The base Apache Hadoop framework is composed of the following modules:
Hadoop Common – contains libraries and utilities needed by other Hadoop modules;
Hadoop Distributed File System (HDFS) #433 – a distributed file-system that stores data on commodity machines, providing very high aggregate bandwidth across the cluster;
Hadoop YARN #340 – (introduced in 2012) a platform responsible for managing computing resources in clusters and using them for scheduling users' applications;
Hadoop MapReduce #222 – an implementation of the MapReduce programming model for large-scale data processing.
The term Hadoop is often used for both base modules and sub-modules and also the ecosystem, or collection of additional software packages that can be installed on top of or alongside Hadoop, such as Apache Pig #416 , Apache Hive #412 , Apache HBase #415 , Apache Phoenix, Apache Spark #261 , Apache ZooKeeper, Cloudera Impala, Apache Flume, Apache Sqoop, Apache Oozie, and Apache Storm.
Apache Hadoop's MapReduce and HDFS components were inspired by Google papers on MapReduce and Google File System.
The Hadoop framework itself is mostly written in the Java programming language, with some native code in C and command line utilities written as shell scripts. Though MapReduce Java code is common, any programming language can be used with Hadoop Streaming to implement the map and reduce parts of the user's program. Other projects in the Hadoop ecosystem expose richer user interfaces.
https://en.wikipedia.org/wiki/Apache_Hadoop
The base Apache Hadoop framework is composed of the following modules:
The term Hadoop is often used for both base modules and sub-modules and also the ecosystem, or collection of additional software packages that can be installed on top of or alongside Hadoop, such as Apache Pig #416 , Apache Hive #412 , Apache HBase #415 , Apache Phoenix, Apache Spark #261 , Apache ZooKeeper, Cloudera Impala, Apache Flume, Apache Sqoop, Apache Oozie, and Apache Storm.
Apache Hadoop's MapReduce and HDFS components were inspired by Google papers on MapReduce and Google File System.
The Hadoop framework itself is mostly written in the Java programming language, with some native code in C and command line utilities written as shell scripts. Though MapReduce Java code is common, any programming language can be used with Hadoop Streaming to implement the map and reduce parts of the user's program. Other projects in the Hadoop ecosystem expose richer user interfaces.