf0524eaf40fe6bf11 10.1093/mnras/staa256 natural sciences physical sciences NULL
|
||||
dedup_wf_001::c221262bdc77cbfd59859a402f0e3991 10.1016/j.jclepro.2018.07.166 engineering and technology other engineering and technologies building & construction
|
||||
doiboost____::d56d9dc21f317b3e009d5b6c8ea87212 10.1103/physrevlett.125.037403 natural sciences physical sciences nuclear & particles physics
|
||||
dedup_wf_001::8a7269c8ee6470b2fb4fd384bc389e08 10.1080/03602532.2017.1316285 natural sciences NULL NULL
|
||||
dedup_wf_001::28342ebbc19833e4e1f4a2b23cf5ee20 10.1001/jamanetworkopen.2019.1868 medical and health sciences other medical science health policy & services
|
||||
dedup_wf_001::c1e1daf2b55dd9ec8e1c7c7458bbc7bc 10.1128/mra.00874-18 natural sciences biological sciences plant biology & botany
|
||||
dedup_wf_001::a2ef4a2720c71907180750e5871298ef 10.1016/j.nancom.2018.03.001 engineering and technology NULL NULL
|
||||
dedup_wf_001::676f46a31519e83a89efcb1c626286fb 10.1112/topo.12174 natural sciences NULL NULL
|
||||
dedup_wf_001::6f2761642f1e39313388e2c4060657dd 10.12688/wellcomeopenres.15846.1 medical and health sciences health sciences NULL
|
||||
dedup_wf_001::e414c1dec599521a9635a60de0f6755b 10.21468/scipostphys.3.1.001 natural sciences physical sciences NULL
|
||||
dedup_wf_001::f3395fe0f330164ea424dc61c86c9a3d 10.1088/1741-4326/ab6c77 natural sciences physical sciences nuclear & particles physics
|
||||
dedup_wf_001::a4f32a97a783117012f1de11797e73f2 10.1109/tpwrs.2019.2944747 engineering and technology electrical engineering, electronic engineering, information engineering electrical & electronic engineering
|
||||
dedup_wf_001::313ae1cd083ae1696d12dd1909f97df8 10.1016/j.expthermflusci.2019.10999410.17863/cam.46212 engineering and technology mechanical engineering mechanical engineering & transports
|
||||
dedup_wf_001::2a300a7d3ca7347791ebcef986bc0682 10.1109/tc.2018.2860012 engineering and technology electrical engineering, electronic engineering, information engineering computer hardware & architecture
|
||||
doiboost____::5b79bd7bd9f87361b4a4abc3cbb2df75 10.1002/mma.6622 natural sciences mathematics numerical & computational mathematics
|
||||
dedup_wf_001::6a3f61f217a2519fbaddea1094e3bfc2 10.1051/radiopro/2020020 natural sciences chemical sciences NULL
|
||||
dedup_wf_001::a3f0430309a639f4234a0e57b10f2dee 10.1007/s12268-019-1003-4 medical and health sciences basic medicine NULL
|
||||
dedup_wf_001::b6b8a3a1cccbee459cf3343485efdb12 10.3390/cancers12010236 medical and health sciences health sciences biochemistry & molecular biology
|
||||
dedup_wf_001::dd06ee7974730e7b09a4f03c83b3f9bd 10.6084/m9.figshare.991261410.6084/m9.figshare.9912614.v110.1080/00268976.2019.1665199 natural sciences chemical sciences physical chemistry
|
||||
dedup_wf_001::027c78bef6f972b5e26dfea55d30fbe3 10.1175/jpo-d-17-0239.1 natural sciences biological sciences marine biology & hydrobiology
|
||||
dedup_wf_001::43edc179aa9e1fbaf582c5203b18b519 10.1007/s13218-020-00674-7 engineering and technology industrial biotechnology industrial engineering & automation
|
||||
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
|
||||
dedup_wf_001::80bc15d69bdc589149631f3439dde5aa 10.1109/ted.2018.2813542 engineering and technology electrical engineering, electronic engineering, information engineering electrical & electronic engineering
|
||||
dedup_wf_001::42c1cfa33e7872944b920cff90f4d99e 10.3989/scimar.04739.25a natural sciences biological sciences NULL
|
||||
dedup_wf_001::9bacdbbaa9da3658b7243d5de8e3ce14 10.3390/su12187503 natural sciences earth and related environmental sciences NULL
|
||||
dedup_wf_001::59e43d3527dcfecb6097fbd5740c8950 10.1016/j.ccell.2018.08.017 medical and health sciences basic medicine biochemistry & molecular biology
|
||||
doiboost____::e024d1b738df3b24bc58fa0228542571 10.1103/physrevresearch.2.023322 natural sciences physical sciences nuclear & particles physics
|
||||
dedup_wf_001::66e9a3237fa8178886d26d3c2d5b9e66 10.1039/c8cp03234c natural sciences NULL NULL
|
||||
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
|
||||
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
|
||||
dedup_wf_001::14ba594e8fd081847bc3f50f56335003 10.1016/j.jclepro.2019.119065 engineering and technology other engineering and technologies building & construction
|
||||
dedup_wf_001::08ac7b33a41bcea2d055ecd8585d632e 10.1111/pce.13392 agricultural and veterinary sciences agriculture, forestry, and fisheries agronomy & agriculture
