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词条 Apache HBase
释义

  1. History

  2. Use cases & production deployments

      Enterprises that use HBase  

  3. See also

  4. References

  5. Bibliography

  6. External links

{{Use dmy dates|date=October 2013}}{{Infobox software
| name = Apache HBase
| logo = Apache_HBase_Logo_with_Orca.png
| logo size = 300px
| screenshot =
| caption =
| developer = Apache Software Foundation
| released = {{Start date and age|2008|03|28}}
| latest release version = 1.4.8
| latest release date = {{release date|df=yes|2018|10|08}}
| latest preview version =
| latest preview date =
| operating system = Cross-platform
| genre = Distributed database
| repo = https://github.com/apache/hbase
| programming language = Java
| license = Apache License 2.0
| website = {{URL|//hbase.apache.org/}}
}}

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.[1] 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 column-oriented key-value data store and has been idolized widely because of its lineage with Hadoop and HDFS. HBase runs on top of HDFS and is well-suited for faster read and write operations on large datasets with high throughput and low input/output latency.

HBase is not a direct replacement for a classic SQL database, however Apache Phoenix project provides a SQL layer for HBase as well as JDBC driver that can be integrated with various analytics and business intelligence applications. The Apache Trafodion project provides a SQL query engine with ODBC and JDBC drivers and distributed ACID transaction protection across multiple statements, tables and rows that use HBase as a storage engine.

HBase is now serving several data-driven websites[2] but Facebook's Messaging Platform recently migrated from HBase to MyRocks.[3][4] Unlike relational and traditional databases, HBase does not support SQL scripting; instead the equivalent is written in Java, employing similarity with a MapReduce application.

In the parlance of Eric Brewer’s CAP Theorem, HBase is a CP type system.

History

Apache HBase began as a project by the company Powerset out of a need to process massive amounts of data for the purposes of natural-language search. It is now a top-level Apache project.[5]

Facebook elected to implement its new messaging platform using HBase in November 2010, but migrated away from HBase in 2018.[3]{{As of|2017|02}}, the 1.2.x series is the current stable release line.

Use cases & production deployments

Enterprises that use HBase

The following is a list of notable enterprises that have used or are using HBase:

  • 23andMe
  • Adobe
  • Airbnb uses HBase as part of its AirStream realtime stream computation framework [6]
  • Alibaba Group
  • Amadeus IT Group, as its main long-term storage DB.
  • Bloomberg, for time series data storage
  • Facebook used HBase for its messaging platform between 2010 and 2018
  • Flurry
  • Imgur uses HBase to power its notifications system[7][8]
  • Kakao[9]
  • Netflix[10]
  • Pinterest
  • Quicken Loans
  • Richrelevance
  • Rocket Fuel
  • Salesforce.com[11]
  • Sears
  • Sophos, for some of their back-end systems.
  • Spotify uses HBase as base for Hadoop and machine learning jobs.[12]
  • Tuenti uses HBase for its messaging platform.[13][14]
  • Xiaomi
  • Yahoo!

See also

{{Portal|Free and open-source software|Java (programming language)}}
  • NoSQL
  • Wide column store
  • Bigtable
  • Apache Cassandra
  • Oracle NOSQL
  • Hypertable
  • Apache Accumulo
  • MongoDB
  • Project Voldemort
  • Riak
  • Sqoop
  • Elasticsearch
  • Apache Phoenix

