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Merge branch 'master' into stable_ids

This commit is contained in:
Claudio Atzori 2020-10-09 13:53:40 +02:00
parent 8958f20813 e751c1402f
commit 3e6c8bca39
13 changed files with 232 additions and 103 deletions
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2
dhp-workflows/dhp-doiboost/src/main/java/eu/dnetlib/doiboost/crossref/Crossref2Oaf.scala
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@ -14,6 +14,8 @@ import scala.collection.JavaConverters._
import scala.collection.mutable import scala.collection.mutable
import scala.util.matching.Regex import scala.util.matching.Regex
case class CrossrefDT(doi: String, json:String) {}
case class mappingAffiliation(name: String) {} case class mappingAffiliation(name: String) {}
case class mappingAuthor(given: Option[String], family: String, ORCID: Option[String], affiliation: Option[mappingAffiliation]) {} case class mappingAuthor(given: Option[String], family: String, ORCID: Option[String], affiliation: Option[mappingAffiliation]) {}

93
dhp-workflows/dhp-doiboost/src/main/java/eu/dnetlib/doiboost/crossref/CrossrefDataset.scala Normal file
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@ -0,0 +1,93 @@
package eu.dnetlib.doiboost.crossref
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf
import org.apache.spark.sql.expressions.Aggregator
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.json4s
import org.json4s.DefaultFormats
import org.json4s.jackson.JsonMethods.parse
import org.slf4j.{Logger, LoggerFactory}
object CrossrefDataset {
def extractTimestamp(input:String): Long = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
lazy val json: json4s.JValue = parse(input)
(json\"indexed"\"timestamp").extractOrElse[Long](0)
}
def main(args: Array[String]): Unit = {
val logger: Logger = LoggerFactory.getLogger(SparkMapDumpIntoOAF.getClass)
val conf: SparkConf = new SparkConf()
val parser = new ArgumentApplicationParser(IOUtils.toString(CrossrefDataset.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/crossref_to_dataset_params.json")))
parser.parseArgument(args)
val spark: SparkSession =
SparkSession
.builder()
.config(conf)
.appName(SparkMapDumpIntoOAF.getClass.getSimpleName)
.master(parser.get("master")).getOrCreate()
import spark.implicits._
val crossrefAggregator = new Aggregator[CrossrefDT, CrossrefDT, CrossrefDT] with Serializable {
override def zero: CrossrefDT = null
override def reduce(b: CrossrefDT, a: CrossrefDT): CrossrefDT = {
if (b == null)
return a
if (a == null)
return b
val tb = extractTimestamp(b.json)
val ta = extractTimestamp(a.json)
if(ta >tb) {
return a
}
b
}
override def merge(a: CrossrefDT, b: CrossrefDT): CrossrefDT = {
if (b == null)
return a
if (a == null)
return b
val tb = extractTimestamp(b.json)
val ta = extractTimestamp(a.json)
if(ta >tb) {
return a
}
b
}
override def bufferEncoder: Encoder[CrossrefDT] = implicitly[Encoder[CrossrefDT]]
override def outputEncoder: Encoder[CrossrefDT] = implicitly[Encoder[CrossrefDT]]
override def finish(reduction: CrossrefDT): CrossrefDT = reduction
}
val sourcePath:String = parser.get("sourcePath")
val targetPath:String = parser.get("targetPath")
val ds:Dataset[CrossrefDT] = spark.read.load(sourcePath).as[CrossrefDT]
ds.groupByKey(_.doi)
.agg(crossrefAggregator.toColumn)
.map(s=>s._2)
.write.mode(SaveMode.Overwrite).save(targetPath)
}
}

29
dhp-workflows/dhp-doiboost/src/main/resources/eu/dnetlib/dhp/doiboost/crossref/oozie_app/workflow.xml
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@ -46,11 +46,11 @@
<job-tracker>${jobTracker}</job-tracker> <job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node> <name-node>${nameNode}</name-node>
<main-class>eu.dnetlib.doiboost.crossref.CrossrefImporter</main-class> <main-class>eu.dnetlib.doiboost.crossref.CrossrefImporter</main-class>
<arg>-t</arg><arg>${workingPath}/input/crossref/index_dump</arg> <arg>-t</arg><arg>${workingPath}/input/crossref/index_dump_1</arg>
