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Apache Parquet
Apache Parquet is a free and open-source column-oriented data storage format in the Apache Hadoop ecosystem. It is similar to RCFile and ORC, the other columnar-storage file formats in Hadoop, and is compatible with most of the data processing frameworks around Hadoop. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in bulk. History The open-source project to build Apache Parquet began as a joint effort between Twitter and Cloudera. Parquet was designed as an improvement on the Trevni columnar storage format created by Doug Cutting, the creator of Hadoop. The first version, Apache Parquet1.0, was released in July 2013. Since April 27, 2015, Apache Parquet has been a top-level Apache Software Foundation (ASF)-sponsored project. Features Apache Parquet is implemented using the record-shredding and assembly algorithm, which accommodates the complex data structures that can be used to store data. The values in each colu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
GitHub
GitHub, Inc. () is an Internet hosting service for software development and version control using Git. It provides the distributed version control of Git plus access control, bug tracking, software feature requests, task management, continuous integration, and wikis for every project. Headquartered in California, it has been a subsidiary of Microsoft since 2018. It is commonly used to host open source software development projects. As of June 2022, GitHub reported having over 83 million developers and more than 200 million repositories, including at least 28 million public repositories. It is the largest source code host . History GitHub.com Development of the GitHub.com platform began on October 19, 2007. The site was launched in April 2008 by Tom Preston-Werner, Chris Wanstrath, P. J. Hyett and Scott Chacon after it had been made available for a few months prior as a beta release. GitHub has an annual keynote called GitHub Universe. Org ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Thrift
Thrift is an interface definition language and binary communication protocol used for defining and creating services for numerous programming languages. It was developed at Facebook for "scalable cross-language services development" and as of 2020 is an open source project in the Apache Software Foundation. With a remote procedure call (RPC) framework it combines a software stack with a code generation engine to build cross-platform services which can connect applications written in a variety of languages and frameworks, including ActionScript, C, C++, C#, Cappuccino, Cocoa, Delphi, Erlang, Go, Haskell, Java, JavaScript, Objective-C, OCaml, Perl, PHP, Python, Ruby, Elixir, Rust, Scala, Smalltalk and Swift. The implementation was described in an April 2007 technical paper released by Facebook, now hosted on Apache. Architecture Thrift includes a complete stack for creating clients and servers. The top part is generated code from the Thrift definition. From this file, the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trino (SQL Query Engine)
Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. Trino can query datalakes that contain open column-oriented data file formats like ORC or Parquet residing on different storage systems like HDFS, AWS S3, Google Cloud Storage, or Azure Blob Storage using the Hive and Iceberg table formats. Trino also has the ability to run federated queries that query tables in different data sources such as MySQL, PostgreSQL, Cassandra, Kafka, MongoDB and Elasticsearch. Trino is released under the Apache License. History In January 2019, the original creators of Presto, Martin Traverso, Dain Sundstrom, and David Phillips, created a fork of the Presto project. They initially kept the name Presto and used the PrestoSQL web handle to distinguish it from the original PrestoDB project. Simultaneously, they announced the Presto Software Foundation. The foundation is a not-for-profit organization de ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Kudu
Apache Kudu is a free and open source column-oriented data store of the Apache Hadoop ecosystem. It is compatible with most of the data processing frameworks in the Hadoop environment. It provides completeness to Hadoop's storage layer to enable fast analytics on fast data. The open source project to build Apache Kudu began as internal project at Cloudera. The first version Apache Kudu 1.0 was released 19 September 2016. Comparison with other storage engines Kudu was designed and optimized for OLAP workloads. Like HBase, it is a real-time store that supports key-indexed record lookup and mutation. Kudu differs from HBase since Kudu's datamodel is a more traditional relational model, while HBase is schemaless. Kudu's "on-disk representation is truly columnar and follows an entirely different storage design than HBase/Bigtable". See also * List of column-oriented DBMSes References External links * Apache Kudu GitHub repository {{DEFAULTSORT:Kudu Kudu The kudus a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Schema Evolution
