mergin with branch beta
This commit is contained in:
commit
639190370a
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@ -1,7 +1,9 @@
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package eu.dnetlib.dhp.collection
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import com.fasterxml.jackson.databind.ObjectMapper
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import eu.dnetlib.dhp.schema.common.ModelSupport
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import eu.dnetlib.dhp.schema.oaf.{Oaf, OafEntity, Relation}
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import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode}
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object CollectionUtils {
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@ -46,4 +48,18 @@ object CollectionUtils {
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List()
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}
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def saveDataset(dataset: Dataset[Oaf], targetPath: String): Unit = {
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implicit val resultEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
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val mapper = new ObjectMapper
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dataset
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.flatMap(i => CollectionUtils.fixRelations(i))
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.filter(i => i != null)
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.map(r => mapper.writeValueAsString(r))(Encoders.STRING)
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.write
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.text(targetPath)
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}
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}
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@ -2,14 +2,14 @@ package eu.dnetlib.dhp.datacite
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import com.fasterxml.jackson.databind.ObjectMapper
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import eu.dnetlib.dhp.application.AbstractScalaApplication
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import eu.dnetlib.dhp.collection.CollectionUtils.fixRelations
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import eu.dnetlib.dhp.collection.CollectionUtils
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import eu.dnetlib.dhp.common.Constants.{MDSTORE_DATA_PATH, MDSTORE_SIZE_PATH}
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import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
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import eu.dnetlib.dhp.schema.mdstore.{MDStoreVersion, MetadataRecord}
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import eu.dnetlib.dhp.schema.oaf.Oaf
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import eu.dnetlib.dhp.utils.DHPUtils.writeHdfsFile
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import eu.dnetlib.dhp.utils.ISLookupClientFactory
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import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
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import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
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import org.slf4j.{Logger, LoggerFactory}
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@ -38,7 +38,7 @@ class GenerateDataciteDatasetSpark (propertyPath:String, args:Array[String], log
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val cleanedMdStoreVersion = mapper.readValue(mdstoreOutputVersion, classOf[MDStoreVersion])
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val outputBasePath = cleanedMdStoreVersion.getHdfsPath
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log.info(s"outputBasePath is '$outputBasePath'")
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val targetPath = s"$outputBasePath/$MDSTORE_DATA_PATH"
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val targetPath = s"$outputBasePath$MDSTORE_DATA_PATH"
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log.info(s"targetPath is '$targetPath'")
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generateDataciteDataset(sourcePath, exportLinks, vocabularies, targetPath, spark)
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@ -54,7 +54,7 @@ class GenerateDataciteDatasetSpark (propertyPath:String, args:Array[String], log
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* @param outputBasePath
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*/
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def reportTotalSize( targetPath: String, outputBasePath: String ):Unit = {
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val total_items = spark.read.load(targetPath).count()
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val total_items = spark.read.text(targetPath).count()
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writeHdfsFile(spark.sparkContext.hadoopConfiguration, s"$total_items", outputBasePath + MDSTORE_SIZE_PATH)
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}
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@ -73,12 +73,12 @@ class GenerateDataciteDatasetSpark (propertyPath:String, args:Array[String], log
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implicit val mrEncoder: Encoder[MetadataRecord] = Encoders.kryo[MetadataRecord]
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implicit val resEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
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spark.read.load(sourcePath).as[DataciteType]
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.filter(d => d.isActive)
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.flatMap(d => DataciteToOAFTransformation.generateOAF(d.json, d.timestamp, d.timestamp, vocabularies, exportLinks))
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.filter(d => d != null)
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.flatMap(i => fixRelations(i)).filter(i => i != null)
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.write.mode(SaveMode.Overwrite).save(targetPath)
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CollectionUtils.saveDataset(
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spark.read.load(sourcePath).as[DataciteType]
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.filter(d => d.isActive)
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.flatMap(d => DataciteToOAFTransformation.generateOAF(d.json, d.timestamp, d.timestamp, vocabularies, exportLinks))
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.filter(d => d != null),
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targetPath)
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}
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}
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@ -6,7 +6,7 @@ import eu.dnetlib.dhp.schema.oaf.Oaf
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import eu.dnetlib.dhp.sx.bio.BioDBToOAF.ScholixResolved
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import org.apache.commons.io.IOUtils
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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.apache.spark.sql.{Encoder, Encoders, SparkSession}
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import org.slf4j.{Logger, LoggerFactory}
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object SparkTransformBioDatabaseToOAF {
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@ -36,13 +36,13 @@ object SparkTransformBioDatabaseToOAF {
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import spark.implicits._
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database.toUpperCase() match {
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case "UNIPROT" =>
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spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.uniprotToOAF(i))).flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
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CollectionUtils.saveDataset(spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.uniprotToOAF(i))), targetPath)
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case "PDB" =>
