Hi All,
Need advice on executing multiple streaming jobs.
Problem:- We have 100's of streaming job. Every streaming job uses new
port. Also, Spark automatically checks port from 4040 to 4056, post that it
fails. One of the workaround, is to provide port explicitly.
Is there a way to tackle this
Hi Community,
I have a use case where i need to call stored procedure through structured
streaming.
I am able to send kafka message and call stored procedure ,
but since foreach sink keeps on executing stored procedure per message
i want to combine all the messages in single dtaframe and then c
I wrote a simple program to read data from HBase, the program works find in
Cloudera backed by HDFS. The program works fine on SPARK RUNTIME 1.6 on
Cloudera. But does NOT work on EMR with Spark Runtime 2.2.1.
But getting an exception while testing data on EMR with S3.
// Spark conf
Spar
Simple Java Program to Connect to Phoenix DB:
SparkConf sparkConf = new SparkConf();
sparkConf.setAppName("Using-spark-phoenix-df");
sparkConf.setMaster("local[*]");
JavaSparkContext sc = new JavaSparkContext(sparkConf);