forked from D-Net/dnet-hadoop
140 lines
6.2 KiB
Java
140 lines
6.2 KiB
Java
package eu.dnetlib.dhp.oa.graph.raw;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
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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.common.HdfsSupport;
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import eu.dnetlib.dhp.schema.common.ModelSupport;
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import eu.dnetlib.dhp.schema.oaf.*;
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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.FilterFunction;
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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.SaveMode;
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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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public class MergeClaimsApplication {
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private static final Logger log = LoggerFactory.getLogger(MergeClaimsApplication.class);
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private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
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public static void main(final String[] args) throws Exception {
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final ArgumentApplicationParser parser =
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new ArgumentApplicationParser(
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IOUtils.toString(
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MigrateMongoMdstoresApplication.class.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 =
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Optional.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 outputRawGaphPath = parser.get("outputRawGaphPath");
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log.info("outputRawGaphPath: {}", outputRawGaphPath);
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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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SparkConf conf = new SparkConf();
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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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runWithSparkSession(
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conf,
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isSparkSessionManaged,
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spark -> {
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String type = clazz.getSimpleName().toLowerCase();
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String rawPath = rawGraphPath + "/" + type;
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String claimPath = claimsGraphPath + "/" + type;
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String outPath = outputRawGaphPath + "/" + type;
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removeOutputDir(spark, outPath);
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mergeByType(spark, rawPath, claimPath, outPath, clazz);
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});
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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 outPath, Class<T> clazz) {
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Dataset<Tuple2<String, T>> raw =
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readFromPath(spark, rawPath, clazz)
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.map(
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(MapFunction<T, Tuple2<String, T>>)
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value ->
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new Tuple2<>(
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ModelSupport.idFn().apply(value), value),
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Encoders.tuple(Encoders.STRING(), Encoders.kryo(clazz)));
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final JavaSparkContext jsc = JavaSparkContext.fromSparkContext(spark.sparkContext());
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Dataset<Tuple2<String, T>> claim =
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jsc.broadcast(readFromPath(spark, claimPath, clazz))
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.getValue()
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.map(
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(MapFunction<T, Tuple2<String, T>>)
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value ->
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new Tuple2<>(
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ModelSupport.idFn().apply(value), value),
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Encoders.tuple(Encoders.STRING(), Encoders.kryo(clazz)));
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raw.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>)
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value -> {
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Optional<Tuple2<String, T>> opRaw =
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Optional.ofNullable(value._1());
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Optional<Tuple2<String, T>> opClaim =
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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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.map(
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(MapFunction<T, String>) value -> OBJECT_MAPPER.writeValueAsString(value),
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Encoders.STRING())
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.write()
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.text(outPath);
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}
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private static <T extends Oaf> Dataset<T> readFromPath(
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SparkSession spark, String path, Class<T> clazz) {
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return spark.read()
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.textFile(path)
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.map(
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(MapFunction<String, T>) value -> OBJECT_MAPPER.readValue(value, clazz),
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Encoders.bean(clazz))
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.filter(
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(FilterFunction<T>)
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value -> Objects.nonNull(ModelSupport.idFn().apply(value)));
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}
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private static void removeOutputDir(SparkSession spark, String path) {
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HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
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}
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}
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