44 lines
1.7 KiB
Scala
44 lines
1.7 KiB
Scala
package eu.dnetlib.dhp.sx.graph
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import com.cloudera.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, 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 entities = List(
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("dataset", classOf[OafDataset]),
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("otherresearchproduct", classOf[OtherResearchProduct]),
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("publication", classOf[Publication]),
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("software", classOf[Software])
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)
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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(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/graph/convert_dataset_json_params.json")))
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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")).getOrCreate()
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val sourcePath = parser.get("sourcePath")
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log.info(s"sourcePath -> $sourcePath")
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val targetPath = parser.get("targetPath")
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log.info(s"targetPath -> $targetPath")
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val mapper = new ObjectMapper()
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implicit val resultEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
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entities.foreach{
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e =>
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val rdd =spark.sparkContext.textFile(s"$sourcePath/${e._1}").map(s => mapper.readValue(s, e._2))
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spark.createDataset(rdd).as[Result].write.mode(SaveMode.Overwrite).save(s"$targetPath/${e._1}")
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}
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}
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}
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