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

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

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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!


Syllabus


WEEK 1: Welcome to the Second Course: Big Data Analysis; Big Data SQL: Hive

WEEK 2: Big Data SQL: Hive (practice week)

WEEK 3: Spark SQL and Spark Dataframe

WEEK 4: Graph Analysis from Big Data Perspective

WEEK 5: PageRank and Recent Advances

WEEK 6: Spark Internals and Optimization



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