S.No | Hadoop 1.X | Hadoop 2.X |
---|---|---|
1 | Hadoop 1.x having only two components for processing the data that two components are HDFS and MapReduce. | Hadoop 2.x having three components for processing the data that three components are HDFS,MapReduce and Yarn. |
2 | Hadoop 1.x supports mapreduce tools and distributed models only but not support non mapreduce tools. | It allows Mapreduce tools and other types of tools and distibuted models like Hbase,Spark. |
3 | In Hadoop 1.x Mapreduce does clustering and resource management Process. | In Hadoop 2.x YARN does clustering and resource management Process. |
4 | Hadoop 1.x have only 4000 nodes per cluster. | Hadoop 2.x have 10000 nodes per cluster. |
5 | Hadoop 1.x works on slot which run only map tasks or reduce tasks. | Hadoop 2.x works on containers which runs on all generic tasks. |
6 | Hadoop 1.x having one name node to manage entire namespaces. | Hadoop 2.x having multiple name node to manage multiple namespaces. |
7 | If namenode failure on hadoop one it needs manual work to overcome the failure. | If namenode failure on hadoop two, it configured to automatic recovery options. |
8 | Hadoop 1.x does not support windows. | It supports windows. |
9 | Namenode failure affects the whole hadoop 1.x stack. | In Hadoop 2.x hbase,pig are handles the namenode failure. |
10 | Hadoop 1.x not support data streaming and real time data processing. | It support data streaming and real time data processing. |
Also Read – Top Ten Difference Between Apache Hbase and Hive
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