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Merge pull request 'Rewrite SparkPropagateRelation exploiting Dataframe API' (#330) from propagate_relation_rewrite into beta 

Reviewed-on: D-Net/dnet-hadoop#330
This commit is contained in:
Claudio Atzori 2023-08-29 10:47:14 +02:00
parent f437be80ad 58665a246c
commit 0515d81c7c
1 changed files with 113 additions and 175 deletions
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202
dhp-workflows/dhp-dedup-openaire/src/main/java/eu/dnetlib/dhp/oa/dedup/SparkPropagateRelation.java
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@ -1,19 +1,6 @@
package eu.dnetlib.dhp.oa.dedup; package eu.dnetlib.dhp.oa.dedup;
import static org.apache.spark.sql.functions.col;
import java.util.Objects;
import org.apache.commons.io.IOUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FilterFunction;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.sql.*;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import eu.dnetlib.dhp.application.ArgumentApplicationParser; import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.schema.common.ModelConstants; import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.common.ModelSupport; import eu.dnetlib.dhp.schema.common.ModelSupport;
@ -21,16 +8,33 @@ import eu.dnetlib.dhp.schema.oaf.DataInfo;
import eu.dnetlib.dhp.schema.oaf.Relation; import eu.dnetlib.dhp.schema.oaf.Relation;
import eu.dnetlib.dhp.utils.ISLookupClientFactory; import eu.dnetlib.dhp.utils.ISLookupClientFactory;
import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService; import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
import org.apache.commons.beanutils.BeanUtils;
import org.apache.commons.io.IOUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FilterFunction;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.api.java.function.ReduceFunction;
import org.apache.spark.sql.*;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import scala.Tuple2; import scala.Tuple2;
import scala.Tuple3; import scala.Tuple3;
import java.util.Arrays;
import java.util.Collections;
import java.util.Iterator;
import java.util.Objects;
import static org.apache.spark.sql.functions.col;
public class SparkPropagateRelation extends AbstractSparkAction { public class SparkPropagateRelation extends AbstractSparkAction {
private static final Logger log = LoggerFactory.getLogger(SparkPropagateRelation.class); private static final Logger log = LoggerFactory.getLogger(SparkPropagateRelation.class);
enum FieldType { private static Encoder<Relation> REL_BEAN_ENC = Encoders.bean(Relation.class);
SOURCE, TARGET
} private static Encoder<Relation> REL_KRYO_ENC = Encoders.kryo(Relation.class);
public SparkPropagateRelation(ArgumentApplicationParser parser, SparkSession spark) { public SparkPropagateRelation(ArgumentApplicationParser parser, SparkSession spark) {
super(parser, spark); super(parser, spark);
@ -71,38 +75,60 @@ public class SparkPropagateRelation extends AbstractSparkAction {
Dataset<Relation> mergeRels = spark Dataset<Relation> mergeRels = spark
.read() .read()
.load(DedupUtility.createMergeRelPath(workingPath, "*", "*")) .load(DedupUtility.createMergeRelPath(workingPath, "*", "*"))
.as(Encoders.bean(Relation.class)); .as(REL_BEAN_ENC);
// <mergedObjectID, dedupID> // <mergedObjectID, dedupID>
Dataset<Tuple2<String, String>> mergedIds = mergeRels Dataset<Row> mergedIds = mergeRels
.where(col("relClass").equalTo(ModelConstants.MERGES)) .where(col("relClass").equalTo(ModelConstants.MERGES))
.select(col("source"), col("target")) .select(col("source").as("dedupID"), col("target").as("mergedObjectID"))
