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HDFS
Apache Hadoop () is a collection of open-source software utilities that facilitates using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage and processing of big data using the MapReduce programming model. Hadoop was originally designed for computer clusters built from commodity hardware, which is still the common use. It has since also found use on clusters of higher-end hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common occurrences and should be automatically handled by the framework. 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. This ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Impala
Apache Impala is an open source massively parallel processing (MPP) SQL query engine for data stored in a computer cluster running Apache Hadoop. Impala has been described as the open-source equivalent of Google F1, which inspired its development in 2012. Description Apache Impala is a query engine that runs on Apache Hadoop. The project was announced in October 2012 with a public beta test distribution and became generally available in May 2013. Impala brings scalable parallel database technology to Hadoop, enabling users to issue low-latency SQL queries to data stored in HDFS and Apache HBase without requiring data movement or transformation. 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. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache HBase
HBase is an open-source non-relational distributed database modeled after Google's Bigtable and written in Java. It is developed as part of Apache Software Foundation's Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System) or Alluxio, providing Bigtable-like capabilities for Hadoop. That is, it provides a fault-tolerant way of storing large quantities of sparse data (small amounts of information caught within a large collection of empty or unimportant data, such as finding the 50 largest items in a group of 2 billion records, or finding the non-zero items representing less than 0.1% of a huge collection). HBase features compression, in-memory operation, and Bloom filters on a per-column basis as outlined in the original Bigtable paper. Tables in HBase can serve as the input and output for MapReduce jobs run in Hadoop, and may be accessed through the Java API but also through REST, Avro or Thrift gateway APIs. HBase is a wide-column store and has been ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Hive
Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API. Since most data warehousing applications work with SQL-based querying languages, Hive aids portability of SQL-based applications to Hadoop. While initially developed by Facebook, Apache Hive is used and developed by other companies such as Netflix and the Financial Industry Regulatory Authority (FINRA). Amazon maintains a software fork of Apache Hive included in Amazon Elastic MapReduce on Amazon Web Services. Features Apache Hive supports ana ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Sqoop
Sqoop is a command-line interface application for transferring data between relational databases and Hadoop. The Apache Sqoop project was retired in June 2021 and moved to the Apache Attic. Description Sqoop supports incremental loads of a single table or a free form SQL query as well as saved jobs which can be run multiple times to import updates made to a database since the last import. Imports can also be used to populate tables in Hive or HBase. Exports can be used to put data from Hadoop into a relational database. Sqoop got the name from "SQL-to-Hadoop". Sqoop became a top-level Apache project in March 2012. Informatica provides a Sqoop-based connector from version 10.1. Pentaho provides open-source Sqoop based connector steps, ''Sqoop Import'' and ''Sqoop Export'', in their ETL suite Pentaho Data Integration since version 4.5 of the software. Microsoft uses a Sqoop-based connector to help transfer data from Microsoft SQL Server databases to Hadoop. Couchbase, Inc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed File System
A clustered file system is a file system which is shared by being simultaneously mounted on multiple servers. There are several approaches to clustering, most of which do not employ a clustered file system (only direct attached storage for each node). Clustered file systems can provide features like location-independent addressing and redundancy which improve reliability or reduce the complexity of the other parts of the cluster. Parallel file systems are a type of clustered file system that spread data across multiple storage nodes, usually for redundancy or performance. Shared-disk file system A shared-disk file system uses a storage area network (SAN) to allow multiple computers to gain direct disk access at the block level. Access control and translation from file-level operations that applications use to block-level operations used by the SAN must take place on the client node. The most common type of clustered file system, the shared-disk file system —by ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Spark
Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance. Originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since. Overview Apache Spark has its architectural foundation in the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. The Dataframe API was released as an abstraction on top of the RDD, followed by the Dataset API. In Spark 1.x, the RDD was the primary application programming interface (API), but as of Spark 2.x use of the Dataset API is encouraged even though the RDD API is not deprecated. The RDD technology still underlies the Dataset API. Spark and its RDDs were developed in 2012 in response to limitations in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Clustered File System
