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You are implementing a batch processing solution by using Azure HDInsight.
You plan to import 300 TB of data.
You plan to use one job that has many concurrent tasks to import the data in memory.
You need to maximize the amount of concurrent tasks for the job.
What should you do?
A.
Use a shuffle join in an Apache Hive query that stores the data in a JSON format.
B.
Use a broadcast join in an Apache Hive query that stores the data in an ORC format.
C.
Increase the number of spark.executor.cores in an Apache Spark job that stores the data in a text format.
D.
Increase the number of spark.executor.instances in an Apache Spark job that stores the data in a text
format.
E.
Decrease the level of parallelism in an Apache Spark job that stores the data in a text format.
F.
Use an action in an Apache Oozie workflow that stores the data in a text format.
G.
Use an Azure Data Factory linked service that stores the data in Azure Data Lake.
H.
Use an Azure Data Factory linked service that stores the data in an Azure DocumentDB database.
Explanation:
https://blog.cloudera.com/blog/2015/03/how-to-tune-your-apache-spark-jobs-part-2/