References

1. ^Chang, et al. (2006). Bigtable: A Distributed Storage System for Structured Data
2. ^{{cite web|url=http://hbase.apache.org/poweredbyhbase.html|title=Apache HBase – Powered By Apache HBase™|author=|date=|website=hbase.apache.org|accessdate=8 April 2018}}
3. ^{{cite web|url=https://code.fb.com/data-infrastructure/migrating-messenger-storage-to-optimize-performance/|title=Migrating Messenger storage to optimize performance|author=|date=|website=www.facebook.com|accessdate=5 July 2018}}
4. ^[https://www.theregister.co.uk/2010/12/17/facebook_messages_tech/ Facebook: Why our 'next-gen' comms ditched MySQL] Retrieved: 17 December 2010
5. ^{{cite news |title=Brief Look on Apache Hbase |url=https://www.tatvasoft.com/blog/brief-look-apache-hbase/ |accessdate=26 December 2017 |ref=6}}
6. ^{{cite web|url=http://www.slideshare.net/HBaseCon/apache-hbase-at-airbnb|title=Apache HBase at Airbnb|first=|last=HBaseCon|date=2 August 2016|website=slideshare.net|accessdate=8 April 2018}}
7. ^{{cite web|url=https://dzone.com/articles/why-imgur-dropped-mysql-in-favor-of-hbase|title=Why Imgur Dropped MySQL in Favor of HBase - DZone Database|author=|date=|website=dzone.com|accessdate=8 April 2018}}
8. ^{{cite web|url=http://blog.imgur.com/2015/09/15/tech-tuesday-imgur-notifications-from-mysql-to-hbase/|title=Tech Tuesday: Imgur Notifications: From MySQL to HBase - The Imgur Blog|author=|date=|website=blog.imgur.com|accessdate=8 April 2018}}
9. ^{{cite web|url=http://apachebigdata2015.sched.org/event/de6abfbd8f0b9e66b1c03feb2b9e2078?iframe=yes&w=i:100;&sidebar=yes&bg=no |title=S2Graph : A Large-Scale Graph Database with HBase |author=Doyung Yoon}}
10. ^{{cite web|url=http://apachebigdata2015.sched.org/event/2a65daf0baa4cfbc227a8cb74a9103a2?iframe=no&w=i:100;&sidebar=yes&bg=no |title=Netflix: Integrating Spark at Petabyte Scale |author=Cheolsoo Park and Ashwin Shankar}}
11. ^{{cite web|url=https://www.slideshare.net/salesforceeng/hbase-at-salesforcecom|title=Hbase at Salesforce.com}}
12. ^{{cite web|url=http://apachebigdata2015.sched.org/event/2a65daf0baa4cfbc227a8cb74a9103a2?iframe=no&w=i:100;&sidebar=yes&bg=no |title=How Apache Drives Spotify's Music Recommendations |author=Josh Baer}}
13. ^{{cite web|url=http://corporate.tuenti.com/en/dev/blog/tuenti-group-chat-simple-yet-complex |title=Tuenti Group Chat: Simple, yet complex}}
14. ^{{cite web|url=https://github.com/tuenti/asyncthrift |title=Tuenti Asyncthrift}}

Bibliography

{{Refbegin}}
  • {{cite book

| first1 = Nick
| last1 = Dimiduk
| first2 = Amandeep
| last2 = Khurana
| date = 28 November 2012
| title = HBase in Action
| publisher = Manning Publications
| edition = 1st
| page = 350
| isbn = 978-1617290527
| url =
}}
  • {{cite book

| first1 = Lars
| last1 = George
| date = 20 September 2011
| title = HBase: The Definitive Guide
| publisher = O'Reilly Media
| edition = 1st
| page = 556
| isbn = 978-1449396107
| url = http://shop.oreilly.com/product/0636920014348.do
}}
  • {{cite book

| first = Yifeng
| last = Jiang
| date = 16 August 2012
| title = HBase Administration Cookbook
| publisher = Packt Publishing
| edition = 1st
| page = 332
| isbn = 978-1849517140
| url = http://www.packtpub.com/hbase-administration-for-optimum-database-performance-cookbook/book
}}{{Refend}}

External links

  • [//hbase.apache.org/ Official Apache HBase homepage]
  • [https://www.netwoven.com/2013/10/10/hbase-overview-of-architecture-and-data-model/ HBase Overview of Architecture]
{{Apache}}{{DEFAULTSORT:Hbase}}

4 : Bigtable implementations|Hadoop|Free database management systems|Structured storage

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