implemented oozie workflow to generate scholix dump filtering relclass semantic
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@ -2,4 +2,5 @@
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{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
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{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the source Path", "paramRequired": true},
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{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the path of the raw graph", "paramRequired": true}
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{"paramName":"r", "paramLongName":"filterRelation", "paramDescription": "the relation to filter", "paramRequired": false}
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]
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@ -3,5 +3,7 @@
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{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the source Path", "paramRequired": true},
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{"paramName":"su", "paramLongName":"scholixUpdatePath", "paramDescription": "the scholix updated Path", "paramRequired": false},
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{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the path of the raw graph", "paramRequired": true},
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{"paramName":"o", "paramLongName":"objectType", "paramDescription": "should be scholix or Summary", "paramRequired": true}
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{"paramName":"o", "paramLongName":"objectType", "paramDescription": "should be scholix or Summary", "paramRequired": true},
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{"paramName":"mp", "paramLongName":"maxPidNumberFilter", "paramDescription": "filter max number of pids in source/target", "paramRequired": false}
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]
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@ -0,0 +1,10 @@
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<configuration>
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<property>
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<name>oozie.use.system.libpath</name>
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<value>true</value>
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</property>
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<property>
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<name>oozie.action.sharelib.for.spark</name>
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<value>spark2</value>
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</property>
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</configuration>
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@ -0,0 +1,145 @@
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<workflow-app name="Create Scholix Dump" xmlns="uri:oozie:workflow:0.5">
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<parameters>
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<property>
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<name>sourcePath</name>
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<description>the working dir base path</description>
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</property>
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<property>
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<name>targetPath</name>
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<description>the final graph path</description>
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</property>
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<property>
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<name>relationFilter</name>
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<description>Filter relation semantic</description>
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</property>
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<property>
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<name>maxNumberOfPid</name>
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<description>filter relation with at least #maxNumberOfPid</description>
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</property>
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</parameters>
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<start to="ImportDatasetEntities"/>
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<kill name="Kill">
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<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
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</kill>
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<action name="ImportDatasetEntities">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<master>yarn</master>
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<mode>cluster</mode>
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<name>Import JSONRDD to Dataset kryo</name>
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<class>eu.dnetlib.dhp.sx.graph.SparkConvertRDDtoDataset</class>
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<jar>dhp-graph-mapper-${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=${sparkDriverMemory}
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--conf spark.extraListeners=${spark2ExtraListeners}
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--conf spark.sql.shuffle.partitions=3000
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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.eventLog.dir=${nameNode}${spark2EventLogDir}
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</spark-opts>
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<arg>--master</arg><arg>yarn</arg>
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<arg>--sourcePath</arg><arg>${sourcePath}</arg>
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<arg>--targetPath</arg><arg>${targetPath}</arg>
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<arg>--filterRelation</arg><arg>${relationFilter}</arg>
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</spark>
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<ok to="CreateSummaries"/>
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<error to="Kill"/>
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</action>
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<action name="CreateSummaries">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<master>yarn</master>
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<mode>cluster</mode>
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<name>Convert Entities to summaries</name>
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<class>eu.dnetlib.dhp.sx.graph.SparkCreateSummaryObject</class>
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<jar>dhp-graph-mapper-${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=${sparkDriverMemory}
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--conf spark.extraListeners=${spark2ExtraListeners}
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--conf spark.sql.shuffle.partitions=20000
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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.eventLog.dir=${nameNode}${spark2EventLogDir}
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</spark-opts>
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<arg>--master</arg><arg>yarn</arg>
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<arg>--sourcePath</arg><arg>${targetPath}/entities</arg>
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<arg>--targetPath</arg><arg>${targetPath}/provision/summaries</arg>
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</spark>
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<ok to="CreateScholix"/>
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<error to="Kill"/>
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</action>
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<action name="CreateScholix">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<master>yarn</master>
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<mode>cluster</mode>
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<name>Generate Scholix Dataset</name>
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<class>eu.dnetlib.dhp.sx.graph.SparkCreateScholix</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.extraListeners=${spark2ExtraListeners}
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--conf spark.sql.shuffle.partitions=30000
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--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
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--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
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--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
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</spark-opts>
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<arg>--master</arg><arg>yarn</arg>
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<arg>--summaryPath</arg><arg>${targetPath}/provision/summaries</arg>
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<arg>--targetPath</arg><arg>${targetPath}/provision/scholix</arg>
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<arg>--relationPath</arg><arg>${targetPath}/relation</arg>
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</spark>
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<ok to="DropJSONPath"/>
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<error to="Kill"/>
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</action>
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<action name="DropJSONPath">
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<fs>
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<delete path='${targetPath}/json'/>
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<mkdir path='${targetPath}/json/'/>
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</fs>
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<ok to="SerializeScholix"/>
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<error to="Kill"/>
