forked from D-Net/dnet-hadoop
109 lines
3.8 KiB
Java
109 lines
3.8 KiB
Java
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package eu.dnetlib.dhp.oa.graph.raw;
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import static eu.dnetlib.dhp.common.GraphSupport.*;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
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import java.util.Objects;
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import java.util.Optional;
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import org.apache.commons.io.IOUtils;
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import org.apache.spark.SparkConf;
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import org.apache.spark.api.java.JavaSparkContext;
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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.SparkSession;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.common.GraphFormat;
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import eu.dnetlib.dhp.schema.common.ModelSupport;
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import eu.dnetlib.dhp.schema.oaf.Oaf;
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import scala.Tuple2;
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public class MergeClaimsApplication {
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private static final Logger log = LoggerFactory.getLogger(MergeClaimsApplication.class);
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public static void main(final String[] args) throws Exception {
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final ArgumentApplicationParser parser = new ArgumentApplicationParser(
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IOUtils
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.toString(
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MigrateMongoMdstoresApplication.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/oa/graph/merge_claims_parameters.json")));
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parser.parseArgument(args);
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Boolean isSparkSessionManaged = Optional
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.ofNullable(parser.get("isSparkSessionManaged"))
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.map(Boolean::valueOf)
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.orElse(Boolean.TRUE);
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log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
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final String rawGraphPath = parser.get("rawGraphPath");
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log.info("rawGraphPath: {}", rawGraphPath);
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final String claimsGraphPath = parser.get("claimsGraphPath");
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log.info("claimsGraphPath: {}", claimsGraphPath);
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final String outputGraph = parser.get("outputGraph");
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log.info("outputGraph: {}", outputGraph);
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final GraphFormat format = Optional
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.ofNullable(parser.get("format"))
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.map(GraphFormat::valueOf)
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.orElse(GraphFormat.DEFAULT);
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log.info("graphFormat: {}", format);
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String graphTableClassName = parser.get("graphTableClassName");
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log.info("graphTableClassName: {}", graphTableClassName);
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Class<? extends Oaf> clazz = (Class<? extends Oaf>) Class.forName(graphTableClassName);
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String hiveMetastoreUris = parser.get("hiveMetastoreUris");
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log.info("hiveMetastoreUris: {}", hiveMetastoreUris);
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SparkConf conf = new SparkConf();
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conf.set("hive.metastore.uris", hiveMetastoreUris);
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conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
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conf.registerKryoClasses(ModelSupport.getOafModelClasses());
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runWithSparkHiveSession(
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conf,
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isSparkSessionManaged,
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spark -> mergeByType(spark, rawGraphPath, claimsGraphPath, outputGraph, format, clazz));
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}
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private static <T extends Oaf> void mergeByType(
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SparkSession spark, String rawPath, String claimPath, String outputGraph, GraphFormat format, Class<T> clazz) {
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Dataset<Tuple2<String, T>> raw = readGraphJSON(spark, rawPath, clazz)
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.map(
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(MapFunction<T, Tuple2<String, T>>) value -> new Tuple2<>(ModelSupport.idFn().apply(value), value),
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Encoders.tuple(Encoders.STRING(), Encoders.kryo(clazz)));
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Dataset<Tuple2<String, T>> claim = readGraphJSON(spark, claimPath, clazz)
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.map(
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(MapFunction<T, Tuple2<String, T>>) value -> new Tuple2<>(ModelSupport.idFn().apply(value), value),
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Encoders.tuple(Encoders.STRING(), Encoders.kryo(clazz)));
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Dataset<T> merged = raw
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.joinWith(claim, raw.col("_1").equalTo(claim.col("_1")), "full_outer")
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.map(
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(MapFunction<Tuple2<Tuple2<String, T>, Tuple2<String, T>>, T>) value -> {
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Optional<Tuple2<String, T>> opRaw = Optional.ofNullable(value._1());
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Optional<Tuple2<String, T>> opClaim = Optional.ofNullable(value._2());
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return opRaw.isPresent()
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? opRaw.get()._2()
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: opClaim.isPresent() ? opClaim.get()._2() : null;
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},
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Encoders.bean(clazz))
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.filter(Objects::nonNull);
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saveGraphTable(merged, clazz, outputGraph, format);
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}
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}
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