64 lines
2.0 KiB
Java
64 lines
2.0 KiB
Java
package eu.dnetlib.dhp.graph;
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import eu.dnetlib.dhp.schema.oaf.Datasource;
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import eu.dnetlib.dhp.schema.oaf.Oaf;
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import eu.dnetlib.dhp.schema.oaf.Publication;
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import org.apache.hadoop.io.Text;
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import org.apache.spark.api.java.JavaRDD;
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import org.apache.spark.api.java.JavaSparkContext;
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import org.apache.spark.api.java.function.PairFunction;
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import org.apache.spark.sql.Dataset;
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import org.apache.spark.sql.Encoder;
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import org.apache.spark.sql.Encoders;
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import org.apache.spark.sql.SparkSession;
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import scala.Tuple2;
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import javax.xml.crypto.Data;
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public class SparkGraphImporterJob {
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public static void main(String[] args) throws Exception{
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//TODO add argument parser
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// final ArgumentApplicationParser parser = new ArgumentApplicationParser(IOUtils.toString(SparkGraphImporterJob.class.getResourceAsStream("/eu/dnetlib/dhp/graph/graph_importer_parameters.json")));
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// parser.parseArgument(args);
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final SparkSession spark = SparkSession
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.builder()
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.appName("ImportGraph")
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//TODO replace with: master(parser.get("master"))
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.master("local[16]")
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.getOrCreate();
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final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
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final JavaRDD<Tuple2<String, String>> inputRDD = sc.sequenceFile("file:///home/sandro/part-m-00000", Text.class, Text.class).map(item -> new Tuple2<>(item._1.toString(), item._2.toString()));
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final JavaRDD<Datasource> datasources = inputRDD
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.filter(s -> s._1().split("@")[2].equalsIgnoreCase("body"))
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.map(Tuple2::_2)
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.map(ProtoConverter::convert)
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.filter(s-> s instanceof Datasource)
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.map(s->(Datasource)s);
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final Encoder<Datasource> encoder = Encoders.bean(Datasource.class);
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final Dataset<Datasource> mdstore = spark.createDataset(datasources.rdd(), encoder);
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System.out.println(mdstore.count());
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//
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//
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// .filter(s -> s instanceof Publication)
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// .count();
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}
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}
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