| /* |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you under the Apache License, Version 2.0 (the |
| * "License"); you may not use this file except in compliance |
| * with the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, |
| * software distributed under the License is distributed on an |
| * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| * KIND, either express or implied. See the License for the |
| * specific language governing permissions and limitations |
| * under the License. |
| */ |
| |
| package org.apache.tinkerpop.gremlin.spark.structure.io; |
| |
| import org.apache.commons.configuration.Configuration; |
| import org.apache.spark.api.java.JavaPairRDD; |
| import org.apache.spark.storage.StorageLevel; |
| import org.apache.tinkerpop.gremlin.hadoop.Constants; |
| import org.apache.tinkerpop.gremlin.hadoop.process.computer.PersistResultGraphAware; |
| import org.apache.tinkerpop.gremlin.hadoop.structure.io.VertexWritable; |
| import org.apache.tinkerpop.gremlin.process.computer.GraphComputer; |
| import org.apache.tinkerpop.gremlin.process.computer.KeyValue; |
| import org.apache.tinkerpop.gremlin.spark.structure.Spark; |
| import org.apache.tinkerpop.gremlin.structure.Direction; |
| import org.apache.tinkerpop.gremlin.util.iterator.IteratorUtils; |
| import org.slf4j.Logger; |
| import org.slf4j.LoggerFactory; |
| |
| import java.util.Iterator; |
| |
| /** |
| * @author Marko A. Rodriguez (http://markorodriguez.com) |
| */ |
| public final class PersistedOutputRDD implements OutputRDD, PersistResultGraphAware { |
| |
| private static final Logger LOGGER = LoggerFactory.getLogger(PersistedOutputRDD.class); |
| |
| @Override |
| public void writeGraphRDD(final Configuration configuration, final JavaPairRDD<Object, VertexWritable> graphRDD) { |
| if (!configuration.getBoolean(Constants.GREMLIN_SPARK_PERSIST_CONTEXT, false)) |
| LOGGER.warn("The SparkContext should be persisted in order for the RDD to persist across jobs. To do so, set " + Constants.GREMLIN_SPARK_PERSIST_CONTEXT + " to true"); |
| if (!configuration.containsKey(Constants.GREMLIN_HADOOP_OUTPUT_LOCATION)) |
| throw new IllegalArgumentException("There is no provided " + Constants.GREMLIN_HADOOP_OUTPUT_LOCATION + " to write the persisted RDD to"); |
| SparkContextStorage.open(configuration).rm(configuration.getString(Constants.GREMLIN_HADOOP_OUTPUT_LOCATION)); // this might be bad cause it unpersists the job RDD |
| // determine which storage level to persist the RDD as with MEMORY_ONLY being the default cache() |
| final StorageLevel storageLevel = StorageLevel.fromString(configuration.getString(Constants.GREMLIN_SPARK_PERSIST_STORAGE_LEVEL, "MEMORY_ONLY")); |
| if (!configuration.getBoolean(Constants.GREMLIN_HADOOP_GRAPH_WRITER_HAS_EDGES, true)) |
| graphRDD.mapValues(vertex -> { |
| vertex.get().dropEdges(Direction.BOTH); |
| return vertex; |
| }).setName(Constants.getGraphLocation(configuration.getString(Constants.GREMLIN_HADOOP_OUTPUT_LOCATION))).persist(storageLevel); |
| else |
| graphRDD.setName(Constants.getGraphLocation(configuration.getString(Constants.GREMLIN_HADOOP_OUTPUT_LOCATION))).persist(storageLevel); |
| Spark.refresh(); // necessary to do really fast so the Spark GC doesn't clear out the RDD |
| } |
| |
| @Override |
| public <K, V> Iterator<KeyValue<K, V>> writeMemoryRDD(final Configuration configuration, final String memoryKey, final JavaPairRDD<K, V> memoryRDD) { |
| if (!configuration.getBoolean(Constants.GREMLIN_SPARK_PERSIST_CONTEXT, false)) |
| LOGGER.warn("The SparkContext should be persisted in order for the RDD to persist across jobs. To do so, set " + Constants.GREMLIN_SPARK_PERSIST_CONTEXT + " to true"); |
| if (!configuration.containsKey(Constants.GREMLIN_HADOOP_OUTPUT_LOCATION)) |
| throw new IllegalArgumentException("There is no provided " + Constants.GREMLIN_HADOOP_OUTPUT_LOCATION + " to write the persisted RDD to"); |
| final String memoryRDDName = Constants.getMemoryLocation(configuration.getString(Constants.GREMLIN_HADOOP_OUTPUT_LOCATION), memoryKey); |
| Spark.removeRDD(memoryRDDName); |
| memoryRDD.setName(memoryRDDName).persist(StorageLevel.fromString(configuration.getString(Constants.GREMLIN_SPARK_PERSIST_STORAGE_LEVEL, "MEMORY_ONLY"))); |
| Spark.refresh(); // necessary to do really fast so the Spark GC doesn't clear out the RDD |
| return IteratorUtils.map(memoryRDD.collect().iterator(), tuple -> new KeyValue<>(tuple._1(), tuple._2())); |
| } |
| |
| @Override |
| public boolean supportsResultGraphPersistCombination(final GraphComputer.ResultGraph resultGraph, final GraphComputer.Persist persist) { |
| return persist.equals(GraphComputer.Persist.NOTHING) || resultGraph.equals(GraphComputer.ResultGraph.NEW); |
| } |
| } |