A clustered file system is a file system which is shared by being simultaneously mounted on multiple servers. There are several approaches to clustering, most of which do not employ a clustered file system (only direct attached storage for each node). Clustered file systems can provide features like location-independent addressing and redundancy which improve reliability or reduce the complexity of the other parts of the cluster. Parallel file systems are a type of clustered file system that spread data across multiple storage nodes, usually for redundancy or performance. Shared-disk file system A shared-disk file system uses a storage area network (SAN) to allow multiple computers to gain direct disk access at the block level. Access control and translation from file-level operations that applications use to block-level operations used by the SAN must take place on the client node. The most common type of clustered file system, the shared-disk file system —by ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parallel File System
A clustered file system is a file system which is shared by being simultaneously mounted on multiple servers. There are several approaches to clustering, most of which do not employ a clustered file system (only direct attached storage for each node). Clustered file systems can provide features like location-independent addressing and redundancy which improve reliability or reduce the complexity of the other parts of the cluster. Parallel file systems are a type of clustered file system that spread data across multiple storage nodes, usually for redundancy or performance. Shared-disk file system A shared-disk file system uses a storage area network (SAN) to allow multiple computers to gain direct disk access at the block level. Access control and translation from file-level operations that applications use to block-level operations used by the SAN must take place on the client node. The most common type of clustered file system, the shared-disk file system —by a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Doug Cutting
Douglass Read Cutting is a software designer, advocate, and creator of open-source search technology. He founded two technology projects, Lucene, and Nutch, with Mike Cafarella. Both projects are now managed through the Apache Software Foundation. Cutting and Cafarella are also the co-founders of Apache Hadoop. Education and early career Cutting graduated from Stanford University in 1985 with a bachelor's degree. Prior to developing Lucene, Cutting held search technology positions at Xerox PARC where he worked on the Scatter/Gather algorithm Cutting, Douglass R., David R. Karger, Jan O. Pedersen, and John W. Tukey. "Scatter/gather: A cluster-based approach to browsing large document collections." SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval. (Reprinted in ACM SIGIR Forum, vol. 51, no. 2, pp. 148-159. ACM, 2017.) Pedersen, Jan O., David Karger, Douglass R. Cutting, and John W. Tukey. "Scatter-gathe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed Processing
A distributed system is a system whose components are located on different networked computers, which communicate and coordinate their actions by passing messages to one another from any system. Distributed computing is a field of computer science that studies distributed systems. The components of a distributed system interact with one another in order to achieve a common goal. Three significant challenges of distributed systems are: maintaining concurrency of components, overcoming the lack of a global clock, and managing the independent failure of components. When a component of one system fails, the entire system does not fail. Examples of distributed systems vary from SOA-based systems to massively multiplayer online games to peer-to-peer applications. A computer program that runs within a distributed system is called a distributed program, and ''distributed programming'' is the process of writing such programs. There are many different types of implementations for t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Flume
Apache Flume is a distributed, reliable, and available software for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application. See also *List of Apache Software Foundation projects * Hortonworks DataFlow References Data mining and machine learning software Flume A flume is a human-made channel for water, in the form of an open declined gravity chute whose walls are raised above the surrounding terrain, in contrast to a trench or ditch. Flumes are not to be confused with aqueducts, which are built to ... Free software programmed in Java (programming language) System administration {{free-software-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache ZooKeeper
Apache ZooKeeper is an open-source server for highly reliable distributed coordination of cloud applications. It is a project of the Apache Software Foundation. ZooKeeper is essentially a service (systems architecture), service for distributed computing, distributed systems offering a hierarchical database model, hierarchical Key-value database, key-value store, which is used to provide a distributed configuration management, configuration service, synchronization (computer science), synchronization service, and directory service, naming registry for large distributed systems (see ''#Use cases, Use cases''). ZooKeeper was a sub-project of Hadoop but is now a Apache Software Foundation#Projects, top-level Apache project in its own right. Overview ZooKeeper's software architecture, architecture supports High-availability cluster, high availability through redundancy (engineering), redundant services. The clients can thus ask another ZooKeeper leader if the first fails to answer. Zoo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