|
||||
|
|
|
@ -0,0 +1,8 @@
|
|||
oci,citing,cited,creation,timespan,journal_sc,author_sc
|
||||
02001000007362801000805046300010563030608046333-0200101010136193701050501630209010637020000083700020400083733,10.1007/s10854-015-3684-x,10.1111/j.1551-2916.2008.02408.x,2015-09-01,P7Y2M,no,no
|
||||
02001000007362801000805046300010563030608046333-02001000007362801000805046300010463020101046309,10.1007/s10854-015-3684-x,10.1007/s10854-014-2114-9,2015-09-01,P1Y2M4D,yes,no
|
||||
02001000007362801000805046300010563030608046333-020010001063619371214271022182329370200010337000937000609,10.1007/s10854-015-3684-x,10.1016/j.ceramint.2013.09.069,2015-09-01,P1Y6M,no,no
|
||||
02001000007362801000805046300010563030608046333-02001000007362801000805046300000963090901036304,10.1007/s10854-015-3684-x,10.1007/s10854-009-9913-4,2015-09-01,P6Y3M10D,yes,no
|
||||
02001000007362801000805046300010563030608046333-02001000106360000030863010009085807025909000307006305,10.1007/s10854-015-3684-x,10.1016/0038-1098(72)90370-5,2015-09-01,P43Y8M,no,no
|
||||
02001000007362801000805046300010563030608056309-02001000106361937281010370200010437000937000308,10.1007/s10854-015-3685-9,10.1016/j.saa.2014.09.038,2015-09-03,P0Y7M,no,no
|
||||
02001000007362801000805046300010563030608056309-0200100010636193722102912171027370200010537000437000106,10.1007/s10854-015-3685-9,10.1016/j.matchar.2015.04.016,2015-09-03,P0Y2M,no,no
|
||||
|
|
@ -0,0 +1,8 @@
|
|||
oci,citing,cited,creation,timespan,journal_sc,author_sc
|
||||
02001000308362804010509076300010963000003086301-0200100020936020001003227000009010004,10.1038/s41597-019-0038-1,10.1029/2010wr009104,2019-04-15,P8Y1M,no,no
|
||||
02001000308362804010509076300010963000003086301-0200100010636280103060463080105025800015900000006006303,10.1038/s41597-019-0038-1,10.1016/s1364-8152(01)00060-3,2019-04-15,P17Y3M,no,no
|
||||
02001000308362804010509076300010963000003086301-02001000007362800000407076300010063000401066333,10.1038/s41597-019-0038-1,10.1007/s00477-010-0416-x,2019-04-15,P8Y9M6D,no,no
|
||||
02001000308362804010509076300010963000003086301-02001000007362800000700046300010363000905016308,10.1038/s41597-019-0038-1,10.1007/s00704-013-0951-8,2019-04-15,P5Y9M23D,no,no
|
||||
02001000308362804010509076300010963000003086301-02001000002361924123705070707,10.1038/s41597-019-0038-1,10.1002/joc.5777,2019-04-15,P0Y8M1D,no,no
|
||||
02001000308362804010509076300010963000003086301-02005010904361714282863020263040504076302000108,10.1038/s41597-019-0038-1,10.5194/hess-22-4547-2018,2019-04-15,P0Y7M18D,no,no
|
||||
02001000308362804010509076300010963000003086301-02001000002361924123703050404,10.1038/s41597-019-0038-1,10.1002/joc.3544,2019-04-15,P6Y9M6D,no,no
|
||||
|
|
@ -0,0 +1,9 @@
|
|||
oci,citing,cited,creation,timespan,journal_sc,author_sc
|
||||
0200100000236090708010101090307000202023727141528-020050302063600040000010307,10.1002/9781119370222.refs,10.5326/0400137,2020-06-22,P16Y3M,no,no
|
||||
0200100000236090708010101090307000202023727141528-0200101010136193701050302630905003337020000073700000301093733,10.1002/9781119370222.refs,10.1111/j.1532-950x.2007.00319.x,2020-06-22,P12Y8M,no,no
|
||||
0200100000236090708010101090307000202023727141528-0200101010136312830370102030509,10.1002/9781119370222.refs,10.1111/vsu.12359,2020-06-22,P4Y10M29D,no,no
|
||||
0200100000236090708010101090307000202023727141528-020050302063600030900020904,10.1002/9781119370222.refs,10.5326/0390294,2020-06-22,P17Y1M,no,no
|
||||
0200100000236090708010101090307000202023727141528-020050302063600040200030701,10.1002/9781119370222.refs,10.5326/0420371,2020-06-22,P13Y9M,no,no
|
||||
0200100000236090708010101090307000202023727141528-0200101010136193701050302630905003337020001033701020000003733,10.1002/9781119370222.refs,10.1111/j.1532-950x.2013.12000.x,2020-06-22,P7Y2M,no,no
|
||||
0200100000236090708010101090307000202023727141528-020010008003600000408000106093702000006370306070200,10.1002/9781119370222.refs,10.1080/00480169.2006.36720,2020-06-22,P13Y6M,no,no
|
||||
0200100000236090708010101090307000202023727141528-0200101010136193701070501630008010337020000063700000003033733,10.1002/9781119370222.refs,10.1111/j.1751-0813.2006.00033.x,2020-06-22,P13Y8M,no,no
|
||||
|
|
@ -89,7 +89,7 @@
|
|||
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
--conf spark.sql.shuffle.partitions=7680
|
||||
--conf spark.sql.shuffle.partitions=15000
|
||||
</spark-opts>
