1)What do you mean by Hadoop?
Hadoop is an open source software framework for processing and storing big size data in a distributed fashion on large clusters of commodity hardware.
2)What do you mean by Hadoop framework?
A Hadoop is free Java based programming framework which supports the processing of big data sets in a distributed computing environment.
3)What do you mean by Hadoop MapReduce?
Hadoop MapReduce framework is used for processing large data sets in parallel across a hadoop cluster. The two step map and reduces process uses by data analysis.
4)What is the NameNode in Hadoop?
The NameNode in Hadoop is the node, where Hadoop stores all the file location information in Hadoop Distributed File System (HDFS). In other words, we can say that NameNode is the centerpiece of a Hadoop Distributed File System.
5)Can we change the file cached by Distributed Cache in Hadoop?
No, because the DistributedCache tracks the caching with timestamp a cached file should not be changed during the job execution.
6)What do you mean by Distributed Cache in mapreduce framework?
The distributed cache is a very effective feature provide by the map reduce framework. The Distributed cache can cache archive, text, jars which could be used by application to increase performance. Application give complete information’s of jobconf object to cache.
7)What is a task tracker in Hadoop?
A task tracker is real component which provides the mapreduce jar on the data nodes and responsible to execute the task given mapreduce. It continuously executes the task and send updated reports to job tracker.
8)What do you mean by Job Tracer in Hadoop?
A JobTracer is a service within runs MapReduce jobs on the cluster.
9)Can you necessary to write jobs for Hadoop in Java language?
No, there are various techniques to deal with non-java codes. A Hadoop Streaming give any shell command to be used as a map or reduce function.
10)What do you mean by combiner in Hadoop?
The combiner is a mini_reduce technique which operates only on data generated by a Mapper. When the Mapper emits the data combiner receives it as input and the output to reducer.
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