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author | jerryshao <saisai.shao@intel.com> | 2015-04-27 23:48:02 -0700 |
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committer | Tathagata Das <tathagata.das1565@gmail.com> | 2015-04-27 23:48:02 -0700 |
commit | 9e4e82b7bca1129bcd5e0274b9ae1b1be3fb93da (patch) | |
tree | 5df0f823975fd6f0ef7132a7346ca993bc30d63b /python/pyspark/streaming/kafka.py | |
parent | 29576e786072bd4218e10036ddfc8d367b1c1446 (diff) | |
download | spark-9e4e82b7bca1129bcd5e0274b9ae1b1be3fb93da.tar.gz spark-9e4e82b7bca1129bcd5e0274b9ae1b1be3fb93da.tar.bz2 spark-9e4e82b7bca1129bcd5e0274b9ae1b1be3fb93da.zip |
[SPARK-5946] [STREAMING] Add Python API for direct Kafka stream
Currently only added `createDirectStream` API, I'm not sure if `createRDD` is also needed, since some Java object needs to be wrapped in Python. Please help to review, thanks a lot.
Author: jerryshao <saisai.shao@intel.com>
Author: Saisai Shao <saisai.shao@intel.com>
Closes #4723 from jerryshao/direct-kafka-python-api and squashes the following commits:
a1fe97c [jerryshao] Fix rebase issue
eebf333 [jerryshao] Address the comments
da40f4e [jerryshao] Fix Python 2.6 Syntax error issue
5c0ee85 [jerryshao] Style fix
4aeac18 [jerryshao] Fix bug in example code
7146d86 [jerryshao] Add unit test
bf3bdd6 [jerryshao] Add more APIs and address the comments
f5b3801 [jerryshao] Small style fix
8641835 [Saisai Shao] Rebase and update the code
589c05b [Saisai Shao] Fix the style
d6fcb6a [Saisai Shao] Address the comments
dfda902 [Saisai Shao] Style fix
0f7d168 [Saisai Shao] Add the doc and fix some style issues
67e6880 [Saisai Shao] Fix test bug
917b0db [Saisai Shao] Add Python createRDD API for Kakfa direct stream
c3fc11d [jerryshao] Modify the docs
2c00936 [Saisai Shao] address the comments
3360f44 [jerryshao] Fix code style
e0e0f0d [jerryshao] Code clean and bug fix
338c41f [Saisai Shao] Add python API and example for direct kafka stream
Diffstat (limited to 'python/pyspark/streaming/kafka.py')
-rw-r--r-- | python/pyspark/streaming/kafka.py | 167 |
1 files changed, 160 insertions, 7 deletions
diff --git a/python/pyspark/streaming/kafka.py b/python/pyspark/streaming/kafka.py index 8d610d6569..e278b29003 100644 --- a/python/pyspark/streaming/kafka.py +++ b/python/pyspark/streaming/kafka.py @@ -17,11 +17,12 @@ from py4j.java_gateway import Py4JJavaError +from pyspark.rdd import RDD from pyspark.storagelevel import StorageLevel from pyspark.serializers import PairDeserializer, NoOpSerializer from pyspark.streaming import DStream -__all__ = ['KafkaUtils', 'utf8_decoder'] +__all__ = ['Broker', 'KafkaUtils', 'OffsetRange', 'TopicAndPartition', 'utf8_decoder'] def utf8_decoder(s): @@ -67,7 +68,104 @@ class KafkaUtils(object): except Py4JJavaError as e: # TODO: use --jar once it also work on driver if 'ClassNotFoundException' in str(e.java_exception): - print(""" + KafkaUtils._printErrorMsg(ssc.sparkContext) + raise e + ser = PairDeserializer(NoOpSerializer(), NoOpSerializer()) + stream = DStream(jstream, ssc, ser) + return stream.map(lambda k_v: (keyDecoder(k_v[0]), valueDecoder(k_v[1]))) + + @staticmethod + def createDirectStream(ssc, topics, kafkaParams, fromOffsets={}, + keyDecoder=utf8_decoder, valueDecoder=utf8_decoder): + """ + .. note:: Experimental + + Create an input stream that directly pulls messages from a Kafka Broker and specific offset. + + This is not a receiver based Kafka input stream, it directly pulls the message from Kafka + in each batch duration and processed without storing. + + This does not use Zookeeper to store offsets. The consumed offsets are tracked + by the stream itself. For interoperability with Kafka monitoring tools that depend on + Zookeeper, you have to update Kafka/Zookeeper yourself from the streaming application. + You can access the offsets used in each batch from the generated RDDs (see + + To recover from driver failures, you have to enable checkpointing in the StreamingContext. + The information on consumed offset can be recovered from the checkpoint. + See the programming guide for details (constraints, etc.). + + :param ssc: StreamingContext object. + :param topics: list of topic_name to consume. + :param kafkaParams: Additional params for Kafka. + :param fromOffsets: Per-topic/partition Kafka offsets defining the (inclusive) starting + point of the stream. + :param keyDecoder: A function used to decode key (default is utf8_decoder). + :param valueDecoder: A function used to decode value (default is utf8_decoder). + :return: A DStream object + """ + if not isinstance(topics, list): + raise TypeError("topics should be list") + if not isinstance(kafkaParams, dict): + raise