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spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.pdbTOOaf(i))).flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
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CollectionUtils.saveDataset(spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.pdbTOOaf(i))), targetPath)
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case "SCHOLIX" =>
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spark.read.load(dbPath).as[ScholixResolved].map(i => BioDBToOAF.scholixResolvedToOAF(i)).flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
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CollectionUtils.saveDataset(spark.read.load(dbPath).as[ScholixResolved].map(i => BioDBToOAF.scholixResolvedToOAF(i)), targetPath)
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case "CROSSREF_LINKS" =>
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spark.createDataset(sc.textFile(dbPath).map(i => BioDBToOAF.crossrefLinksToOaf(i))).flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null).write.mode(SaveMode.Overwrite).save(targetPath)
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CollectionUtils.saveDataset(spark.createDataset(sc.textFile(dbPath).map(i => BioDBToOAF.crossrefLinksToOaf(i))), targetPath)
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}
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}
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@ -1,8 +1,9 @@
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package eu.dnetlib.dhp.sx.bio.ebi
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import eu.dnetlib.dhp.application.ArgumentApplicationParser
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import eu.dnetlib.dhp.collection.CollectionUtils
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import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
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import eu.dnetlib.dhp.schema.oaf.Result
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import eu.dnetlib.dhp.schema.oaf.{Oaf, Result}
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import eu.dnetlib.dhp.sx.bio.pubmed._
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import eu.dnetlib.dhp.utils.ISLookupClientFactory
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import org.apache.commons.io.IOUtils
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@ -177,7 +178,7 @@ object SparkCreateBaselineDataFrame {
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implicit val PMEncoder: Encoder[PMArticle] = Encoders.kryo(classOf[PMArticle])
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implicit val PMJEncoder: Encoder[PMJournal] = Encoders.kryo(classOf[PMJournal])
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implicit val PMAEncoder: Encoder[PMAuthor] = Encoders.kryo(classOf[PMAuthor])
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implicit val resultEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
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implicit val resultEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
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if (!"true".equalsIgnoreCase(skipUpdate)) {
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downloadBaseLineUpdate(s"$workingPath/baseline", hdfsServerUri)
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@ -192,9 +193,10 @@ object SparkCreateBaselineDataFrame {
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}
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val exported_dataset = spark.read.load(s"$workingPath/baseline_dataset").as[PMArticle]
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exported_dataset
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.map(a => PubMedToOaf.convert(a, vocabularies)).as[Result]
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.filter(p => p != null)
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.write.mode(SaveMode.Overwrite).save(targetPath)
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CollectionUtils.saveDataset(exported_dataset
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.map(a => PubMedToOaf.convert(a, vocabularies)).as[Oaf]
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.filter(p => p != null),
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targetPath)
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}
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}
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@ -34,10 +34,9 @@ object SparkEBILinksToOaf {
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val ebLinks: Dataset[EBILinkItem] = spark.read.load(sourcePath).as[EBILinkItem].filter(l => l.links != null && l.links.startsWith("{"))
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ebLinks.flatMap(j => BioDBToOAF.parse_ebi_links(j.links))
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CollectionUtils.saveDataset(ebLinks.flatMap(j => BioDBToOAF.parse_ebi_links(j.links))
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.filter(p => BioDBToOAF.EBITargetLinksFilter(p))
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.flatMap(p => BioDBToOAF.convertEBILinksToOaf(p))
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.flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null)
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.write.mode(SaveMode.Overwrite).save(targetPath)
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.flatMap(p => BioDBToOAF.convertEBILinksToOaf(p)),
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targetPath)
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}
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}
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@ -109,7 +109,7 @@ object PubMedToOaf {
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* @param vocabularies the vocabularies
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* @return The OAF instance if the mapping did not fail
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*/
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def convert(article: PMArticle, vocabularies: VocabularyGroup): Result = {
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def convert(article: PMArticle, vocabularies: VocabularyGroup): Oaf = {
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if (article.getPublicationTypes == null)
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return null
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@ -1,6 +1,6 @@
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package eu.dnetlib.dhp.oa.graph.raw
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import com.fasterxml.jackson.databind.ObjectMapper
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import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper}
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import eu.dnetlib.dhp.application.ArgumentApplicationParser
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import eu.dnetlib.dhp.common.HdfsSupport
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import eu.dnetlib.dhp.schema.common.ModelSupport
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@ -8,7 +8,10 @@ import eu.dnetlib.dhp.schema.oaf.Oaf
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import eu.dnetlib.dhp.utils.DHPUtils
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import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
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import org.apache.spark.{SparkConf, SparkContext}
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import org.json4s.DefaultFormats
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import org.json4s.jackson.JsonMethods.parse
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import org.slf4j.LoggerFactory
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import scala.collection.JavaConverters._
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import scala.io.Source
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@ -50,19 +53,39 @@ object CopyHdfsOafSparkApplication {
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val validPaths: List[String] = paths.filter(p => HdfsSupport.exists(p, sc.hadoopConfiguration)).toList
