forked from D-Net/dnet-hadoop
fixed spark memory issue in SparkSplitOafTODLIEntities
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3a81a940b7
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1d9fdb7367
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@ -4,7 +4,6 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser
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import eu.dnetlib.dhp.schema.oaf.{Oaf, Relation}
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import eu.dnetlib.dhp.schema.scholexplorer.{DLIDataset, DLIPublication, DLIUnknown}
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import eu.dnetlib.dhp.sx.ebi.EBIAggregator
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import eu.dnetlib.dhp.sx.ebi.model.{PMArticle, PMAuthor, PMJournal}
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import org.apache.commons.io.IOUtils
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import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
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import org.slf4j.LoggerFactory
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@ -18,38 +17,38 @@ object SparkSplitOafTODLIEntities {
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}
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def main(args: Array[String]): Unit = {
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val parser = new ArgumentApplicationParser(IOUtils.toString(SparkSplitOafTODLIEntities.getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/argumentparser/input_extract_entities_parameters.json")))
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val logger = LoggerFactory.getLogger(SparkSplitOafTODLIEntities.getClass)
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parser.parseArgument(args)
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val workingPath: String = parser.get("workingPath")
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logger.info(s"Working dir path = $workingPath")
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def extract_dataset(spark:SparkSession, workingPath:String) :Unit = {
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implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
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implicit val datEncoder: Encoder[DLIDataset] = Encoders.kryo[DLIDataset]
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val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf].repartition(4000)
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val ebi_dataset:Dataset[DLIDataset] = spark.read.load(s"$workingPath/ebi/baseline_dataset_ebi").as[DLIDataset].repartition(1000)
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OAFDataset
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.filter(s => s != null && s.isInstanceOf[DLIDataset])
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.map(s =>s.asInstanceOf[DLIDataset])
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.union(ebi_dataset)
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.map(d => (d.getId, d))(Encoders.tuple(Encoders.STRING, datEncoder))
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.groupByKey(_._1)(Encoders.STRING)
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.agg(EBIAggregator.getDLIDatasetAggregator().toColumn)
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.map(p => p._2)
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.repartition(2000)
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.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/dataset")
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}
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def extract_publication(spark:SparkSession, workingPath:String) :Unit = {
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implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
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implicit val pubEncoder: Encoder[DLIPublication] = Encoders.kryo[DLIPublication]
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implicit val datEncoder: Encoder[DLIDataset] = Encoders.kryo[DLIDataset]
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implicit val unkEncoder: Encoder[DLIUnknown] = Encoders.kryo[DLIUnknown]
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implicit val relEncoder: Encoder[Relation] = Encoders.kryo[Relation]
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val spark:SparkSession = SparkSession
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.builder()
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.appName(SparkSplitOafTODLIEntities.getClass.getSimpleName)
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.config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
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.master(parser.get("master"))
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.getOrCreate()
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val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf]
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val ebi_dataset:Dataset[DLIDataset] = spark.read.load(s"$workingPath/ebi/baseline_dataset_ebi").as[DLIDataset]
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val ebi_publication:Dataset[DLIPublication] = spark.read.load(s"$workingPath/ebi/baseline_publication_ebi").as[DLIPublication]
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val ebi_relation:Dataset[Relation] = spark.read.load(s"$workingPath/ebi/baseline_relation_ebi").as[Relation]
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val ebi_publication:Dataset[DLIPublication] = spark.read.load(s"$workingPath/ebi/baseline_publication_ebi").as[DLIPublication].repartition(1000)
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OAFDataset
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@ -60,20 +59,17 @@ object SparkSplitOafTODLIEntities {
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.groupByKey(_._1)(Encoders.STRING)
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.agg(EBIAggregator.getDLIPublicationAggregator().toColumn)
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.map(p => p._2)
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.repartition(1000)
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.repartition(2000)
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.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/publication")
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OAFDataset
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.filter(s => s != null && s.isInstanceOf[DLIDataset])
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.map(s =>s.asInstanceOf[DLIDataset])
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.union(ebi_dataset)
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.map(d => (d.getId, d))(Encoders.tuple(Encoders.STRING, datEncoder))
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.groupByKey(_._1)(Encoders.STRING)
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.agg(EBIAggregator.getDLIDatasetAggregator().toColumn)
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.map(p => p._2)
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.repartition(1000)
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.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/dataset")
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}
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def extract_unknown(spark:SparkSession, workingPath:String) :Unit = {
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implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
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implicit val unkEncoder: Encoder[DLIUnknown] = Encoders.kryo[DLIUnknown]
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val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf]
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OAFDataset
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.filter(s => s != null && s.isInstanceOf[DLIUnknown])
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@ -82,9 +78,18 @@ object SparkSplitOafTODLIEntities {
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.groupByKey(_._1)(Encoders.STRING)
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.agg(EBIAggregator.getDLIUnknownAggregator().toColumn)
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.map(p => p._2)
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.repartition(1000)
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.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/unknown")
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}
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def extract_relations(spark:SparkSession, workingPath:String) :Unit = {
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implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
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implicit val relEncoder: Encoder[Relation] = Encoders.kryo[Relation]
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val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf]
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val ebi_relation:Dataset[Relation] = spark.read.load(s"$workingPath/ebi/baseline_relation_ebi").as[Relation].repartition(2000)
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OAFDataset
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.filter(s => s != null && s.isInstanceOf[Relation])
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@ -94,9 +99,35 @@ object SparkSplitOafTODLIEntities {
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.groupByKey(_._1)(Encoders.STRING)
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.agg(EBIAggregator.getRelationAggregator().toColumn)
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.map(p => p._2)
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.repartition(1000)
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.repartition(4000)
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.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/relation")
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}
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def main(args: Array[String]): Unit = {
