50 lines
1.6 KiB
Scala
50 lines
1.6 KiB
Scala
package eu.dnetlib.dhp.sx.ebi
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import eu.dnetlib.dhp.application.ArgumentApplicationParser
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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.rdd.RDD
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import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
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import eu.dnetlib.dhp.sx.ebi.model.{PMArticle, PMAuthor, PMJournal, PMParser}
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import scala.io.Source
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import scala.xml.pull.XMLEventReader
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object SparkCreateBaselineDataFrame {
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def main(args: Array[String]): Unit = {
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val conf: SparkConf = new SparkConf()
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val parser = new ArgumentApplicationParser(IOUtils.toString(SparkCreateEBIDataFrame.getClass.getResourceAsStream("/eu/dnetlib/dhp/sx/ebi/ebi_to_df_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(SparkCreateEBIDataFrame.getClass.getSimpleName)
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.master(parser.get("master")).getOrCreate()
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val sc = spark.sparkContext
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val workingPath = parser.get("workingPath")
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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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val k: RDD[(String, String)] = sc.wholeTextFiles(s"$workingPath/baseline",2000)
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val ds:Dataset[PMArticle] = spark.createDataset(k.filter(i => i._1.endsWith(".gz")).flatMap(i =>{
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val xml = new XMLEventReader(Source.fromBytes(i._2.getBytes()))
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new PMParser(xml)
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} ))
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ds.write.mode(SaveMode.Overwrite).save(s"$workingPath/baseline_dataset")
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}
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}
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