<arg>-n</arg><arg>${nameNode}</arg> <arg>-n</arg><arg>${nameNode}</arg>
<arg>-ts</arg><arg>${timestamp}</arg> <arg>-ts</arg><arg>${timestamp}</arg>
</java> </java>
<ok to="ExtractCrossrefToOAF"/> <ok to="End"/>
<error to="Kill"/> <error to="Kill"/>
</action> </action>
@ -68,7 +68,7 @@
--driver-memory=${sparkDriverMemory} --driver-memory=${sparkDriverMemory}
${sparkExtraOPT} ${sparkExtraOPT}
</spark-opts> </spark-opts>
<arg>--sourcePath</arg><arg>${workingPath}/input/crossref/index_dump,${workingPath}/crossref/index_dump</arg> <arg>--sourcePath</arg><arg>${workingPath}/input/crossref/index_dump,${workingPath}/input/crossref/index_dump_1,${workingPath}/crossref/index_dump</arg>
<arg>--targetPath</arg><arg>${workingPath}/input/crossref</arg> <arg>--targetPath</arg><arg>${workingPath}/input/crossref</arg>
<arg>--master</arg><arg>yarn-cluster</arg> <arg>--master</arg><arg>yarn-cluster</arg>
</spark> </spark>
@ -76,5 +76,28 @@
<error to="Kill"/> <error to="Kill"/>
</action> </action>
<action name="GenerateDataset">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>ExtractCrossrefToOAF</name>
<class>eu.dnetlib.doiboost.crossref.CrossrefDataset</class>
<jar>dhp-doiboost-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
${sparkExtraOPT}
</spark-opts>
<arg>--sourcePath</arg><arg>/data/doiboost/crossref/cr_dataset</arg>
<arg>--targetPath</arg><arg>/data/doiboost/crossref/crossrefDataset</arg>
<arg>--master</arg><arg>yarn-cluster</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>
</action>
<end name="End"/> <end name="End"/>
</workflow-app> </workflow-app>

6
dhp-workflows/dhp-doiboost/src/main/resources/eu/dnetlib/dhp/doiboost/crossref_to_dataset_params.json Normal file
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@ -0,0 +1,6 @@
[
{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the path of the sequencial file to read", "paramRequired": true},
{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the working dir path", "paramRequired": true},
{"paramName":"m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true}
]

2
dhp-workflows/dhp-doiboost/src/main/resources/eu/dnetlib/dhp/doiboost/intersection/oozie_app/workflow.xml
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@ -89,7 +89,7 @@
</spark-opts> </spark-opts>
<arg>--dbPublicationPath</arg><arg>${workingDirPath}/doiBoostPublicationFiltered</arg> <arg>--dbPublicationPath</arg><arg>${workingDirPath}/doiBoostPublicationFiltered</arg>
<arg>--dbDatasetPath</arg><arg>${workingDirPath}/crossrefDataset</arg> <arg>--dbDatasetPath</arg><arg>${workingDirPath}/crossrefDataset</arg>
<arg>--crossRefRelation</arg><arg>/data/doiboost/input/crossref/relations</arg> <arg>--crossRefRelation</arg><arg>${workingDirPath}/crossrefRelation</arg>
<arg>--dbaffiliationRelationPath</arg><arg>${workingDirPath}/doiBoostPublicationAffiliation</arg> <arg>--dbaffiliationRelationPath</arg><arg>${workingDirPath}/doiBoostPublicationAffiliation</arg>
<arg>-do</arg><arg>${workingDirPath}/doiBoostOrganization</arg> <arg>-do</arg><arg>${workingDirPath}/doiBoostOrganization</arg>
<arg>--targetPath</arg><arg>${workingDirPath}/actionDataSet</arg> <arg>--targetPath</arg><arg>${workingDirPath}/actionDataSet</arg>

59
dhp-workflows/dhp-doiboost/src/test/java/eu/dnetlib/dhp/doiboost/QueryTest.scala
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@ -1,54 +1,45 @@
package eu.dnetlib.dhp.doiboost package eu.dnetlib.dhp.doiboost
import eu.dnetlib.dhp.schema.oaf.{Publication, Relation, StructuredProperty, Dataset => OafDataset} import eu.dnetlib.dhp.schema.oaf.Project
import org.apache.spark.SparkContext
import org.apache.spark.sql.functions.{col, sum} import org.apache.spark.sql.functions.{col, sum}
import org.apache.hadoop.io.Text
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession} import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession}
import org.codehaus.jackson.map.ObjectMapper
import org.json4s.DefaultFormats
import org.json4s
import org.json4s.DefaultFormats
import org.json4s.JsonAST._
import org.json4s.jackson.JsonMethods._
