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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. The ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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The Apache () are a group of culturally related Native American tribes in the Southwestern United States, which include the Chiricahua, Jicarilla, Lipan, Mescalero, Mimbreño, Ndendahe (Bedonkohe or Mogollon and Nednhi or Carrizaleño and Janero), Salinero, Plains (Kataka or Semat or "Kiowa-Apache") and Western Apache ( Aravaipa, Pinaleño, Coyotero, Tonto). Distant cousins of the Apache are the Navajo, with whom they share the Southern Athabaskan languages. There are Apache communities in Oklahoma and Texas, and reservations in Arizona and New Mexico. Apache people have moved throughout the United States and elsewhere, including urban centers. The Apache Nations are politically autonomous, speak several different languages, and have distinct cultures. Historically, the Apache homelands have consisted of high mountains, sheltered and watered valleys, deep canyons, deserts, and the southern Great Plains, including areas in what is now Eastern Arizona, Northern Mexico (Sono ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Pig
Apache Pig is a high-level platform for creating programs that run on Hadoop, 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 (programming language), 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 (programming language), Java, Python (programming language), Python, JavaScript, Ruby (programming language), Ruby or Groovy (programming language), Groovy and then call directly from the language. History Apache Pig was originally developed at Yahoo!, 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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Sentry
The Apache () are a group of culturally related Native American tribes in the Southwestern United States, which include the Chiricahua, Jicarilla, Lipan, Mescalero, Mimbreño, Ndendahe (Bedonkohe or Mogollon and Nednhi or Carrizaleño and Janero), Salinero, Plains (Kataka or Semat or "Kiowa-Apache") and Western Apache ( Aravaipa, Pinaleño, Coyotero, Tonto). Distant cousins of the Apache are the Navajo, with whom they share the Southern Athabaskan languages. There are Apache communities in Oklahoma and Texas, and reservations in Arizona and New Mexico. Apache people have moved throughout the United States and elsewhere, including urban centers. The Apache Nations are politically autonomous, speak several different languages, and have distinct cultures. Historically, the Apache homelands have consisted of high mountains, sheltered and watered valleys, deep canyons, deserts, and the southern Great Plains, including areas in what is now Eastern Arizona, Northern Mexico ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ldap
The Lightweight Directory Access Protocol (LDAP ) is an open, vendor-neutral, industry standard application protocol for accessing and maintaining distributed directory information services over an Internet Protocol (IP) network. Directory services play an important role in developing intranet and Internet applications by allowing the sharing of information about users, systems, networks, services, and applications throughout the network. As examples, directory services may provide any organized set of records, often with a hierarchical structure, such as a corporate email directory. Similarly, a telephone directory is a list of subscribers with an address and a phone number. LDAP is specified in a series of Internet Engineering Task Force (IETF) Standard Track publications called Request for Comments (RFCs), using the description language ASN.1. The latest specification is Version 3, published aRFC 4511ref name="gracion Gracion.com. Retrieved on 2013-07-17. (a road map to the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Kerberos (protocol)
Kerberos () is a computer-network authentication protocol that works on the basis of ''tickets'' to allow nodes communicating over a non-secure network to prove their identity to one another in a secure manner. Its designers aimed it primarily at a client–server model, and it provides mutual authentication—both the user and the server verify each other's identity. Kerberos protocol messages are protected against eavesdropping and replay attacks. Kerberos builds on symmetric-key cryptography and requires a trusted third party, and optionally may use public-key cryptography during certain phases of authentication.RFC 4556, abstract. Kerberos uses UDP port 88 by default. The protocol was named after the character '' Kerberos'' (or ''Cerberus'') from Greek mythology, the ferocious three-headed guard dog of Hades. History and development Massachusetts Institute of Technology (MIT) developed Kerberos in 1988 to protect network services provided by Project Athena. The protocol is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache ORC
The Apache () are a group of culturally related Native American tribes in the Southwestern United States, which include the Chiricahua, Jicarilla, Lipan, Mescalero, Mimbreño, Ndendahe (Bedonkohe or Mogollon and Nednhi or Carrizaleño and Janero), Salinero, Plains (Kataka or Semat or "Kiowa-Apache") and Western Apache ( Aravaipa, Pinaleño, Coyotero, Tonto). Distant cousins of the Apache are the Navajo, with whom they share the Southern Athabaskan languages. There are Apache communities in Oklahoma and Texas, and reservations in Arizona and New Mexico. Apache people have moved throughout the United States and elsewhere, including urban centers. The Apache Nations are politically autonomous, speak several different languages, and have distinct cultures. Historically, the Apache homelands have consisted of high mountains, sheltered and watered valleys, deep canyons, deserts, and the southern Great Plains, including areas in what is now Eastern Arizona, Northern Mexico (Sono ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 column ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
RCFile
Within computing database management systems, the RCFile (Record Columnar File) is a data placement structure that determines how to store relational tables on computer clusters. It is designed for systems using the MapReduce framework. The RCFile structure includes a data storage format, data compression approach, and optimization techniques for data reading. It is able to meet all the four requirements of data placement: (1) fast data loading, (2) fast query processing, (3) highly efficient storage space utilization, and (4) a strong adaptivity to dynamic data access patterns. RCFile is the result of research and collaborative efforts from Facebook, The Ohio State University, and the Institute of Computing Technology at the Chinese Academy of Sciences. Summary Data storage format For example, a table in a database consists of 4 columns (c1 to c4): To serialize the table, RCFile partitions this table first horizontally and then vertically, instead of only partitioning the table ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Avro
Avro is a row-oriented remote procedure call and data serialization framework developed within Apache's Hadoop project. It uses JSON for defining data types and protocols, and serializes data in a compact binary format. Its primary use is in Apache Hadoop, where it can provide both a serialization format for persistent data, and a wire format for communication between Hadoop nodes, and from client programs to the Hadoop services. Avro uses a schema to structure the data that is being encoded. It has two different types of schema languages; one for human editing (Avro IDL) and another which is more machine-readable based on JSON. It is similar to Thrift and Protocol Buffers, but does not require running a code-generation program when a schema changes (unless desired for statically-typed languages). Apache Spark SQL can access Avro as a data source. Avro Object Container File An Avro Object Container File consists of: * A file header, followed by * one or more file dat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lempel–Ziv–Oberhumer
Lempel–Ziv–Oberhumer (LZO) is a lossless data compression algorithm that is focused on decompression speed. Design The original "lzop" implementation, released in 1996, was developed by Markus Franz Xaver Johannes Oberhumer, based on earlier algorithms by Abraham Lempel and Jacob Ziv. The LZO library implements a number of algorithms with the following characteristics: * Higher compression speed compared to DEFLATE compression * Very fast decompression * Requires an additional buffer during compression (of size 8 kB or 64 kB, depending on compression level) * Requires no additional memory for decompression other than the source and destination buffers * Allows the user to adjust the balance between compression ratio and compression speed, without affecting the speed of decompression LZO supports overlapping compression and in-place decompression. As a block compression algorithm, it compresses and decompresses blocks of data. Block size must be the same for compres ... [...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 ar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
