added first implementation of Pangaea Mapping

dhp-workflows/dhp-dedup-openaire/src/main/java/eu/dnetlib/dhp/oa/dedup/SparkPropagateRelation.java

@@ -139,8 +139,9 @@ public class SparkPropagateRelation extends AbstractSparkAction {
 
 		return relSourceTarget
 			.filter(
-				(FilterFunction<Tuple2<Tuple2<Tuple3<String, Relation, String>, Tuple2<String, String>>, Tuple2<String, String>>>)
+				(FilterFunction<Tuple2<Tuple2<Tuple3<String, Relation, String>, Tuple2<String, String>>, Tuple2<String, String>>>) r -> r
-						r -> r._1()._1() != null || r._2() != null)
+					._1()
+					._1() != null || r._2() != null)
 			.map(mapRel, Encoders.bean(Relation.class))
 			.distinct();
 	}

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/sx/pangaea/PangaeaUtils.scala

@@ -0,0 +1,85 @@
+package eu.dnetlib.sx.pangaea
+
+
+import org.apache.spark.sql.expressions.Aggregator
+import org.apache.spark.sql.{Encoder, Encoders}
+import org.json4s
+import org.json4s.DefaultFormats
+import org.json4s.jackson.JsonMethods.parse
+
+import java.text.SimpleDateFormat
+import java.util.Date
+
+
+case class PangaeaDataModel(datestamp:String, identifier:String, xml:String) {}
+
+
+
+object PangaeaUtils {
+
+
+  def toDataset(input:String):PangaeaDataModel = {
+    implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
+    lazy val json: json4s.JValue = parse(input)
+
+    val  d = new Date()
+    val s:String =  s"${new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSS")format(d)}Z"
+
+    val ds = (json \ "internal-datestamp").extractOrElse[String](s)
+    val identifier= (json \ "metadatalink").extractOrElse[String]()
+    val xml= (json \ "xml").extract[String]
+    PangaeaDataModel(ds, identifier,xml)
+  }
+
+
+  def getDatasetAggregator(): Aggregator[(String, PangaeaDataModel), PangaeaDataModel, PangaeaDataModel] =   new Aggregator[(String, PangaeaDataModel), PangaeaDataModel, PangaeaDataModel]{
+
+
+      override def zero: PangaeaDataModel = null
+
+      override def reduce(b: PangaeaDataModel, a: (String, PangaeaDataModel)): PangaeaDataModel = {
+        if (b == null)
+          a._2
+        else {
+          if (a == null)
+            b
+          else {
+            val ts1 = b.datestamp
+            val ts2 = a._2.datestamp
+            if (ts1 > ts2)
+              b
+            else
+              a._2
+
+          }
+        }
+      }
+
+      override def merge(b1: PangaeaDataModel, b2: PangaeaDataModel): PangaeaDataModel = {
+        if (b1 == null)
+          b2
+        else {
+          if (b2 == null)
+            b1
+          else {
+            val ts1 = b1.datestamp
+            val ts2 = b2.datestamp
+            if (ts1 > ts2)
+              b1
+            else
+              b2
+
+          }
+        }
+      }
+      override def finish(reduction: PangaeaDataModel): PangaeaDataModel = reduction
+
+      override def bufferEncoder: Encoder[PangaeaDataModel] = Encoders.kryo[PangaeaDataModel]
+
+      override def outputEncoder: Encoder[PangaeaDataModel] = Encoders.kryo[PangaeaDataModel]
+    }
+
+
+
+
+}

dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/sx/pangaea/SparkGeneratePanagaeaDataset.scala

