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tolerant parsing of OAF-store-graph mdstores #180

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claudio.atzori merged 2 commits from graph_interpretation_mdstores into beta 2022-01-04 11:32:29 +01:00
Conversation 0 Commits 2 Files Changed 12 +65 -29
7 changed files with 65 additions and 29 deletions
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13
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/collection/CollectionUtils.scala
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@ -1,7 +1,9 @@
package eu.dnetlib.dhp.collection
import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.schema.common.ModelSupport
import eu.dnetlib.dhp.schema.oaf.{Oaf, OafEntity, Relation}
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode}
object CollectionUtils {
@ -46,4 +48,15 @@ object CollectionUtils {
List()
}
def saveDataset(d: Dataset[Oaf], targetPath: String):Unit = {
implicit val resultEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
val mapper = new ObjectMapper
d
.flatMap(i => CollectionUtils.fixRelations(i))
.filter(i => i != null)
.map(r => mapper.writeValueAsString(r))(Encoders.STRING)
.write.mode(SaveMode.Overwrite).save(targetPath)
}
}

16
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/datacite/GenerateDataciteDatasetSpark.scala
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@ -2,14 +2,14 @@ package eu.dnetlib.dhp.datacite
import com.fasterxml.jackson.databind.ObjectMapper
import eu.dnetlib.dhp.application.AbstractScalaApplication
import eu.dnetlib.dhp.collection.CollectionUtils.fixRelations
import eu.dnetlib.dhp.collection.CollectionUtils
import eu.dnetlib.dhp.common.Constants.{MDSTORE_DATA_PATH, MDSTORE_SIZE_PATH}
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.mdstore.{MDStoreVersion, MetadataRecord}
import eu.dnetlib.dhp.schema.oaf.Oaf
import eu.dnetlib.dhp.utils.DHPUtils.writeHdfsFile
import eu.dnetlib.dhp.utils.ISLookupClientFactory
import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
@ -73,12 +73,12 @@ class GenerateDataciteDatasetSpark (propertyPath:String, args:Array[String], log
implicit val mrEncoder: Encoder[MetadataRecord] = Encoders.kryo[MetadataRecord]
implicit val resEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
spark.read.load(sourcePath).as[DataciteType]
.filter(d => d.isActive)
.flatMap(d => DataciteToOAFTransformation.generateOAF(d.json, d.timestamp, d.timestamp, vocabularies, exportLinks))
.filter(d => d != null)
.flatMap(i => fixRelations(i)).filter(i => i != null)
.write.mode(SaveMode.Overwrite).save(targetPath)
CollectionUtils.saveDataset(
spark.read.load(sourcePath).as[DataciteType]
.filter(d => d.isActive)
.flatMap(d => DataciteToOAFTransformation.generateOAF(d.json, d.timestamp, d.timestamp, vocabularies, exportLinks))
.filter(d => d != null),
targetPath)
}
}

10
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/SparkTransformBioDatabaseToOAF.scala
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@ -6,7 +6,7 @@ import eu.dnetlib.dhp.schema.oaf.Oaf
import eu.dnetlib.dhp.sx.bio.BioDBToOAF.ScholixResolved
import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf
import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
object SparkTransformBioDatabaseToOAF {
@ -36,13 +36,13 @@ object SparkTransformBioDatabaseToOAF {
import spark.implicits._
database.toUpperCase() match {
case "UNIPROT" =>
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)
CollectionUtils.saveDataset(spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.uniprotToOAF(i))), targetPath)
case "PDB" =>
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)
CollectionUtils.saveDataset(spark.createDataset(sc.textFile(dbPath).flatMap(i => BioDBToOAF.pdbTOOaf(i))), targetPath)
case "SCHOLIX" =>
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)
CollectionUtils.saveDataset(spark.read.load(dbPath).as[ScholixResolved].map(i => BioDBToOAF.scholixResolvedToOAF(i)), targetPath)
case "CROSSREF_LINKS" =>
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)
CollectionUtils.saveDataset(spark.createDataset(sc.textFile(dbPath).map(i => BioDBToOAF.crossrefLinksToOaf(i))), targetPath)
}
}

14
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/ebi/SparkCreateBaselineDataFrame.scala
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@ -1,8 +1,9 @@
package eu.dnetlib.dhp.sx.bio.ebi
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.collection.CollectionUtils
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup
import eu.dnetlib.dhp.schema.oaf.Result
import eu.dnetlib.dhp.schema.oaf.{Oaf, Result}
import eu.dnetlib.dhp.sx.bio.pubmed._
import eu.dnetlib.dhp.utils.ISLookupClientFactory
import org.apache.commons.io.IOUtils
@ -177,7 +178,7 @@ object SparkCreateBaselineDataFrame {
implicit val PMEncoder: Encoder[PMArticle] = Encoders.kryo(classOf[PMArticle])
implicit val PMJEncoder: Encoder[PMJournal] = Encoders.kryo(classOf[PMJournal])
implicit val PMAEncoder: Encoder[PMAuthor] = Encoders.kryo(classOf[PMAuthor])
implicit val resultEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
implicit val resultEncoder: Encoder[Oaf] = Encoders.kryo(classOf[Oaf])
if (!"true".equalsIgnoreCase(skipUpdate)) {
downloadBaseLineUpdate(s"$workingPath/baseline", hdfsServerUri)
@ -192,9 +193,10 @@ object SparkCreateBaselineDataFrame {
}
val exported_dataset = spark.read.load(s"$workingPath/baseline_dataset").as[PMArticle]
exported_dataset
.map(a => PubMedToOaf.convert(a, vocabularies)).as[Result]
.filter(p => p != null)
.write.mode(SaveMode.Overwrite).save(targetPath)
CollectionUtils.saveDataset(exported_dataset
.map(a => PubMedToOaf.convert(a, vocabularies)).as[Oaf]
.filter(p => p != null),
targetPath)
}
}

