115 lines
4.2 KiB
Scala
115 lines
4.2 KiB
Scala
package eu.dnetlib.dhp.sx.graph
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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.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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object SparkConvertRDDtoDataset {
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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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val parser = new ArgumentApplicationParser(
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IOUtils.toString(
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getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/convert_dataset_json_params.json")
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)
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)
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parser.parseArgument(args)
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val spark: SparkSession =
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SparkSession
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.builder()
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.config(conf)
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.appName(getClass.getSimpleName)
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.master(parser.get("master"))
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.getOrCreate()
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val sourcePath = parser.get("sourcePath")
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log.info(s"sourcePath -> $sourcePath")
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val t = parser.get("targetPath")
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log.info(s"targetPath -> $t")
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val entityPath = s"$t/entities"
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val relPath = s"$t/relation"
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val mapper = new ObjectMapper()
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implicit val datasetEncoder: Encoder[OafDataset] = Encoders.kryo(classOf[OafDataset])
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implicit val publicationEncoder: Encoder[Publication] = Encoders.kryo(classOf[Publication])
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implicit val relationEncoder: Encoder[Relation] = Encoders.kryo(classOf[Relation])
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implicit val orpEncoder: Encoder[OtherResearchProduct] =
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Encoders.kryo(classOf[OtherResearchProduct])
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implicit val softwareEncoder: Encoder[Software] = Encoders.kryo(classOf[Software])
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log.info("Converting dataset")
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val rddDataset = spark.sparkContext
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.textFile(s"$sourcePath/dataset")
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.map(s => mapper.readValue(s, classOf[OafDataset]))
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.filter(r => r.getDataInfo != null && r.getDataInfo.getDeletedbyinference == false)
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spark
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.createDataset(rddDataset)
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.as[OafDataset]
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.write
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.mode(SaveMode.Overwrite)
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.save(s"$entityPath/dataset")
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log.info("Converting publication")
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val rddPublication = spark.sparkContext
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.textFile(s"$sourcePath/publication")
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.map(s => mapper.readValue(s, classOf[Publication]))
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.filter(r => r.getDataInfo != null && r.getDataInfo.getDeletedbyinference == false)
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spark
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.createDataset(rddPublication)
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.as[Publication]
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.write
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.mode(SaveMode.Overwrite)
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.save(s"$entityPath/publication")
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log.info("Converting software")
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val rddSoftware = spark.sparkContext
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.textFile(s"$sourcePath/software")
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.map(s => mapper.readValue(s, classOf[Software]))
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.filter(r => r.getDataInfo != null && r.getDataInfo.getDeletedbyinference == false)
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spark
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.createDataset(rddSoftware)
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.as[Software]
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.write
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.mode(SaveMode.Overwrite)
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.save(s"$entityPath/software")
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log.info("Converting otherresearchproduct")
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val rddOtherResearchProduct = spark.sparkContext
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.textFile(s"$sourcePath/otherresearchproduct")
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.map(s => mapper.readValue(s, classOf[OtherResearchProduct]))
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.filter(r => r.getDataInfo != null && r.getDataInfo.getDeletedbyinference == false)
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spark
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.createDataset(rddOtherResearchProduct)
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.as[OtherResearchProduct]
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.write
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.mode(SaveMode.Overwrite)
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.save(s"$entityPath/otherresearchproduct")
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log.info("Converting Relation")
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val relationSemanticFilter = List(
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"cites",
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"iscitedby",
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"merges",
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"ismergedin",
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"HasAmongTopNSimilarDocuments",
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"IsAmongTopNSimilarDocuments"
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)
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val rddRelation = spark.sparkContext
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.textFile(s"$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(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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