hadoop in hindi | Introduction of hadoop | What is Hadoop

Hadoop is an open source, a Java-based programming framework that supports the processing and storage of extremely large data sets in a distributed computing environment.
 Hadoop is capable to work on the cluster(thousand of interconnected machines) and handle to thousand of terabytes data.
Hadoop provides rapid data transfer rate.
 Hadoop is capable to work on a cluster(thousand of interconnected machines) and handle to thousand of terabytes data.
It is developed by doug cutting and Mike cafarella in 2006.
It was inspired by Google’s MapReduce programming framework.
1. HDFS( Hadoop Distributed file system)- HDFS Architecture: It has 2 Types of Nodes-
1. NameNode
2. Data Node
3. YARN(Yet another resource Negotiator)
NameNode is also known as the Master
NameNode only stores the metadata of HDFS .
NameNode does not store the actual data or the dataset. The data stored in the DataNodes physically.
NameNode knows the list of the blocks and its location for any given file in HDFS. With this information, NameNode knows how to construct the file from blocks.
NameNode is a single point of failure in Hadoop cluster.
NameNode is usually configured with a lot of memory (RAM). Because the block locations help in main memory.
DataNode is responsible for storing the actual data in HDFS.
DataNode is also known as the Slave
NameNode and DataNode are in constant communication.
When a DataNode is down, it does not affect the availability of data or the cluster. NameNode will arrange for replication for the blocks managed by the DataNode that is not available.
Apache Hadoop 2.0 includes YARN, which separates the resource management and processing components. 

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