forked from antonis.lempesis/dnet-hadoop
WIP: trying to find a way to build the records for the index
This commit is contained in:
parent
7ba586d2e5
commit
97c239ee0d
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@ -26,6 +26,11 @@
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<artifactId>commons-lang3</artifactId>
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</dependency>
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<dependency>
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<groupId>com.fasterxml.jackson.core</groupId>
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<artifactId>jackson-databind</artifactId>
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</dependency>
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<dependency>
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<groupId>eu.dnetlib.dhp</groupId>
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<artifactId>dhp-common</artifactId>
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@ -1,5 +1,8 @@
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package eu.dnetlib.dhp.schema.oaf;
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import com.fasterxml.jackson.core.JsonProcessingException;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import java.io.Serializable;
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public abstract class Oaf implements Serializable {
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@ -23,4 +26,14 @@ public abstract class Oaf implements Serializable {
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public void setLastupdatetimestamp(Long lastupdatetimestamp) {
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this.lastupdatetimestamp = lastupdatetimestamp;
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}
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@Override
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public String toString() {
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try {
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return new ObjectMapper().writeValueAsString(this);
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} catch (JsonProcessingException e) {
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throw new RuntimeException(e);
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}
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}
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}
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@ -1,3 +1,5 @@
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sparkDriverMemory=16G
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sparkExecutorMemory=16G
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sparkDriverMemory=7G
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sparkExecutorMemory=7G
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sparkExecutorMemoryOverhead=5G
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hive_db_name=claudio
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sourcePath=/tmp/db_openaireplus_services_beta.export.2019.11.06
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@ -0,0 +1,53 @@
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package eu.dnetlib.dhp.graph;
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import com.fasterxml.jackson.core.JsonProcessingException;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.schema.oaf.Relation;
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import java.io.Serializable;
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public class EntityRelEntity implements Serializable {
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private TypedRow source;
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private Relation relation;
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private TypedRow target;
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public EntityRelEntity(TypedRow source) {
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this.source = source;
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}
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public TypedRow getSource() {
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return source;
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}
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public EntityRelEntity setSource(TypedRow source) {
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this.source = source;
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return this;
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}
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public Relation getRelation() {
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return relation;
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}
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public EntityRelEntity setRelation(Relation relation) {
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this.relation = relation;
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return this;
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}
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public TypedRow getTarget() {
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return target;
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}
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public EntityRelEntity setTarget(TypedRow target) {
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this.target = target;
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return this;
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}
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@Override
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public String toString() {
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try {
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return new ObjectMapper().writeValueAsString(this);
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} catch (JsonProcessingException e) {
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throw new RuntimeException(e);
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}
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}
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}
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@ -0,0 +1,139 @@
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package eu.dnetlib.dhp.graph;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.schema.oaf.*;
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import org.apache.hadoop.io.Text;
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import org.apache.spark.api.java.JavaPairRDD;
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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.Optional;
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import org.apache.spark.api.java.function.PairFunction;
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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 scala.Tuple2;
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import java.io.Serializable;
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public class GraphJoiner implements Serializable {
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public static final int MAX_RELS = 100;
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public void join(final SparkSession spark, final String inputPath, final String hiveDbName, final String outPath) {