.distinct() .distinct()
.map(
(MapFunction<Row, Tuple2<String, String>>) r -> new Tuple2<>(r.getString(1), r.getString(0)),
Encoders.tuple(Encoders.STRING(), Encoders.STRING()))
.cache(); .cache();
final String relationPath = DedupUtility.createEntityPath(graphBasePath, "relation"); Dataset<Row> allRels = spark.read()
.schema(REL_BEAN_ENC.schema())
.json(DedupUtility.createEntityPath(graphBasePath, "relation"));
Dataset<Relation> rels = spark.read().textFile(relationPath).map(patchRelFn(), Encoders.bean(Relation.class)); Dataset<Relation> dedupedRels = allRels
.joinWith(mergedIds, allRels.col("source").equalTo(mergedIds.col("mergedObjectID")), "left_outer")
.joinWith(mergedIds, col("_1.target").equalTo(mergedIds.col("mergedObjectID")), "left_outer")
.select("_1._1", "_1._2.dedupID", "_2.dedupID")
.as(Encoders.tuple(REL_BEAN_ENC, Encoders.STRING(), Encoders.STRING()))
.flatMap(SparkPropagateRelation::addInferredRelations, REL_KRYO_ENC);
Dataset<Relation> newRels = createNewRels(rels, mergedIds, getFixRelFn()); Dataset<Relation> processedRelations = distinctRelations(dedupedRels.union(mergeRels.map((MapFunction<Relation, Relation>) r -> r, REL_KRYO_ENC)))
.filter((FilterFunction<Relation>) r -> !Objects.equals(r.getSource(), r.getTarget()));
Dataset<Relation> updated = processDataset( save(processedRelations, outputRelationPath, SaveMode.Overwrite);
processDataset(rels, mergedIds, FieldType.SOURCE, getDeletedFn()), }
mergedIds,
FieldType.TARGET,
getDeletedFn());
save( private static Iterator<Relation> addInferredRelations(Tuple3<Relation, String, String> t) throws Exception {
distinctRelations( Relation existingRel = t._1();
newRels String newSource = t._2();
.union(updated) String newTarget = t._3();
.union(mergeRels)
.map((MapFunction<Relation, Relation>) r -> r, Encoders.kryo(Relation.class))) if (newSource == null && newTarget == null) {
.filter((FilterFunction<Relation>) r -> !Objects.equals(r.getSource(), r.getTarget())), return Collections.singleton(t._1()).iterator();
outputRelationPath, SaveMode.Overwrite); }
// update existing relation
if (existingRel.getDataInfo() == null) {
existingRel.setDataInfo(new DataInfo());
}
existingRel.getDataInfo().setDeletedbyinference(true);
// Create new relation inferred by dedupIDs
Relation inferredRel = (Relation) BeanUtils.cloneBean(existingRel);
inferredRel.setDataInfo((DataInfo) BeanUtils.cloneBean(existingRel.getDataInfo()));
inferredRel.getDataInfo().setDeletedbyinference(false);
if (newSource != null)
inferredRel.setSource(newSource);
if (newTarget != null)
inferredRel.setTarget(newTarget);
return Arrays.asList(existingRel, inferredRel).iterator();
} }
private Dataset<Relation> distinctRelations(Dataset<Relation> rels) { private Dataset<Relation> distinctRelations(Dataset<Relation> rels) {
@ -110,54 +136,14 @@ public class SparkPropagateRelation extends AbstractSparkAction {
.filter(getRelationFilterFunction()) .filter(getRelationFilterFunction())
.groupByKey( .groupByKey(
(MapFunction<Relation, String>) r -> String (MapFunction<Relation, String>) r -> String
.join(r.getSource(), r.getTarget(), r.getRelType(), r.getSubRelType(), r.getRelClass()), .join(" ", r.getSource(), r.getTarget(), r.getRelType(), r.getSubRelType(), r.getRelClass()),
Encoders.STRING()) Encoders.STRING())
.agg(new RelationAggregator().toColumn()) .reduceGroups((ReduceFunction<Relation>) (b, a) -> {
.map((MapFunction<Tuple2<String, Relation>, Relation>) Tuple2::_2, Encoders.bean(Relation.class)); b.mergeFrom(a);
return b;
} }
)
