forked from D-Net/dnet-hadoop
42 lines
1.5 KiB
Scala
42 lines
1.5 KiB
Scala
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package eu.dnetlib.doiboost.orcid
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import eu.dnetlib.dhp.application.ArgumentApplicationParser
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import eu.dnetlib.dhp.schema.oaf.Publication
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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 org.slf4j.{Logger, LoggerFactory}
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object SparkConvertORCIDToOAF {
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def main(args: Array[String]): Unit = {
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val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
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val conf: SparkConf = new SparkConf()
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val parser = new ArgumentApplicationParser(IOUtils.toString(SparkConvertORCIDToOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_map_to_oaf_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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implicit val mapEncoderPubs: Encoder[Publication] = Encoders.bean(classOf[Publication])
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val sourcePath = parser.get("sourcePath")
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val targetPath = parser.get("targetPath")
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val inputRDD:RDD[String] = spark.sparkContext.textFile(s"$sourcePath")
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println(s"SourcePath is $sourcePath, targetPath is $targetPath master is ${parser.get("master")} ")
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logger.info("Converting ORCID to OAF")
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val d:Dataset[Publication] = spark.createDataset(inputRDD.map(ORCIDToOAF.convertTOOAF).filter(p=>p!=null)).as[Publication]
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d.write.mode(SaveMode.Overwrite).save(targetPath)
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}
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}
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