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final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
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/*
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JavaPairRDD<String, TypedRow> entities = sc.sequenceFile(inputPath + "/publication", Text.class, Text.class)
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.map(item -> new ObjectMapper().readValue(item._2().toString(), Publication.class))
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.map(oaf -> new TypedRow("publication", oaf))
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.mapToPair(toPair());
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*/
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JavaPairRDD<String, TypedRow> entities = sc.sequenceFile(inputPath + "/datasource", Text.class, Text.class)
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.map(item -> new ObjectMapper().readValue(item._2().toString(), Datasource.class))
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.map(oaf -> new TypedRow("datasource", oaf))
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.mapToPair(toPair())
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.union(sc.sequenceFile(inputPath + "/organization", Text.class, Text.class)
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.map(item -> new ObjectMapper().readValue(item._2().toString(), Organization.class))
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.map(oaf -> new TypedRow("organization", oaf))
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.mapToPair(toPair()))
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.union(sc.sequenceFile(inputPath + "/project", Text.class, Text.class)
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.map(item -> new ObjectMapper().readValue(item._2().toString(), Project.class))
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.map(oaf -> new TypedRow("project", oaf))
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.mapToPair(toPair()))
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.union(sc.sequenceFile(inputPath + "/dataset", Text.class, Text.class)
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.map(item -> new ObjectMapper().readValue(item._2().toString(), Dataset.class))
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.map(oaf -> new TypedRow("dataset", oaf))
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.mapToPair(toPair()))
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.union(sc.sequenceFile(inputPath + "/otherresearchproduct", Text.class, Text.class)
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.map(item -> new ObjectMapper().readValue(item._2().toString(), OtherResearchProduct.class))
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.map(oaf -> new TypedRow("otherresearchproduct", oaf))
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.mapToPair(toPair()))
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.union(sc.sequenceFile(inputPath + "/software", Text.class, Text.class)
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.map(item -> new ObjectMapper().readValue(item._2().toString(), Software.class))
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.map(oaf -> new TypedRow("software", oaf))
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.mapToPair(toPair()));
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/*
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.union(sc.sequenceFile(inputPath + "/publication", Text.class, Text.class)
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.map(item -> new ObjectMapper().readValue(item._2().toString(), Publication.class))
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.map(oaf -> new TypedRow("publication", oaf))
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.mapToPair(toPair()));
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*/
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/*
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JavaRDD<Relation> rels = sc.sequenceFile(inputPath + "/relation", Text.class, Text.class)
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.map(item -> new ObjectMapper().readValue(item._2().toString(), Relation.class))
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.map(oaf -> new TypedRow("relation", oaf))
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.mapToPair(toPair())
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.groupByKey()
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.map(t -> Iterables.limit(t._2(), MAX_RELS))
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.flatMap(t -> t.iterator())
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.map(t -> (Relation) t.getOaf());
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spark.createDataset(rels.rdd(), Encoders.bean(Relation.class))
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.write()
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.mode(SaveMode.Overwrite)
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.saveAsTable(hiveDbName + ".relation_100");
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*/
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JavaPairRDD<String, TypedRow> bounded_rels = spark.table(hiveDbName + ".relation_" + MAX_RELS)
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.as(Encoders.bean(Relation.class))
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.javaRDD()
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.map(r -> new TypedRow("relation", r))
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.mapToPair(toPair());
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// build the adjacency list: e -> r
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JavaPairRDD<String, Tuple2<TypedRow, Optional<TypedRow>>> adjacency_list = entities.leftOuterJoin(bounded_rels);
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JavaRDD<EntityRelEntity> linked_entities = adjacency_list
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.mapToPair(toPairTarget()) // make rel.targetid explicit so that we can join it
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.leftOuterJoin(entities) // again with the entities to get the target entity
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.map(l -> toEntityRelEntity(l)); // and map it to a more readable representation
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spark.createDataFrame(linked_entities, EntityRelEntity.class)
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.write()
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.mode(SaveMode.Overwrite)
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.saveAsTable(hiveDbName + ".linked_entities");
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}
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private EntityRelEntity toEntityRelEntity(Tuple2<String, Tuple2<Tuple2<String, Tuple2<TypedRow, Optional<TypedRow>>>, Optional<TypedRow>>> l) {
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// extract the entity source
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final EntityRelEntity res = new EntityRelEntity(l._2()._1()._2()._1());
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if(l._2()._1()._2()._2().isPresent() && l._2()._2().isPresent()) {
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// extract the relationship
