The Apache™ Hadoop® is an open-source software framework for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common and should be automatically handled by the framework.
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.
The project includes these modules:
• Hadoop Common: The common utilities that support the other Hadoop modules.
• Hadoop Distributed File System (HDFS™): A distributed file system that provides high-throughput access to application data.
• Hadoop YARN: A framework for job scheduling and cluster resource management.
• Hadoop MapReduce: A YARN-based system for parallel processing of large data sets.
Other Hadoop-related projects at Apache include:
• Ambari™: A web-based tool for provisioning, managing, and monitoring Apache Hadoop clusters which includes support for Hadoop HDFS, Hadoop MapReduce, Hive, HCatalog, HBase, ZooKeeper, Oozie, Pig and Sqoop. Ambari also provides a dashboard for viewing cluster health such as heatmaps and ability to view MapReduce, Pig and Hive applications visually alongwith features to diagnose their performance characteristics in a user-friendly manner.
• Avro™: A data serialization system.
• Cassandra™: A scalable multi-master database with no single points of failure.
• Chukwa™: A data collection system for managing large distributed systems.
• HBase™: A scalable, distributed database that supports structured data storage for large tables.
• Hive™: A data warehouse infrastructure that provides data summarization and ad hoc querying.
• Mahout™: A Scalable machine learning and data mining library.
• Pig™: A high-level data-flow language and execution framework for parallel computation.
• Spark™: A fast and general compute engine for Hadoop data. Spark provides a simple and expressive programming model that supports a wide range of applications, including ETL, machine learning, stream processing, and graph computation.
• Tez™: A generalized data-flow programming framework, built on Hadoop YARN, which provides a powerful and flexible engine to execute an arbitrary DAG of tasks to process data for both batch and interactive use-cases. Tez is being adopted by Hive™, Pig™ and other frameworks in the Hadoop ecosystem, and also by other commercial software (e.g. ETL tools), to replace Hadoop™ MapReduce as the underlying execution engine.
• ZooKeeper™: A high-performance coordination service for distributed applications.
Contents related to 'Apache Hadoop'
Apache Ambari: Ambari makes Hadoop management simpler by providing a consistent, secure platform for operational control.
Apache Avro: Apache Avro is a data serialization system.
Apache Cassandra: Apache Cassandra is a free and open-source distributed database management system designed to handle large amounts of data across many commodity servers.
Apache Chukwa: Chukwa is an open source data collection system for monitoring large distributed systems
Apache HBase: HBase is an open source, non-relational, distributed database modeled after Google's BigTable and written in Java
Apache Hive: Apache Hive is a data warehouse infrastructure built on top of Hadoop for providing data summarization, query, and analysis.
Apache Mahout: Apache Mahout is a library of scalable machine-learning algorithms, implemented on top of Apache Hadoop and using the MapReduce paradigm.
Apache Pig: Apache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs
Apache Spark: Apache® Spark™ is a powerful open source processing engine built around speed, ease of use, and sophisticated analytics
Apache Tez: The Apache Tez project is aimed at building an application framework which allows for a complex directed-acyclic-graph of tasks for processing data.
Apache ZooKeeper: Apache ZooKeeper is a software project of the Apache Software Foundation, providing an open source distributed configuration service, synchronization service, and naming registry for large distributed systems