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https://issues.apache.org/jira/browse/APEXMALHAR-2086?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15345868#comment-15345868
]
ASF GitHub Bot commented on APEXMALHAR-2086:
--------------------------------------------
Github user siyuanh commented on a diff in the pull request:
https://github.com/apache/apex-malhar/pull/298#discussion_r68180895
--- Diff:
kafka/src/main/java/org/apache/apex/malhar/kafka/KafkaSinglePortExactlyOnceOutputOperator.java
---
@@ -0,0 +1,369 @@
+/**
+ * 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.apex.malhar.kafka;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.ExecutionException;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import org.apache.apex.malhar.lib.wal.FSWindowDataManager;
+import org.apache.apex.malhar.lib.wal.WindowDataManager;
+
+import org.apache.kafka.clients.consumer.ConsumerRecord;
+import org.apache.kafka.clients.consumer.ConsumerRecords;
+import org.apache.kafka.clients.consumer.KafkaConsumer;
+import org.apache.kafka.clients.producer.ProducerRecord;
+import org.apache.kafka.common.PartitionInfo;
+import org.apache.kafka.common.TopicPartition;
+
+import com.datatorrent.api.Context;
+import com.datatorrent.api.DefaultInputPort;
+import com.datatorrent.api.Operator;
+
+import static
org.apache.kafka.clients.consumer.ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG;
+import static
org.apache.kafka.clients.consumer.ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG;
+import static
org.apache.kafka.clients.consumer.ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG;
+
+/**
+ * Kafka output operator with exactly once processing semantics under
certain conditions.,
+ *
+ * This operator uses *Key* to distinguish the messages written by
particular instance of the Output operator.
+ * Operator users can only use *value* for storing the data.
+ *
+ * @displayName Single Port Exactly Once Kafka Output(0.9.0)
+ * @category Messaging
+ * @tags output operator
+ *
+ */
+@org.apache.hadoop.classification.InterfaceStability.Evolving
+public class KafkaSinglePortExactlyOnceOutputOperator<T> extends
AbstractKafkaOutputOperator<String, T>
+ implements Operator.CheckpointNotificationListener
+{
+ private transient String key;
+ private transient String appName;
+ private transient Integer operatorId;
+ private transient Long windowId;
+ private transient Map<T, Integer> partialWindowTuples = new HashMap<>();
+ private transient KafkaConsumer consumer;
+
+ private WindowDataManager windowDataManager = new FSWindowDataManager();
+ private final int KAFKA_CONNECT_ATTEMPT = 10;
+ private final String KEY_SEPARATOR = "#";
+ private final String KEY_SERIALIZER =
"org.apache.kafka.common.serialization.StringDeserializer";
+ private final String VALUE_SERIALIZER =
"org.apache.kafka.common.serialization.StringDeserializer";
+
+ public final transient DefaultInputPort<T> inputPort = new
DefaultInputPort<T>()
+ {
+ @Override
+ public void process(T tuple)
+ {
+ sendTuple(tuple);
+ }
+ };
+
+ @Override
+ public void setup(Context.OperatorContext context)
+ {
+ super.setup(context);
+
+ this.operatorId = context.getId();
+ this.windowDataManager.setup(context);
+ this.appName = context.getValue(Context.DAGContext.APPLICATION_NAME);
+ this.key = appName + KEY_SEPARATOR + (new Integer(operatorId));
+ this.consumer = KafkaConsumerInit();
+ }
+
+ @Override
+ public void beginWindow(long windowId)
+ {
+ this.windowId = windowId;
+
+ if (windowId == windowDataManager.getLargestRecoveryWindow()) {
+ rebuildPartialWindow();
+ }
+ }
+
+ @Override
+ public void checkpointed(long windowId)
+ {
+ }
+
+ @Override
+ public void committed(long windowId)
+ {
+ try {
+ windowDataManager.deleteUpTo(operatorId, windowId);
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
+
+ @Override
+ public void beforeCheckpoint(long windowId)
+ {
+ }
+
+ @Override
+ public void teardown()
+ {
+ consumer.close();
+ super.teardown();
+ }
+
+ @Override
+ public void endWindow()
+ {
+ if (!partialWindowTuples.isEmpty() && windowId >
windowDataManager.getLargestRecoveryWindow()) {
+ throw new RuntimeException("Violates Exactly once. Not all the
tuples received after operator reset.");
+ }
+
+ try {
+ this.windowDataManager.save(getPartitionsAndOffsets(), operatorId,
windowId);
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ } catch (InterruptedException e) {
+ e.printStackTrace();
+ } catch (ExecutionException e) {
+ e.printStackTrace();
+ }
+ }
+