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res.setRelation((Relation) l._2()._1()._2()._2().get().getOaf());
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// extract the related entity
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res.setTarget(l._2()._2().get());
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}
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return res;
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}
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private PairFunction<Tuple2<String, Tuple2<TypedRow, Optional<TypedRow>>>, String, Tuple2<String, Tuple2<TypedRow, Optional<TypedRow>>>> toPairTarget() {
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return e -> {
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Optional<TypedRow> o = e._2()._2();
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if (o.isPresent()) {
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return new Tuple2<>(((Relation) o.get().getOaf()).getTarget(), e);
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} else {
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return new Tuple2<>(null, e);
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}
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};
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}
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private PairFunction<TypedRow, String, TypedRow> toPair() {
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return e -> {
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if (!"relation".equals(e.getType())) {
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return new Tuple2<>( ((OafEntity) e.getOaf()).getId(), e);
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} else {
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return new Tuple2<>( ((Relation) e.getOaf()).getSource(), e);
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}
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};
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}
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}
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@ -1,32 +1,14 @@
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package eu.dnetlib.dhp.graph;
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import com.google.common.collect.Sets;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.schema.common.EntityPayload;
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import org.apache.commons.io.IOUtils;
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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.apache.hadoop.io.compress.GzipCodec;
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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.Row;
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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 scala.Tuple2;
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import scala.runtime.AbstractFunction1;
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import java.util.List;
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import java.util.Set;
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import java.util.stream.Collectors;
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import static org.apache.commons.lang3.StringUtils.substringAfter;
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import static org.apache.commons.lang3.StringUtils.substringBefore;
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import static org.apache.spark.sql.Encoders.bean;
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public class SparkGraphIndexingJob {
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private final static String ENTITY_NODES_PATH = "/tmp/entity_node";
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private static final long LIMIT = 100;
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public static void main(String[] args) throws Exception {
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@ -37,13 +19,10 @@ public class SparkGraphIndexingJob {
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.appName(SparkGraphIndexingJob.class.getSimpleName())
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.master(parser.get("master"))
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.config("hive.metastore.uris", parser.get("hive_metastore_uris"))
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.config("spark.driver.cores", 1)
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.config("spark.executor.cores", 1)
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.config("spark.yarn.executor.memoryOverhead", "4G")
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.config("spark.yarn.driver.memoryOverhead", "4G")
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.enableHiveSupport()
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.getOrCreate();
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final String inputPath = parser.get("sourcePath");
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final String hiveDbName = parser.get("hive_db_name");
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final FileSystem fs = FileSystem.get(spark.sparkContext().hadoopConfiguration());
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@ -51,52 +30,7 @@ public class SparkGraphIndexingJob {
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fs.delete(new Path(ENTITY_NODES_PATH), true);
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}
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spark
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.sql(getJoinEntitiesSQL(hiveDbName))
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.transform(toEntityNode())
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/*
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.map((MapFunction<EntityNode, String>) r -> {
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return null;
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}, bean(String.class))
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*/
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.rdd()
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.saveAsTextFile(ENTITY_NODES_PATH, GzipCodec.class);
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}
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private static AbstractFunction1<Dataset<Row>, Dataset<EntityNode>> toEntityNode() {
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return new AbstractFunction1<Dataset<Row>, Dataset<EntityNode>>() {
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@Override
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public Dataset<EntityNode> apply(Dataset<Row> d) {
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return d.map((MapFunction<Row, EntityNode>) r -> {
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final List<String> res = r.getList(r.fieldIndex("related_entity"));
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final byte[] payload = r.getAs("payload");
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return new EntityNode(r.getAs("id"), r.getAs("type"), new String(payload))
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.setRelatedEntities(res
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.stream()
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.map(re -> new Tuple2<>(substringBefore(re, "@@"), substringAfter(re, "@@")))
