forked from D-Net/dnet-hadoop
[scholexplorer]
- Minor fix on SparkConvertRDDtoDataset -first implementation of retrieve datacite dump
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package eu.dnetlib.dhp.sx.graph
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import eu.dnetlib.dhp.application.AbstractScalaApplication
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import eu.dnetlib.dhp.schema.oaf.{Oaf, Result}
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import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
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import org.apache.spark.sql.functions.max
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import org.slf4j.Logger
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class SparkRetrieveDataciteDelta (propertyPath:String, args:Array[String], log:Logger) extends AbstractScalaApplication(propertyPath, args, log:Logger) {
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def retrieveLastCollectedFrom(spark:SparkSession, entitiesPath:String):String = {
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log.info("Retrieve last entities collected From")
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implicit val oafEncoder:Encoder[Result] = Encoders.kryo[Result]
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import spark.implicits._
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val entitiesDS = spark.read.load(s"$entitiesPath/*").as[Result]
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entitiesDS.filter(r => r.getDateofcollection!= null).map(_.getDateofcollection).select(max("value")).first.getString(0)
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}
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/**
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* Here all the spark applications runs this method
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* where the whole logic of the spark node is defined
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*/
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override def run(): Unit = {
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val sourcePath = parser.get("sourcePath")
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log.info(s"SourcePath is '$sourcePath'")
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val datacitePath = parser.get("datacitePath")
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log.info(s"DatacitePath is '$datacitePath'")
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log.info("Retrieve last entities collected From")
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implicit val oafEncoder:Encoder[Result] = Encoders.kryo[Result]
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val lastCollectionDate = retrieveLastCollectedFrom(spark, s"$sourcePath/entities")
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}
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}
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@ -79,7 +79,7 @@
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--executor-cores=${sparkExecutorCores}
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--executor-cores=${sparkExecutorCores}
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--driver-memory=${sparkDriverMemory}
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--driver-memory=${sparkDriverMemory}
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--conf spark.extraListeners=${spark2ExtraListeners}
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--conf spark.extraListeners=${spark2ExtraListeners}
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--conf spark.sql.shuffle.partitions=20000
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--conf spark.sql.shuffle.partitions=30000
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--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
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--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
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--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
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--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
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--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
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--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
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@ -2,12 +2,11 @@ package eu.dnetlib.dhp.sx.graph
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import com.fasterxml.jackson.databind.ObjectMapper
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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.application.ArgumentApplicationParser
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import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Relation, Software,Dataset => OafDataset}
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import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Relation, Result, Software, Dataset => OafDataset}
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import org.apache.commons.io.IOUtils
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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.SparkConf
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import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
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import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
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import org.slf4j.{Logger, LoggerFactory}
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import org.slf4j.{Logger, LoggerFactory}
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object SparkConvertRDDtoDataset {
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object SparkConvertRDDtoDataset {
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def main(args: Array[String]): Unit = {
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def main(args: Array[String]): Unit = {
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@ -40,31 +39,32 @@ object SparkConvertRDDtoDataset {
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log.info("Converting dataset")
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log.info("Converting dataset")
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val rddDataset = spark.sparkContext.textFile(s"$sourcePath/dataset").map(s => mapper.readValue(s, classOf[OafDataset]))
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val rddDataset =spark.sparkContext.textFile(s"$sourcePath/dataset").map(s => mapper.readValue(s, classOf[OafDataset])).filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
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spark.createDataset(rddDataset).as[OafDataset].write.mode(SaveMode.Overwrite).save(s"$entityPath/dataset")
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spark.createDataset(rddDataset).as[OafDataset].write.mode(SaveMode.Overwrite).save(s"$entityPath/dataset")
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log.info("Converting publication")
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log.info("Converting publication")
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val rddPublication = spark.sparkContext.textFile(s"$sourcePath/publication").map(s => mapper.readValue(s, classOf[Publication]))
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val rddPublication =spark.sparkContext.textFile(s"$sourcePath/publication").map(s => mapper.readValue(s, classOf[Publication])).filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
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spark.createDataset(rddPublication).as[Publication].write.mode(SaveMode.Overwrite).save(s"$entityPath/publication")
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spark.createDataset(rddPublication).as[Publication].write.mode(SaveMode.Overwrite).save(s"$entityPath/publication")
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log.info("Converting software")
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log.info("Converting software")
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val rddSoftware = spark.sparkContext.textFile(s"$sourcePath/software").map(s => mapper.readValue(s, classOf[Software]))
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val rddSoftware =spark.sparkContext.textFile(s"$sourcePath/software").map(s => mapper.readValue(s, classOf[Software])).filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
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spark.createDataset(rddSoftware).as[Software].write.mode(SaveMode.Overwrite).save(s"$entityPath/software")
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spark.createDataset(rddSoftware).as[Software].write.mode(SaveMode.Overwrite).save(s"$entityPath/software")
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log.info("Converting otherresearchproduct")
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log.info("Converting otherresearchproduct")
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val rddOtherResearchProduct = spark.sparkContext.textFile(s"$sourcePath/otherresearchproduct").map(s => mapper.readValue(s, classOf[OtherResearchProduct]))
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val rddOtherResearchProduct =spark.sparkContext.textFile(s"$sourcePath/otherresearchproduct").map(s => mapper.readValue(s, classOf[OtherResearchProduct])).filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
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spark.createDataset(rddOtherResearchProduct).as[OtherResearchProduct].write.mode(SaveMode.Overwrite).save(s"$entityPath/otherresearchproduct")
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spark.createDataset(rddOtherResearchProduct).as[OtherResearchProduct].write.mode(SaveMode.Overwrite).save(s"$entityPath/otherresearchproduct")
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log.info("Converting Relation")
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log.info("Converting Relation")
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val relationSemanticFilter = List("cites", "iscitedby", "merges", "ismergedin")
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val relationSemanticFilter = List("cites", "iscitedby","merges", "ismergedin", "HasAmongTopNSimilarDocuments","IsAmongTopNSimilarDocuments" )
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val rddRelation = spark.sparkContext.textFile(s"$sourcePath/relation")
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val rddRelation =spark.sparkContext.textFile(s"$sourcePath/relation")
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.map(s => mapper.readValue(s, classOf[Relation]))
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.map(s => mapper.readValue(s, classOf[Relation]))
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.filter(r => r.getSource.startsWith("50") && r.getTarget.startsWith("50"))
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.filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
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.filter(r=> r.getSource.startsWith("50") && r.getTarget.startsWith("50"))
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.filter(r => !relationSemanticFilter.exists(k => k.equalsIgnoreCase(r.getRelClass)))
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.filter(r => !relationSemanticFilter.exists(k => k.equalsIgnoreCase(r.getRelClass)))
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spark.createDataset(rddRelation).as[Relation].write.mode(SaveMode.Overwrite).save(s"$relPath")
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spark.createDataset(rddRelation).as[Relation].write.mode(SaveMode.Overwrite).save(s"$relPath")
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