import scala.:: import scala.::
import scala.collection.JavaConverters._ import scala.collection.JavaConverters._
class QueryTest { class QueryTest {
def extract_payload(input:String) :String = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
lazy val json: json4s.JValue = parse(input)
compact(render((json \ "payload")))
def extractLicense(p:Publication):Tuple2[String,String] = {
val tmp = p.getInstance().asScala.map(i => i.getLicense.getValue).distinct.mkString(",")
(p.getId,tmp)
} }
def myQuery(spark:SparkSession, sc:SparkContext): Unit = {
def hasDOI(publication: Publication, doi:String):Boolean = { implicit val mapEncoderPub: Encoder[Project] = Encoders.kryo[Project]
val s = publication.getOriginalId.asScala.filter(i => i.equalsIgnoreCase(doi)) // val ds:Dataset[Project] = spark.createDataset(sc.sequenceFile("", classOf[Text], classOf[Text])
// .map(_._2.toString)
s.nonEmpty // .map(s => new ObjectMapper().readValue(s, classOf[Project])))
//
} // ds.write.saveAsTable()
def hasNullHostedBy(publication: Publication):Boolean = {
publication.getInstance().asScala.exists(i => i.getHostedby == null || i.getHostedby.getValue == null)
}
def myQuery(spark:SparkSession): Unit = {
implicit val mapEncoderPub: Encoder[Publication] = Encoders.kryo[Publication]
implicit val mapEncoderDat: Encoder[OafDataset] = Encoders.kryo[OafDataset]
implicit val mapEncoderRel: Encoder[Relation] = Encoders.kryo[Relation]
val doiboostPubs:Dataset[Publication] = spark.read.load("/data/doiboost/process/doiBoostPublicationFiltered").as[Publication]
val relFunder: Dataset[Relation] = spark.read.format("org.apache.spark.sql.parquet").load("/data/doiboost/process/crossrefRelation").as[Relation]
doiboostPubs.filter(p => p.getDateofacceptance != null && p.getDateofacceptance.getValue!= null && p.getDateofacceptance.getValue.length > 0 )
doiboostPubs.filter(p=>hasDOI(p, "10.1016/j.is.2020.101522")).collect()(0).getDescription.get(0).getValue
doiboostPubs.filter(p=> hasNullHostedBy(p)).count()
doiboostPubs.map(p=> (p.getId, p.getBestaccessright.getClassname))(Encoders.tuple(Encoders.STRING,Encoders.STRING))
} }
} }

2
dhp-workflows/dhp-doiboost/src/test/java/eu/dnetlib/doiboost/crossref/CrossrefMappingTest.scala
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@ -19,8 +19,6 @@ class CrossrefMappingTest {
@Test @Test
def testFunderRelationshipsMapping(): Unit = { def testFunderRelationshipsMapping(): Unit = {
val template = Source.fromInputStream(getClass.getResourceAsStream("article_funder_template.json")).mkString val template = Source.fromInputStream(getClass.getResourceAsStream("article_funder_template.json")).mkString

6
dhp-workflows/dhp-graph-mapper/pom.xml
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@ -84,6 +84,12 @@
<version>${project.version}</version> <version>${project.version}</version>
</dependency> </dependency>
<dependency>
<groupId>eu.dnetlib.dhp</groupId>
<artifactId>dhp-dedup-openaire</artifactId>
<version>${project.version}</version>
</dependency>
<dependency> <dependency>
<groupId>com.jayway.jsonpath</groupId> <groupId>com.jayway.jsonpath</groupId>
<artifactId>json-path</artifactId> <artifactId>json-path</artifactId>

19
dhp-workflows/dhp-graph-mapper/src/main/java/eu/dnetlib/dhp/sx/ebi/EBIAggregator.scala
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@ -1,4 +1,5 @@
package eu.dnetlib.dhp.sx.ebi package eu.dnetlib.dhp.sx.ebi
import eu.dnetlib.dhp.oa.dedup.AuthorMerger
import eu.dnetlib.dhp.schema.oaf.{Publication, Relation, Dataset => OafDataset} import eu.dnetlib.dhp.schema.oaf.{Publication, Relation, Dataset => OafDataset}
import eu.dnetlib.dhp.schema.scholexplorer.{DLIDataset, DLIPublication, DLIUnknown} import eu.dnetlib.dhp.schema.scholexplorer.{DLIDataset, DLIPublication, DLIUnknown}
import org.apache.spark.sql.{Encoder, Encoders} import org.apache.spark.sql.{Encoder, Encoders}
@ -14,6 +15,7 @@ object EBIAggregator {
override def reduce(b: OafDataset, a: (String, OafDataset)): OafDataset = { override def reduce(b: OafDataset, a: (String, OafDataset)): OafDataset = {
