[Transformative Agreement] removed not needed class. Read directly the json and no need to pass from the csv
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package eu.dnetlib.dhp.actionmanager.transformativeagreement;
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import static eu.dnetlib.dhp.actionmanager.Constants.DEFAULT_DELIMITER;
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import static eu.dnetlib.dhp.actionmanager.Constants.isSparkSessionManaged;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
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import java.io.Serializable;
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import java.util.Arrays;
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import java.util.Optional;
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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.api.java.function.MapFunction;
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import org.apache.spark.sql.*;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import eu.dnetlib.dhp.actionmanager.opencitations.model.COCI;
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import eu.dnetlib.dhp.actionmanager.transformativeagreement.model.TransformativeAgreementModel;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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public class ReadTransformativeAgreement implements Serializable {
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private static final Logger log = LoggerFactory.getLogger(ReadTransformativeAgreement.class);
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public static void main(String[] args) throws Exception {
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String jsonConfiguration = IOUtils
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.toString(
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ReadTransformativeAgreement.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/actionmanager/transformativeagreement/input_read_parameters.json"));
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final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
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parser.parseArgument(args);
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final String outputPath = parser.get("outputPath");
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log.info("outputPath: {}", outputPath);
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final String inputFile = parser.get("inputFile");
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log.info("inputFile {}", inputFile);
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Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
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log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
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SparkConf sconf = new SparkConf();
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final String delimiter = Optional
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.ofNullable(parser.get("delimiter"))
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.orElse(DEFAULT_DELIMITER);
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runWithSparkSession(
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sconf,
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isSparkSessionManaged,
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spark -> {
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doRead(
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spark,
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inputFile,
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outputPath,
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delimiter);
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});
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}
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private static void doRead(SparkSession spark, String inputFile,
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String outputPath,
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String delimiter) {
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Dataset<Row> data = spark
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.read()
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.format("csv")
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.option("sep", delimiter)
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.option("inferSchema", "true")
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.option("header", "true")
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.load(inputFile)
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.repartition(100);
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data.map((MapFunction<Row, TransformativeAgreementModel>) row -> {
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TransformativeAgreementModel trm = new TransformativeAgreementModel();
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trm.setInstitution(row.getString(2));
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trm.setDoi(row.getString(7));
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return trm;
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}, Encoders.bean(TransformativeAgreementModel.class))
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.write()
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.mode(SaveMode.Overwrite)
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.option("compression", "gzip")
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.json(outputPath + inputFile);
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}
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}
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