Fixed problem on duplicated identifier
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264723ffd8
commit
ec3e238de6
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@ -14,7 +14,7 @@ import scala.collection.JavaConverters._
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import scala.collection.mutable
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import scala.util.matching.Regex
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case class CrossrefDT(doi: String, json:String) {}
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case class CrossrefDT(doi: String, json:String, timestamp: Long) {}
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case class mappingAffiliation(name: String) {}
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@ -29,69 +29,90 @@ object SparkMapDumpIntoOAF {
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.appName(SparkMapDumpIntoOAF.getClass.getSimpleName)
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.master(parser.get("master")).getOrCreate()
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implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
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implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
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implicit val mapEncoderRelatons: Encoder[Relation] = Encoders.kryo[Relation]
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implicit val mapEncoderDatasets: Encoder[oaf.Dataset] = Encoders.kryo[OafDataset]
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val sc = spark.sparkContext
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val targetPath = parser.get("targetPath")
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import spark.implicits._
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sc.sequenceFile(parser.get("sourcePath"), classOf[IntWritable], classOf[Text])
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.map(k => k._2.toString).map(CrossrefImporter.decompressBlob)
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.flatMap(k => Crossref2Oaf.convert(k)).saveAsObjectFile(s"${targetPath}/mixObject")
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val inputRDD = sc.objectFile[Oaf](s"${targetPath}/mixObject").filter(p=> p!= null)
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val distinctPubs:RDD[Publication] = inputRDD.filter(k => k != null && k.isInstanceOf[Publication])
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.map(k => k.asInstanceOf[Publication]).map { p: Publication => Tuple2(p.getId, p) }.reduceByKey { case (p1: Publication, p2: Publication) =>
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var r = if (p1 == null) p2 else p1
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if (p1 != null && p2 != null) {
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if (p1.getLastupdatetimestamp != null && p2.getLastupdatetimestamp != null) {
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if (p1.getLastupdatetimestamp < p2.getLastupdatetimestamp)
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r = p2
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else
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r = p1
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} else {
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r = if (p1.getLastupdatetimestamp == null) p2 else p1
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}
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}
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r
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}.map(_._2)
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val pubs:Dataset[Publication] = spark.createDataset(distinctPubs)
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pubs.write.mode(SaveMode.Overwrite).save(s"${targetPath}/publication")
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spark.read.load(parser.get("sourcePath")).as[CrossrefDT]
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.flatMap(k => Crossref2Oaf.convert(k.json))
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.filter(o => o != null)
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.write.mode(SaveMode.Overwrite).save(s"$targetPath/mixObject")
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val distincDatasets:RDD[OafDataset] = inputRDD.filter(k => k != null && k.isInstanceOf[OafDataset])
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.map(k => k.asInstanceOf[OafDataset]).map(p => Tuple2(p.getId, p)).reduceByKey { case (p1: OafDataset, p2: OafDataset) =>
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var r = if (p1 == null) p2 else p1
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if (p1 != null && p2 != null) {
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if (p1.getLastupdatetimestamp != null && p2.getLastupdatetimestamp != null) {
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if (p1.getLastupdatetimestamp < p2.getLastupdatetimestamp)
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r = p2
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else
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r = p1
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} else {
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r = if (p1.getLastupdatetimestamp == null) p2 else p1
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}
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}
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r
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}.map(_._2)
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val ds:Dataset[Oaf] = spark.read.load(s"$targetPath/mixObject").as[Oaf]
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spark.createDataset(distincDatasets).write.mode(SaveMode.Overwrite).save(s"${targetPath}/dataset")
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ds.filter(o => o.isInstanceOf[Publication]).map(o => o.asInstanceOf[Publication]).write.save(s"$targetPath/publication")
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ds.filter(o => o.isInstanceOf[Relation]).map(o => o.asInstanceOf[Relation]).write.save(s"$targetPath/relation")
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ds.filter(o => o.isInstanceOf[OafDataset]).map(o => o.asInstanceOf[OafDataset]).write.save(s"$targetPath/dataset")
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val distinctRels =inputRDD.filter(k => k != null && k.isInstanceOf[Relation])
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.map(k => k.asInstanceOf[Relation]).map(r=> (s"${r.getSource}::${r.getTarget}",r))
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.reduceByKey { case (p1: Relation, p2: Relation) =>
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if (p1 == null) p2 else p1
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}.map(_._2)
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val rels: Dataset[Relation] = spark.createDataset(distinctRels)
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rels.write.mode(SaveMode.Overwrite).save(s"${targetPath}/relations")
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//
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//
