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Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames (Coursera)

No doubt working with huge data volumes is hard, but to move a mountain, you have to deal with a lot of small stones. But why strain yourself? Using Mapreduce and Spark you tackle the issue partially, thus leaving some space for high-level tools. Stop struggling to make your big data workflow productive and efficient, make use of the tools we are offering you.

This course will teach you how to:

– Warehouse your data efficiently using Hive, Spark SQL and Spark DataFframes.

– Work with large graphs, such as social graphs or networks.

– Optimize your Spark applications for maximum performance.

Precisely, you will master your knowledge in:

– Writing and executing Hive & Spark SQL queries;

– Reasoning how the queries are translated into actual execution primitives (be it MapReduce jobs or Spark transformations);

– Organizing your data in Hive to optimize disk space usage and execution times;

– Constructing Spark DataFrames and using them to write ad-hoc analytical jobs easily;

– Processing large graphs with Spark GraphFrames;

– Debugging, profiling and optimizing Spark application performance.

Still in doubt? Check this out. Become a data ninja by taking this course!

Course 2 of 5 in the Big Data for Data Engineers Specialization

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