forked from D-Net/dnet-hadoop
287 lines
9.3 KiB
Java
287 lines
9.3 KiB
Java
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package eu.dnetlib.dhp.actionmanager.stats_actionsets;
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import static eu.dnetlib.dhp.actionmanager.Constants.*;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
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import java.io.Serializable;
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import java.util.ArrayList;
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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 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.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 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.common.ModelConstants;
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import eu.dnetlib.dhp.schema.oaf.*;
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import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
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import scala.Tuple2;
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/**
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* created the Atomic Action for each type of results
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*/
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public class StatsAtomicActionsJob implements Serializable {
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private static final Logger log = LoggerFactory.getLogger(StatsAtomicActionsJob.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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StatsAtomicActionsJob.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/actionmanager/stats_actionsets/input_actionset_parameter.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 outputPath = parser.get("outputPath");
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log.info("outputPath {}: ", outputPath);
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SparkConf conf = new SparkConf();
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conf.set("hive.metastore.uris", parser.get("hive_metastore_uris"));
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final String dbname = parser.get("statsDB");
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final String workingPath = parser.get("workingPath");
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runWithSparkHiveSession(
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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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prepareGreenData(dbname, spark, workingPath + "/greenOADB", "indi_pub_green_oa", "id");
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prepareDiamondData(dbname, spark, workingPath + "/diamondOADΒ", "indi_pub_diamond", "id");
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preparePubliclyFundedData(
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dbname, spark, workingPath + "/publiclyFundedDΒ", "indi_funded_result_with_fundref", "id");
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prepareOAColourData(dbname, spark, workingPath + "/oacolourDB", "", "id");
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writeActionSet(spark, workingPath, outputPath);
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});
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}
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private static void prepareGreenData(String dbname, SparkSession spark, String workingPath, String tableName,
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String resultAttributeName) {
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spark
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.sql(
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String
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.format(
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"select %s as id, green_oa as green_oa " +
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"from %s.%s",
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resultAttributeName, dbname, tableName))
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.as(Encoders.bean(StatsGreenOAModel.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(workingPath);
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}
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private static void prepareDiamondData(String dbname, SparkSession spark, String workingPath, String tableName,
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String resultAttributeName) {
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spark
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.sql(
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String
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.format(
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"select %s as id, in_diamond_journal as in_diamond_journal " +
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"from %s.%s",
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resultAttributeName, dbname, tableName))
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.as(Encoders.bean(StatsDiamondOAModel.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(workingPath);
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}
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private static void preparePubliclyFundedData(String dbname, SparkSession spark, String workingPath,
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String tableName,
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String resultAttributeName) {
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spark
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.sql(
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String
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.format(
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"select %s as id, fundref as publicly_funded " +
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"from %s.%s",
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resultAttributeName, dbname, tableName))
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.as(Encoders.bean(StatsPubliclyFundedModel.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(workingPath);
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}
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private static void prepareOAColourData(String dbname, SparkSession spark, String workingPath, String tableName,
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String resultAttributeName) {
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spark
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.sql(
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String
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.format(
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"select b.%s as id, is_gold, is_bronze_oa, is_hybrid from %s.indi_pub_bronze_oa b " +
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"left outer join %s.indi_pub_gold_oa g on g.id=b.id " +
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"left outer join %s.indi_pub_hybrid h on b.id=h.id",
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resultAttributeName, dbname, dbname, dbname))
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.as(Encoders.bean(StatsOAColourModel.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(workingPath);
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}
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public static void writeActionSet(SparkSession spark, String inputPath, String outputPath) {
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getFinalIndicatorsGreenResult(spark, inputPath + "/greenOADB")
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.toJavaRDD()
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.map(p -> new AtomicAction(p.getClass(), p))
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.union(
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getFinalIndicatorsDiamondResult(spark, inputPath + "/diamondOADΒ")
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.toJavaRDD()
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.map(p -> new AtomicAction(p.getClass(), p)))