b.mergeFrom(a._2) b.mergeFrom(a._2)
b.setAuthor(AuthorMerger.mergeAuthor(a._2.getAuthor, b.getAuthor))
if (b.getId == null) if (b.getId == null)
b.setId(a._2.getId) b.setId(a._2.getId)
b b
@ -22,6 +24,7 @@ object EBIAggregator {
override def merge(wx: OafDataset, wy: OafDataset): OafDataset = { override def merge(wx: OafDataset, wy: OafDataset): OafDataset = {
wx.mergeFrom(wy) wx.mergeFrom(wy)
wx.setAuthor(AuthorMerger.mergeAuthor(wy.getAuthor, wx.getAuthor))
if(wx.getId == null && wy.getId.nonEmpty) if(wx.getId == null && wy.getId.nonEmpty)
wx.setId(wy.getId) wx.setId(wy.getId)
wx wx
@ -35,8 +38,6 @@ object EBIAggregator {
Encoders.kryo(classOf[OafDataset]) Encoders.kryo(classOf[OafDataset])
} }
def getDLIUnknownAggregator(): Aggregator[(String, DLIUnknown), DLIUnknown, DLIUnknown] = new Aggregator[(String, DLIUnknown), DLIUnknown, DLIUnknown]{ def getDLIUnknownAggregator(): Aggregator[(String, DLIUnknown), DLIUnknown, DLIUnknown] = new Aggregator[(String, DLIUnknown), DLIUnknown, DLIUnknown]{
override def zero: DLIUnknown = new DLIUnknown() override def zero: DLIUnknown = new DLIUnknown()
@ -69,6 +70,7 @@ object EBIAggregator {
override def reduce(b: DLIDataset, a: (String, DLIDataset)): DLIDataset = { override def reduce(b: DLIDataset, a: (String, DLIDataset)): DLIDataset = {
b.mergeFrom(a._2) b.mergeFrom(a._2)
b.setAuthor(AuthorMerger.mergeAuthor(a._2.getAuthor, b.getAuthor))
if (b.getId == null) if (b.getId == null)
b.setId(a._2.getId) b.setId(a._2.getId)
b b
@ -76,6 +78,7 @@ object EBIAggregator {
override def merge(wx: DLIDataset, wy: DLIDataset): DLIDataset = { override def merge(wx: DLIDataset, wy: DLIDataset): DLIDataset = {
wx.mergeFrom(wy) wx.mergeFrom(wy)
wx.setAuthor(AuthorMerger.mergeAuthor(wy.getAuthor, wx.getAuthor))
if(wx.getId == null && wy.getId.nonEmpty) if(wx.getId == null && wy.getId.nonEmpty)
wx.setId(wy.getId) wx.setId(wy.getId)
wx wx
@ -96,6 +99,8 @@ object EBIAggregator {
override def reduce(b: DLIPublication, a: (String, DLIPublication)): DLIPublication = { override def reduce(b: DLIPublication, a: (String, DLIPublication)): DLIPublication = {
b.mergeFrom(a._2) b.mergeFrom(a._2)
b.setAuthor(AuthorMerger.mergeAuthor(a._2.getAuthor, b.getAuthor))
if (b.getId == null) if (b.getId == null)
b.setId(a._2.getId) b.setId(a._2.getId)
b b
@ -104,6 +109,7 @@ object EBIAggregator {
override def merge(wx: DLIPublication, wy: DLIPublication): DLIPublication = { override def merge(wx: DLIPublication, wy: DLIPublication): DLIPublication = {
wx.mergeFrom(wy) wx.mergeFrom(wy)
wx.setAuthor(AuthorMerger.mergeAuthor(wy.getAuthor, wx.getAuthor))
if(wx.getId == null && wy.getId.nonEmpty) if(wx.getId == null && wy.getId.nonEmpty)
wx.setId(wy.getId) wx.setId(wy.getId)
wx wx
@ -124,6 +130,7 @@ object EBIAggregator {
override def reduce(b: Publication, a: (String, Publication)): Publication = { override def reduce(b: Publication, a: (String, Publication)): Publication = {
b.mergeFrom(a._2) b.mergeFrom(a._2)
b.setAuthor(AuthorMerger.mergeAuthor(a._2.getAuthor, b.getAuthor))
if (b.getId == null) if (b.getId == null)
b.setId(a._2.getId) b.setId(a._2.getId)
b b
@ -132,6 +139,7 @@ object EBIAggregator {
override def merge(wx: Publication, wy: Publication): Publication = { override def merge(wx: Publication, wy: Publication): Publication = {
wx.mergeFrom(wy) wx.mergeFrom(wy)
wx.setAuthor(AuthorMerger.mergeAuthor(wy.getAuthor, wx.getAuthor))
if(wx.getId == null && wy.getId.nonEmpty) if(wx.getId == null && wy.getId.nonEmpty)
wx.setId(wy.getId) wx.setId(wy.getId)
wx wx
@ -145,7 +153,6 @@ object EBIAggregator {
Encoders.kryo(classOf[Publication]) Encoders.kryo(classOf[Publication])
} }
def getRelationAggregator(): Aggregator[(String, Relation), Relation, Relation] = new Aggregator[(String, Relation), Relation, Relation]{ def getRelationAggregator(): Aggregator[(String, Relation), Relation, Relation] = new Aggregator[(String, Relation), Relation, Relation]{
