81 lines
3.7 KiB
Java
81 lines
3.7 KiB
Java
package eu.dnetlib.dedup;
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import eu.dnetlib.dedup.graph.ConnectedComponent;
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import eu.dnetlib.dedup.graph.GraphProcessor;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.schema.oaf.Relation;
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import eu.dnetlib.pace.config.DedupConfig;
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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.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.function.FlatMapFunction;
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import org.apache.spark.api.java.function.PairFunction;
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import org.apache.spark.graphx.Edge;
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import org.apache.spark.rdd.RDD;
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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 scala.Tuple2;
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import java.util.ArrayList;
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import java.util.List;
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public class SparkCreateConnectedComponent {
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public static void main(String[] args) throws Exception {
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final ArgumentApplicationParser parser = new ArgumentApplicationParser(IOUtils.toString(SparkCreateConnectedComponent.class.getResourceAsStream("/eu/dnetlib/dhp/dedup/dedup_parameters.json")));
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parser.parseArgument(args);
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final SparkSession spark = SparkSession
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.builder()
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.appName(SparkCreateConnectedComponent.class.getSimpleName())
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.master(parser.get("master"))
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.getOrCreate();
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final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
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final String inputPath = parser.get("sourcePath");
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final String entity = parser.get("entity");
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final String targetPath = parser.get("targetPath");
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// final DedupConfig dedupConf = DedupConfig.load(IOUtils.toString(SparkCreateConnectedComponent.class.getResourceAsStream("/eu/dnetlib/dhp/dedup/conf/org.curr.conf2.json")));
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final DedupConfig dedupConf = DedupConfig.load(parser.get("dedupConf"));
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final JavaPairRDD<Object, String> vertexes = sc.textFile(inputPath + "/" + entity)
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.map(s -> MapDocumentUtil.getJPathString(dedupConf.getWf().getIdPath(), s))
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.mapToPair((PairFunction<String, Object, String>)
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s -> new Tuple2<Object, String>((long) s.hashCode(), s)
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);
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final Dataset<Relation> similarityRelations = spark.read().load(DedupUtility.createSimRelPath(targetPath,entity)).as(Encoders.bean(Relation.class));
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final RDD<Edge<String>> edgeRdd = similarityRelations.javaRDD().map(it -> new Edge<>(it.getSource().hashCode(), it.getTarget().hashCode(), it.getRelClass())).rdd();
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final JavaRDD<ConnectedComponent> cc = GraphProcessor.findCCs(vertexes.rdd(), edgeRdd, 20).toJavaRDD();
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final Dataset<Relation> mergeRelation = spark.createDataset(cc.filter(k->k.getDocIds().size()>1).flatMap((FlatMapFunction<ConnectedComponent, Relation>) c ->
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c.getDocIds()
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.stream()
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.flatMap(id -> {
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List<Relation> tmp = new ArrayList<>();
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Relation r = new Relation();
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r.setSource(c.getCcId());
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r.setTarget(id);
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r.setRelClass("merges");
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tmp.add(r);
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r = new Relation();
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r.setTarget(c.getCcId());
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r.setSource(id);
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r.setRelClass("isMergedIn");
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tmp.add(r);
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return tmp.stream();
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}).iterator()).rdd(), Encoders.bean(Relation.class));
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mergeRelation.write().mode("overwrite").save(DedupUtility.createMergeRelPath(targetPath,entity));
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}
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}
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