7
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/ebi/SparkEBILinksToOaf.scala
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@ -34,10 +34,9 @@ object SparkEBILinksToOaf {
val ebLinks: Dataset[EBILinkItem] = spark.read.load(sourcePath).as[EBILinkItem].filter(l => l.links != null && l.links.startsWith("{"))
ebLinks.flatMap(j => BioDBToOAF.parse_ebi_links(j.links))
CollectionUtils.saveDataset(ebLinks.flatMap(j => BioDBToOAF.parse_ebi_links(j.links))
.filter(p => BioDBToOAF.EBITargetLinksFilter(p))
.flatMap(p => BioDBToOAF.convertEBILinksToOaf(p))
.flatMap(i => CollectionUtils.fixRelations(i)).filter(i => i != null)
.write.mode(SaveMode.Overwrite).save(targetPath)
.flatMap(p => BioDBToOAF.convertEBILinksToOaf(p)),
targetPath)
}
}

2
dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/pubmed/PubMedToOaf.scala
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@ -109,7 +109,7 @@ object PubMedToOaf {
* @param vocabularies the vocabularies
* @return The OAF instance if the mapping did not fail
*/
def convert(article: PMArticle, vocabularies: VocabularyGroup): Result = {
def convert(article: PMArticle, vocabularies: VocabularyGroup): Oaf = {
if (article.getPublicationTypes == null)
return null

32
dhp-workflows/dhp-graph-mapper/src/main/scala/eu/dnetlib/dhp/oa/graph/raw/CopyHdfsOafSparkApplication.scala
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@ -1,6 +1,6 @@
package eu.dnetlib.dhp.oa.graph.raw
import com.fasterxml.jackson.databind.ObjectMapper
import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper}
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.common.HdfsSupport
import eu.dnetlib.dhp.schema.common.ModelSupport
@ -8,7 +8,10 @@ import eu.dnetlib.dhp.schema.oaf.Oaf
import eu.dnetlib.dhp.utils.DHPUtils
import org.apache.spark.sql.{Encoder, Encoders, SaveMode, SparkSession}
import org.apache.spark.{SparkConf, SparkContext}
import org.json4s.DefaultFormats
import org.json4s.jackson.JsonMethods.parse
import org.slf4j.LoggerFactory
import scala.collection.JavaConverters._
import scala.io.Source
@ -45,18 +48,21 @@ object CopyHdfsOafSparkApplication {
log.info("hdfsPath: {}", hdfsPath)
implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
import spark.implicits._
val paths = DHPUtils.mdstorePaths(mdstoreManagerUrl, mdFormat, mdLayout, mdInterpretation, true).asScala
val validPaths: List[String] = paths.filter(p => HdfsSupport.exists(p, sc.hadoopConfiguration)).toList
if (validPaths.nonEmpty) {
val oaf = spark.read.load(validPaths: _*).as[Oaf]
val mapper = new ObjectMapper()
val l = ModelSupport.oafTypes.entrySet.asScala.map(e => e.getKey).toList
val oaf = spark.read.load(validPaths: _*).as[String]
val mapper = new ObjectMapper().configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false)
val l = ModelSupport.oafTypes.entrySet.asScala.toList
l.foreach(
e =>
oaf.filter(o => o.getClass.getSimpleName.equalsIgnoreCase(e))
oaf
.filter(o => isOafType(o, e.getKey))
.map(j => mapper.readValue(j, e.getValue).asInstanceOf[Oaf])
.map(s => mapper.writeValueAsString(s))(Encoders.STRING)
.write
.option("compression", "gzip")
@ -65,4 +71,20 @@ object CopyHdfsOafSparkApplication {
)
}
}
def isOafType(input: String, oafType: String): Boolean = {
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
lazy val json: org.json4s.JValue = parse(input)
if (oafType == "relation") {
val hasSource = (json \ "source").extractOrElse[String](null)
val hasTarget = (json \ "target").extractOrElse[String](null)
hasSource != null && hasTarget != null
} else {
val hasId = (json \ "id").extractOrElse[String](null)
val resultType = (json \ "resulttype" \ "classid").extractOrElse[String](null)
hasId != null && oafType.equalsIgnoreCase(resultType)
}
}
}