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</action>
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<action name="SerializeScholix">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<master>yarn</master>
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<mode>cluster</mode>
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<name>Serialize scholix to JSON</name>
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<class>eu.dnetlib.dhp.sx.graph.SparkConvertObjectToJson</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.extraListeners=${spark2ExtraListeners}
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--conf spark.sql.shuffle.partitions=6000
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--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
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--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
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--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
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</spark-opts>
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<arg>--master</arg><arg>yarn</arg>
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<arg>--sourcePath</arg><arg>${targetPath}/provision/scholix/scholix</arg>
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<arg>--targetPath</arg><arg>${targetPath}/json/scholix_json</arg>
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<arg>--objectType</arg><arg>scholix</arg>
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<arg>--maxPidNumberFilter</arg><arg>maxNumberOfPid</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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@ -4,6 +4,7 @@ import com.fasterxml.jackson.databind.ObjectMapper
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import eu.dnetlib.dhp.application.ArgumentApplicationParser
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import eu.dnetlib.dhp.schema.sx.scholix.Scholix
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import eu.dnetlib.dhp.schema.sx.summary.ScholixSummary
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import eu.dnetlib.dhp.sx.graph.SparkConvertObjectToJson.toInt
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import org.apache.commons.io.IOUtils
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import org.apache.hadoop.io.compress.GzipCodec
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import org.apache.spark.SparkConf
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@ -12,6 +13,14 @@ import org.slf4j.{Logger, LoggerFactory}
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object SparkConvertObjectToJson {
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def toInt(s: String): Option[Int] = {
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try {
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Some(s.toInt)
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} catch {
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case e: Exception => None
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}
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}
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def main(args: Array[String]): Unit = {
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val log: Logger = LoggerFactory.getLogger(getClass)
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val conf: SparkConf = new SparkConf()
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log.info(s"objectType -> $objectType")
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val scholixUpdatePath = parser.get("scholixUpdatePath")
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log.info(s"scholixUpdatePath -> $scholixUpdatePath")
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val maxPidNumberFilter = parser.get("maxPidNumberFilter")
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log.info(s"maxPidNumberFilter -> $maxPidNumberFilter")
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implicit val scholixEncoder: Encoder[Scholix] = Encoders.kryo[Scholix]
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implicit val summaryEncoder: Encoder[ScholixSummary] = Encoders.kryo[ScholixSummary]
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case "scholix" =>
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log.info("Serialize Scholix")
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val d: Dataset[Scholix] = spark.read.load(sourcePath).as[Scholix]
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val u: Dataset[Scholix] = spark.read.load(s"$scholixUpdatePath/scholix").as[Scholix]
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d.union(u)
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// val u: Dataset[Scholix] = spark.read.load(s"$scholixUpdatePath/scholix").as[Scholix]
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if (maxPidNumberFilter != null && toInt(maxPidNumberFilter).isDefined) {
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val mp = toInt(maxPidNumberFilter).get
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d
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.filter(s => (s.getSource.getIdentifier.size() <= mp) && (s.getTarget.getIdentifier.size() <= mp))
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.map(s => mapper.writeValueAsString(s))(Encoders.STRING)
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.rdd
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.saveAsTextFile(targetPath, classOf[GzipCodec])
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} else {
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d
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.repartition(8000)
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.map(s => mapper.writeValueAsString(s))(Encoders.STRING)
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.rdd
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.saveAsTextFile(targetPath, classOf[GzipCodec])
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}
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case "summary" =>
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log.info("Serialize Summary")
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val d: Dataset[ScholixSummary] = spark.read.load(sourcePath).as[ScholixSummary]
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@ -4,9 +4,11 @@ import com.fasterxml.jackson.databind.ObjectMapper
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import eu.dnetlib.dhp.application.ArgumentApplicationParser
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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.lang3.StringUtils
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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.slf4j.{Logger, LoggerFactory}
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import scala.collection.JavaConverters._
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object SparkConvertRDDtoDataset {
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val t = parser.get("targetPath")
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log.info(s"targetPath -> $t")
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val filterRelation = parser.get("filterRelation")
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log.info(s"filterRelation -> $filterRelation")
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val entityPath = s"$t/entities"
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val relPath = s"$t/relation"
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val mapper = new ObjectMapper()
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log.info("Converting Relation")
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if (filterRelation != null && StringUtils.isNoneBlank(filterRelation)) {
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val rddRelation = spark.sparkContext
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.textFile(s"$sourcePath/relation")
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.map(s => mapper.readValue(s, classOf[Relation]))
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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 OpenCitations relations
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.filter(r =>
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r.getCollectedfrom != null && r.getCollectedfrom.size() > 0 && !r.getCollectedfrom.asScala.exists(k =>
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"opencitations".equalsIgnoreCase(k.getValue)
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)
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)
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.filter(r => r.getRelClass != null && r.getRelClass.equalsIgnoreCase(filterRelation))
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spark.createDataset(rddRelation).as[Relation].write.mode(SaveMode.Overwrite).save(s"$relPath")
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} else {
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val relationSemanticFilter = List(
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// "cites",
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// "iscitedby",
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// "cites",
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// "iscitedby",
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"merges",
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"ismergedin",
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"HasAmongTopNSimilarDocuments",
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)
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.filter(r => !relationSemanticFilter.exists(k => k.equalsIgnoreCase(r.getRelClass)))
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spark.createDataset(rddRelation).as[Relation].write.mode(SaveMode.Overwrite).save(s"$relPath")
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}
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}
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}
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