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//
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// sc.sequenceFile(parser.get("sourcePath"), classOf[IntWritable], classOf[Text])
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// .map(k => k._2.toString).map(CrossrefImporter.decompressBlob)
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// .flatMap(k => Crossref2Oaf.convert(k)).saveAsObjectFile(s"${targetPath}/mixObject")
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//
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// val inputRDD = sc.objectFile[Oaf](s"${targetPath}/mixObject").filter(p=> p!= null)
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//
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// val distinctPubs:RDD[Publication] = inputRDD.filter(k => k != null && k.isInstanceOf[Publication])
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// .map(k => k.asInstanceOf[Publication]).map { p: Publication => Tuple2(p.getId, p) }.reduceByKey { case (p1: Publication, p2: Publication) =>
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// var r = if (p1 == null) p2 else p1
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// if (p1 != null && p2 != null) {
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// if (p1.getLastupdatetimestamp != null && p2.getLastupdatetimestamp != null) {
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// if (p1.getLastupdatetimestamp < p2.getLastupdatetimestamp)
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// r = p2
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// else
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// r = p1
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// } else {
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// r = if (p1.getLastupdatetimestamp == null) p2 else p1
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// }
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// }
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// r
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// }.map(_._2)
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//
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// val pubs:Dataset[Publication] = spark.createDataset(distinctPubs)
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// pubs.write.mode(SaveMode.Overwrite).save(s"${targetPath}/publication")
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//
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//
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// val distincDatasets:RDD[OafDataset] = inputRDD.filter(k => k != null && k.isInstanceOf[OafDataset])
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// .map(k => k.asInstanceOf[OafDataset]).map(p => Tuple2(p.getId, p)).reduceByKey { case (p1: OafDataset, p2: OafDataset) =>
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// var r = if (p1 == null) p2 else p1
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// if (p1 != null && p2 != null) {
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// if (p1.getLastupdatetimestamp != null && p2.getLastupdatetimestamp != null) {
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// if (p1.getLastupdatetimestamp < p2.getLastupdatetimestamp)
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// r = p2
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// else
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// r = p1
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// } else {
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// r = if (p1.getLastupdatetimestamp == null) p2 else p1
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// }
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// }
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// r
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// }.map(_._2)
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//
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// spark.createDataset(distincDatasets).write.mode(SaveMode.Overwrite).save(s"${targetPath}/dataset")
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//
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//
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//
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// val distinctRels =inputRDD.filter(k => k != null && k.isInstanceOf[Relation])
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// .map(k => k.asInstanceOf[Relation]).map(r=> (s"${r.getSource}::${r.getTarget}",r))
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// .reduceByKey { case (p1: Relation, p2: Relation) =>
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// if (p1 == null) p2 else p1
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// }.map(_._2)
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//
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// val rels: Dataset[Relation] = spark.createDataset(distinctRels)
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//
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// rels.write.mode(SaveMode.Overwrite).save(s"${targetPath}/relations")
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}
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@ -16,10 +16,10 @@
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<name>sparkExecutorCores</name>
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<description>number of cores used by single executor</description>
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</property>
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<property>
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<name>timestamp</name>
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<description>Timestamp for incremental Harvesting</description>
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</property>
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<!-- <property>-->
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<!-- <name>timestamp</name>-->
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<!-- <description>Timestamp for incremental Harvesting</description>-->
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<!-- </property>-->
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</parameters>
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@ -30,29 +30,29 @@
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<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
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</kill>
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<action name="ResetWorkingPath">
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<fs>
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<delete path='${workingPath}/input/crossref/index_dump'/>
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<!-- <mkdir path='${workingPath}/input/crossref'/>-->
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</fs>
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<ok to="ImportCrossRef"/>
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<error to="Kill"/>
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</action>
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<!-- <action name="ResetWorkingPath">-->