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.map(re -> new RelatedEntity(r.getAs("reltype"), r.getAs("subreltype"), r.getAs("relclass"), re._1(), re._2()))
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.limit(LIMIT)
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.collect(Collectors.toList()));
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}, bean(EntityNode.class));
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}
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};
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}
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private static String getJoinEntitiesSQL(String hiveDbName) {
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return String.format(
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"SELECT " +
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"E_s.id AS id, " +
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"E_s.type AS type, " +
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"E_s.payload AS payload, " +
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"r.reltype AS reltype, r.subreltype AS subreltype, r.relclass AS relclass, " +
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"collect_list(concat(E_t.type, '@@', E_t.payload)) AS related_entity " +
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"FROM %s.entities " + "" /*"TABLESAMPLE(0.1 PERCENT) "*/ + "E_s " +
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"LEFT JOIN %s.relation r ON (r.source = E_s.id) " +
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"JOIN %s.entities E_t ON (E_t.id = r.target) \n" +
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"GROUP BY E_s.id, E_s.type, E_s.payload, r.reltype, r.subreltype, r.relclass", hiveDbName, hiveDbName, hiveDbName);
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new GraphJoiner().join(spark, inputPath, hiveDbName, ENTITY_NODES_PATH);
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}
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}
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@ -0,0 +1,44 @@
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package eu.dnetlib.dhp.graph;
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import com.fasterxml.jackson.core.JsonProcessingException;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.schema.oaf.Oaf;
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import java.io.Serializable;
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public class TypedRow implements Serializable {
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private String type;
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private Oaf oaf;
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public TypedRow(String type, Oaf oaf) {
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this.type = type;
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this.oaf = oaf;
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}
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public String getType() {
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return type;
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}
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public TypedRow setType(String type) {
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this.type = type;
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return this;
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}
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public Oaf getOaf() {
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return oaf;
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}
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public TypedRow setOaf(Oaf oaf) {
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this.oaf = oaf;
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return this;
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}
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@Override
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public String toString() {
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try {
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return new ObjectMapper().writeValueAsString(this);
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} catch (JsonProcessingException e) {
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throw new RuntimeException(e);
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}
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}
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}
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@ -1,5 +1,6 @@
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[
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{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
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{"paramName":"h", "paramLongName":"hive_metastore_uris","paramDescription": "the hive metastore uris", "paramRequired": true},
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{"paramName":"db", "paramLongName":"hive_db_name", "paramDescription": "the target hive database name", "paramRequired": true}
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{"paramName":"db", "paramLongName":"hive_db_name", "paramDescription": "the target hive database name", "paramRequired": true},
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{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the path of the sequencial file to read", "paramRequired": true}
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]
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@ -33,8 +33,9 @@
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<name>GraphIndexing</name>
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<class>eu.dnetlib.dhp.graph.SparkGraphIndexingJob</class>
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<jar>dhp-graph-provision-${projectVersion}.jar</jar>
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<spark-opts>--executor-memory ${sparkExecutorMemory} --executor-cores ${sparkExecutorCores} --driver-memory=${sparkDriverMemory} --conf spark.extraListeners="com.cloudera.spark.lineage.NavigatorAppListener" --conf spark.sql.queryExecutionListeners="com.cloudera.spark.lineage.NavigatorQueryListener" --conf spark.sql.warehouse.dir="/user/hive/warehouse"</spark-opts>
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<spark-opts>--executor-memory ${sparkExecutorMemory} --executor-cores ${sparkExecutorCores} --driver-memory=${sparkDriverMemory} --conf spark.extraListeners="com.cloudera.spark.lineage.NavigatorAppListener" --conf spark.sql.queryExecutionListeners="com.cloudera.spark.lineage.NavigatorQueryListener" --conf spark.sql.warehouse.dir="/user/hive/warehouse" --conf spark.yarn.executor.memoryOverhead=${sparkExecutorMemoryOverhead}</spark-opts>
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<arg>-mt</arg> <arg>yarn-cluster</arg>
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<arg>--sourcePath</arg><arg>${sourcePath}</arg>
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<arg>--hive_db_name</arg><arg>${hive_db_name}</arg>
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<arg>--hive_metastore_uris</arg><arg>${hive_metastore_uris}</arg>
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</spark>
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