// redirect the relations to the dedupID .map((MapFunction<Tuple2<String, Relation>, Relation>) Tuple2::_2, REL_BEAN_ENC);
private static Dataset<Relation> createNewRels(
Dataset<Relation> rels, // all the relations to be redirected
Dataset<Tuple2<String, String>> mergedIds, // merge rels: <mergedObjectID, dedupID>
MapFunction<Tuple2<Tuple2<Tuple3<String, Relation, String>, Tuple2<String, String>>, Tuple2<String, String>>, Relation> mapRel) {
// <sourceID, relation, targetID>
Dataset<Tuple3<String, Relation, String>> mapped = rels
.map(
(MapFunction<Relation, Tuple3<String, Relation, String>>) r -> new Tuple3<>(getId(r, FieldType.SOURCE),
r, getId(r, FieldType.TARGET)),
Encoders.tuple(Encoders.STRING(), Encoders.kryo(Relation.class), Encoders.STRING()));
// < <sourceID, relation, target>, <sourceID, dedupID> >
Dataset<Tuple2<Tuple3<String, Relation, String>, Tuple2<String, String>>> relSource = mapped
.joinWith(mergedIds, mapped.col("_1").equalTo(mergedIds.col("_1")), "left_outer");
// < <<sourceID, relation, targetID>, <sourceID, dedupID>>, <targetID, dedupID> >
Dataset<Tuple2<Tuple2<Tuple3<String, Relation, String>, Tuple2<String, String>>, Tuple2<String, String>>> relSourceTarget = relSource
.joinWith(mergedIds, relSource.col("_1._3").equalTo(mergedIds.col("_1")), "left_outer");
return relSourceTarget
.filter(
(FilterFunction<Tuple2<Tuple2<Tuple3<String, Relation, String>, Tuple2<String, String>>, Tuple2<String, String>>>) r -> r
._1()
._1() != null || r._2() != null)
.map(mapRel, Encoders.bean(Relation.class))
.distinct();
}
private static Dataset<Relation> processDataset(
Dataset<Relation> rels,
Dataset<Tuple2<String, String>> mergedIds,
FieldType type,
MapFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, String>>, Relation> mapFn) {
final Dataset<Tuple2<String, Relation>> mapped = rels
.map(
(MapFunction<Relation, Tuple2<String, Relation>>) r -> new Tuple2<>(getId(r, type), r),
Encoders.tuple(Encoders.STRING(), Encoders.kryo(Relation.class)));
return mapped
.joinWith(mergedIds, mapped.col("_1").equalTo(mergedIds.col("_1")), "left_outer")
.map(mapFn, Encoders.bean(Relation.class));
} }
private FilterFunction<Relation> getRelationFilterFunction() { private FilterFunction<Relation> getRelationFilterFunction() {
@ -167,52 +153,4 @@ public class SparkPropagateRelation extends AbstractSparkAction {
StringUtils.isNotBlank(r.getSubRelType()) || StringUtils.isNotBlank(r.getSubRelType()) ||
StringUtils.isNotBlank(r.getRelClass()); StringUtils.isNotBlank(r.getRelClass());
} }
private static String getId(Relation r, FieldType type) {
switch (type) {
case SOURCE:
return r.getSource();
case TARGET:
return r.getTarget();
default:
throw new IllegalArgumentException("");
}
}
private static MapFunction<Tuple2<Tuple2<Tuple3<String, Relation, String>, Tuple2<String, String>>, Tuple2<String, String>>, Relation> getFixRelFn() {
return value -> {
Relation r = value._1()._1()._2();
String newSource = value._1()._2() != null ? value._1()._2()._2() : null;
String newTarget = value._2() != null ? value._2()._2() : null;
if (r.getDataInfo() == null) {
r.setDataInfo(new DataInfo());
}
r.getDataInfo().setDeletedbyinference(false);
if (newSource != null)
r.setSource(newSource);
if (newTarget != null)
r.setTarget(newTarget);
return r;
};
}
private static MapFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, String>>, Relation> getDeletedFn() {
return value -> {
if (value._2() != null) {
Relation r = value._1()._2();
if (r.getDataInfo() == null) {
r.setDataInfo(new DataInfo());
}
r.getDataInfo().setDeletedbyinference(true);
return r;
}
return value._1()._2();
};
}
} }