org.apache.streampipes.wrapper.spark.SparkRuntime Maven / Gradle / Ivy
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* 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,
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* See the License for the specific language governing permissions and
* limitations under the License.
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*/
package org.apache.streampipes.wrapper.spark;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.apache.kafka.common.serialization.StringSerializer;
import org.apache.spark.SparkConf;
import org.apache.spark.launcher.SparkAppHandle;
import org.apache.spark.launcher.SparkLauncher;
import org.apache.spark.streaming.Duration;
import org.apache.spark.streaming.api.java.JavaDStream;
import org.apache.spark.streaming.api.java.JavaInputDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;
import org.apache.spark.streaming.kafka010.ConsumerStrategies;
import org.apache.spark.streaming.kafka010.KafkaUtils;
import org.apache.spark.streaming.kafka010.LocationStrategies;
import org.apache.streampipes.model.SpDataStream;
import org.apache.streampipes.model.base.InvocableStreamPipesEntity;
import org.apache.streampipes.model.grounding.KafkaTransportProtocol;
import org.apache.streampipes.wrapper.spark.converter.JsonToMapFormat;
import java.io.Serializable;
import java.util.Arrays;
import java.util.Base64;
import java.util.HashMap;
import java.util.Map;
public abstract class SparkRuntime implements Runnable, Serializable {
private static final long serialVersionUID = 1L;
protected final SparkDeploymentConfig deploymentConfig;
protected Thread thread;
protected SparkAppHandle appHandle;
protected SparkLauncher launcher;
protected JavaStreamingContext streamingContext;
protected I graph;
protected Map kafkaParams;
public SparkRuntime(I graph, SparkDeploymentConfig deploymentConfig) {
this.graph = graph;
this.deploymentConfig = deploymentConfig;
kafkaParams = new HashMap<>();
kafkaParams.put("bootstrap.servers", this.deploymentConfig.getKafkaHost());
kafkaParams.put("key.deserializer", StringDeserializer.class);
kafkaParams.put("value.deserializer", StringDeserializer.class);
kafkaParams.put("key.serializer", StringSerializer.class);
kafkaParams.put("value.serializer", StringSerializer.class);
kafkaParams.put("group.id", "use_a_separate_group_id_for_each_stream");
kafkaParams.put("auto.offset.reset", "latest");
kafkaParams.put("enable.auto.commit", false);
}
public boolean startExecution() {
if (this.deploymentConfig.isRunLocal()) {
try {
SparkConf conf = new SparkConf().setAppName(this.deploymentConfig.getAppName())
.setMaster(this.deploymentConfig.getSparkHost());
streamingContext = new JavaStreamingContext(conf, new Duration(this.deploymentConfig.getSparkBatchDuration()));
JavaDStream> messageStream1 = null;
JavaInputDStream> source1 = getStream1Source(streamingContext);
if (source1 != null) {
messageStream1 = source1.flatMap(new JsonToMapFormat(graph));
} else {
throw new Exception("At least one source must be defined for a Spark SEPA");
}
//TODO: zweiter Stream. Kann das Spark?
//TODO: Error Handling
execute(messageStream1);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
else {
try {
byte[] data = getSerializationData();
String enc = Base64.getEncoder().encodeToString(data);
//System.out.println("Sending data: '" + enc + "'");
launcher = new SparkLauncher()
.setAppResource(this.deploymentConfig.getJarFile())
.setMainClass(this.getClass().getName())
.addAppArgs(enc)
//.redirectError()
//.redirectOutput(ProcessBuilder.Redirect.PIPE)
.setMaster(this.deploymentConfig.getSparkHost())
.setConf(SparkLauncher.DRIVER_MEMORY, "2g");//TODO
appHandle = launcher.startApplication();
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
}
protected abstract byte[] getSerializationData();
public abstract boolean execute(JavaDStream>... convertedStream);
public void run() {
try {
streamingContext.start();
if (deploymentConfig.isRunLocal()) {
streamingContext.awaitTermination();
}
} catch (Exception e) {
e.printStackTrace();
}
}
public boolean stop() {
try {
appHandle.stop();
//streamingContext.stop();
//streamingContext.awaitTermination();
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
private JavaInputDStream> getStream1Source(JavaStreamingContext streamingContext) {
return getStreamSource(0, streamingContext);
}
private JavaInputDStream> getStream2Source(JavaStreamingContext streamingContext) {
return getStreamSource(1, streamingContext);
}
/**
* This method takes the i's input stream and creates a source for the Spark streaming job
* Currently just kafka is supported as a protocol
* TODO Add also jms support
*
* @param i
* @param streamingContext
* @return
*/
private JavaInputDStream> getStreamSource(int i, JavaStreamingContext streamingContext) {
if (graph.getInputStreams().size() - 1 >= i) {
SpDataStream stream = graph.getInputStreams().get(i);
if (stream != null) {
KafkaTransportProtocol protocol = (KafkaTransportProtocol) stream.getEventGrounding().getTransportProtocol();
//System.out.println("Listening on Kafka topic '" + protocol.getTopicName() + "'");
return KafkaUtils.createDirectStream(streamingContext, LocationStrategies.PreferConsistent(),
ConsumerStrategies.Subscribe(Arrays.asList(protocol.getTopicDefinition().getActualTopicName()),
kafkaParams));
}
else {
return null;
}
}
else {
return null;
}
}
}