Title: Hadoop
Author: Kriko
Published: Jun 15, 2023
Last modified: Jul 7, 2026

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# Hadoop

Hadoop is an open-source framework and ecosystem of software tools developed for
processing and storing large volumes of data. Maintained by the Apache Software 
Foundation, it is designed to help organisations manage large and complex datasets
efficiently.

Effective big [data](https://kriko.io/services/data-analysis-insight) management
plays an important role in both the operational performance and long-term development
of a business. Hadoop-based technologies allow valuable [data](https://kriko.io/services/data-analysis-insight)
to be processed and used in different ways. They also enable data-intensive workloads
that require significant computing power to be managed simultaneously across distributed
environments.

The Hadoop ecosystem consists of several components used in [data](https://kriko.io/services/data-analysis-insight)
storage, processing and analysis. Its core components include:

**Hadoop Distributed File System (HDFS):** HDFS is a distributed file system designed
to store large datasets. [Data](https://kriko.io/services/data-analysis-insight)
is divided into smaller blocks and distributed across multiple nodes, providing 
high availability, scalability and fault tolerance.

**MapReduce:** MapReduce is a distributed programming model used to process large
datasets in parallel. It divides processing tasks across multiple nodes and consists
of stages such as [data](https://kriko.io/services/data-analysis-insight) splitting,
mapping, shuffling and reducing.

**YARN, or Yet Another Resource Negotiator:** YARN is responsible for managing computing
resources and scheduling workloads within a Hadoop cluster. It enables different
applications to run on the same cluster while ensuring that available resources 
are allocated efficiently. This makes it easier to monitor and manage workloads 
across the Hadoop environment.

**Hadoop Common:** Hadoop Common provides the shared libraries, utilities and services
required by the other Hadoop modules. It contains the core resources and tools needed
to support distributed [data](https://kriko.io/services/data-analysis-insight) processing.

The origins of the Hadoop ecosystem can be traced back to research papers published
by Google on distributed file systems and large-scale [data](https://kriko.io/services/data-analysis-insight)
processing. Hadoop was later developed at Yahoo! as a practical framework for managing
web-scale data.

Today, Hadoop is widely used in areas such as big [data](https://kriko.io/services/data-analysis-insight)
analytics, [data](https://kriko.io/services/data-analysis-insight) warehousing, 
machine learning and artificial intelligence. Its open-source structure, scalability
and support from a large global community have contributed significantly to its 
widespread adoption.

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