override def zero: Relation = new Relation() override def zero: Relation = new Relation()
@ -166,10 +173,4 @@ object EBIAggregator {
override def outputEncoder: Encoder[Relation] = override def outputEncoder: Encoder[Relation] =
Encoders.kryo(classOf[Relation]) Encoders.kryo(classOf[Relation])
} }
} }

8
dhp-workflows/dhp-graph-mapper/src/main/resources/eu/dnetlib/dhp/oa/graph/hive/oozie_app/lib/scripts/postprocessing.sql
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@ -1,10 +1,10 @@
DROP VIEW IF EXISTS ${hiveDbName}.result; DROP VIEW IF EXISTS ${hiveDbName}.result;
CREATE VIEW IF NOT EXISTS ${hiveDbName}.result as CREATE VIEW IF NOT EXISTS ${hiveDbName}.result as
select id, dateofcollection, title, publisher, bestaccessright, datainfo, collectedfrom, pid, author, resulttype, language, country, subject, description, dateofacceptance, relevantdate, embargoenddate, resourcetype, context, externalreference, instance from ${hiveDbName}.publication p select id, originalid, dateofcollection, title, publisher, bestaccessright, datainfo, collectedfrom, pid, author, resulttype, language, country, subject, description, dateofacceptance, relevantdate, embargoenddate, resourcetype, context, externalreference, instance from ${hiveDbName}.publication p
union all union all
select id, dateofcollection, title, publisher, bestaccessright, datainfo, collectedfrom, pid, author, resulttype, language, country, subject, description, dateofacceptance, relevantdate, embargoenddate, resourcetype, context, externalreference, instance from ${hiveDbName}.dataset d select id, originalid, dateofcollection, title, publisher, bestaccessright, datainfo, collectedfrom, pid, author, resulttype, language, country, subject, description, dateofacceptance, relevantdate, embargoenddate, resourcetype, context, externalreference, instance from ${hiveDbName}.dataset d
union all union all
select id, dateofcollection, title, publisher, bestaccessright, datainfo, collectedfrom, pid, author, resulttype, language, country, subject, description, dateofacceptance, relevantdate, embargoenddate, resourcetype, context, externalreference, instance from ${hiveDbName}.software s select id, originalid, dateofcollection, title, publisher, bestaccessright, datainfo, collectedfrom, pid, author, resulttype, language, country, subject, description, dateofacceptance, relevantdate, embargoenddate, resourcetype, context, externalreference, instance from ${hiveDbName}.software s
union all union all
select id, dateofcollection, title, publisher, bestaccessright, datainfo, collectedfrom, pid, author, resulttype, language, country, subject, description, dateofacceptance, relevantdate, embargoenddate, resourcetype, context, externalreference, instance from ${hiveDbName}.otherresearchproduct o; select id, originalid, dateofcollection, title, publisher, bestaccessright, datainfo, collectedfrom, pid, author, resulttype, language, country, subject, description, dateofacceptance, relevantdate, embargoenddate, resourcetype, context, externalreference, instance from ${hiveDbName}.otherresearchproduct o;

1
dhp-workflows/dhp-graph-mapper/src/test/java/eu/dnetlib/dhp/sx/graph/SparkScholexplorerGraphImporterTest.java
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@ -2,4 +2,5 @@
package eu.dnetlib.dhp.sx.graph; package eu.dnetlib.dhp.sx.graph;
public class SparkScholexplorerGraphImporterTest { public class SparkScholexplorerGraphImporterTest {
} }

10
dhp-workflows/dhp-graph-mapper/src/test/resources/eu/dnetlib/dhp/sx/graph/publication.json Normal file
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@ -0,0 +1,10 @@
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100
dhp-workflows/dhp-graph-provision-scholexplorer/src/main/java/eu/dnetlib/dhp/export/SparkExportContentForOpenAire.scala
View File

@ -32,10 +32,10 @@ object SparkExportContentForOpenAire {
.master(parser.get("master")).getOrCreate() .master(parser.get("master")).getOrCreate()
val sc:SparkContext = spark.sparkContext