|
||||
<arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
|
||||
<arg>--o</arg><arg>${graphOutputPath}</arg>
|
||||
|
|
@ -114,7 +114,7 @@
|
|||
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
--conf spark.sql.shuffle.partitions=7680
|
||||
--conf spark.sql.shuffle.partitions=15000
|
||||
</spark-opts>
|
||||
<arg>--graphInputPath</arg><arg>${graphBasePath}</arg>
|
||||
<arg>--outputPath</arg><arg>${workingPath}/grouped_entities</arg>
|
||||
|
|
|
|||
|
|
@ -70,7 +70,7 @@ case object Crossref2Oaf {
|
|||
"reference-book" -> "0002 Book",
|
||||
"monograph" -> "0002 Book",
|
||||
"journal-article" -> "0001 Article",
|
||||
"dissertation" -> "0006 Doctoral thesis",
|
||||
"dissertation" -> "0044 Thesis",
|
||||
"other" -> "0038 Other literature type",
|
||||
"peer-review" -> "0015 Review",
|
||||
"proceedings" -> "0004 Conference object",
|
||||
|
|
@ -206,11 +206,16 @@ case object Crossref2Oaf {
|
|||
else {
|
||||
instance.setDateofacceptance(asField(createdDate.getValue))
|
||||
}
|
||||
val s: String = (json \ "URL").extract[String]
|
||||
val links: List[String] = ((for {JString(url) <- json \ "link" \ "URL"} yield url) ::: List(s)).filter(p => p != null).distinct
|
||||
if (links.nonEmpty) {
|
||||
instance.setUrl(links.asJava)
|
||||
}
|
||||
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 && p.toLowerCase().contains(doi.toLowerCase())).distinct
|
||||
// if (links.nonEmpty) {
|
||||
// instance.setUrl(links.asJava)
|
||||
// }
|
||||
if(s.nonEmpty)
|
||||
{
|
||||
instance.setUrl(s.asJava)
|
||||
}
|
||||
|
||||
result.setInstance(List(instance).asJava)
|
||||
|
||||
//IMPORTANT
|
||||
|
|
|
|||
|
|
@ -111,26 +111,9 @@ object SparkProcessMAG {
|
|||
.map(item => ConversionUtil.updatePubsWithConferenceInfo(item))
|
||||
.write
|
||||
.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")
|
||||
|
||||
|
||||
// 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"$workingPath/PaperAbstract")).as[MagPaperAbstract]
|
||||
|
||||
|
||||
|
|
@ -162,12 +145,14 @@ object SparkProcessMAG {
|
|||
.write.mode(SaveMode.Overwrite)
|
||||
.save(s"$workingPath/mag_publication")
|
||||
|
||||
spark.read.load(s"$workingPath/mag_publication").as[Publication]
|
||||
.filter(p => p.getId == null)
|
||||
.groupByKey(p => p.getId)
|
||||
.reduceGroups((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
|
||||
.map(_._2)
|
||||
.write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
|
||||
|
||||
val s:RDD[Publication] = spark.read.load(s"$workingPath/mag_publication").as[Publication]
|
||||
.map(p=>Tuple2(p.getId, p)).rdd.reduceByKey((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
|
||||
.map(_._2)
|
||||
|
||||
spark.createDataset(s).as[Publication].write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
|
||||
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -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))
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,614 @@
|
|||
|
||||
{
|
||||
"indexed": {
|
||||
"date-parts": [
|
||||
[
|
||||
2021,
|
||||
10,
|
||||
31
|
||||
]
|
||||
],
|
||||
"date-time": "2021-10-31T15:48:01Z",
|
||||
"timestamp": 1635695281393
|
||||
},
|
||||
"reference-count": 39,
|
||||
"publisher": "Elsevier BV",
|
||||
"license": [
|
||||
{
|
||||
"start": {
|
||||
"date-parts": [
|
||||
[
|
||||
2019,
|
||||
12,
|
||||
1
|
||||
]
|
||||
],
|
||||
"date-time": "2019-12-01T00:00:00Z",
|
||||
"timestamp": 1575158400000
|
||||
},
|
||||
"content-version": "tdm",
|
||||
"delay-in-days": 0,
|
||||
"URL": "https://www.elsevier.com/tdm/userlicense/1.0/"
|
||||
},
|
||||
{
|
||||
"start": {
|
||||
"date-parts": [
|
||||
[
|
||||
2019,
|
||||
9,
|
||||
13
|
||||
]
|
||||
],
|
||||
"date-time": "2019-09-13T00:00:00Z",
|
||||
"timestamp": 1568332800000
|
||||
},
|
||||
"content-version": "vor",
|
||||
"delay-in-days": 0,
|
||||
"URL": "http://creativecommons.org/licenses/by/4.0/"
|
||||
}
|
||||
],
|
||||
"funder": [
|
||||
{
|
||||
"DOI": "10.13039/100001182",
|
||||
"name": "INSTAP",
|
||||
"doi-asserted-by": "publisher"
|
||||
},
|
||||
{
|
||||
"DOI": "10.13039/100014440",
|
||||
"name": "Ministry of Science, Innovation and Universities",
|
||||
"doi-asserted-by": "publisher",
|
||||
"award": [
|
||||
"RYC-2016-19637"
|
||||
]
|
||||
},
|
||||
{
|
||||
"DOI": "10.13039/100010661",
|
||||
"name": "European Union’s Horizon 2020",
|
||||
"doi-asserted-by": "publisher",
|
||||
"award": [
|
||||
"746446"
|
||||
