Github user siyuanh commented on a diff in the pull request:
https://github.com/apache/apex-malhar/pull/294#discussion_r68977507
--- Diff:
contrib/src/main/java/com/datatorrent/contrib/kafka/AbstractTupleUniqueExactlyOnceKafkaOutputOperator.java
---
@@ -0,0 +1,610 @@
+/**
+ * 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 com.datatorrent.contrib.kafka;
+
+import java.util.Collection;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.Set;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import org.apache.commons.lang3.StringUtils;
+import org.apache.hadoop.classification.InterfaceStability;
+
+import com.google.common.base.Splitter;
+import com.google.common.collect.Lists;
+import com.google.common.collect.Maps;
+import com.google.common.collect.Sets;
+
+import com.datatorrent.api.Context.OperatorContext;
+import com.datatorrent.api.DefaultInputPort;
+import com.datatorrent.common.util.Pair;
+
+import kafka.api.OffsetRequest;
+import kafka.javaapi.consumer.SimpleConsumer;
+import kafka.javaapi.producer.Producer;
+import kafka.producer.KeyedMessage;
+import kafka.producer.ProducerConfig;
+import kafka.serializer.StringDecoder;
+
+/**
+ * Assumptions: - assume the value of incoming tuples are not duplicate(at
least
+ * in one window) among all operator partitions. - assume one Kafka
partition
+ * can be written by multiple operator partitions at the same time -
assume the
+ * the Kafka partition was decided by tuple value itself( not depended on
+ * operator partition)
+ *
+ * Notes: - the order of data could be changed when replay. - the data
could go
+ * to the other partition when replay. For example if the upstream operator
+ * failed.
+ *
+ * Implementation: for each Kafka partition, load minimum last window and
the
+ * minimum offset of the last window of all operator partitions. And then
load
+ * the tuples from Kafka based on this minimum offset. When processing
tuple, if
+ * the window id is less than the minimum last window, just ignore the
tuple. If
+ * window id equals loaded minimum window id, and tuple equals any of
loaded
+ * tuple, ignore it. Else, send to Kafka
+ *
+ * @displayName Abstract Tuple Unique Exactly Once Kafka Output
+ * @category Messaging
+ * @tags output operator
+ */
[email protected]
+public abstract class AbstractTupleUniqueExactlyOnceKafkaOutputOperator<T,
K, V>
+ extends AbstractKafkaOutputOperator<K, V>
+{
+ public static final String DEFAULT_CONTROL_TOPIC = "ControlTopic";
+ protected transient int partitionNum = 1;
+
+ /**
+ * allow client set the partitioner as partitioner may need some
attributes
+ */
+ protected kafka.producer.Partitioner partitioner;
+
+ protected transient int operatorPartitionId;
+
+ protected String controlTopic = DEFAULT_CONTROL_TOPIC;
+
+ //The control info includes the time, use this time to track the head of
control info we care.
+ protected int controlInfoTrackBackTime = 120000;
+
+ /**
+ * max number of offset need to check
+ */
+ protected int maxNumOffsetsOfControl = 1000;
+
+ protected String controlProducerProperties;
+ protected Set<String> brokerSet;
+
+ protected transient long currentWindowId;
+
+ /**
+ * the map from Kafka partition id to the control offset. this one is
+ * checkpointed and as the start offset to load the recovery control
+ * information Note: this only keep the information of this operator
+ * partition.
+ */
+ protected transient Map<Integer, Long> partitionToLastControlOffset =
Maps.newHashMap();
+
+ /**
+ * keep the minimal last window id for recovery. If only one partition
+ * crashed, it is ok just use the last window id of this operator
partition as
+ * the recovery window id If all operator partitions crashed, should use
the
+ * minimal last window id as the recovery window id, as the data may go
to the
+ * other partitions. But as the operator can't distinguish which is the
case.
+ * use the most general one.
+ */
+ protected transient long minRecoveryWindowId = -2;
+ protected transient long maxRecoveryWindowId = -2;
+
+ /**
+ * A map from Kafka partition id to lastMessages writtten to this kafka
--- End diff --
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