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val parser = new ArgumentApplicationParser(IOUtils.toString(SparkSplitOafTODLIEntities.getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/argumentparser/input_extract_entities_parameters.json")))
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val logger = LoggerFactory.getLogger(SparkSplitOafTODLIEntities.getClass)
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parser.parseArgument(args)
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val workingPath: String = parser.get("workingPath")
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val entity:String = parser.get("entity")
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logger.info(s"Working dir path = $workingPath")
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val spark:SparkSession = SparkSession
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.builder()
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.appName(SparkSplitOafTODLIEntities.getClass.getSimpleName)
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.config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
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.master(parser.get("master"))
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.getOrCreate()
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entity match {
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case "publication" => extract_publication(spark, workingPath)
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case "dataset" => extract_dataset(spark,workingPath)
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case "relation" => extract_relations(spark, workingPath)
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case "unknown" => extract_unknown(spark, workingPath)
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}
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@ -1,4 +1,5 @@
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[
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{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
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{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the work dir path", "paramRequired": true}
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{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the work dir path", "paramRequired": true},
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{"paramName":"e", "paramLongName":"entity", "paramDescription": "the work dir path", "paramRequired": true}
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]
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@ -14,30 +14,103 @@
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</property>
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</parameters>
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<start to="ExtractDLIEntities"/>
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<start to="ExtractDLIPublication"/>
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<kill name="Kill">
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<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
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</kill>
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<action name="ExtractDLIEntities">
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<action name="ExtractDLIPublication">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<job-tracker>${jobTracker}</job-tracker>
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<name-node>${nameNode}</name-node>
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<name>Extract DLI Entities</name>
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<name>Extract DLI Entities (Publication)</name>
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<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
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<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
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<spark-opts>
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--executor-memory ${sparkExecutorMemory}
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--executor-cores=${sparkExecutorCores}
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--driver-memory=${sparkDriverMemory}
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--conf spark.sql.shuffle.partitions=3840
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--conf spark.sql.shuffle.partitions=5000
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${sparkExtraOPT}
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</spark-opts>
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<arg>-mt</arg> <arg>yarn-cluster</arg>
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<arg>--workingPath</arg><arg>${workingPath}</arg>
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<arg>-e</arg><arg>publication</arg>
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</spark>
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<ok to="ExtractDLIDataset"/>
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<error to="Kill"/>
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</action>
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<action name="ExtractDLIDataset">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<job-tracker>${jobTracker}</job-tracker>
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<name-node>${nameNode}</name-node>
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<name>Extract DLI Entities (Dataset)</name>
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<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
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<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
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<spark-opts>
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--executor-memory ${sparkExecutorMemory}
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--executor-cores=${sparkExecutorCores}
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--driver-memory=${sparkDriverMemory}
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--conf spark.sql.shuffle.partitions=5000
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${sparkExtraOPT}
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</spark-opts>
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<arg>-mt</arg> <arg>yarn-cluster</arg>
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<arg>--workingPath</arg><arg>${workingPath}</arg>
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<arg>-e</arg><arg>dataset</arg>
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</spark>
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<ok to="ExtractDLIUnknown"/>
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<error to="Kill"/>
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</action>
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<action name="ExtractDLIUnknown">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<job-tracker>${jobTracker}</job-tracker>
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<name-node>${nameNode}</name-node>
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<name>Extract DLI Entities (Unknown)</name>
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<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
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<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
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<spark-opts>
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--executor-memory ${sparkExecutorMemory}
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--executor-cores=${sparkExecutorCores}
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--driver-memory=${sparkDriverMemory}
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--conf spark.sql.shuffle.partitions=5000
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${sparkExtraOPT}
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</spark-opts>
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<arg>-mt</arg> <arg>yarn-cluster</arg>
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<arg>--workingPath</arg><arg>${workingPath}</arg>
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<arg>-e</arg><arg>unknown</arg>
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</spark>
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<ok to="ExtractDLIRelation"/>
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<error to="Kill"/>
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</action>
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<action name="ExtractDLIRelation">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<job-tracker>${jobTracker}</job-tracker>
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<name-node>${nameNode}</name-node>
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<name>Extract DLI Entities (Relation)</name>
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<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
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<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
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<spark-opts>
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--executor-memory ${sparkExecutorMemory}
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--executor-cores=${sparkExecutorCores}
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--driver-memory=${sparkDriverMemory}
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--conf spark.sql.shuffle.partitions=5000
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${sparkExtraOPT}
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</spark-opts>
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<arg>-mt</arg> <arg>yarn-cluster</arg>
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<arg>--workingPath</arg><arg>${workingPath}</arg>
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<arg>-e</arg><arg>relation</arg>
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</spark>
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<ok to="End"/>
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<error to="Kill"/>
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