| /** |
| * 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.kafka.streams.processor; |
| |
| /** |
| * Determine how records are distributed among the partitions in a Kafka topic. If not specified, the underlying producer's |
| * {@link org.apache.kafka.clients.producer.internals.DefaultPartitioner} will be used to determine the partition. |
| * <p> |
| * Kafka topics are divided into one or more <i>partitions</i>. Since each partition must fit on the servers that host it, so |
| * using multiple partitions allows the topic to scale beyond a size that will fit on a single machine. Partitions also enable you |
| * to use multiple instances of your topology to process in parallel all of the records on the topology's source topics. |
| * <p> |
| * When a topology is instantiated, each of its sources are assigned a subset of that topic's partitions. That means that only |
| * those processors in that topology instance will consume the records from those partitions. In many cases, Kafka Streams will |
| * automatically manage these instances, and adjust when new topology instances are added or removed. |
| * <p> |
| * Some topologies, though, need more control over which records appear in each partition. For example, some topologies that have |
| * stateful processors may want all records within a range of keys to always be delivered to and handled by the same topology instance. |
| * An upstream topology producing records to that topic can use a custom <i>stream partitioner</i> to precisely and consistently |
| * determine to which partition each record should be written. |
| * <p> |
| * To do this, create a <code>StreamPartitioner</code> implementation, and when you build your topology specify that custom partitioner |
| * when {@link TopologyBuilder#addSink(String, String, org.apache.kafka.common.serialization.Serializer, org.apache.kafka.common.serialization.Serializer, StreamPartitioner, String...) adding a sink} |
| * for that topic. |
| * <p> |
| * All StreamPartitioner implementations should be stateless and a pure function so they can be shared across topic and sink nodes. |
| * |
| * @param <K> the type of keys |
| * @param <V> the type of values |
| * @see TopologyBuilder#addSink(String, String, org.apache.kafka.common.serialization.Serializer, |
| * org.apache.kafka.common.serialization.Serializer, StreamPartitioner, String...) |
| * @see TopologyBuilder#addSink(String, String, StreamPartitioner, String...) |
| */ |
| public interface StreamPartitioner<K, V> { |
| |
| /** |
| * Determine the partition number for a record with the given key and value and the current number of partitions. |
| * |
| * @param key the key of the record |
| * @param value the value of the record |
| * @param numPartitions the total number of partitions |
| * @return an integer between 0 and {@code numPartitions-1}, or {@code null} if the default partitioning logic should be used |
| */ |
| Integer partition(K key, V value, int numPartitions); |
| } |