[scholexplorer]

- Minor fix on SparkConvertRDDtoDataset
-first implementation of retrieve datacite dump
This commit is contained in:
Sandro La Bruzzo 2021-12-14 09:56:55 +01:00
parent e30e5ac8a8
commit e5bff64f2e
3 changed files with 69 additions and 15 deletions

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@ -0,0 +1,54 @@
package eu.dnetlib.dhp.sx.graph
import eu.dnetlib.dhp.application.AbstractScalaApplication
import eu.dnetlib.dhp.schema.oaf.{Oaf, Result}
import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
import org.apache.spark.sql.functions.max
import org.slf4j.Logger
class SparkRetrieveDataciteDelta (propertyPath:String, args:Array[String], log:Logger) extends AbstractScalaApplication(propertyPath, args, log:Logger) {
def retrieveLastCollectedFrom(spark:SparkSession, entitiesPath:String):String = {
log.info("Retrieve last entities collected From")
implicit val oafEncoder:Encoder[Result] = Encoders.kryo[Result]
import spark.implicits._
val entitiesDS = spark.read.load(s"$entitiesPath/*").as[Result]
entitiesDS.filter(r => r.getDateofcollection!= null).map(_.getDateofcollection).select(max("value")).first.getString(0)
}
/**
* Here all the spark applications runs this method
* where the whole logic of the spark node is defined
*/
override def run(): Unit = {
val sourcePath = parser.get("sourcePath")
log.info(s"SourcePath is '$sourcePath'")
val datacitePath = parser.get("datacitePath")
log.info(s"DatacitePath is '$datacitePath'")
log.info("Retrieve last entities collected From")
implicit val oafEncoder:Encoder[Result] = Encoders.kryo[Result]
val lastCollectionDate = retrieveLastCollectedFrom(spark, s"$sourcePath/entities")
}
}

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@ -79,7 +79,7 @@
--executor-cores=${sparkExecutorCores} --executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
--conf spark.extraListeners=${spark2ExtraListeners} --conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.shuffle.partitions=20000 --conf spark.sql.shuffle.partitions=30000
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}

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@ -2,12 +2,11 @@ package eu.dnetlib.dhp.sx.graph
import com.fasterxml.jackson.databind.ObjectMapper import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.application.ArgumentApplicationParser import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Relation, Software,Dataset => OafDataset} import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Relation, Result, Software, Dataset => OafDataset}
import org.apache.commons.io.IOUtils import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf import org.apache.spark.SparkConf
import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession} import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory} import org.slf4j.{Logger, LoggerFactory}
object SparkConvertRDDtoDataset { object SparkConvertRDDtoDataset {
def main(args: Array[String]): Unit = { def main(args: Array[String]): Unit = {
@ -40,31 +39,32 @@ object SparkConvertRDDtoDataset {
log.info("Converting dataset") log.info("Converting dataset")
val rddDataset = spark.sparkContext.textFile(s"$sourcePath/dataset").map(s => mapper.readValue(s, classOf[OafDataset])) val rddDataset =spark.sparkContext.textFile(s"$sourcePath/dataset").map(s => mapper.readValue(s, classOf[OafDataset])).filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
spark.createDataset(rddDataset).as[OafDataset].write.mode(SaveMode.Overwrite).save(s"$entityPath/dataset") spark.createDataset(rddDataset).as[OafDataset].write.mode(SaveMode.Overwrite).save(s"$entityPath/dataset")
log.info("Converting publication") log.info("Converting publication")
val rddPublication = spark.sparkContext.textFile(s"$sourcePath/publication").map(s => mapper.readValue(s, classOf[Publication])) val rddPublication =spark.sparkContext.textFile(s"$sourcePath/publication").map(s => mapper.readValue(s, classOf[Publication])).filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
spark.createDataset(rddPublication).as[Publication].write.mode(SaveMode.Overwrite).save(s"$entityPath/publication") spark.createDataset(rddPublication).as[Publication].write.mode(SaveMode.Overwrite).save(s"$entityPath/publication")
log.info("Converting software") log.info("Converting software")
val rddSoftware = spark.sparkContext.textFile(s"$sourcePath/software").map(s => mapper.readValue(s, classOf[Software])) val rddSoftware =spark.sparkContext.textFile(s"$sourcePath/software").map(s => mapper.readValue(s, classOf[Software])).filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
spark.createDataset(rddSoftware).as[Software].write.mode(SaveMode.Overwrite).save(s"$entityPath/software") spark.createDataset(rddSoftware).as[Software].write.mode(SaveMode.Overwrite).save(s"$entityPath/software")
log.info("Converting otherresearchproduct") log.info("Converting otherresearchproduct")
val rddOtherResearchProduct = spark.sparkContext.textFile(s"$sourcePath/otherresearchproduct").map(s => mapper.readValue(s, classOf[OtherResearchProduct])) val rddOtherResearchProduct =spark.sparkContext.textFile(s"$sourcePath/otherresearchproduct").map(s => mapper.readValue(s, classOf[OtherResearchProduct])).filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
spark.createDataset(rddOtherResearchProduct).as[OtherResearchProduct].write.mode(SaveMode.Overwrite).save(s"$entityPath/otherresearchproduct") spark.createDataset(rddOtherResearchProduct).as[OtherResearchProduct].write.mode(SaveMode.Overwrite).save(s"$entityPath/otherresearchproduct")
log.info("Converting Relation") log.info("Converting Relation")
val relationSemanticFilter = List("cites", "iscitedby", "merges", "ismergedin") val relationSemanticFilter = List("cites", "iscitedby","merges", "ismergedin", "HasAmongTopNSimilarDocuments","IsAmongTopNSimilarDocuments" )
val rddRelation = spark.sparkContext.textFile(s"$sourcePath/relation") val rddRelation =spark.sparkContext.textFile(s"$sourcePath/relation")
.map(s => mapper.readValue(s, classOf[Relation])) .map(s => mapper.readValue(s, classOf[Relation]))
.filter(r => r.getSource.startsWith("50") && r.getTarget.startsWith("50")) .filter(r=> r.getDataInfo!= null && r.getDataInfo.getDeletedbyinference == false)
.filter(r=> r.getSource.startsWith("50") && r.getTarget.startsWith("50"))
.filter(r => !relationSemanticFilter.exists(k => k.equalsIgnoreCase(r.getRelClass))) .filter(r => !relationSemanticFilter.exists(k => k.equalsIgnoreCase(r.getRelClass)))
spark.createDataset(rddRelation).as[Relation].write.mode(SaveMode.Overwrite).save(s"$relPath") spark.createDataset(rddRelation).as[Relation].write.mode(SaveMode.Overwrite).save(s"$relPath")