+ public WindowDataManager getWindowDataManager()
+ {
+ return windowDataManager;
+ }
+
+ public void setWindowDataManager(WindowDataManager windowDataManager)
+ {
+ this.windowDataManager = windowDataManager;
+ }
+
+ private boolean doesKeyBelongsToThisInstance(Integer operatorId, String
key)
+ {
+ String[] split = key.split(KEY_SEPARATOR);
+
+ if (split.length != 2) {
+ return false;
+ }
+
+ if ((Integer.parseInt(split[1]) == operatorId) &&
(split[0].equals(appName))) {
+ return true;
+ }
+
+ return false;
+ }
+
+ private boolean alreadyInKafka(T message)
+ {
+ if ( windowId <= windowDataManager.getLargestRecoveryWindow() ) {
+ return true;
+ }
+
+ if (partialWindowTuples.containsKey(message)) {
+
+ Integer val = partialWindowTuples.get(message);
+
+ if ( val == 0 ) {
+ return false;
+ } else if ( val == 1 ) {
+ partialWindowTuples.remove(message);
+ } else {
+ partialWindowTuples.put(message, val - 1);
+ }
+
+ return true;
+ }
+
+ return false;
+ }
+
+ private Map<Integer,Long> getPartitionsAndOffsets() throws
ExecutionException, InterruptedException
+ {
+ List<PartitionInfo> partitionInfoList =
consumer.partitionsFor(getTopic());
+ List<TopicPartition> topicPartitionList = new java.util.ArrayList<>();
+
+ for ( PartitionInfo partitionInfo: partitionInfoList) {
+ topicPartitionList.add(new TopicPartition(getTopic(),
partitionInfo.partition()) );
+ }
+
+ Map<Integer,Long> parttionsAndOffset = new HashMap<>();
+ consumer.assign(topicPartitionList);
+
+ for ( PartitionInfo partitionInfo: partitionInfoList) {
+
+ try {
+
+ TopicPartition topicPartition = new TopicPartition(getTopic(),
partitionInfo.partition());
+ consumer.seekToEnd(topicPartition);
+ parttionsAndOffset.put(partitionInfo.partition(),
consumer.position(topicPartition));
+
+ } catch (Exception ex) {
+ throw new RuntimeException(ex);
+ }
+ }
+
+ return parttionsAndOffset;
+ }
+
+ private void rebuildPartialWindow()
+ {
+ logger.info("Rebuild the partial window after " +
windowDataManager.getLargestRecoveryWindow());
+
+ Map<Integer,Long> storedOffsets = getStoredOffsets();
+ Map<Integer,Long> currentOffsets = getCurrentOffsets();
+
+ if (storedOffsets == null || currentOffsets == null) {
+ logger.debug("No tuples found while building partial window " +
windowDataManager.getLargestRecoveryWindow());
+ return;
+ }
+
+ List<TopicPartition> topicPartitions = new ArrayList<>();
+
+ for (Map.Entry<Integer,Long> entry: currentOffsets.entrySet()) {
+
+ topicPartitions.add(new TopicPartition(getTopic(), entry.getKey()));
+ }
+
+ consumer.assign(topicPartitions);
+
+ for (Map.Entry<Integer,Long> entry: currentOffsets.entrySet()) {
+
+ Long storedOffset = 0L;
+ Integer currentPartition = entry.getKey();
+ Long currentOffset = entry.getValue();
+
+ if (storedOffsets.containsKey(currentPartition)) {
+ storedOffset = storedOffsets.get(currentPartition);
+ }
+
+ if (storedOffset >= currentOffset) {
+ continue;
+ }
+
+ consumer.seek(new TopicPartition(getTopic(), currentPartition),
storedOffset);
+
+ int kafkaAttempt = 0;
+
+ while ( true ) {
+
+ ConsumerRecords<String, String> consumerRecords =
consumer.poll(100);
+
+ if (consumerRecords.count() == 0) {
+ if (kafkaAttempt++ == KAFKA_CONNECT_ATTEMPT) {
--- End diff --
If some other operator are pushing data into same partition, it goes to
infinite loop. The ConsumerRecord would give you an offset, you should break
the while loop if the offset is bigger than the current offset you load before.
> Kafka Output Operator with Kafka 0.9 API
> ----------------------------------------
>
> Key: APEXMALHAR-2086
> URL: https://issues.apache.org/jira/browse/APEXMALHAR-2086
> Project: Apache Apex Malhar
> Issue Type: New Feature
> Reporter: Sandesh
> Assignee: Sandesh
>
> Goal : 2 Operartors for Kafka Output
> 1. Simple Kafka Output Operator
> - Supports Atleast Once
> - Expose most used producer properties as class properties
> 2. Exactly Once Kafka Output ( Not possible in all the cases, will be
> documented later )
>
> Design for Exactly Once
> Window Data Manager - Stores the Kafka partitions offsets.
> Kafka Key - Used by the operator = AppID#OperatorId
> During recovery. Partially written window is re-created using the following
> approach:
> Tuples between the largest recovery offsets and the current offset are
> checked. Based on the key, tuples written by the other entities are
> discarded.
> Only tuples which are not in the recovered set are emitted.
> Tuples needs to be unique within the window.
>
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