forked from D-Net/dnet-hadoop
104 lines
3.5 KiB
Java
104 lines
3.5 KiB
Java
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package eu.dnetlib.dhp.broker.oa;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
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import java.util.Map;
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import java.util.Optional;
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import java.util.Set;
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import java.util.stream.Collectors;
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import org.apache.commons.io.IOUtils;
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import org.apache.commons.lang3.StringUtils;
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import org.apache.spark.SparkConf;
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import org.apache.spark.SparkContext;
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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.util.LongAccumulator;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.broker.model.Event;
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import eu.dnetlib.dhp.broker.oa.matchers.UpdateMatcher;
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import eu.dnetlib.dhp.broker.oa.util.ClusterUtils;
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import eu.dnetlib.dhp.broker.oa.util.EventFinder;
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import eu.dnetlib.dhp.broker.oa.util.EventGroup;
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import eu.dnetlib.dhp.broker.oa.util.aggregators.simple.ResultGroup;
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public class GenerateEventsJob {
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private static final Logger log = LoggerFactory.getLogger(GenerateEventsJob.class);
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public static void main(final 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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GenerateEventsJob.class
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.getResourceAsStream("/eu/dnetlib/dhp/broker/oa/generate_events.json")));
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parser.parseArgument(args);
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final 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 workingDir = parser.get("workingDir");
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log.info("workingDir: {}", workingDir);
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final String eventsPath = parser.get("outputDir") + "/events";
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log.info("eventsPath: {}", eventsPath);
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final Set<String> dsIdWhitelist = ClusterUtils.parseParamAsList(parser, "datasourceIdWhitelist");
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log.info("datasourceIdWhitelist: {}", StringUtils.join(dsIdWhitelist, ","));
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final Set<String> dsTypeWhitelist = ClusterUtils.parseParamAsList(parser, "datasourceTypeWhitelist");
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log.info("datasourceTypeWhitelist: {}", StringUtils.join(dsTypeWhitelist, ","));
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final Set<String> dsIdBlacklist = ClusterUtils.parseParamAsList(parser, "datasourceIdBlacklist");
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log.info("datasourceIdBlacklist: {}", StringUtils.join(dsIdBlacklist, ","));
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final Set<String> topicWhitelist = ClusterUtils.parseParamAsList(parser, "topicWhitelist");
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log.info("topicWhitelist: {}", StringUtils.join(topicWhitelist, ","));
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final SparkConf conf = new SparkConf();
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runWithSparkSession(conf, isSparkSessionManaged, spark -> {
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ClusterUtils.removeDir(spark, eventsPath);
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final Map<String, LongAccumulator> accumulators = prepareAccumulators(spark.sparkContext());
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final LongAccumulator total = spark.sparkContext().longAccumulator("total_events");
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final Dataset<ResultGroup> groups = ClusterUtils
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.readPath(spark, workingDir + "/duplicates", ResultGroup.class);
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final Dataset<Event> dataset = groups
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.map(
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g -> EventFinder
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.generateEvents(g, dsIdWhitelist, dsIdBlacklist, dsTypeWhitelist, topicWhitelist, accumulators),
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Encoders
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.bean(EventGroup.class))
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.flatMap(g -> g.getData().iterator(), Encoders.bean(Event.class));
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ClusterUtils.save(dataset, eventsPath, Event.class, total);
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});
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}
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public static Map<String, LongAccumulator> prepareAccumulators(final SparkContext sc) {
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return EventFinder
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.getMatchers()
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.stream()
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.map(UpdateMatcher::accumulatorName)
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.distinct()
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.collect(Collectors.toMap(s -> s, s -> sc.longAccumulator(s)));
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}
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}
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