forked from D-Net/dnet-hadoop
82 lines
2.6 KiB
Java
82 lines
2.6 KiB
Java
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package eu.dnetlib.dhp.oa.graph.hive;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
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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.JavaSparkContext;
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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.schema.common.ModelSupport;
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public class GraphHiveImporterJob {
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private static final Logger log = LoggerFactory.getLogger(GraphHiveImporterJob.class);
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private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
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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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GraphHiveImporterJob.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/oa/graph/input_graph_hive_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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String inputPath = parser.get("inputPath");
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log.info("inputPath: {}", inputPath);
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String hiveDbName = parser.get("hiveDbName");
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log.info("hiveDbName: {}", hiveDbName);
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String hiveMetastoreUris = parser.get("hiveMetastoreUris");
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log.info("hiveMetastoreUris: {}", hiveMetastoreUris);
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SparkConf conf = new SparkConf();
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conf.set("hive.metastore.uris", hiveMetastoreUris);
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runWithSparkHiveSession(
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conf, isSparkSessionManaged, spark -> loadGraphAsHiveDB(spark, inputPath, hiveDbName));
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}
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// protected for testing
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private static void loadGraphAsHiveDB(SparkSession spark, String inputPath, String hiveDbName) {
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spark.sql(String.format("DROP DATABASE IF EXISTS %s CASCADE", hiveDbName));
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spark.sql(String.format("CREATE DATABASE IF NOT EXISTS %s", hiveDbName));
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final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
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// Read the input file and convert it into RDD of serializable object
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ModelSupport.oafTypes
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.forEach(
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(name, clazz) -> spark
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.createDataset(
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sc
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.textFile(inputPath + "/" + name)
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.map(s -> OBJECT_MAPPER.readValue(s, clazz))
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.rdd(),
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Encoders.bean(clazz))
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.write()
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.mode(SaveMode.Overwrite)
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.saveAsTable(hiveDbName + "." + name));
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}
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}
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