]
|
||||
}
|
||||
],
|
||||
"content-domain": {
|
||||
"domain": [
|
||||
"elsevier.com",
|
||||
"sciencedirect.com"
|
||||
],
|
||||
"crossmark-restriction": true
|
||||
},
|
||||
"short-container-title": [
|
||||
"Journal of Archaeological Science"
|
||||
],
|
||||
"published-print": {
|
||||
"date-parts": [
|
||||
[
|
||||
2019,
|
||||
12
|
||||
]
|
||||
]
|
||||
},
|
||||
"DOI": "10.1016/j.jas.2019.105013",
|
||||
"type": "journal-article",
|
||||
"created": {
|
||||
"date-parts": [
|
||||
[
|
||||
2019,
|
||||
9,
|
||||
25
|
||||
]
|
||||
],
|
||||
"date-time": "2019-09-25T20:05:08Z",
|
||||
"timestamp": 1569441908000
|
||||
},
|
||||
"page": "105013",
|
||||
"update-policy": "http://dx.doi.org/10.1016/elsevier_cm_policy",
|
||||
"source": "Crossref",
|
||||
"is-referenced-by-count": 21,
|
||||
"title": [
|
||||
"A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery"
|
||||
],
|
||||
"prefix": "10.1016",
|
||||
"volume": "112",
|
||||
"author": [
|
||||
{
|
||||
"given": "H.A.",
|
||||
"family": "Orengo",
|
||||
"sequence": "first",
|
||||
"affiliation": [
|
||||
|
||||
]
|
||||
},
|
||||
{
|
||||
"given": "A.",
|
||||
"family": "Garcia-Molsosa",
|
||||
"sequence": "additional",
|
||||
"affiliation": [
|
||||
|
||||
]
|
||||
}
|
||||
],
|
||||
"member": "78",
|
||||
"reference": [
|
||||
{
|
||||
"key": "10.1016/j.jas.2019.105013_bib1",
|
||||
"doi-asserted-by": "crossref",
|
||||
"first-page": "85",
|
||||
"DOI": "10.1080/17538947.2016.1250829",
|
||||
"article-title": "Remote sensing heritage in a petabyte-scale: satellite data and heritage Earth Engine© applications",
|
||||
"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",
|
||||
"first-page": "1",
|
||||
"article-title": "Extracting meaning from ploughsoil assemblages: assessments of the past, strategies for the future",
|
||||
"author": "Alcock",
|
||||
"year": "2000"
|
||||
},
|
||||
{
|
||||
"key": "10.1016/j.jas.2019.105013_bib3",
|
||||
"series-title": "Side-by-Side Survey. Comparative Regional Studies in the Mediterranean World",
|
||||
"first-page": "1",
|
||||
"article-title": "Introduction",
|
||||
"author": "Alcock",
|
||||
"year": "2004"
|
||||
},
|
||||
{
|
||||
"key": "10.1016/j.jas.2019.105013_bib4",
|
||||
"doi-asserted-by": "crossref",
|
||||
"first-page": "93",
|
||||
"DOI": "10.1111/j.1538-4632.1995.tb00338.x",
|
||||
"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"
|
||||
},
|
||||
{
|
||||
"issue": "1/2",
|
||||
"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"
|
||||
},
|
||||
{
|
||||
"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"
|
||||
},
|
||||
{
|
||||
"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"
|
||||
}
|
||||
],
|
||||
"container-title": [
|
||||
"Journal of Archaeological Science"
|
||||
],
|
||||
"original-title": [
|
||||
|
||||
],
|
||||
"language": "en",
|
||||
"link": [
|
||||
{
|
||||
"URL": "https://api.elsevier.com/content/article/PII:S0305440319301001?httpAccept=text/xml",
|
||||
"content-type": "text/xml",
|
||||
"content-version": "vor",
|
||||
"intended-application": "text-mining"
|
||||
},
|
||||
{
|
||||
"URL": "https://api.elsevier.com/content/article/PII:S0305440319301001?httpAccept=text/plain",
|
||||
"content-type": "text/plain",
|
||||
"content-version": "vor",
|
||||
"intended-application": "text-mining"
|
||||
}
|
||||
],
|
||||
"deposited": {
|
||||
"date-parts": [
|
||||
[
|
||||
2019,
|
||||
11,
|
||||
25
|
||||
]
|
||||
],
|
||||
"date-time": "2019-11-25T06:46:34Z",
|
||||
"timestamp": 1574664394000
|
||||
},
|
||||
"score": 1,
|
||||
"subtitle": [
|
||||
|
||||
],
|
||||
"short-title": [
|
||||
|
||||
],
|
||||
"issued": {
|
||||
"date-parts": [
|
||||
[
|
||||
2019,
|
||||
12
|
||||
]
|
||||
]
|
||||
},
|
||||
"references-count": 39,
|
||||
"alternative-id": [
|
||||
"S0305440319301001"
|
||||
],
|
||||
"URL": "http://dx.doi.org/10.1016/j.jas.2019.105013",
|
||||
"relation": {
|
||||
|
||||
},
|
||||
"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"
|
||||
}
|
||||
|
|
@ -26,6 +26,24 @@ public class 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 PROPAGATION_DATA_INFO_TYPE = "propagation";
|
||||
|
|
@ -86,10 +104,25 @@ public class PropagationConstant {
|
|||
|
||||
public static DataInfo getDataInfo(
|
||||
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();
|
||||
di.setInferred(true);
|
||||
di.setInferred(inferred);
|
||||
di.setDeletedbyinference(false);
|
||||
di.setTrust("0.85");