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.union(
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getFinalIndicatorsPubliclyFundedResult(spark, inputPath + "/publiclyFundedDΒ")
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.toJavaRDD()
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.map(p -> new AtomicAction(p.getClass(), p)))
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.union(
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getFinalIndicatorsOAColourResult(spark, inputPath + "/oacolourDB")
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.toJavaRDD()
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.map(p -> new AtomicAction(p.getClass(), 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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public static Measure newMeasureInstance(String id) {
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Measure m = new Measure();
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m.setId(id);
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m.setUnit(new ArrayList<>());
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return m;
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}
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private static Dataset<Result> getFinalIndicatorsGreenResult(SparkSession spark, String inputPath) {
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return readPath(spark, inputPath, StatsGreenOAModel.class)
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.map((MapFunction<StatsGreenOAModel, Result>) usm -> {
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Result r = new Result();
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r.setId("50|" + usm.getId());
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r.setMeasures(getMeasure(usm.isGreen_oa(), "green_oa"));
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return r;
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}, Encoders.bean(Result.class));
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}
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private static Dataset<Result> getFinalIndicatorsDiamondResult(SparkSession spark, String inputPath) {
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return readPath(spark, inputPath, StatsDiamondOAModel.class)
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.map((MapFunction<StatsDiamondOAModel, Result>) usm -> {
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Result r = new Result();
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r.setId("50|" + usm.getId());
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r.setMeasures(getMeasure(usm.isIn_diamond_journal(), "in_diamond_journal"));
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return r;
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}, Encoders.bean(Result.class));
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}
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private static Dataset<Result> getFinalIndicatorsPubliclyFundedResult(SparkSession spark, String inputPath) {
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return readPath(spark, inputPath, StatsPubliclyFundedModel.class)
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.map((MapFunction<StatsPubliclyFundedModel, Result>) usm -> {
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Result r = new Result();
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r.setId("50|" + usm.getId());
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r.setMeasures(getMeasure(usm.isPublicly_funded(), "publicly_funded"));
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return r;
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}, Encoders.bean(Result.class));
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}
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private static Dataset<Result> getFinalIndicatorsOAColourResult(SparkSession spark, String inputPath) {
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return readPath(spark, inputPath, StatsOAColourModel.class)
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.map((MapFunction<StatsOAColourModel, Result>) usm -> {
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Result r = new Result();
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r.setId("50|" + usm.getId());
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r.setMeasures(getMeasureOAColour(usm.isIs_gold(), usm.isIs_bronze_oa(), usm.isIs_hybrid()));
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return r;
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}, Encoders.bean(Result.class));
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}
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private static List<Measure> getMeasure(Boolean is_model_oa, String model_type) {
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DataInfo dataInfo = OafMapperUtils
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.dataInfo(
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false,
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UPDATE_DATA_INFO_TYPE,
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true,
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false,
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OafMapperUtils
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.qualifier(
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UPDATE_MEASURE_STATS_MODEL_CLASS_ID,
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UPDATE_CLASS_NAME,
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ModelConstants.DNET_PROVENANCE_ACTIONS,
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ModelConstants.DNET_PROVENANCE_ACTIONS),
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"");
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return Arrays
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.asList(
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OafMapperUtils
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.newMeasureInstance(model_type, String.valueOf(is_model_oa), UPDATE_KEY_STATS_MODEL, dataInfo));
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}
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private static List<Measure> getMeasureOAColour(Boolean is_gold, Boolean is_bronze_oa, Boolean is_hybrid) {
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DataInfo dataInfo = OafMapperUtils
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.dataInfo(
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false,
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UPDATE_DATA_INFO_TYPE,
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true,
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false,
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OafMapperUtils
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.qualifier(
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UPDATE_MEASURE_STATS_MODEL_CLASS_ID,
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UPDATE_CLASS_NAME,
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ModelConstants.DNET_PROVENANCE_ACTIONS,
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ModelConstants.DNET_PROVENANCE_ACTIONS),
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"");
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return Arrays
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.asList(
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OafMapperUtils
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.newMeasureInstance("is_gold", String.valueOf(is_gold), UPDATE_KEY_STATS_MODEL, dataInfo),
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OafMapperUtils
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.newMeasureInstance("is_bronze_oa", String.valueOf(is_bronze_oa), UPDATE_KEY_STATS_MODEL, dataInfo),
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OafMapperUtils
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.newMeasureInstance("is_hybrid", String.valueOf(is_hybrid), UPDATE_KEY_STATS_MODEL, dataInfo));
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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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