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Difference between revisions of "Hadoop"

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== What is Hadoop? ==
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Apache '''Hadoop''' is an open-source software framework for storing and processing large amounts of data distributed across a cluster of computers. It is designed to handle large volumes of structured and unstructured data and is commonly used for storing and analyzing data from various sources, such as web logs, sensor data, and social media feeds.
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Hadoop consists of several components, including the Hadoop Distributed File System (HDFS), which is a distributed file system designed to store very large data sets; and the MapReduce programming model, which is a framework for writing applications that can process large amounts of data in parallel.
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Hadoop is designed to be scalable and fault-tolerant. It is able to store and process large amounts of data by distributing it across a cluster of machines and can automatically recover from hardware failures.
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Hadoop is often used in conjunction with other tools and frameworks, such as Apache Impala, Apache Hive, and Apache Pig, which provide additional functionality for storing, querying, and analyzing data.
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==See Also==
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*[[Big Data]]
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==References==
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<references />

Latest revision as of 00:27, 29 December 2022

What is Hadoop?

Apache Hadoop is an open-source software framework for storing and processing large amounts of data distributed across a cluster of computers. It is designed to handle large volumes of structured and unstructured data and is commonly used for storing and analyzing data from various sources, such as web logs, sensor data, and social media feeds.

Hadoop consists of several components, including the Hadoop Distributed File System (HDFS), which is a distributed file system designed to store very large data sets; and the MapReduce programming model, which is a framework for writing applications that can process large amounts of data in parallel.

Hadoop is designed to be scalable and fault-tolerant. It is able to store and process large amounts of data by distributing it across a cluster of machines and can automatically recover from hardware failures.

Hadoop is often used in conjunction with other tools and frameworks, such as Apache Impala, Apache Hive, and Apache Pig, which provide additional functionality for storing, querying, and analyzing data.



See Also



References