In computer science, schema versioning and schema evolution, deal with the need to retain current data and software system functionality in the face of changing database structure. The problem is not limited to the modification of the schema. It, in fact, affects the data stored under the given schema and the queries (and thus the applications) posed on that schema. A database design is sometimes created as a "as of now" instance and thus schema evolution is not considered. (This is different but related to where a database is designed as a "one size fits all" which doesn't cover attribute volatility). This assumption, almost unrealistic in the context of traditional information systems, becomes unacceptable in the context of systems that retain large volumes of historical information or those such as Web Information Systems, that due to the distributed Distribution may refer to: Mathematics *Distribution (mathematics), generalized functions used to formulate solutions of pa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Run-length Encoding
Run-length encoding (RLE) is a form of lossless data compression in which ''runs'' of data (sequences in which the same data value occurs in many consecutive data elements) are stored as a single data value and count, rather than as the original run. This is most efficient on data that contains many such runs, for example, simple graphic images such as icons, line drawings, Conway's Game of Life, and animations. For files that do not have many runs, RLE could increase the file size. RLE may also be used to refer to an early graphics file format supported by CompuServe for compressing black and white images, but was widely supplanted by their later Graphics Interchange Format (GIF). RLE also refers to a little-used image format in Windows 3.x, with the extension rle, which is a run-length encoded bitmap, used to compress the Windows 3.x startup screen. Example Consider a screen containing plain black text on a solid white background. There will be many long runs of white pixe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dictionary Coder
A dictionary coder, also sometimes known as a substitution coder, is a class of lossless data compression algorithms which operate by searching for matches between the text to be compressed and a set of strings contained in a data structure (called the 'dictionary') maintained by the encoder. When the encoder finds such a match, it substitutes a reference to the string's position in the data structure. Methods and applications Some dictionary coders use a 'static dictionary', one whose full set of strings is determined before coding begins and does not change during the coding process. This approach is most often used when the message or set of messages to be encoded is fixed and large; for instance, an application that stores the contents of a book in the limited storage space of a PDA generally builds a static dictionary from a concordance of the text and then uses that dictionary to compress the verses. This scheme of using Huffman coding to represent indices into a concord ... [...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 i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Presto (SQL Query Engine)
Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, and allows use of multiple data sources within a query. Presto is community-driven open-source software released under the Apache License. History Presto was originally designed and developed at Facebook, Inc. (later renamed Meta) for their data analysts to run interactive queries on its large data warehouse in Apache Hadoop. The first four developers were Martin Traverso, Dain Sundstrom, David Phillips, and Eric Hwang. Before Presto, the data analysts at Facebook relied on Apache Hive for running SQL analytics on their multi-petabyte data warehouse. Hive was deemed too slow for Facebook's scale and Presto was invented to fill the gap to run fast queries. Original development started in 2012 and deplo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cascading (software)
Cascading is a software abstraction layer for Apache Hadoop and Apache Flink. Cascading is used to create and execute complex data processing workflows on a Hadoop cluster using any JVM-based language (Java, JRuby, Clojure, etc.), hiding the underlying complexity of MapReduce jobs. It is open source and available under the Apache License. Commercial support is available from Driven, Inc. Cascading was originally authored by Chris Wensel, who later founded Concurrent, Inc, which has been re-branded as Driven. Cascading is being actively developed by the community and a number of add-on modules are available. Architecture To use Cascading, Apache Hadoop must also be installed, and the Hadoop job .jar must contain the Cascading .jars. Cascading consists of a data processing API, integration API, process planner and process scheduler. Cascading leverages the scalability of Hadoop but abstracts standard data processing operations away from underlying map and reduce tasks. Develo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Pig
Apache Pig is a high-level platform for creating programs that run on Apache Hadoop. The language for this platform is called Pig Latin. Pig can execute its Hadoop jobs in MapReduce, Apache Tez, or Apache Spark. Pig Latin abstracts the programming from the Java MapReduce idiom into a notation which makes MapReduce programming high level, similar to that of SQL for relational database management systems. Pig Latin can be extended using user-defined functions (UDFs) which the user can write in Java, Python, JavaScript, Ruby or Groovy and then call directly from the language. History Apache Pig was originally developed at Yahoo Research around 2006 for researchers to have an ad hoc way of creating and executing MapReduce jobs on very large data sets. In 2007, it was moved into the Apache Software Foundation. Naming Regarding the naming of the Pig programming language, the name was chosen arbitrarily and stuck because it was memorable, easy to spell, and for novelty. Examp ... [...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] |