|
||||
di.setTrust(trust);
|
||||
di.setInferenceprovenance(inference_provenance);
|
||||
di.setProvenanceaction(getQualifier(inference_class_id, inference_class_name, qualifierSchema));
|
||||
return di;
|
||||
|
|
|
|||
|
|
@ -0,0 +1,107 @@
|
|||
package eu.dnetlib.dhp.oa.graph.resolution
|
||||
|
||||
import com.fasterxml.jackson.databind.ObjectMapper
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser
|
||||
import eu.dnetlib.dhp.common.HdfsSupport
|
||||
import eu.dnetlib.dhp.schema.common.EntityType
|
||||
import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Result, Software, Dataset => OafDataset}
|
||||
import org.apache.commons.io.IOUtils
|
||||
import org.apache.hadoop.fs.{FileSystem, Path}
|
||||
import org.apache.spark.SparkConf
|
||||
import org.apache.spark.sql._
|
||||
import org.slf4j.{Logger, LoggerFactory}
|
||||
|
||||
object SparkResolveEntities {
|
||||
|
||||
val mapper = new ObjectMapper()
|
||||
val entities = List(EntityType.dataset,EntityType.publication, EntityType.software, EntityType.otherresearchproduct)
|
||||
|
||||
def main(args: Array[String]): Unit = {
|
||||
val log: Logger = LoggerFactory.getLogger(getClass)
|
||||
val conf: SparkConf = new SparkConf()
|
||||
val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/oa/graph/resolution/resolve_entities_params.json")))
|
||||
parser.parseArgument(args)
|
||||
val spark: SparkSession =
|
||||
SparkSession
|
||||
.builder()
|
||||
.config(conf)
|
||||
.appName(getClass.getSimpleName)
|
||||
.master(parser.get("master")).getOrCreate()
|
||||
|
||||
|
||||
val graphBasePath = parser.get("graphBasePath")
|
||||
log.info(s"graphBasePath -> $graphBasePath")
|
||||
val workingPath = parser.get("workingPath")
|
||||
log.info(s"workingPath -> $workingPath")
|
||||
val unresolvedPath = parser.get("unresolvedPath")
|
||||
log.info(s"unresolvedPath -> $unresolvedPath")
|
||||
|
||||
val fs = FileSystem.get(spark.sparkContext.hadoopConfiguration)
|
||||
fs.mkdirs(new Path(workingPath))
|
||||
|
||||
resolveEntities(spark, workingPath, unresolvedPath)
|
||||
generateResolvedEntities(spark, workingPath, graphBasePath)
|
||||
|
||||
// TO BE conservative we keep the original entities in the working dir
|
||||
// and save the resolved entities on the graphBasePath
|
||||
//In future these lines of code should be removed
|
||||
entities.foreach {
|
||||
e =>
|
||||
fs.rename(new Path(s"$graphBasePath/$e"), new Path(s"$workingPath/${e}_old"))
|
||||
fs.rename(new Path(s"$workingPath/resolvedGraph/$e"), new Path(s"$graphBasePath/$e"))
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
||||
def resolveEntities(spark: SparkSession, workingPath: String, unresolvedPath: String) = {
|
||||
implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
|
||||
import spark.implicits._
|
||||
|
||||
val rPid: Dataset[(String, String)] = spark.read.load(s"$workingPath/relationResolvedPid").as[(String, String)]
|
||||
val up: Dataset[(String, Result)] = spark.read.text(unresolvedPath).as[String].map(s => mapper.readValue(s, classOf[Result])).map(r => (r.getId, r))(Encoders.tuple(Encoders.STRING, resEncoder))
|
||||
|
||||
rPid.joinWith(up, rPid("_2").equalTo(up("_1")), "inner").map {
|
||||
r =>
|
||||
val result = r._2._2
|
||||
val dnetId = r._1._1
|
||||
result.setId(dnetId)
|
||||
result
|
||||
}.write.mode(SaveMode.Overwrite).save(s"$workingPath/resolvedEntities")
|
||||
}
|
||||
|
||||
|
||||
def deserializeObject(input:String, entity:EntityType ) :Result = {
|
||||
|
||||
entity match {
|
||||
case EntityType.publication => mapper.readValue(input, classOf[Publication])
|
||||
case EntityType.dataset => mapper.readValue(input, classOf[OafDataset])
|
||||
case EntityType.software=> mapper.readValue(input, classOf[Software])
|
||||
case EntityType.otherresearchproduct=> mapper.readValue(input, classOf[OtherResearchProduct])
|
||||
}
|
||||
}
|
||||
|
||||
def generateResolvedEntities(spark:SparkSession, workingPath: String, graphBasePath:String) = {
|
||||
|
||||
implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
|
||||
import spark.implicits._
|
||||
|
||||
val re:Dataset[Result] = spark.read.load(s"$workingPath/resolvedEntities").as[Result]
|
||||
entities.foreach {
|
||||
e =>
|
||||
|
||||
spark.read.text(s"$graphBasePath/$e").as[String]
|
||||
.map(s => deserializeObject(s, e))
|
||||
.union(re)
|
||||
.groupByKey(_.getId)
|
||||
.reduceGroups {
|
||||
(x, y) =>
|
||||
x.mergeFrom(y)
