Hadoop Yarn
About Hadoop Yarn
The key element of Hadoop 2.0 is YARN. By enabling the processing of data stored in HDFS for batch processing, stream processing, interactive processing, and graph processing, YARN helps in the opening up of Hadoop. By doing this, it makes it easier to execute distributed applications other than MapReduce.
Why is Hadoop Yarn important?
YARN increases system efficiency by enabling various data processing engines, including graph processing, interactive processing, stream processing, batch processing, and more, to execute and process data stored in HDFS (Hadoop Distributed File System).
YARN is made to let individual applications use cluster resources in a shared, secure, and multi-tenant way (via the ApplicationMaster). Additionally, it keeps track of the cluster topology to effectively plan and optimize data access, i.e., minimize data mobility for applications.
Who should take the Hadoop Yarn Exam?
- This course is for anyone who aspires a career as a Hadoop Developer.
Hadoop Yarn Certification Course Outline
- Understanding Big Data and Hadoop
- Hadoop Architecture and HDFS
- Hadoop MapReduce Framework
- Advanced Hadoop MapReduce
- Apache Pig
- Apache Hive
- Advanced Apache Hive and HBase
- Advanced Apache HBase
- Processing Distributed Data with Apache Spark
- Oozie and Hadoop Project