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fixed spark memory issue in SparkSplitOafTODLIEntities

This commit is contained in:
Sandro La Bruzzo 2020-10-28 12:30:32 +01:00
parent 3a81a940b7
commit 1d9fdb7367
3 changed files with 149 additions and 44 deletions

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@ -4,7 +4,6 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.schema.oaf.{Oaf, Relation}
import eu.dnetlib.dhp.schema.scholexplorer.{DLIDataset, DLIPublication, DLIUnknown}
import eu.dnetlib.dhp.sx.ebi.EBIAggregator
import eu.dnetlib.dhp.sx.ebi.model.{PMArticle, PMAuthor, PMJournal}
import org.apache.commons.io.IOUtils
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.LoggerFactory
@ -18,38 +17,38 @@ object SparkSplitOafTODLIEntities {
}
def main(args: Array[String]): Unit = {
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkSplitOafTODLIEntities.getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/argumentparser/input_extract_entities_parameters.json")))
val logger = LoggerFactory.getLogger(SparkSplitOafTODLIEntities.getClass)
parser.parseArgument(args)
val workingPath: String = parser.get("workingPath")
logger.info(s"Working dir path = $workingPath")
def extract_dataset(spark:SparkSession, workingPath:String) :Unit = {
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val datEncoder: Encoder[DLIDataset] = Encoders.kryo[DLIDataset]
val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf].repartition(4000)
val ebi_dataset:Dataset[DLIDataset] = spark.read.load(s"$workingPath/ebi/baseline_dataset_ebi").as[DLIDataset].repartition(1000)
OAFDataset
.filter(s => s != null && s.isInstanceOf[DLIDataset])
.map(s =>s.asInstanceOf[DLIDataset])
.union(ebi_dataset)
.map(d => (d.getId, d))(Encoders.tuple(Encoders.STRING, datEncoder))
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getDLIDatasetAggregator().toColumn)
.map(p => p._2)
.repartition(2000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/dataset")
}
def extract_publication(spark:SparkSession, workingPath:String) :Unit = {
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val pubEncoder: Encoder[DLIPublication] = Encoders.kryo[DLIPublication]
implicit val datEncoder: Encoder[DLIDataset] = Encoders.kryo[DLIDataset]
implicit val unkEncoder: Encoder[DLIUnknown] = Encoders.kryo[DLIUnknown]
implicit val relEncoder: Encoder[Relation] = Encoders.kryo[Relation]
val spark:SparkSession = SparkSession
.builder()
.appName(SparkSplitOafTODLIEntities.getClass.getSimpleName)
.config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
.master(parser.get("master"))
.getOrCreate()
val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf]
val ebi_dataset:Dataset[DLIDataset] = spark.read.load(s"$workingPath/ebi/baseline_dataset_ebi").as[DLIDataset]
val ebi_publication:Dataset[DLIPublication] = spark.read.load(s"$workingPath/ebi/baseline_publication_ebi").as[DLIPublication]
val ebi_relation:Dataset[Relation] = spark.read.load(s"$workingPath/ebi/baseline_relation_ebi").as[Relation]
val ebi_publication:Dataset[DLIPublication] = spark.read.load(s"$workingPath/ebi/baseline_publication_ebi").as[DLIPublication].repartition(1000)
OAFDataset
@ -60,20 +59,17 @@ object SparkSplitOafTODLIEntities {
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getDLIPublicationAggregator().toColumn)
.map(p => p._2)
.repartition(1000)
.repartition(2000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/publication")
OAFDataset
.filter(s => s != null && s.isInstanceOf[DLIDataset])
.map(s =>s.asInstanceOf[DLIDataset])
.union(ebi_dataset)
.map(d => (d.getId, d))(Encoders.tuple(Encoders.STRING, datEncoder))
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getDLIDatasetAggregator().toColumn)
.map(p => p._2)
.repartition(1000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/dataset")
}
def extract_unknown(spark:SparkSession, workingPath:String) :Unit = {
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val unkEncoder: Encoder[DLIUnknown] = Encoders.kryo[DLIUnknown]
val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf]
OAFDataset
.filter(s => s != null && s.isInstanceOf[DLIUnknown])
@ -82,9 +78,18 @@ object SparkSplitOafTODLIEntities {
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getDLIUnknownAggregator().toColumn)
.map(p => p._2)
.repartition(1000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/unknown")
}
def extract_relations(spark:SparkSession, workingPath:String) :Unit = {
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
implicit val relEncoder: Encoder[Relation] = Encoders.kryo[Relation]
val OAFDataset:Dataset[Oaf] = spark.read.load(s"$workingPath/input/OAFDataset").as[Oaf]
val ebi_relation:Dataset[Relation] = spark.read.load(s"$workingPath/ebi/baseline_relation_ebi").as[Relation].repartition(2000)
OAFDataset
.filter(s => s != null && s.isInstanceOf[Relation])
@ -94,9 +99,35 @@ object SparkSplitOafTODLIEntities {
.groupByKey(_._1)(Encoders.STRING)
.agg(EBIAggregator.getRelationAggregator().toColumn)
.map(p => p._2)
.repartition(1000)
.repartition(4000)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/graph/relation")
}
def main(args: Array[String]): Unit = {
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkSplitOafTODLIEntities.getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/argumentparser/input_extract_entities_parameters.json")))
val logger = LoggerFactory.getLogger(SparkSplitOafTODLIEntities.getClass)
parser.parseArgument(args)
val workingPath: String = parser.get("workingPath")
val entity:String = parser.get("entity")
logger.info(s"Working dir path = $workingPath")
val spark:SparkSession = SparkSession
.builder()
.appName(SparkSplitOafTODLIEntities.getClass.getSimpleName)
.config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
.master(parser.get("master"))
.getOrCreate()
entity match {
case "publication" => extract_publication(spark, workingPath)
case "dataset" => extract_dataset(spark,workingPath)
case "relation" => extract_relations(spark, workingPath)
case "unknown" => extract_unknown(spark, workingPath)
}