@@ -0,0 +1,53 @@
+package eu.dnetlib.sx.pangaea
+
+import eu.dnetlib.dhp.application.ArgumentApplicationParser
+import eu.dnetlib.dhp.sx.ebi.SparkCreateEBIDataFrame
+import org.apache.spark.rdd.RDD
+import org.apache.spark.{SparkConf, SparkContext}
+import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
+import org.slf4j.{Logger, LoggerFactory}
+
+import scala.collection.JavaConverters._
+import scala.io.Source
+
+object SparkGeneratePanagaeaDataset {
+
+
+  def main(args: Array[String]): Unit = {
+    val logger: Logger = LoggerFactory.getLogger(getClass)
+    val conf: SparkConf = new SparkConf()
+    val parser = new ArgumentApplicationParser(Source.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/pangaea/pangaea_to_dataset.json")).mkString)
+    parser.parseArgument(args)
+
+
+    val spark: SparkSession =
+      SparkSession
+        .builder()
+        .config(conf)
+        .appName(SparkCreateEBIDataFrame.getClass.getSimpleName)
+        .master(parser.get("master")).getOrCreate()
+
+    parser.getObjectMap.asScala.foreach(s => logger.info(s"${s._1} -> ${s._2}"))
+    logger.info("Converting sequential file into Dataset")
+    val sc:SparkContext = spark.sparkContext
+
+    val workingPath:String = parser.get("workingPath")
+
+    implicit val pangaeaEncoders: Encoder[PangaeaDataModel] = Encoders.kryo[PangaeaDataModel]
+
+    val inputRDD:RDD[PangaeaDataModel] =  sc.textFile(s"$workingPath/update").map(s => PangaeaUtils.toDataset(s))
+
+    spark.createDataset(inputRDD).as[PangaeaDataModel]
+      .map(s => (s.identifier,s))(Encoders.tuple(Encoders.STRING, pangaeaEncoders))
+       .groupByKey(_._1)(Encoders.STRING)
+      .agg(PangaeaUtils.getDatasetAggregator().toColumn)
+      .map(s => s._2)
+      .write.mode(SaveMode.Overwrite).save(s"$workingPath/dataset_updated")
+
+  }
+
+
+
+
+
+}

dhp-workflows/dhp-graph-mapper/src/main/resources/eu/dnetlib/dhp/sx/pangaea/oozie_app/config-default.xml

@@ -0,0 +1,19 @@
+<configuration>
+    <property>
+        <name>jobTracker</name>
+        <value>yarnRM</value>
+    </property>
+    <property>
+        <name>nameNode</name>
+        <value>hdfs://nameservice1</value>
+    </property>
+    <property>
+        <name>oozie.use.system.libpath</name>
+        <value>true</value>
+    </property>
+    <property>
+        <name>oozie.action.sharelib.for.spark</name>
+        <value>spark2</value>
+    </property>
+
+</configuration>

dhp-workflows/dhp-graph-mapper/src/main/resources/eu/dnetlib/dhp/sx/pangaea/oozie_app/workflow.xml

@@ -0,0 +1,40 @@
+    <workflow-app name="Transform_Pangaea_Workflow" xmlns="uri:oozie:workflow:0.5">
+    <parameters>
+        <property>
+            <name>pangaeaWorkingPath</name>
+            <description>the Pangaea Working Path</description>
+        </property>
+    </parameters>
+
+    <start to="ConvertDataset"/>
+
+    <kill name="Kill">
+        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
+    </kill>
+
+    <action name="ConvertDataset">
+        <spark xmlns="uri:oozie:spark-action:0.2">
+            <master>yarn</master>
+            <mode>cluster</mode>
+            <name>Convert Pangaea to Dataset</name>
+            <class>eu.dnetlib.sx.pangaea.SparkGeneratePanagaeaDataset</class>
+            <jar>dhp-graph-mapper-${projectVersion}.jar</jar>
+            <spark-opts>
+                --executor-memory=${sparkExecutorMemory}
+                --executor-cores=${sparkExecutorCores}
+                --driver-memory=${sparkDriverMemory}
+                --conf spark.extraListeners=${spark2ExtraListeners}
+                --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
+                --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
+                --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
+            </spark-opts>
+            <arg>--workingPath</arg><arg>${pangaeaWorkingPath}</arg>
+            <arg>--master</arg><arg>yarn</arg>
+        </spark>
+        <ok to="End"/>
+        <error to="Kill"/>
+    </action>
+
+    <end name="End"/>
+
+</workflow-app>

dhp-workflows/dhp-graph-mapper/src/main/resources/eu/dnetlib/dhp/sx/pangaea/pangaea_to_dataset.json

@@ -0,0 +1,4 @@
+[
+  {"paramName":"mt",  "paramLongName":"master",             "paramDescription": "should be local or yarn",                                  "paramRequired": true},
+  {"paramName":"w",   "paramLongName":"workingPath",         "paramDescription": "the path of the sequencial file to read",                  "paramRequired": true}
+]

dhp-workflows/dhp-graph-mapper/src/test/java/eu/dnetlib/dhp/sx/pangaea/PangaeaTransformTest.scala

@@ -0,0 +1,25 @@
+package eu.dnetlib.dhp.sx.pangaea
+
+import org.junit.jupiter.api.Test
+import java.util.TimeZone
+import java.text.SimpleDateFormat
+import java.util.Date
+class PangaeaTransformTest {
+
+
+
+  @Test
+  def test_dateStamp() :Unit ={
+
+
+
+    val  d = new Date()
+
+    val s:String =  s"${new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSS")format(d)}Z"
+
+
+    println(s)
+
+  }
+
+}