forked from D-Net/dnet-hadoop
100 lines
4.4 KiB
Java
100 lines
4.4 KiB
Java
package eu.dnetlib.dhp.oa.graph.dump;
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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.dump.oaf.Projects;
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import eu.dnetlib.dhp.schema.dump.oaf.Result;
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import eu.dnetlib.dhp.schema.oaf.Project;
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import eu.dnetlib.dhp.schema.oaf.Relation;
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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.function.MapFunction;
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import org.apache.spark.api.java.function.MapGroupsFunction;
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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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import java.io.Serializable;
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import java.util.Arrays;
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import java.util.List;
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import java.util.Optional;
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import java.util.stream.Collectors;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
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public class SparkPrepareResultProject implements Serializable {
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private static final Logger log = LoggerFactory.getLogger(SparkPrepareResultProject.class);
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public static void main(String[] args) throws Exception {
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String jsonConfiguration = IOUtils
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.toString(
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SparkPrepareResultProject.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/oa/graph/dump/project_prepare_parameters.json"));
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final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
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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 inputPath = parser.get("sourcePath");
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log.info("inputPath: {}", inputPath);
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final String outputPath = parser.get("outputPath");
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log.info("outputPath: {}", outputPath);
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SparkConf conf = new SparkConf();
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runWithSparkSession(
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conf,
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isSparkSessionManaged,
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spark -> {
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Utils.removeOutputDir(spark, outputPath);
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prepareResultProjectList(spark, inputPath, outputPath);
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});
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}
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private static void prepareResultProjectList(SparkSession spark, String inputPath, String outputPath) {
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Dataset<Relation> relation = Utils.readPath(spark, inputPath + "/relation" , Relation.class)
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.filter("dataInfo.deletedbyinference = false and relClass = 'produces'");
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Dataset<Project> projects = Utils.readPath(spark, inputPath + "/project" , Project.class);
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projects.joinWith(relation, projects.col("id").equalTo(relation.col("source")))
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.groupByKey((MapFunction<Tuple2<Project,Relation>,String>)value -> value._2().getTarget(), Encoders.STRING())
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.mapGroups((MapGroupsFunction<String, Tuple2<Project,Relation>, ResultProject>) (s, it) ->
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{
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Tuple2<Project, Relation> first = it.next();
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ResultProject rp = new ResultProject();
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rp.setResultId(first._2().getTarget());
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Project p = first._1();
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Projects ps = Projects.newInstance(p.getId(), p.getCode().getValue(), p.getAcronym().getValue(),
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p.getTitle().getValue(), p.getFundingtree()
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.stream()
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.map(ft -> ft.getValue()).collect(Collectors.toList()));
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List<Projects> projList = Arrays.asList(ps);
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rp.setProjectsList(projList);
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it.forEachRemaining(c -> {
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Project op = c._1();
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projList.add(Projects.newInstance(op.getId(), op.getCode().getValue(),
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op.getAcronym().getValue(), op.getTitle().getValue(),
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op.getFundingtree().stream().map(ft -> ft.getValue()).collect(Collectors.toList())));
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});
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return rp;
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} ,Encoders.bean(ResultProject.class))
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.write()
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.json(outputPath);
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}
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}
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