dnet-hadoop/dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/projecttoresult/SparkResultToProjectThrough...

135 lines
4.0 KiB
Java

package eu.dnetlib.dhp.projecttoresult;
import static eu.dnetlib.dhp.PropagationConstant.*;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import java.util.ArrayList;
import java.util.List;
import java.util.Optional;
import org.apache.commons.io.IOUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FlatMapFunction;
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.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.oaf.Relation;
import scala.Tuple2;
public class SparkResultToProjectThroughSemRelJob {
private static final Logger log = LoggerFactory.getLogger(SparkResultToProjectThroughSemRelJob.class);
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
.toString(
SparkResultToProjectThroughSemRelJob.class
.getResourceAsStream(
"/eu/dnetlib/dhp/projecttoresult/input_projecttoresult_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
final String outputPath = parser.get("outputPath");
log.info("outputPath {}: ", outputPath);
final String potentialUpdatePath = parser.get("potentialUpdatePath");
log.info("potentialUpdatePath {}: ", potentialUpdatePath);
final String alreadyLinkedPath = parser.get("alreadyLinkedPath");
log.info("alreadyLinkedPath {}: ", alreadyLinkedPath);
SparkConf conf = new SparkConf();
runWithSparkSession(
conf,
isSparkSessionManaged,
spark -> {
execPropagation(
spark, outputPath, alreadyLinkedPath, potentialUpdatePath);
});
}
private static void execPropagation(
SparkSession spark,
String outputPath,
String alreadyLinkedPath,
String potentialUpdatePath) {
Dataset<ResultProjectSet> toaddrelations = readPath(spark, potentialUpdatePath, ResultProjectSet.class);
Dataset<ResultProjectSet> alreadyLinked = readPath(spark, alreadyLinkedPath, ResultProjectSet.class);
toaddrelations
.joinWith(
alreadyLinked,
toaddrelations.col("resultId").equalTo(alreadyLinked.col("resultId")),
"left_outer")
.flatMap(mapRelationRn(), Encoders.bean(Relation.class))
.write()
.mode(SaveMode.Append)
.option("compression", "gzip")
.json(outputPath);
}
private static FlatMapFunction<Tuple2<ResultProjectSet, ResultProjectSet>, Relation> mapRelationRn() {
return value -> {
List<Relation> newRelations = new ArrayList<>();
ResultProjectSet potentialUpdate = value._1();
Optional<ResultProjectSet> alreadyLinked = Optional.ofNullable(value._2());
alreadyLinked
.ifPresent(
resultProjectSet -> resultProjectSet
.getProjectSet()
.forEach(
(p -> potentialUpdate.getProjectSet().remove(p))));
String resId = potentialUpdate.getResultId();
potentialUpdate
.getProjectSet()
.forEach(
projectId -> {
newRelations
.add(
getRelation(
resId,
projectId,
ModelConstants.IS_PRODUCED_BY,
ModelConstants.RESULT_PROJECT,
ModelConstants.OUTCOME,
PROPAGATION_DATA_INFO_TYPE,
PROPAGATION_RELATION_RESULT_PROJECT_SEM_REL_CLASS_ID,
PROPAGATION_RELATION_RESULT_PROJECT_SEM_REL_CLASS_NAME));
newRelations
.add(
getRelation(
projectId,
resId,
ModelConstants.PRODUCES,
ModelConstants.RESULT_PROJECT,
ModelConstants.OUTCOME,
PROPAGATION_DATA_INFO_TYPE,
PROPAGATION_RELATION_RESULT_PROJECT_SEM_REL_CLASS_ID,
PROPAGATION_RELATION_RESULT_PROJECT_SEM_REL_CLASS_NAME));
});
return newRelations.iterator();
};
}
}