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val types = ModelSupport.oafTypes.entrySet
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.asScala
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.map(e => Tuple2(e.getKey, e.getValue))
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if (validPaths.nonEmpty) {
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val oaf = spark.read.load(validPaths: _*).as[Oaf]
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val mapper = new ObjectMapper()
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val l = ModelSupport.oafTypes.entrySet.asScala.map(e => e.getKey).toList
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l.foreach(
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e =>
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oaf.filter(o => o.getClass.getSimpleName.equalsIgnoreCase(e))
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.map(s => mapper.writeValueAsString(s))(Encoders.STRING)
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.write
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.option("compression", "gzip")
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.mode(SaveMode.Append)
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.text(s"$hdfsPath/${e}")
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val oaf = spark.read.textFile(validPaths: _*)
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val mapper = new ObjectMapper().configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false)
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types.foreach(t => oaf
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.filter(o => isOafType(o, t._1))
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.map(j => mapper.readValue(j, t._2).asInstanceOf[Oaf])
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.map(s => mapper.writeValueAsString(s))(Encoders.STRING)
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.write
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.option("compression", "gzip")
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.mode(SaveMode.Append)
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.text(s"$hdfsPath/${t._1}")
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)
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}
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}
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def isOafType(input: String, oafType: String): Boolean = {
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implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
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lazy val json: org.json4s.JValue = parse(input)
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if (oafType == "relation") {
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val hasSource = (json \ "source").extractOrElse[String](null)
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val hasTarget = (json \ "target").extractOrElse[String](null)
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hasSource != null && hasTarget != null
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} else {
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val hasId = (json \ "id").extractOrElse[String](null)
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val resultType = (json \ "resulttype" \ "classid").extractOrElse[String](null)
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hasId != null && oafType.equalsIgnoreCase(resultType)
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}
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}
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}
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@ -0,0 +1,65 @@
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package eu.dnetlib.dhp.oa.graph.raw;
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import static org.junit.jupiter.api.Assertions.assertFalse;
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import static org.junit.jupiter.api.Assertions.assertTrue;
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import java.io.IOException;
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import org.apache.commons.io.IOUtils;
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import org.junit.jupiter.api.Test;
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public class CopyHdfsOafSparkApplicationTest {
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@Test
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void testIsOafType() throws IOException {
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assertTrue(
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CopyHdfsOafSparkApplication
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.isOafType(
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IOUtils
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.toString(
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getClass().getResourceAsStream("/eu/dnetlib/dhp/oa/graph/raw/publication_1.json")),
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"publication"));
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assertTrue(
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CopyHdfsOafSparkApplication
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.isOafType(
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IOUtils
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.toString(
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getClass().getResourceAsStream("/eu/dnetlib/dhp/oa/graph/raw/dataset_1.json")),
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"dataset"));
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assertTrue(
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CopyHdfsOafSparkApplication
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.isOafType(
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IOUtils
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.toString(
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getClass().getResourceAsStream("/eu/dnetlib/dhp/oa/graph/raw/relation_1.json")),
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"relation"));
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assertFalse(
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CopyHdfsOafSparkApplication
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.isOafType(
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IOUtils
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.toString(
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getClass().getResourceAsStream("/eu/dnetlib/dhp/oa/graph/raw/publication_1.json")),
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"dataset"));
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assertFalse(
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CopyHdfsOafSparkApplication
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.isOafType(
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IOUtils
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.toString(
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getClass().getResourceAsStream("/eu/dnetlib/dhp/oa/graph/raw/dataset_1.json")),
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"publication"));
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assertTrue(
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CopyHdfsOafSparkApplication
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.isOafType(
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IOUtils
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.toString(
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getClass()
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.getResourceAsStream(
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"/eu/dnetlib/dhp/oa/graph/raw/publication_2_unknownProperty.json")),
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"publication"));
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|
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}
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}
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File diff suppressed because one or more lines are too long
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@ -0,0 +1 @@
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