Source code for pyspark.streaming.kinesis

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from py4j.protocol import Py4JJavaError

from pyspark.serializers import PairDeserializer, NoOpSerializer
from pyspark.storagelevel import StorageLevel
from pyspark.streaming import DStream

__all__ = ['KinesisUtils', 'InitialPositionInStream', 'utf8_decoder']

[docs]def utf8_decoder(s): """ Decode the unicode as UTF-8 """ if s is None: return None return s.decode('utf-8')
[docs]class KinesisUtils(object): @staticmethod
[docs] def createStream(ssc, kinesisAppName, streamName, endpointUrl, regionName, initialPositionInStream, checkpointInterval, storageLevel=StorageLevel.MEMORY_AND_DISK_2, awsAccessKeyId=None, awsSecretKey=None, decoder=utf8_decoder): """ Create an input stream that pulls messages from a Kinesis stream. This uses the Kinesis Client Library (KCL) to pull messages from Kinesis. Note: The given AWS credentials will get saved in DStream checkpoints if checkpointing is enabled. Make sure that your checkpoint directory is secure. :param ssc: StreamingContext object :param kinesisAppName: Kinesis application name used by the Kinesis Client Library (KCL) to update DynamoDB :param streamName: Kinesis stream name :param endpointUrl: Url of Kinesis service (e.g., :param regionName: Name of region used by the Kinesis Client Library (KCL) to update DynamoDB (lease coordination and checkpointing) and CloudWatch (metrics) :param initialPositionInStream: In the absence of Kinesis checkpoint info, this is the worker's initial starting position in the stream. The values are either the beginning of the stream per Kinesis' limit of 24 hours (InitialPositionInStream.TRIM_HORIZON) or the tip of the stream (InitialPositionInStream.LATEST). :param checkpointInterval: Checkpoint interval for Kinesis checkpointing. See the Kinesis Spark Streaming documentation for more details on the different types of checkpoints. :param storageLevel: Storage level to use for storing the received objects (default is StorageLevel.MEMORY_AND_DISK_2) :param awsAccessKeyId: AWS AccessKeyId (default is None. If None, will use DefaultAWSCredentialsProviderChain) :param awsSecretKey: AWS SecretKey (default is None. If None, will use DefaultAWSCredentialsProviderChain) :param decoder: A function used to decode value (default is utf8_decoder) :return: A DStream object """ jlevel = ssc._sc._getJavaStorageLevel(storageLevel) jduration = ssc._jduration(checkpointInterval) try: # Use KinesisUtilsPythonHelper to access Scala's KinesisUtils helper = except TypeError as e: if str(e) == "'JavaPackage' object is not callable": KinesisUtils._printErrorMsg(ssc.sparkContext) raise jstream = helper.createStream(ssc._jssc, kinesisAppName, streamName, endpointUrl, regionName, initialPositionInStream, jduration, jlevel, awsAccessKeyId, awsSecretKey) stream = DStream(jstream, ssc, NoOpSerializer()) return v: decoder(v))
@staticmethod def _printErrorMsg(sc): print(""" ________________________________________________________________________________________________ Spark Streaming's Kinesis libraries not found in class path. Try one of the following. 1. Include the Kinesis library and its dependencies with in the spark-submit command as $ bin/spark-submit --packages org.apache.spark:spark-streaming-kinesis-asl:%s ... 2. Download the JAR of the artifact from Maven Central, Group Id = org.apache.spark, Artifact Id = spark-streaming-kinesis-asl-assembly, Version = %s. Then, include the jar in the spark-submit command as $ bin/spark-submit --jars <spark-streaming-kinesis-asl-assembly.jar> ... ________________________________________________________________________________________________ """ % (sc.version, sc.version))
[docs]class InitialPositionInStream(object): LATEST, TRIM_HORIZON = (0, 1)