Explain the distributed Cache in MapReduce framework.

1.	Explain the distributed Cache in MapReduce framework.
Answer» Distributed Cache is a significant feature provided by the MapReduce Framework, practiced when you want to share the FILES across all nodes in a Hadoop cluster. These files can be jar files or simple properties files. Hadoop's MapReduce framework allows the facility to cache SMALL to moderate read-only files such as text files, ZIP files, jar files, ETC., and distribute them to all the Datanodes(worker-nodes) MapReduce jobs are running. All Datanode gets a COPY of the file(local-copy), which is sent by Distributed Cache.

Answer»

Distributed Cache is a significant feature provided by the MapReduce Framework, practiced when you want to share the FILES across all nodes in a Hadoop cluster. These files can be jar files or simple properties files.

Hadoop's MapReduce framework allows the facility to cache SMALL to moderate read-only files such as text files, ZIP files, jar files, ETC., and distribute them to all the Datanodes(worker-nodes) MapReduce jobs are running. All Datanode gets a COPY of the file(local-copy), which is sent by Distributed Cache.

Discussion

No Comment Found

Related InterviewSolutions

Mention the consequences of Distributed Applications.
Explain the architecture of Flume.
What is Apache Flume in Hadoop ?
What is the default File format to import data using Apache sqoop?
Where is table data stored in Apache Hive by default?
If the source data gets updated every now and then, how will you synchronize the data in HDFS that is imported by Sqoop?
How do you differentiate inner bag and outer bag in Pig.
Why do we need to perform partitioning in Hive?
Are Multiline Comments supported in Hive? Why?
Compare differences between Local Metastore and Remote Metastore