Merge pull request 'bipFinder_master_test' (#84) from bipFinder_master_test into master
commit
5bd999efe7
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package eu.dnetlib.dhp.actionmanager.bipfinder;
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import java.io.Serializable;
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import java.util.List;
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/**
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* Rewriting of the bipFinder input data by extracting the identifier of the result (doi)
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*/
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public class BipScore implements Serializable {
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private String id; // doi
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private List<Score> scoreList; // unit as given in the inputfile
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public String getId() {
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return id;
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}
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public void setId(String id) {
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this.id = id;
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}
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public List<Score> getScoreList() {
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return scoreList;
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}
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public void setScoreList(List<Score> scoreList) {
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this.scoreList = scoreList;
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}
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}
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package eu.dnetlib.dhp.actionmanager.bipfinder;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
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import java.io.Serializable;
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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 org.apache.commons.io.IOUtils;
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import org.apache.hadoop.io.Text;
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import org.apache.hadoop.mapred.SequenceFileOutputFormat;
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import org.apache.spark.SparkConf;
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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.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.SparkSession;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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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.action.AtomicAction;
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import eu.dnetlib.dhp.schema.oaf.*;
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import eu.dnetlib.dhp.schema.oaf.KeyValue;
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import scala.Tuple2;
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/**
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* created the Atomic Action for each tipe of results
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*/
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public class SparkAtomicActionScoreJob implements Serializable {
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private static String DOI = "doi";
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private static final Logger log = LoggerFactory.getLogger(SparkAtomicActionScoreJob.class);
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private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
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public static <I extends Result> void main(String[] args) throws Exception {
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String jsonConfiguration = IOUtils
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.toString(
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SparkAtomicActionScoreJob.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/actionmanager/bipfinder/input_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("inputPath");
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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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final String bipScorePath = parser.get("bipScorePath");
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log.info("bipScorePath: {}", bipScorePath);
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final String resultClassName = parser.get("resultTableName");
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log.info("resultTableName: {}", resultClassName);
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Class<I> inputClazz = (Class<I>) Class.forName(resultClassName);
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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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removeOutputDir(spark, outputPath);
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prepareResults(spark, inputPath, outputPath, bipScorePath, inputClazz);
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});
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}
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private static <I extends Result> void prepareResults(SparkSession spark, String inputPath, String outputPath,
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String bipScorePath, Class<I> inputClazz) {
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final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
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JavaRDD<BipDeserialize> bipDeserializeJavaRDD = sc
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.textFile(bipScorePath)
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.map(item -> OBJECT_MAPPER.readValue(item, BipDeserialize.class));
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Dataset<BipScore> bipScores = spark
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.createDataset(bipDeserializeJavaRDD.flatMap(entry -> entry.keySet().stream().map(key -> {
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BipScore bs = new BipScore();
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bs.setId(key);
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bs.setScoreList(entry.get(key));
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return bs;
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}).collect(Collectors.toList()).iterator()).rdd(), Encoders.bean(BipScore.class));
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System.out.println(bipScores.count());
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Dataset<I> results = readPath(spark, inputPath, inputClazz);
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results.createOrReplaceTempView("result");
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Dataset<PreparedResult> preparedResult = spark
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.sql(
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"select pIde.value value, id " +
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"from result " +
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"lateral view explode (pid) p as pIde " +
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"where dataInfo.deletedbyinference = false and pIde.qualifier.classid = '" + DOI + "'")
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.as(Encoders.bean(PreparedResult.class));
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bipScores
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.joinWith(
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preparedResult, bipScores.col("id").equalTo(preparedResult.col("value")),
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"inner")
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.map((MapFunction<Tuple2<BipScore, PreparedResult>, BipScore>) value -> {
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BipScore ret = value._1();
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ret.setId(value._2().getId());
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return ret;
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}, Encoders.bean(BipScore.class))
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.groupByKey((MapFunction<BipScore, String>) value -> value.getId(), Encoders.STRING())
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.mapGroups((MapGroupsFunction<String, BipScore, Result>) (k, it) -> {
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Result ret = new Result();
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ret.setDataInfo(getDataInfo());
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BipScore first = it.next();
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ret.setId(first.getId());
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ret.setMeasures(getMeasure(first));
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it.forEachRemaining(value -> ret.getMeasures().addAll(getMeasure(value)));
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return ret;
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}, Encoders.bean(Result.class))
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.toJavaRDD()
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.map(p -> new AtomicAction(inputClazz, p))
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.mapToPair(
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aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()),
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new Text(OBJECT_MAPPER.writeValueAsString(aa))))
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.saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class);
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}
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private static List<Measure> getMeasure(BipScore value) {
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return value
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.getScoreList()
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.stream()
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.map(score -> {
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Measure m = new Measure();
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m.setId(score.getId());
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m
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.setUnit(
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score
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.getUnit()
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.stream()
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.map(unit -> {
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KeyValue kv = new KeyValue();
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kv.setValue(unit.getValue());
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kv.setKey(unit.getKey());
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kv.setDataInfo(getDataInfo());
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return kv;
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})
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.collect(Collectors.toList()));
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return m;
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})
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.collect(Collectors.toList());
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}
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private static DataInfo getDataInfo() {
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DataInfo di = new DataInfo();
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di.setInferred(false);
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di.setInvisible(false);
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di.setDeletedbyinference(false);
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di.setTrust("");
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Qualifier qualifier = new Qualifier();
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qualifier.setClassid("sysimport:actionset");
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qualifier.setClassname("Harvested");
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qualifier.setSchemename("dnet:provenanceActions");
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qualifier.setSchemeid("dnet:provenanceActions");
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di.setProvenanceaction(qualifier);
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return di;
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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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public static <R> Dataset<R> readPath(
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SparkSession spark, String inputPath, Class<R> clazz) {
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return spark
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.read()
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.textFile(inputPath)
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.map((MapFunction<String, R>) value -> OBJECT_MAPPER.readValue(value, clazz), Encoders.bean(clazz));
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}
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}
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