val workingPath = parser.get("workingDirPath") val workingPath = parser.get("workingDirPath")
implicit val dliPubEncoder: Encoder[DLIPublication] = Encoders.kryo(classOf[DLIPublication])
implicit val dliDatEncoder: Encoder[DLIDataset] = Encoders.kryo(classOf[DLIDataset])
implicit val pubEncoder: Encoder[Publication] = Encoders.bean(classOf[Publication]) implicit val pubEncoder: Encoder[Publication] = Encoders.bean(classOf[Publication])
implicit val datEncoder: Encoder[OafDataset] = Encoders.bean(classOf[OafDataset]) implicit val datEncoder: Encoder[OafDataset] = Encoders.bean(classOf[OafDataset])
implicit val relEncoder: Encoder[Relation] = Encoders.bean(classOf[Relation]) implicit val relEncoder: Encoder[Relation] = Encoders.bean(classOf[Relation])
@ -43,40 +43,41 @@ object SparkExportContentForOpenAire {
import spark.implicits._ import spark.implicits._
val relRDD:RDD[Relation] = sc.textFile(s"$workingPath/relation_j") val dsRel = spark.read.load(s"$workingPath/relation_b").as[Relation]
.map(s => new ObjectMapper().readValue(s, classOf[Relation])) dsRel.filter(r => r.getDataInfo==null || r.getDataInfo.getDeletedbyinference ==false).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/relationDS")
.filter(p => p.getDataInfo.getDeletedbyinference == false)
spark.createDataset(relRDD).write.mode(SaveMode.Overwrite).save(s"$workingPath/relationDS")
val datRDD:RDD[OafDataset] = sc.textFile(s"$workingPath/dataset")
.map(s => new ObjectMapper().readValue(s, classOf[DLIDataset])) val dsPubs = spark.read.load(s"$workingPath/publication").as[DLIPublication]
dsPubs
.filter(p=>p.getDataInfo.getDeletedbyinference == false)
.map(DLIToOAF.convertDLIPublicationToOAF)
.filter(p=>p!= null)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/export/publicationDS")
val dsDataset = spark.read.load(s"$workingPath/dataset").as[DLIDataset]
dsDataset
.filter(p => p.getDataInfo.getDeletedbyinference == false) .filter(p => p.getDataInfo.getDeletedbyinference == false)
.map(DLIToOAF.convertDLIDatasetTOOAF).filter(p=>p!= null) .map(DLIToOAF.convertDLIDatasetTOOAF).filter(p=>p!= null)
spark.createDataset(datRDD).write.mode(SaveMode.Overwrite).save(s"$workingPath/datasetDS") .write.mode(SaveMode.Overwrite).save(s"$workingPath/export/datasetDS")
val pubRDD:RDD[Publication] = sc.textFile(s"$workingPath/publication")
.map(s => new ObjectMapper().readValue(s, classOf[DLIPublication]))
.filter(p => p.getDataInfo.getDeletedbyinference == false)
.map(DLIToOAF.convertDLIPublicationToOAF).filter(p=>p!= null)
spark.createDataset(pubRDD).write.mode(SaveMode.Overwrite).save(s"$workingPath/publicationDS")
val pubs:Dataset[Publication] = spark.read.load(s"$workingPath/publicationDS").as[Publication]
val dats :Dataset[OafDataset] = spark.read.load(s"$workingPath/datasetDS").as[OafDataset] val pubs:Dataset[Publication] = spark.read.load(s"$workingPath/export/publicationDS").as[Publication]
val relDS1 :Dataset[Relation] = spark.read.load(s"$workingPath/relationDS").as[Relation] val dats :Dataset[OafDataset] = spark.read.load(s"$workingPath/export/datasetDS").as[OafDataset]
val relDS1 :Dataset[Relation] = spark.read.load(s"$workingPath/export/relationDS").as[Relation]
val pub_id = pubs.select("id").distinct() val pub_id = pubs.select("id").distinct()
val dat_id = dats.select("id").distinct() val dat_id = dats.select("id").distinct()
pub_id.joinWith(relDS1, pub_id("id").equalTo(relDS1("source"))).map(k => k._2).write.mode(SaveMode.Overwrite).save(s"$workingPath/relationDS_f1") pub_id.joinWith(relDS1, pub_id("id").equalTo(relDS1("source"))).map(k => k._2).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/relationDS_f1")
val relDS2= spark.read.load(s"$workingPath/relationDS_f1").as[Relation] val relDS2= spark.read.load(s"$workingPath/export/relationDS_f1").as[Relation]
relDS2.joinWith(dat_id, relDS2("target").equalTo(dats("id"))).map(k => k._1).write.mode(SaveMode.Overwrite).save(s"$workingPath/relationDS_filtered") relDS2.joinWith(dat_id, relDS2("target").equalTo(dats("id"))).map(k => k._1).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/relationDS_filtered")