|
||||
x
|
||||
}.map(_._2)
|
||||
.filter(r => r.getClass.getSimpleName.toLowerCase != "result")
|
||||
.map(r => mapper.writeValueAsString(r))(Encoders.STRING)
|
||||
.write.mode(SaveMode.Overwrite).option("compression", "gzip").text(s"$workingPath/resolvedGraph/$e")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -96,6 +96,21 @@ object SparkResolveRelation {
|
|||
.text(s"$graphBasePath/relation")
|
||||
}
|
||||
|
||||
def extractInstanceCF(input: String): List[(String, String)] = {
|
||||
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
|
||||
lazy val json: json4s.JValue = parse(input)
|
||||
val result: List[(String, String)] = for {
|
||||
JObject(iObj) <- json \ "instance"
|
||||
JField("collectedfrom", JObject(cf)) <- iObj
|
||||
JField("instancetype", JObject(instancetype)) <- iObj
|
||||
JField("value", JString(collectedFrom)) <- cf
|
||||
JField("classname", JString(classname)) <- instancetype
|
||||
} yield (classname, collectedFrom)
|
||||
|
||||
result
|
||||
|
||||
}
|
||||
|
||||
|
||||
def extractPidsFromRecord(input: String): (String, List[(String, String)]) = {
|
||||
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
|
||||
|
|
@ -108,14 +123,7 @@ object SparkResolveRelation {
|
|||
JField("classid", JString(pidType)) <- qualifier
|
||||
} yield (pidValue, pidType)
|
||||
|
||||
val alternateIds: List[(String, String)] = for {
|
||||
JObject(pids) <- json \\ "alternateIdentifier"
|
||||
JField("value", JString(pidValue)) <- pids
|
||||
JField("qualifier", JObject(qualifier)) <- pids
|
||||
JField("classid", JString(pidType)) <- qualifier
|
||||
} yield (pidValue, pidType)
|
||||
|
||||
(id, result ::: alternateIds)
|
||||
(id, result)
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -128,7 +136,7 @@ object SparkResolveRelation {
|
|||
source != null
|
||||
}
|
||||
|
||||
private def extractPidResolvedTableFromJsonRDD(spark: SparkSession, graphPath: String, workingPath: String) = {
|
||||
def extractPidResolvedTableFromJsonRDD(spark: SparkSession, graphPath: String, workingPath: String) = {
|
||||
import spark.implicits._
|
||||
|
||||
val d: RDD[(String, String)] = spark.sparkContext.textFile(s"$graphPath/*")
|
||||
|
|
|
|||
|
|
@ -59,7 +59,12 @@ object SparkConvertRDDtoDataset {
|
|||
log.info("Converting Relation")
|
||||
|
||||
|
||||
val rddRelation =spark.sparkContext.textFile(s"$sourcePath/relation").map(s => mapper.readValue(s, classOf[Relation])).filter(r=> r.getSource.startsWith("50") && r.getTarget.startsWith("50"))
|
||||
val relationSemanticFilter = List("cites", "iscitedby","merges", "ismergedin")
|
||||
|
||||
val rddRelation =spark.sparkContext.textFile(s"$sourcePath/relation")
|
||||
.map(s => mapper.readValue(s, classOf[Relation]))
|
||||
.filter(r=> r.getSource.startsWith("50") && r.getTarget.startsWith("50"))
|
||||
.filter(r => !relationSemanticFilter.exists(k => k.equalsIgnoreCase(r.getRelClass)))
|
||||
spark.createDataset(rddRelation).as[Relation].write.mode(SaveMode.Overwrite).save(s"$relPath")
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,9 +1,13 @@
|
|||
<workflow-app name="Resolve Relation" xmlns="uri:oozie:workflow:0.5">
|
||||
<workflow-app name="Resolve relation and entities" xmlns="uri:oozie:workflow:0.5">
|
||||
<parameters>
|
||||
<property>
|
||||
<name>graphBasePath</name>
|
||||
<description>the path of the graph</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>unresolvedPath</name>
|
||||
<description>the path of the unresolved Entities</description>
|
||||
</property>
|
||||
</parameters>
|
||||
|
||||
<start to="ResolveRelations"/>
|
||||
|
|
@ -33,8 +37,36 @@
|
|||
<arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
|
||||
<arg>--workingPath</arg><arg>${workingDir}</arg>
|
||||
</spark>
|
||||
<ok to="ResolveEntities"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
<action name="ResolveEntities">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
<name>Resolve Entities in raw graph</name>
|
||||
<class>eu.dnetlib.dhp.oa.graph.resolution.SparkResolveEntities</class>
|
||||
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
|
||||
<spark-opts>
|
||||
--executor-memory=${sparkExecutorMemory}
|
||||
--executor-cores=${sparkExecutorCores}
|
||||
--driver-memory=${sparkDriverMemory}
|
||||
--conf spark.extraListeners=${spark2ExtraListeners}
|
||||
--conf spark.sql.shuffle.partitions=10000
|
||||
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