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<!-- <fs>-->
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<!-- <delete path='${workingPath}/input/crossref/index_dump'/>-->
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<!--<!– <mkdir path='${workingPath}/input/crossref'/>–>-->
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<!-- </fs>-->
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<!-- <ok to="ImportCrossRef"/>-->
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<!-- <error to="Kill"/>-->
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<!-- </action>-->
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<action name="ImportCrossRef">
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<java>
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<job-tracker>${jobTracker}</job-tracker>
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<name-node>${nameNode}</name-node>
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<main-class>eu.dnetlib.doiboost.crossref.CrossrefImporter</main-class>
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<arg>-t</arg><arg>${workingPath}/input/crossref/index_dump_1</arg>
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<arg>-n</arg><arg>${nameNode}</arg>
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<arg>-ts</arg><arg>${timestamp}</arg>
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</java>
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<ok to="End"/>
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<error to="Kill"/>
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</action>
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<!-- <action name="ImportCrossRef">-->
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<!-- <java>-->
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<!-- <job-tracker>${jobTracker}</job-tracker>-->
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<!-- <name-node>${nameNode}</name-node>-->
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<!-- <main-class>eu.dnetlib.doiboost.crossref.CrossrefImporter</main-class>-->
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<!-- <arg>-t</arg><arg>${workingPath}/input/crossref/index_dump_1</arg>-->
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<!-- <arg>-n</arg><arg>${nameNode}</arg>-->
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<!-- <arg>-ts</arg><arg>${timestamp}</arg>-->
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<!-- </java>-->
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<!-- <ok to="End"/>-->
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<!-- <error to="Kill"/>-->
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<!-- </action>-->
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<action name="ExtractCrossrefToOAF">
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@ -68,7 +68,7 @@
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--driver-memory=${sparkDriverMemory}
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${sparkExtraOPT}
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</spark-opts>
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<arg>--sourcePath</arg><arg>${workingPath}/input/crossref/index_dump,${workingPath}/input/crossref/index_dump_1,${workingPath}/crossref/index_dump</arg>
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<arg>--sourcePath</arg><arg>${workingPath}/input/crossref/crossref_ds</arg>
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<arg>--targetPath</arg><arg>${workingPath}/input/crossref</arg>
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<arg>--master</arg><arg>yarn-cluster</arg>
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</spark>
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@ -78,26 +78,26 @@
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<action name="GenerateDataset">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<master>yarn-cluster</master>
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<mode>cluster</mode>
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<name>ExtractCrossrefToOAF</name>
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<class>eu.dnetlib.doiboost.crossref.CrossrefDataset</class>
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<jar>dhp-doiboost-${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=${sparkDriverMemory}
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${sparkExtraOPT}
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</spark-opts>
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<arg>--sourcePath</arg><arg>/data/doiboost/crossref/cr_dataset</arg>
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<arg>--targetPath</arg><arg>/data/doiboost/crossref/crossrefDataset</arg>
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<arg>--master</arg><arg>yarn-cluster</arg>
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</spark>
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<ok to="End"/>
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<error to="Kill"/>
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</action>
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<!-- <action name="GenerateDataset">-->
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<!-- <spark xmlns="uri:oozie:spark-action:0.2">-->
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<!-- <master>yarn-cluster</master>-->
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<!-- <mode>cluster</mode>-->
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<!-- <name>ExtractCrossrefToOAF</name>-->
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<!-- <class>eu.dnetlib.doiboost.crossref.CrossrefDataset</class>-->
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<!-- <jar>dhp-doiboost-${projectVersion}.jar</jar>-->
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<!-- <spark-opts>-->
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<!-- --executor-memory=${sparkExecutorMemory}-->
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<!-- --executor-cores=${sparkExecutorCores}-->
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<!-- --driver-memory=${sparkDriverMemory}-->
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<!-- ${sparkExtraOPT}-->
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<!-- </spark-opts>-->
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<!-- <arg>--sourcePath</arg><arg>/data/doiboost/crossref/cr_dataset</arg>-->
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<!-- <arg>--targetPath</arg><arg>/data/doiboost/crossref/crossrefDataset</arg>-->
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<!-- <arg>--master</arg><arg>yarn-cluster</arg>-->
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<!-- </spark>-->
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<!-- <ok to="End"/>-->
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<!-- <error to="Kill"/>-->
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<!-- </action>-->
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<end name="End"/>
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</workflow-app>
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