val r_source = relDS2.select(relDS2("source")).distinct() val r_source = relDS2.select(relDS2("source")).distinct()
@ -87,22 +88,20 @@ object SparkExportContentForOpenAire {
pubs.joinWith(r_source, pubs("id").equalTo(r_source("source")), "inner").map(k => k._1) pubs.joinWith(r_source, pubs("id").equalTo(r_source("source")), "inner").map(k => k._1)
.withColumn("row",row_number.over(w2)).where($"row" === 1).drop("row") .withColumn("row",row_number.over(w2)).where($"row" === 1).drop("row")
.write.mode(SaveMode.Overwrite).save(s"$workingPath/publicationDS_filtered") .write.mode(SaveMode.Overwrite).save(s"$workingPath/export/publicationDS_filtered")
dats.joinWith(r_target, dats("id").equalTo(r_target("target")), "inner").map(k => k._1) dats.joinWith(r_target, dats("id").equalTo(r_target("target")), "inner").map(k => k._1)
.withColumn("row",row_number.over(w2)).where($"row" === 1).drop("row") .withColumn("row",row_number.over(w2)).where($"row" === 1).drop("row")
.write.mode(SaveMode.Overwrite).save(s"$workingPath/datasetAS") .write.mode(SaveMode.Overwrite).save(s"$workingPath/export/datasetAS")
spark.createDataset(sc.textFile(s"$workingPath/dataset")
.map(s => new ObjectMapper().readValue(s, classOf[DLIDataset]))
.map(DLIToOAF.convertDLIDatasetToExternalReference)
.filter(p => p != null)).as[DLIExternalReference].write.mode(SaveMode.Overwrite).save(s"$workingPath/externalReference")
val pf = spark.read.load(s"$workingPath/publicationDS_filtered").select("id") dsDataset.map(DLIToOAF.convertDLIDatasetToExternalReference).filter(p => p != null).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/externalReference")
val relDS3 = spark.read.load(s"$workingPath/relationDS").as[Relation]
val pf = spark.read.load(s"$workingPath/export/publicationDS_filtered").select("id")
val relDS3 = spark.read.load(s"$workingPath/export/relationDS").as[Relation]
val relationTo = pf.joinWith(relDS3, pf("id").equalTo(relDS3("source")),"inner").map(t =>t._2) val relationTo = pf.joinWith(relDS3, pf("id").equalTo(relDS3("source")),"inner").map(t =>t._2)
val extRef = spark.read.load(s"$workingPath/externalReference").as[DLIExternalReference] val extRef = spark.read.load(s"$workingPath/export/externalReference").as[DLIExternalReference]
spark.createDataset(relationTo.joinWith(extRef, relationTo("target").equalTo(extRef("id")), "inner").map(d => { spark.createDataset(relationTo.joinWith(extRef, relationTo("target").equalTo(extRef("id")), "inner").map(d => {
val r = d._1 val r = d._1
@ -112,11 +111,11 @@ object SparkExportContentForOpenAire {
var dli_ext = ArrayBuffer[DLIExternalReference]() var dli_ext = ArrayBuffer[DLIExternalReference]()
f._2.foreach(d => if (dli_ext.size < 100) dli_ext += d ) f._2.foreach(d => if (dli_ext.size < 100) dli_ext += d )
(f._1, dli_ext) (f._1, dli_ext)
})).write.mode(SaveMode.Overwrite).save(s"$workingPath/externalReference_grouped") })).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/externalReference_grouped")
val pubf :Dataset[Publication] = spark.read.load(s"$workingPath/publicationDS_filtered").as[Publication] val pubf :Dataset[Publication] = spark.read.load(s"$workingPath/export/publicationDS_filtered").as[Publication]
val groupedERf:Dataset[(String, List[DLIExternalReference])]= spark.read.load(s"$workingPath/externalReference_grouped").as[(String, List[DLIExternalReference])] val groupedERf:Dataset[(String, List[DLIExternalReference])]= spark.read.load(s"$workingPath/export/externalReference_grouped").as[(String, List[DLIExternalReference])]
groupedERf.joinWith(pubf,pubf("id").equalTo(groupedERf("_1"))).map(t => groupedERf.joinWith(pubf,pubf("id").equalTo(groupedERf("_1"))).map(t =>
{ {
@ -128,29 +127,28 @@ object SparkExportContentForOpenAire {
} else } else
publication publication
} }
).write.mode(SaveMode.Overwrite).save(s"$workingPath/publicationAS") ).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/publicationAS")
