Certificate in MapReduce
About MapReduce
A parallel, distributed algorithm called MapReduce is a programming concept with an accompanying implementation for handling and producing large amounts of data on a cluster. A map method, which conducts filtering and sorting, and a reduce method, which does a summary operation, make up a map reduction program. Petabytes of data are divided into smaller bits and processed concurrently on inexpensive Hadoop servers to enable concurrent processing.
Why is MapReduce important?
The fundamental advantage of MapReduce is that it makes it simple for users to spread out data processing across several computer nodes. Mappers and reducers are the data processing primitives utilized in the MapReduce paradigm. It might be challenging to separate a data processing application into mappers and reducers at times.
Who should take the MapReduce Exam?
- Students who want to learn Hadoop MapReduce.
- Those who have only basic theoretical knowledge of MapReduce.
- Engineers who want to switch their careers to Hadoop.
MapReduce Certification Course Outline
- Overview of MapReduce
- Basic Flow of a MapReduce program
- MapReduce Program flow with Example
- Types of File Input formats in MapReduce
- The default structure of classes in MapReduce
- MapReduce word count program
- Set of MapReduce programs
- Distributed cache implementation
- Input split class
- Joins in MapReduce
- Counters in MapReduce
- Creating custom input formatter
- File types in Hadoop
- Chaining in MapReduce