96 lines
4.0 KiB
Java
96 lines
4.0 KiB
Java
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package eu.dnetlib.dhp.transformation;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
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import java.io.IOException;
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import java.util.Map;
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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.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 org.apache.spark.util.LongAccumulator;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.data.mdstore.manager.common.model.MDStoreVersion;
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import eu.dnetlib.dhp.aggregation.common.AggregationCounter;
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import eu.dnetlib.dhp.aggregation.common.AggregationUtility;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.model.mdstore.MetadataRecord;
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import eu.dnetlib.dhp.utils.ISLookupClientFactory;
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import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
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public class TransformSparkJobNode {
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private static final Logger log = LoggerFactory.getLogger(TransformSparkJobNode.class);
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public static void main(String[] args) throws Exception {
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final ArgumentApplicationParser parser = new ArgumentApplicationParser(
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IOUtils
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.toString(
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TransformSparkJobNode.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/transformation/transformation_input_parameters.json")));
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parser.parseArgument(args);
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Boolean isSparkSessionManaged = Optional
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.ofNullable(parser.get("isSparkSessionManaged"))
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.map(Boolean::valueOf)
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.orElse(Boolean.TRUE);
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log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
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final String mdstoreInputVersion = parser.get("mdstoreInputVersion");
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final String mdstoreOutputVersion = parser.get("mdstoreOutputVersion");
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// TODO this variable will be used after implementing Messaging with DNet Aggregator
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final ObjectMapper jsonMapper = new ObjectMapper();
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final MDStoreVersion nativeMdStoreVersion = jsonMapper.readValue(mdstoreInputVersion, MDStoreVersion.class);
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final MDStoreVersion cleanedMdStoreVersion = jsonMapper.readValue(mdstoreOutputVersion, MDStoreVersion.class);
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final String isLookupUrl = parser.get("isLookupUrl");
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log.info(String.format("isLookupUrl: %s", isLookupUrl));
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final ISLookUpService isLookupService = ISLookupClientFactory.getLookUpService(isLookupUrl);
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SparkConf conf = new SparkConf();
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runWithSparkSession(
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conf,
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isSparkSessionManaged,
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spark -> transformRecords(
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parser.getObjectMap(), isLookupService, spark, nativeMdStoreVersion.getHdfsPath(),
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cleanedMdStoreVersion.getHdfsPath()));
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}
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public static void transformRecords(final Map<String, String> args, final ISLookUpService isLookUpService,
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final SparkSession spark, final String inputPath, final String outputPath)
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throws DnetTransformationException, IOException {
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final LongAccumulator totalItems = spark.sparkContext().longAccumulator("TotalItems");
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final LongAccumulator errorItems = spark.sparkContext().longAccumulator("errorItems");
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final LongAccumulator transformedItems = spark.sparkContext().longAccumulator("transformedItems");
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final AggregationCounter ct = new AggregationCounter(totalItems, errorItems, transformedItems);
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final Encoder<MetadataRecord> encoder = Encoders.bean(MetadataRecord.class);
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final Dataset<MetadataRecord> mdstoreInput = spark.read().format("parquet").load(inputPath).as(encoder);
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final MapFunction<MetadataRecord, MetadataRecord> XSLTTransformationFunction = TransformationFactory
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.getTransformationPlugin(args, ct, isLookUpService);
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mdstoreInput.map(XSLTTransformationFunction, encoder).write().save(outputPath + "/store");
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log.info("Transformed item " + ct.getProcessedItems().count());
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log.info("Total item " + ct.getTotalItems().count());
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log.info("Transformation Error item " + ct.getErrorItems().count());
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AggregationUtility.writeTotalSizeOnHDFS(spark, ct.getProcessedItems().count(), outputPath + "/size");
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}
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}
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