150 lines
4.6 KiB
Java
150 lines
4.6 KiB
Java
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package eu.dnetlib.dhp.actionmanager.usagestats;
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import static eu.dnetlib.dhp.actionmanager.Constants.*;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
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import java.io.Serializable;
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import java.util.Arrays;
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import java.util.List;
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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.api.java.function.MapGroupsFunction;
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import org.apache.spark.sql.Dataset;
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import org.apache.spark.sql.Encoders;
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import org.apache.spark.sql.SaveMode;
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import org.apache.spark.sql.SparkSession;
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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.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.common.HdfsSupport;
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import eu.dnetlib.dhp.schema.common.ModelConstants;
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import eu.dnetlib.dhp.schema.oaf.DataInfo;
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import eu.dnetlib.dhp.schema.oaf.Measure;
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import eu.dnetlib.dhp.schema.oaf.Result;
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import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
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/**
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* created the Atomic Action for each type of results
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*/
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public class SparkAtomicActionUsageJob implements Serializable {
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private static final Logger log = LoggerFactory.getLogger(SparkAtomicActionUsageJob.class);
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private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
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public static <I extends Result> void main(String[] args) throws Exception {
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String jsonConfiguration = IOUtils
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.toString(
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SparkAtomicActionUsageJob.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/actionmanager/usagestats/input_actionset_parameter.json"));
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final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
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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 outputPath = parser.get("outputPath");
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log.info("outputPath {}: ", outputPath);
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SparkConf conf = new SparkConf();
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conf.set("hive.metastore.uris", parser.get("hive_metastore_uris"));
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final String dbname = parser.get("usagestatsdb");
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final String workingPath = parser.get("workingPath");
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runWithSparkHiveSession(
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conf,
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isSparkSessionManaged,
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spark -> {
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removeOutputDir(spark, outputPath);
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prepareResults(dbname, spark, workingPath);
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prepareActionSet(spark, workingPath, outputPath);
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});
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}
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public static void prepareResults(String db, SparkSession spark, String workingPath) {
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spark
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.sql(
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"Select result_id, downloads, views " +
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"from " + db + ".usage_stats")
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.as(Encoders.bean(UsageStatsModel.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(workingPath);
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}
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public static void prepareActionSet(SparkSession spark, String inputPath, String outputPath) {
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readPath(spark, inputPath, UsageStatsModel.class)
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.groupByKey((MapFunction<UsageStatsModel, String>) us -> us.getResult_id(), Encoders.STRING())
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.mapGroups((MapGroupsFunction<String, UsageStatsModel, Result>) (k, it) -> {
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UsageStatsModel first = it.next();
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it.forEachRemaining(us -> {
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first.setDownloads(first.getDownloads() + us.getDownloads());
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first.setViews(first.getViews() + us.getViews());
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});
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Result res = new Result();
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res.setId("50|" + k);
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res.setMeasures(getMeasure(first.getDownloads(), first.getViews()));
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return res;
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}, Encoders.bean(Result.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);
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}
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private static List<Measure> getMeasure(Long downloads, Long views) {
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DataInfo dataInfo = OafMapperUtils
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.dataInfo(
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false,
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UPDATE_DATA_INFO_TYPE,
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true,
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false,
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OafMapperUtils
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.qualifier(
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UPDATE_MEASURE_USAGE_COUNTS_CLASS_ID,
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UPDATE_CLASS_NAME,
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ModelConstants.DNET_PROVENANCE_ACTIONS,
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ModelConstants.DNET_PROVENANCE_ACTIONS),
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"");
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return Arrays
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.asList(
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OafMapperUtils
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.newMeasureInstance("downloads", String.valueOf(downloads), UPDATE_KEY_USAGE_COUNTS, dataInfo),
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OafMapperUtils.newMeasureInstance("views", String.valueOf(views), UPDATE_KEY_USAGE_COUNTS, dataInfo));
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}
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private static void removeOutputDir(SparkSession spark, String path) {
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HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
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}
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public static <R> Dataset<R> readPath(
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SparkSession spark, String inputPath, Class<R> clazz) {
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return spark
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.read()
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.textFile(inputPath)
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.map((MapFunction<String, R>) value -> OBJECT_MAPPER.readValue(value, clazz), Encoders.bean(clazz));
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}
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}
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