TypeError("kafkaParams should be dict") + + try: + helperClass = ssc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \ + .loadClass("org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper") + helper = helperClass.newInstance() + + jfromOffsets = dict([(k._jTopicAndPartition(helper), + v) for (k, v) in fromOffsets.items()]) + jstream = helper.createDirectStream(ssc._jssc, kafkaParams, set(topics), jfromOffsets) + except Py4JJavaError as e: + if 'ClassNotFoundException' in str(e.java_exception): + KafkaUtils._printErrorMsg(ssc.sparkContext) + raise e + + ser = PairDeserializer(NoOpSerializer(), NoOpSerializer()) + stream = DStream(jstream, ssc, ser) + return stream.map(lambda k_v: (keyDecoder(k_v[0]), valueDecoder(k_v[1]))) + + @staticmethod + def createRDD(sc, kafkaParams, offsetRanges, leaders={}, + keyDecoder=utf8_decoder, valueDecoder=utf8_decoder): + """ + .. note:: Experimental + + Create a RDD from Kafka using offset ranges for each topic and partition. + :param sc: SparkContext object + :param kafkaParams: Additional params for Kafka + :param offsetRanges: list of offsetRange to specify topic:partition:[start, end) to consume + :param leaders: Kafka brokers for each TopicAndPartition in offsetRanges. May be an empty + map, in which case leaders will be looked up on the driver. + :param keyDecoder: A function used to decode key (default is utf8_decoder) + :param valueDecoder: A function used to decode value (default is utf8_decoder) + :return: A RDD object + """ + if not isinstance(kafkaParams, dict): + raise TypeError("kafkaParams should be dict") + if not isinstance(offsetRanges, list): + raise TypeError("offsetRanges should be list") + + try: + helperClass = sc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \ + .loadClass("org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper") + helper = helperClass.newInstance() + joffsetRanges = [o._jOffsetRange(helper) for o in offsetRanges] + jleaders = dict([(k._jTopicAndPartition(helper), + v._jBroker(helper)) for (k, v) in leaders.items()]) + jrdd = helper.createRDD(sc._jsc, kafkaParams, joffsetRanges, jleaders) + except Py4JJavaError as e: + if 'ClassNotFoundException' in str(e.java_exception): + KafkaUtils._printErrorMsg(sc) + raise e + + ser = PairDeserializer(NoOpSerializer(), NoOpSerializer()) + rdd = RDD(jrdd, sc, ser) + return rdd.map(lambda k_v: (keyDecoder(k_v[0]), valueDecoder(k_v[1]))) + + @staticmethod + def _printErrorMsg(sc): + print(""" ________________________________________________________________________________________________ Spark Streaming's Kafka libraries not found in class path. Try one of the following. @@ -85,8 +183,63 @@ ________________________________________________________________________________ ________________________________________________________________________________________________ -""" % (ssc.sparkContext.version, ssc.sparkContext.version)) - raise e - ser = PairDeserializer(NoOpSerializer(), NoOpSerializer()) - stream = DStream(jstream, ssc, ser) - return stream.map(lambda k_v: (keyDecoder(k_v[0]), valueDecoder(k_v[1]))) +""" % (sc.version, sc.version)) + + +class OffsetRange(object): + """ + Represents a range of offsets from a single Kafka TopicAndPartition. + """ + + def __init__(self, topic, partition, fromOffset, untilOffset): + """ + Create a OffsetRange to represent range of offsets + :param topic: Kafka topic name. + :param partition: Kafka partition id. + :param fromOffset: Inclusive starting offset. + :param untilOffset: Exclusive ending offset. + """ + self._topic = topic + self._partition = partition + self._fromOffset = fromOffset + self._untilOffset = untilOffset + + def _jOffsetRange(self, helper): + return helper.createOffsetRange(self._topic, self._partition, self._fromOffset, + self._untilOffset) + + +class TopicAndPartition(object): + """ + Represents a specific top and partition for Kafka. + """ + + def __init__(self, topic, partition): + """ + Create a Python TopicAndPartition to map to the Java related object + :param topic: Kafka topic name. + :param partition: Kafka partition id. + """ + self._topic = topic + self._partition = partition + + def _jTopicAndPartition(self, helper): + return helper.createTopicAndPartition(self._topic, self._partition) + + +class Broker(object): + """ + Represent the host and port info for a Kafka broker. + """ + + def __init__(self, host, port): + """ + Create a Python Broker to map to the Java related object. + :param host: Broker's hostname. + :param port: Broker's port. + """ + self._host = host + self._port = port + + def _jBroker(self, helper): + return helper.createBroker(self._host, self._port) |