Dynamic Width File in Spark_2016
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This document discusses how to efficiently handle dynamic width files in Spark using Scala, Spark RDDs, and dataframes. It demonstrates reading in a dynamic width source file from mainframe sources, defining a schema, executing code to create a dataframe with the schema, registering the dataframe as a temporary table, and running analytical queries on the temporary table.
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Dynamic Width File in Spark_2016
- 1. How to handle Dynamic Width File in Spark Dynamic WidthFile is a common type of source fromMainframe sources;The Belowdemonstrationis one of the efficient ways to handle dynamic widthFile usingScala, Spark RDDandDataframe. Check thiscode, Execute in your REPL. Source File Schema of the File Code to be Executed
- 2. Dataframe Schema Registeringas Temp Table and Show the Data ImplementingAnalytical Queryinto the temptable SELECT id,fname,lname,CAST(sum(subject_wise_marks.marks)/numberofsubjectasDouble) as percentage FROMscore LATERALVIEW explode(subjectwisemarks) marks_tableas subject_wise_marksgroupbyid,fname,lname,numberofsubject; Result