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  2. Data-intensive computing - Wikipedia

    en.wikipedia.org/wiki/Data-intensive_computing

    Hadoop implements a distributed data processing scheduling and execution environment and framework for MapReduce jobs. Hadoop includes a distributed file system called HDFS which is analogous to GFS in the Google MapReduce implementation. The Hadoop execution environment supports additional distributed data processing capabilities which are ...

  3. RCFile - Wikipedia

    en.wikipedia.org/wiki/RCFile

    RCFile has been adopted in real-world systems for big data analytics. RCFile became the default data placement structure in Facebook's production Hadoop cluster. [ 2 ] By 2010 it was the world's largest Hadoop cluster, [ 3 ] where 40 terabytes compressed data sets are added every day. [ 4 ]

  4. MapR - Wikipedia

    en.wikipedia.org/wiki/MapR

    MapR was a business software company headquartered in Santa Clara, California.MapR software provides access to a variety of data sources from a single computer cluster, including big data workloads such as Apache Hadoop and Apache Spark, a distributed file system, a multi-model database management system, and event stream processing, combining analytics in real-time with operational applications.

  5. MapReduce - Wikipedia

    en.wikipedia.org/wiki/MapReduce

    MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...

  6. Apache Hadoop - Wikipedia

    en.wikipedia.org/wiki/Apache_Hadoop

    The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part which is a MapReduce programming model. Hadoop splits files into large blocks and distributes them across nodes in a cluster. It then transfers packaged code into nodes to process the data in parallel.

  7. Distributed file system for cloud - Wikipedia

    en.wikipedia.org/wiki/Distributed_file_system...

    Modern data centers must support large, heterogenous environments, consisting of large numbers of computers of varying capacities. Cloud computing coordinates the operation of all such systems, with techniques such as data center networking (DCN), the MapReduce framework, which supports data-intensive computing applications in parallel and distributed systems, and virtualization techniques ...

  8. Apache Impala - Wikipedia

    en.wikipedia.org/wiki/Apache_Impala

    Impala is integrated with Hadoop to use the same file and data formats, metadata, security and resource management frameworks used by MapReduce, Apache Hive, Apache Pig and other Hadoop software. Impala is promoted for analysts and data scientists to perform analytics on data stored in Hadoop via SQL or business intelligence tools. The result ...

  9. Apache Hive - Wikipedia

    en.wikipedia.org/wiki/Apache_Hive

    Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. [3] [4] Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.