</spark-opts>
|
||||
<arg>--master</arg><arg>yarn</arg>
|
||||
<arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
|
||||
<arg>--unresolvedPath</arg><arg>${unresolvedPath}</arg>
|
||||
<arg>--workingPath</arg><arg>${workingDir}</arg>
|
||||
</spark>
|
||||
<ok to="End"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
<end name="End"/>
|
||||
|
||||
</workflow-app>
|
||||
|
|
@ -0,0 +1,6 @@
|
|||
[
|
||||
{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
|
||||
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the source Path", "paramRequired": true},
|
||||
{"paramName":"u", "paramLongName":"unresolvedPath", "paramDescription": "the source Path", "paramRequired": true},
|
||||
{"paramName":"g", "paramLongName":"graphBasePath", "paramDescription": "the path of the raw graph", "paramRequired": true}
|
||||
]
|
||||
|
|
@ -331,7 +331,6 @@ public class DumpJobTest {
|
|||
Assertions
|
||||
.assertEquals(
|
||||
Constants.accessRightsCoarMap.get(ModelConstants.ACCESS_RIGHT_OPEN), gr.getBestaccessright().getCode());
|
||||
Assertions.assertEquals(null, gr.getBestaccessright().getOpenAccessRoute());
|
||||
|
||||
Assertions.assertEquals("One Ecosystem", gr.getContainer().getName());
|
||||
Assertions.assertEquals("2367-8194", gr.getContainer().getIssnOnline());
|
||||
|
|
|
|||
|
|
@ -0,0 +1,190 @@
|
|||
package eu.dnetlib.dhp.oa.graph.resolution
|
||||
|
||||
|
||||
import com.fasterxml.jackson.databind.ObjectMapper
|
||||
import eu.dnetlib.dhp.schema.common.EntityType
|
||||
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils
|
||||
import eu.dnetlib.dhp.schema.oaf.{Result, StructuredProperty}
|
||||
import org.apache.commons.io.FileUtils
|
||||
import org.apache.spark.SparkConf
|
||||
import org.apache.spark.sql._
|
||||
import org.junit.jupiter.api.Assertions._
|
||||
import org.junit.jupiter.api.TestInstance.Lifecycle
|
||||
import org.junit.jupiter.api.{AfterAll, BeforeAll, Test, TestInstance}
|
||||
|
||||
import java.nio.file.{Files, Path}
|
||||
import scala.collection.JavaConverters._
|
||||
import scala.io.Source
|
||||
|
||||
@TestInstance(Lifecycle.PER_CLASS)
|
||||
class ResolveEntitiesTest extends Serializable {
|
||||
|
||||
var workingDir:Path = null
|
||||
|
||||
val FAKE_TITLE = "FAKETITLE"
|
||||
val FAKE_SUBJECT = "FAKESUBJECT"
|
||||
|
||||
var sparkSession:Option[SparkSession] = None
|
||||
|
||||
|
||||
@BeforeAll
|
||||
def setUp() :Unit = {
|
||||
workingDir = Files.createTempDirectory(getClass.getSimpleName)
|
||||
|
||||
val conf = new SparkConf()
|
||||
sparkSession = Some(SparkSession
|
||||
.builder()
|
||||
.config(conf)
|
||||
.appName(getClass.getSimpleName)
|
||||
.master("local[*]").getOrCreate())
|
||||
populateDatasets(sparkSession.get)
|
||||
generateUpdates(sparkSession.get)
|
||||
|
||||
}
|
||||
|
||||
|
||||
@AfterAll
|
||||
def tearDown():Unit = {
|
||||
FileUtils.deleteDirectory(workingDir.toFile)
|
||||
sparkSession.get.stop()
|
||||
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
def generateUpdates(spark:SparkSession):Unit = {
|
||||
val template = Source.fromInputStream(this.getClass.getResourceAsStream("updates")).mkString
|
||||
|
||||
|
||||
val pids:List[String] = template.lines.map{id =>
|
||||
val r = new Result
|
||||
r.setId(id.toLowerCase.trim)
|
||||
r.setSubject(List(OafMapperUtils.structuredProperty(FAKE_SUBJECT, OafMapperUtils.qualifier("fos","fosCS", "fossSchema", "fossiFIgo"), null)).asJava)
|
||||
r.setTitle(List(OafMapperUtils.structuredProperty(FAKE_TITLE, OafMapperUtils.qualifier("fos","fosCS", "fossSchema", "fossiFIgo"), null)).asJava)
|
||||
r
|
||||
}.map{r =>
|
||||
val mapper = new ObjectMapper()
|
||||
|
||||
mapper.writeValueAsString(r)}.toList
|
||||
|
||||
|
||||
val sc =spark.sparkContext
|
||||
|
||||
println(sc.parallelize(pids).count())
|
||||
|
||||
spark.createDataset(sc.parallelize(pids))(Encoders.STRING).write.mode(SaveMode.Overwrite).option("compression", "gzip").text(s"$workingDir/updates")
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
import spark.implicits._
|
||||
implicit val resEncoder: Encoder[Result] = Encoders.bean(classOf[Result])
|
||||
val ds = spark.read.text(s"$workingDir/updates").as[String].map{s => val mapper = new ObjectMapper()
|
||||
mapper.readValue(s, classOf[Result])}.collect()
|
||||
|
||||
|
||||
|
||||
|
||||
assertEquals(4, ds.length)
|
||||
ds.foreach{r => assertNotNull(r.getSubject)}
|
||||
ds.foreach{r => assertEquals(1,r.getSubject.size())}
