forked from D-Net/dnet-hadoop
trying to avoid OOM in SparkPropagateRelation
This commit is contained in:
parent
069ef5eaed
commit
011b342bc9
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@ -2,6 +2,7 @@ package eu.dnetlib.dhp.oa.dedup;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.schema.oaf.*;
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import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpException;
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import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
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import eu.dnetlib.pace.config.DedupConfig;
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@ -70,6 +71,36 @@ abstract class AbstractSparkAction implements Serializable {
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protected static SparkSession getSparkSession(ArgumentApplicationParser parser) {
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SparkConf conf = new SparkConf();
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conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
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conf.registerKryoClasses(new Class[] {
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Author.class,
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Context.class,
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Country.class,
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DataInfo.class,
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Dataset.class,
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Datasource.class,
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ExternalReference.class,
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ExtraInfo.class,
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Field.class,
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GeoLocation.class,
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Instance.class,
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Journal.class,
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KeyValue.class,
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Oaf.class,
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OafEntity.class,
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OAIProvenance.class,
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Organization.class,
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OriginDescription.class,
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OtherResearchProduct.class,
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Project.class,
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Publication.class,
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Qualifier.class,
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Relation.class,
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Result.class,
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Software.class,
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StructuredProperty.class
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});
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return SparkSession
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.builder()
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.appName(SparkCreateSimRels.class.getSimpleName())
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@ -4,61 +4,50 @@ import com.fasterxml.jackson.databind.DeserializationFeature;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.schema.oaf.DataInfo;
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import eu.dnetlib.dhp.schema.oaf.Oaf;
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import eu.dnetlib.dhp.schema.oaf.Relation;
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import eu.dnetlib.dhp.utils.ISLookupClientFactory;
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import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
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import eu.dnetlib.pace.util.MapDocumentUtil;
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import org.apache.commons.io.IOUtils;
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import org.apache.commons.logging.Log;
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import org.apache.commons.logging.LogFactory;
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import org.apache.hadoop.fs.FileStatus;
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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.SparkConf;
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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.Function;
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import org.apache.spark.api.java.function.PairFunction;
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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.Row;
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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 scala.Tuple2;
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import java.io.IOException;
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import static org.apache.spark.sql.functions.col;
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public class SparkPropagateRelation extends AbstractSparkAction {
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private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper()
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.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);;
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private static final Logger log = LoggerFactory.getLogger(SparkPropagateRelation.class);
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public static final int NUM_PARTITIONS = 3000;
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private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper()
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.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
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enum FieldType {
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SOURCE,
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TARGET
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}
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final static String SOURCEJSONPATH = "$.source";
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final static String TARGETJSONPATH = "$.target";
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private static final Log log = LogFactory.getLog(SparkPropagateRelation.class);
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public SparkPropagateRelation(ArgumentApplicationParser parser, SparkSession spark) throws Exception {
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super(parser, spark);
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}
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public static void main(String[] args) throws Exception {
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ArgumentApplicationParser parser = new ArgumentApplicationParser(
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IOUtils.toString(
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SparkCreateSimRels.class.getResourceAsStream("/eu/dnetlib/dhp/oa/dedup/propagateRelation_parameters.json")));
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IOUtils.toString(SparkCreateSimRels.class.getResourceAsStream(
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"/eu/dnetlib/dhp/oa/dedup/propagateRelation_parameters.json")));
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parser.parseArgument(args);
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new SparkPropagateRelation(parser, getSparkSession(parser)).run(ISLookupClientFactory.getLookUpService(parser.get("isLookUpUrl")));
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new SparkPropagateRelation(parser, getSparkSession(parser))
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.run(ISLookupClientFactory.getLookUpService(parser.get("isLookUpUrl")));
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}
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@Override
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@ -68,96 +57,114 @@ public class SparkPropagateRelation extends AbstractSparkAction {
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final String workingPath = parser.get("workingPath");
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final String dedupGraphPath = parser.get("dedupGraphPath");
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System.out.println(String.format("graphBasePath: '%s'", graphBasePath));
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System.out.println(String.format("workingPath: '%s'", workingPath));
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System.out.println(String.format("dedupGraphPath:'%s'", dedupGraphPath));
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log.info("graphBasePath: '{}'", graphBasePath);
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log.info("workingPath: '{}'", workingPath);
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log.info("dedupGraphPath: '{}'", dedupGraphPath);
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final String relationsPath = DedupUtility.createEntityPath(dedupGraphPath, "relation");
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final String newRelsPath = DedupUtility.createEntityPath(workingPath, "newRels");
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final String fixedSourceId = DedupUtility.createEntityPath(workingPath, "fixedSourceId");
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final String deletedSourceId = DedupUtility.createEntityPath(workingPath, "deletedSourceId");
