forked from D-Net/dnet-hadoop
simplified import procedure, maps the infospace as hive tables
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1e7a2ac41d
commit
a52d5bde4f
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@ -32,11 +32,6 @@
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<version>1.0.4-SNAPSHOT</version>
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</dependency>
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<dependency>
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<groupId>de.javakaffee</groupId>
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<artifactId>kryo-serializers</artifactId>
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</dependency>
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</dependencies>
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@ -3,11 +3,11 @@ package eu.dnetlib.dhp.graph;
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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 org.apache.commons.io.IOUtils;
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import org.apache.commons.lang.StringUtils;
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import org.apache.hadoop.io.Text;
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import org.apache.spark.api.java.JavaRDD;
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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 scala.Tuple2;
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@ -19,29 +19,27 @@ public class SparkGraphImporterJob {
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parser.parseArgument(args);
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final SparkSession spark = SparkSession
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.builder()
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.appName("ImportGraph")
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.appName(SparkGraphImporterJob.class.getSimpleName())
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.master(parser.get("master"))
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.config("hive.metastore.uris", parser.get("hive.metastore.uris"))
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.enableHiveSupport()
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.getOrCreate();
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final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
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final String inputPath = parser.get("sourcePath");
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final String outputPath = parser.get("targetPath");
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final String filter = parser.get("filter");
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// Read the input file and convert it into RDD of serializable object
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final JavaRDD<Tuple2<String, String>> inputRDD = sc.sequenceFile(inputPath, Text.class, Text.class)
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.map(item -> new Tuple2<>(item._1.toString(), item._2.toString()));
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GraphMappingUtils.types.forEach((name, clazz) -> {
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if (StringUtils.isNotBlank(filter) || filter.toLowerCase().contains(name)) {
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spark.createDataset(inputRDD
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.filter(s -> s._1().equals(clazz.getName()))
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.map(Tuple2::_2)
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.map(s -> new ObjectMapper().readValue(s, clazz))
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.rdd(), Encoders.bean(clazz))
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.write()
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.save(outputPath + "/" + name);
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}
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final JavaRDD<Tuple2<String, String>> inputRDD = sc.sequenceFile(inputPath + "/" + name, Text.class, Text.class)
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.map(item -> new Tuple2<>(item._1.toString(), item._2.toString()));
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spark.createDataset(inputRDD
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.filter(s -> s._1().equals(clazz.getName()))
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.map(Tuple2::_2)
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.map(s -> new ObjectMapper().readValue(s, clazz))
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.rdd(), Encoders.bean(clazz))
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.write()
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.mode(SaveMode.Overwrite)
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.saveAsTable("openaire." + name);
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});
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}
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@ -1,6 +1,5 @@
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[
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{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
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{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the path of the sequencial file to read", "paramRequired": true},
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{"paramName":"f", "paramLongName":"filter", "paramDescription": "csv of typology of dataframe to be generated", "paramRequired": false},
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{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the path where store DataFrames on HDFS", "paramRequired": true}
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{"paramName":"h", "paramLongName":"hive.metastore.uris","paramDescription": "the hive metastore uris", "paramRequired": true}
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]
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@ -16,7 +16,7 @@
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<value>spark2</value>
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</property>
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<property>
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<name>filter</name>
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<value></value>
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<name>hive.metastore.uris</name>
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<value>thrift://iis-cdh5-test-m3.ocean.icm.edu.pl:9083</value>
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</property>
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</configuration>
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@ -4,10 +4,6 @@
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<name>sourcePath</name>
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<description>the source path</description>
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</property>
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<property>
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<name>targetPath</name>
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<description>the target path</description>
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</property>
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<property>
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<name>sparkDriverMemory</name>
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<description>memory for driver process</description>
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@ -20,10 +16,6 @@
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<name>sparkExecutorCores</name>
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<description>number of cores used by single executor</description>
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</property>
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<property>
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<name>filter</name>
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<description>csv string to filter the entities to generate</description>
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</property>
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</parameters>
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<start to="MapGraphIntoDataFrame"/>
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@ -41,12 +33,10 @@
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<name>MapGraphIntoDataFrame</name>
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<class>eu.dnetlib.dhp.graph.SparkGraphImporterJob</class>
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<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
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<spark-opts>--executor-memory ${sparkExecutorMemory} --executor-cores ${sparkExecutorCores} --driver-memory=${sparkDriverMemory} --conf spark.extraListeners="com.cloudera.spark.lineage.NavigatorAppListener" --conf spark.sql.queryExecutionListeners="com.cloudera.spark.lineage.NavigatorQueryListener"</spark-opts>
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<spark-opts>--executor-memory ${sparkExecutorMemory} --executor-cores ${sparkExecutorCores} --driver-memory=${sparkDriverMemory} --conf spark.extraListeners="com.cloudera.spark.lineage.NavigatorAppListener" --conf spark.sql.queryExecutionListeners="com.cloudera.spark.lineage.NavigatorQueryListener" --conf spark.sql.warehouse.dir="/user/hive/warehouse"</spark-opts>
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<arg>-mt</arg> <arg>yarn-cluster</arg>
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<arg>--sourcePath</arg><arg>${sourcePath}</arg>
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<arg>--targetPath</arg><arg>${targetPath}</arg>
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<arg>--filter</arg><arg>${filter}</arg>
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<arg>--hive.metastore.uris</arg><arg>${hive.metastore.uris}</arg>
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</spark>
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<ok to="End"/>
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<error to="Kill"/>
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