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Official CCA Spark and Hadoop Developer Exam Syllabus:
Transform, Stage, and Store
Convert a set of data values in a given format stored in HDFS into new data values or a new data format and write them into HDFS.
Load data from HDFS for use in Spark applications
Write the results back into HDFS using Spark
Read and write files in a variety of file formats
Perform standard extract, transform, load (ETL) processes on data using the Spark API
Data Analysis
Use Spark SQL to interact with the metastore programmatically in your applications. Generate reports by using queries against loaded data.
Use metastore tables as an input source or an output sink for Spark applications
Understand the fundamentals of querying datasets in Spark
Filter data using Spark
Write queries that calculate aggregate statistics
Join disparate datasets using Spark
Produce ranked or sorted data
Configuration
This is a practical exam and the candidate should be familiar with all aspects of generating a result, not just writing code.
Supply command-line options to change your application configuration, such as increasing available memory
Official CCA Spark and Hadoop Developer Exam Details:
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