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final String outputRelationPath = DedupUtility.createEntityPath(dedupGraphPath, "relation");
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deletePath(outputRelationPath);
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final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
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Dataset<Relation> mergeRels = spark.read()
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.load(DedupUtility.createMergeRelPath(workingPath, "*", "*"))
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.as(Encoders.bean(Relation.class));
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deletePath(relationsPath);
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deletePath(newRelsPath);
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deletePath(fixedSourceId);
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deletePath(deletedSourceId);
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final Dataset<Relation> mergeRels = spark.read().load(DedupUtility.createMergeRelPath(workingPath, "*", "*")).as(Encoders.bean(Relation.class));
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final JavaPairRDD<String, String> mergedIds = mergeRels
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.where("relClass == 'merges'")
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.select(mergeRels.col("source"), mergeRels.col("target"))
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Dataset<Tuple2<String, String>> mergedIds = mergeRels
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.where(col("relClass").equalTo("merges"))
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.select(col("source"), col("target"))
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.distinct()
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.toJavaRDD()
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.mapToPair((PairFunction<Row, String, String>) r -> new Tuple2<String, String>(r.getString(1), r.getString(0)));
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.map((MapFunction<Row, Tuple2<String, String>>)
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r -> new Tuple2<>(r.getString(1), r.getString(0)),
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Encoders.tuple(Encoders.STRING(), Encoders.STRING()))
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.cache();
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final String relationPath = DedupUtility.createEntityPath(graphBasePath, "relation");
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Dataset<Relation> rels = spark.read()
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.textFile(relationPath)
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.map(patchRelFn(), Encoders.bean(Relation.class));
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Dataset<Relation> newRels =
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processDataset(
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processDataset(rels, mergedIds, FieldType.SOURCE, getFixRelFn(FieldType.SOURCE)),
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mergedIds, FieldType.TARGET, getFixRelFn(FieldType.TARGET))
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.filter(SparkPropagateRelation::containsDedup);
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Dataset<Relation> updated = processDataset(
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processDataset(rels, mergedIds, FieldType.SOURCE, getDeletedFn()),
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mergedIds, FieldType.TARGET, getDeletedFn());
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save(newRels.union(updated), outputRelationPath);
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sc.textFile(DedupUtility.createEntityPath(graphBasePath, "relation"))
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.repartition(NUM_PARTITIONS)
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.mapToPair(
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(PairFunction<String, String, String>) s ->
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new Tuple2<String, String>(MapDocumentUtil.getJPathString(SOURCEJSONPATH, s), s))
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.leftOuterJoin(mergedIds)
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.map((Function<Tuple2<String, Tuple2<String, Optional<String>>>, String>) v1 -> {
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if (v1._2()._2().isPresent()) {
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return replaceField(v1._2()._1(), v1._2()._2().get(), FieldType.SOURCE);
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}
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return v1._2()._1();
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})
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.saveAsTextFile(fixedSourceId, GzipCodec.class);
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sc.textFile(fixedSourceId)
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.mapToPair(
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(PairFunction<String, String, String>) s ->
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new Tuple2<String, String>(MapDocumentUtil.getJPathString(TARGETJSONPATH, s), s))
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.leftOuterJoin(mergedIds)
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.map((Function<Tuple2<String, Tuple2<String, Optional<String>>>, String>) v1 -> {
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if (v1._2()._2().isPresent()) {
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return replaceField(v1._2()._1(), v1._2()._2().get(), FieldType.TARGET);
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private static Dataset<Relation> processDataset(Dataset<Relation> rels, Dataset<Tuple2<String, String>> mergedIds, FieldType type,
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MapFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, String>>, Relation> mapFn) {
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final Dataset<Tuple2<String, Relation>> mapped = rels
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.map((MapFunction<Relation, Tuple2<String, Relation>>)
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r -> new Tuple2<>(getId(r, type), r),
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Encoders.tuple(Encoders.STRING(), Encoders.kryo(Relation.class)));
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return mapped
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.joinWith(mergedIds, mapped.col("_1").equalTo(mergedIds.col("_1")), "left_outer")
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.map(mapFn, Encoders.bean(Relation.class));
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}
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return v1._2()._1();
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}).filter(SparkPropagateRelation::containsDedup)
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.repartition(NUM_PARTITIONS)
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.saveAsTextFile(newRelsPath, GzipCodec.class);
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//update deleted by inference
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sc.textFile(DedupUtility.createEntityPath(graphBasePath, "relation"))
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.repartition(NUM_PARTITIONS)
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.mapToPair((PairFunction<String, String, String>) s ->
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new Tuple2<String, String>(MapDocumentUtil.getJPathString(SOURCEJSONPATH, s), s))
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.leftOuterJoin(mergedIds)
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.map((Function<Tuple2<String, Tuple2<String, Optional<String>>>, String>) v1 -> {
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if (v1._2()._2().isPresent()) {
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return updateDeletedByInference(v1._2()._1(), Relation.class);
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private static MapFunction<String, Relation> patchRelFn() {
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return value -> {
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final Relation rel = OBJECT_MAPPER.readValue(value, Relation.class);
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if (rel.getDataInfo() == null) {
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rel.setDataInfo(new DataInfo());
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}
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return v1._2()._1();
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})
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.saveAsTextFile(deletedSourceId, GzipCodec.class);
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sc.textFile(deletedSourceId)
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.repartition(NUM_PARTITIONS)
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.mapToPair(
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(PairFunction<String, String, String>) s ->
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new Tuple2<String, String>(MapDocumentUtil.getJPathString(TARGETJSONPATH, s), s))
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.leftOuterJoin(mergedIds)
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.map((Function<Tuple2<String, Tuple2<String, Optional<String>>>, String>) v1 -> {
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if (v1._2()._2().isPresent()) {
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return updateDeletedByInference(v1._2()._1(), Relation.class);
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return rel;