spark.createDataset(sc.textFile(s"$workingPath/dataset") dsDataset
.map(s => new ObjectMapper().readValue(s, classOf[DLIDataset]))
.map(DLIToOAF.convertClinicalTrial) .map(DLIToOAF.convertClinicalTrial)
.filter(p => p != null)) .filter(p => p != null)
.write.mode(SaveMode.Overwrite).save(s"$workingPath/clinicalTrials") .write.mode(SaveMode.Overwrite).save(s"$workingPath/export/clinicalTrials")
val ct:Dataset[(String,String)] = spark.read.load(s"$workingPath/clinicalTrials").as[(String,String)] val ct:Dataset[(String,String)] = spark.read.load(s"$workingPath/export/clinicalTrials").as[(String,String)]
val relDS= spark.read.load(s"$workingPath/relationDS_f1").as[Relation] val relDS= spark.read.load(s"$workingPath/export/relationDS_f1").as[Relation]
relDS.joinWith(ct, relDS("target").equalTo(ct("_1")), "inner") relDS.joinWith(ct, relDS("target").equalTo(ct("_1")), "inner")
.map(k =>{ .map(k =>{
val currentRel = k._1 val currentRel = k._1
currentRel.setTarget(k._2._2) currentRel.setTarget(k._2._2)
currentRel currentRel
}).write.mode(SaveMode.Overwrite).save(s"$workingPath/clinicalTrialsRels") }).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/clinicalTrialsRels")
val clRels:Dataset[Relation] = spark.read.load(s"$workingPath/clinicalTrialsRels").as[Relation] val clRels:Dataset[Relation] = spark.read.load(s"$workingPath/export/clinicalTrialsRels").as[Relation]
val rels:Dataset[Relation] = spark.read.load(s"$workingPath/relationDS_filtered").as[Relation] val rels:Dataset[Relation] = spark.read.load(s"$workingPath/export/relationDS_filtered").as[Relation]
rels.union(clRels).flatMap(r => { rels.union(clRels).flatMap(r => {
val inverseRel = new Relation val inverseRel = new Relation
@ -162,18 +160,18 @@ object SparkExportContentForOpenAire {
inverseRel.setSubRelType(r.getSubRelType) inverseRel.setSubRelType(r.getSubRelType)
inverseRel.setRelClass(DLIToOAF.rel_inverse(r.getRelClass)) inverseRel.setRelClass(DLIToOAF.rel_inverse(r.getRelClass))
List(r, inverseRel) List(r, inverseRel)
}).write.mode(SaveMode.Overwrite).save(s"$workingPath/relationAS") }).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/relationAS")
spark.read.load(s"$workingPath/publicationAS").as[Publication].map(DLIToOAF.fixInstance).write.mode(SaveMode.Overwrite).save(s"$workingPath/publicationAS_fixed") spark.read.load(s"$workingPath/export/publicationAS").as[Publication].map(DLIToOAF.fixInstance).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/publicationAS_fixed")
spark.read.load(s"$workingPath/datasetAS").as[OafDataset].map(DLIToOAF.fixInstanceDataset).write.mode(SaveMode.Overwrite).save(s"$workingPath/datasetAS_fixed") spark.read.load(s"$workingPath/export/datasetAS").as[OafDataset].map(DLIToOAF.fixInstanceDataset).write.mode(SaveMode.Overwrite).save(s"$workingPath/export/datasetAS_fixed")
val fRels:Dataset[(String,String)] = spark.read.load(s"$workingPath/relationAS").as[Relation].map(DLIToOAF.toActionSet) val fRels:Dataset[(String,String)] = spark.read.load(s"$workingPath/export/relationAS").as[Relation].map(DLIToOAF.toActionSet)
val fpubs:Dataset[(String,String)] = spark.read.load(s"$workingPath/publicationAS_fixed").as[Publication].map(DLIToOAF.toActionSet) val fpubs:Dataset[(String,String)] = spark.read.load(s"$workingPath/export/publicationAS_fixed").as[Publication].map(DLIToOAF.toActionSet)
val fdats:Dataset[(String,String)] = spark.read.load(s"$workingPath/datasetAS_fixed").as[OafDataset].map(DLIToOAF.toActionSet) val fdats:Dataset[(String,String)] = spark.read.load(s"$workingPath/export/datasetAS_fixed").as[OafDataset].map(DLIToOAF.toActionSet)
fRels.union(fpubs).union(fdats).rdd.map(s => (new Text(s._1), new Text(s._2))).saveAsHadoopFile(s"$workingPath/rawset", classOf[Text], classOf[Text], classOf[SequenceFileOutputFormat[Text,Text]], classOf[GzipCodec]) fRels.union(fpubs).union(fdats).rdd.map(s => (new Text(s._1), new Text(s._2))).saveAsHadoopFile(s"$workingPath/export/rawset", classOf[Text], classOf[Text], classOf[SequenceFileOutputFormat[Text,Text]], classOf[GzipCodec])
} }