|
||||
ds.foreach{r => assertNotNull(r.getTitle)}
|
||||
ds.foreach{r => assertEquals(1,r.getTitle.size())}
|
||||
|
||||
|
||||
|
||||
ds.flatMap(r => r.getTitle.asScala.map(t => t.getValue)).foreach(t => assertEquals(FAKE_TITLE,t))
|
||||
ds.flatMap(r => r.getSubject.asScala.map(t => t.getValue)).foreach(t => assertEquals(FAKE_SUBJECT,t))
|
||||
|
||||
println("generated Updates")
|
||||
}
|
||||
|
||||
|
||||
def populateDatasets(spark:SparkSession):Unit = {
|
||||
import spark.implicits._
|
||||
val entities =SparkResolveEntities.entities
|
||||
|
||||
entities.foreach{
|
||||
e =>
|
||||
val template = Source.fromInputStream(this.getClass.getResourceAsStream(s"$e")).mkString
|
||||
spark.createDataset(spark.sparkContext.parallelize(template.lines.toList)).as[String].write.option("compression", "gzip").text(s"$workingDir/graph/$e")
|
||||
println(s"Created Dataset $e")
|
||||
}
|
||||
SparkResolveRelation.extractPidResolvedTableFromJsonRDD(spark, s"$workingDir/graph", s"$workingDir/work")
|
||||
|
||||
}
|
||||
|
||||
|
||||
@Test
|
||||
def testResolution():Unit = {
|
||||
val spark:SparkSession = sparkSession.get
|
||||
implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
|
||||
SparkResolveEntities.resolveEntities(spark,s"$workingDir/work", s"$workingDir/updates" )
|
||||
|
||||
val ds = spark.read.load(s"$workingDir/work/resolvedEntities").as[Result]
|
||||
|
||||
assertEquals(3, ds.count())
|
||||
|
||||
ds.collect().foreach{
|
||||
r =>
|
||||
assertTrue(r.getId.startsWith("50"))
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
private def structuredPContainsValue(l:java.util.List[StructuredProperty], exptectedValue:String):Boolean = {
|
||||
l.asScala.exists(p =>p.getValue!= null && p.getValue.equalsIgnoreCase(exptectedValue))
|
||||
}
|
||||
|
||||
@Test
|
||||
def testUpdate():Unit = {
|
||||
val spark:SparkSession = sparkSession.get
|
||||
import spark.implicits._
|
||||
implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
|
||||
val m = new ObjectMapper()
|
||||
SparkResolveEntities.resolveEntities(spark,s"$workingDir/work", s"$workingDir/updates" )
|
||||
SparkResolveEntities.generateResolvedEntities(spark,s"$workingDir/work",s"$workingDir/graph" )
|
||||
|
||||
|
||||
|
||||
|
||||
val pubDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/publication").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.publication))
|
||||
val t = pubDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
|
||||
|
||||
|
||||
|
||||
val datDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/dataset").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.dataset))
|
||||
val td = datDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
|
||||
|
||||
|
||||
val softDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/software").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.software))
|
||||
val ts = softDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
|
||||
|
||||
|
||||
val orpDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/otherresearchproduct").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.otherresearchproduct))
|
||||
val to = orpDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
|
||||
|
||||
|
||||
assertEquals(0, t)
|
||||
assertEquals(2, td)
|
||||
assertEquals(1, ts)
|
||||
assertEquals(0, to)
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
|
|
@ -0,0 +1,4 @@
|
|||
unresolved::10.17026/dans-x3z-fsq5::doi
|
||||
unresolved::10.17026/dans-xsw-qtnx::doi
|
||||
unresolved::10.5281/zenodo.1473694::doi
|
||||
unresolved::10.17632/fake::doi
|
||||
4
pom.xml
4
pom.xml
|
|
@ -550,7 +550,7 @@
|
|||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-site-plugin</artifactId>
|
||||
<version>3.7.1</version>
|
||||
<version>3.9.1</version>
|
||||
</plugin>
|
||||
|
||||
<plugin>
|
||||
|
|
@ -753,7 +753,7 @@
|
|||
<mockito-core.version>3.3.3</mockito-core.version>
|
||||
<mongodb.driver.version>3.4.2</mongodb.driver.version>
|
||||
<vtd.version>[2.12,3.0)</vtd.version>
|
||||
<dhp-schemas.version>[2.8.21]</dhp-schemas.version>
|
||||
<dhp-schemas.version>[2.8.22]</dhp-schemas.version>
|
||||
<dnet-actionmanager-api.version>[4.0.3]</dnet-actionmanager-api.version>
|
||||
<dnet-actionmanager-common.version>[6.0.5]</dnet-actionmanager-common.version>
|
||||
<dnet-openaire-broker-common.version>[3.1.6]</dnet-openaire-broker-common.version>
|
||||
|
|
|
|||
Loading…
Reference in New Issue