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};
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}
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return v1._2()._1();
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})
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.repartition(NUM_PARTITIONS)
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.saveAsTextFile(DedupUtility.createEntityPath(workingPath, "updated"), GzipCodec.class);
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JavaRDD<String> newRels = sc
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.textFile(newRelsPath);
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private static String getId(Relation r, FieldType type) {
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switch (type) {
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case SOURCE:
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return r.getSource();
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case TARGET:
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return r.getTarget();
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default:
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throw new IllegalArgumentException("");
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}
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}
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sc
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.textFile(DedupUtility.createEntityPath(workingPath, "updated"))
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.union(newRels)
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.repartition(NUM_PARTITIONS)
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.saveAsTextFile(relationsPath, GzipCodec.class);
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private static MapFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, String>>, Relation> getFixRelFn(FieldType type) {
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return value -> {
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if (value._2() != null) {
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Relation r = value._1()._2();
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String id = value._2()._2();
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if (r.getDataInfo() == null) {
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r.setDataInfo(new DataInfo());
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}
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r.getDataInfo().setDeletedbyinference(false);
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switch (type) {
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case SOURCE:
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r.setSource(id);
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return r;
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case TARGET:
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r.setTarget(id);
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return r;
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default:
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throw new IllegalArgumentException("");
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}
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}
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return value._1()._2();
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};
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}
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private static MapFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, String>>, Relation> getDeletedFn() {
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return value -> {
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if (value._2() != null) {
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Relation r = value._1()._2();
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if (r.getDataInfo() == null) {
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r.setDataInfo(new DataInfo());
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}
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r.getDataInfo().setDeletedbyinference(true);
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return r;
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}
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return value._1()._2();
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};
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}
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private void deletePath(String path) {
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@ -173,45 +180,15 @@ public class SparkPropagateRelation extends AbstractSparkAction {
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}
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}
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private static boolean containsDedup(final String json) {
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final String source = MapDocumentUtil.getJPathString(SOURCEJSONPATH, json);
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final String target = MapDocumentUtil.getJPathString(TARGETJSONPATH, json);
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return source.toLowerCase().contains("dedup") || target.toLowerCase().contains("dedup");
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private static void save(Dataset<Relation> dataset, String outPath) {
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dataset
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.write()
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.option("compression", "gzip")
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.json(outPath);
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}
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private static String replaceField(final String json, final String id, final FieldType type) {
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try {
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Relation relation = OBJECT_MAPPER.readValue(json, Relation.class);
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if (relation.getDataInfo() == null) {
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relation.setDataInfo(new DataInfo());
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}
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relation.getDataInfo().setDeletedbyinference(false);
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switch (type) {
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case SOURCE:
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relation.setSource(id);
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return OBJECT_MAPPER.writeValueAsString(relation);
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case TARGET:
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relation.setTarget(id);
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return OBJECT_MAPPER.writeValueAsString(relation);
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default:
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throw new IllegalArgumentException("");
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}
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} catch (IOException e) {
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throw new RuntimeException("unable to deserialize json relation: " + json, e);
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}
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private static boolean containsDedup(final Relation r) {
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return r.getSource().toLowerCase().contains("dedup") || r.getTarget().toLowerCase().contains("dedup");
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}
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private static <T extends Oaf> String updateDeletedByInference(final String json, final Class<T> clazz) {
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try {
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Oaf entity = OBJECT_MAPPER.readValue(json, clazz);
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if (entity.getDataInfo() == null) {
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entity.setDataInfo(new DataInfo());
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}
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entity.getDataInfo().setDeletedbyinference(true);
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return OBJECT_MAPPER.writeValueAsString(entity);
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} catch (IOException e) {
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throw new RuntimeException("Unable to convert json", e);
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}
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}
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}
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@ -105,11 +105,6 @@
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<action name="PropagateRelation">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<prepare>
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<delete path="${dedupGraphPath}/relation"/>
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<delete path="${workingPath}/newRels"/>
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<delete path="${workingPath}/updated"/>
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</prepare>
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<master>yarn</master>
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<mode>cluster</mode>
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<name>Update Relations</name>
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