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bigdata-beast · ‎08-28-2019

Am using spark 2.3.0 and python 2.7.13. Am trying to build a streaming pipeline but am getting error while trying to createStream. below is the code snippet am using . Am trying it pyspark2 --master="local[*]". I have the jars in my local which am setting using config option (read online that kinesis asl & spark should have compatible jar versions: from __future__ import print_function import sys from pyspark.sql import SparkSession from pyspark.sql.functions import * from pyspark.storagelevel import StorageLevel from pyspark.streaming import DStream from pyspark.streaming import StreamingContext from pyspark.streaming.kinesis import KinesisUtils, InitialPositionInStream spark = SparkSession.builder.appName("TestStreaming").config("spark.jars","spark-streaming-kinesis-asl_2.11-2.3.0.jar")\ .config("spark.jars","spark-streaming-kinesis-asl-assembly_2.11-2.0.0.jar")\ .config("spark.jars","aws-java-sdk-1.11.310.jar")\ .config("spark.jars","amazon-kinesis-client-1.9.0.jar")\ .getOrCreate() ssc = StreamingContext(spark, 2) lines = KinesisUtils.createStream(ssc, "TestStreaming", "cwlog-kinesis-stream-SDLC-catalina", "https://kinesis.us-east-1.amazonaws.com", "us-east-1", InitialPositionInStream.LATEST, 2, StorageLevel.MEMORY_AND_DISK_2) Am getting below on executing "lines": Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/opt/cloudera/parcels/SPARK2-2.3.0.cloudera3-1.cdh5.13.3.p0.458809/lib/spark2/python/pyspark/streaming/kinesis.py", line 79, in createStream jlevel = ssc._sc._getJavaStorageLevel(storageLevel) AttributeError: 'SparkSession' object has no attribute '_getJavaStorageLevel'

bigdata-beast · ‎12-14-2018

The same can be peformed in hive using concat_ws('.',from_unixtime(cast(epochmillis/1000 as BIGINT),'yyyy-MM-dd HH:mm:ss'),cast(floor(epochmillis % 1000) as STRING)) to get the timestamp with milliseconds. Is this efficient way of doing it ?

bigdata-beast · ‎11-01-2018

Please post this query in a new thread. this is not related to the post. To answer your query. Try these steps: Use --direct path, it helps improve performance. Select appropriate --split-by key that is of numerical type (like INT) & also is continuous. This ensures the mappers get appx. equal chunk of data to process & thus makes full use of parallel processing. Try increasing the --fetch-size , by default it is 1000. Try using --boundary-query [sqoop handles this internally but if that is not efficient then you can override it with this boundary query].

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Last Visited	‎10-08-2019 10:28 AM

Date Registered	‎11-01-2018 08:14 AM
Last Visited	‎10-08-2019 10:28 AM
Total Messages Posted	4

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