/** * 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 kafka.consumer import java.util.concurrent.BlockingQueue import kafka.serializer.Decoder import kafka.message.MessageAndMetadata class KafkaStream[K,V](private val queue: BlockingQueue[FetchedDataChunk], consumerTimeoutMs: Int, private val keyDecoder: Decoder[K], private val valueDecoder: Decoder[V], val clientId: String) extends Iterable[MessageAndMetadata[K,V]] with java.lang.Iterable[MessageAndMetadata[K,V]] { private val iter: ConsumerIterator[K,V] = new ConsumerIterator[K,V](queue, consumerTimeoutMs, keyDecoder, valueDecoder, clientId) /** * Create an iterator over messages in the stream. */ def iterator(): ConsumerIterator[K,V] = iter /** * This method clears the queue being iterated during the consumer rebalancing. This is mainly * to reduce the number of duplicates received by the consumer */ def clear() { iter.clearCurrentChunk() } override def toString(): String = { "%s kafka stream".format(clientId) } }