| # |
| # 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. |
| # |
| |
| """ |
| Create a queue of RDDs that will be mapped/reduced one at a time in |
| 1 second intervals. |
| |
| To run this example use |
| `$ bin/spark-submit examples/src/main/python/streaming/queue_stream.py |
| """ |
| import time |
| |
| from pyspark import SparkContext |
| from pyspark.streaming import StreamingContext |
| |
| if __name__ == "__main__": |
| |
| sc = SparkContext(appName="PythonStreamingQueueStream") |
| ssc = StreamingContext(sc, 1) |
| |
| # Create the queue through which RDDs can be pushed to |
| # a QueueInputDStream |
| rddQueue = [] |
| for i in range(5): |
| rddQueue += [ssc.sparkContext.parallelize([j for j in range(1, 1001)], 10)] |
| |
| # Create the QueueInputDStream and use it do some processing |
| inputStream = ssc.queueStream(rddQueue) |
| mappedStream = inputStream.map(lambda x: (x % 10, 1)) |
| reducedStream = mappedStream.reduceByKey(lambda a, b: a + b) |
| reducedStream.pprint() |
| |
| ssc.start() |
| time.sleep(6) |
| ssc.stop(stopSparkContext=True, stopGraceFully=True) |