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@ -1,4 +1,5 @@
[
{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the work dir path", "paramRequired": true}
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the work dir path", "paramRequired": true},
{"paramName":"e", "paramLongName":"entity", "paramDescription": "the work dir path", "paramRequired": true}
]

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@ -14,30 +14,103 @@
</property>
</parameters>
<start to="ExtractDLIEntities"/>
<start to="ExtractDLIPublication"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="ExtractDLIEntities">
<action name="ExtractDLIPublication">
<spark xmlns="uri:oozie:spark-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Extract DLI Entities</name>
<name>Extract DLI Entities (Publication)</name>
<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory ${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=3840
--conf spark.sql.shuffle.partitions=5000
${sparkExtraOPT}
</spark-opts>
<arg>-mt</arg> <arg>yarn-cluster</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>-e</arg><arg>publication</arg>
</spark>
<ok to="ExtractDLIDataset"/>
<error to="Kill"/>
</action>
<action name="ExtractDLIDataset">
<spark xmlns="uri:oozie:spark-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Extract DLI Entities (Dataset)</name>
<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory ${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=5000
${sparkExtraOPT}
</spark-opts>
<arg>-mt</arg> <arg>yarn-cluster</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>-e</arg><arg>dataset</arg>
</spark>
<ok to="ExtractDLIUnknown"/>
<error to="Kill"/>
</action>
<action name="ExtractDLIUnknown">
<spark xmlns="uri:oozie:spark-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Extract DLI Entities (Unknown)</name>
<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory ${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=5000
${sparkExtraOPT}
</spark-opts>
<arg>-mt</arg> <arg>yarn-cluster</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>-e</arg><arg>unknown</arg>
</spark>
<ok to="ExtractDLIRelation"/>
<error to="Kill"/>
</action>
<action name="ExtractDLIRelation">
<spark xmlns="uri:oozie:spark-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Extract DLI Entities (Relation)</name>
<class>eu.dnetlib.dhp.sx.graph.SparkSplitOafTODLIEntities</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory ${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.sql.shuffle.partitions=5000
${sparkExtraOPT}
</spark-opts>
<arg>-mt</arg> <arg>yarn-cluster</arg>
<arg>--workingPath</arg><arg>${workingPath}</arg>
<arg>-e</arg><arg>relation</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>