BigQuery

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BigQuery
Type of site
Infrastructure as a service
Available in English
Owner Google
Website cloud.google.com/products/bigquery/
Registration Required
Launched May 19, 2010; 7 years ago (2010-05-19)
Current status Active

BigQuery is a RESTful web service that enables interactive analysis of massively large datasets working in conjunction with Google Storage. It is an Infrastructure as a Service (IaaS) that may be used complementarily with MapReduce.

History[edit]

After a limited testing period in 2010, BigQuery was generally available in November 2011 at the Google Atmosphere conference.[1] In 2014, MapR introduced the Apache Drill project, which was meant to solve similar problems.[2] In April, 2016, European users of the service suffered a 12-hour outage.[3] In May, 2016, support was announced for Google Sheets.[4]

Design[edit]

BigQuery provides an external access to the Dremel technology,[5][6] a scalable, interactive ad hoc query system for analysis of read-only nested data. To use the data in BigQuery, it first must be uploaded to Google Storage and in a second step imported using the BigQuery HTTP API. BigQuery requires all requests to be authenticated, supporting a number of Google-proprietary mechanisms as well as OAuth.

Features[edit]

  • Managing data - create and delete tables based on a JSON-encoded schema, import data encoded as CSV or JSON from Google Storage.
  • Query - the queries are expressed in a standard SQL dialect[7] and the results are returned in JSON with a maximum reply length of approximately 128 MB, or an unlimited size when large query results are enabled.[8]
  • Integration - BigQuery can be used from Google Apps Script, Google Spreadsheets, or any language that can work with its REST API or client libraries[9].
  • Access control - is possible to share datasets with arbitrary individuals, groups, or the world.

References[edit]

  1. ^ Iain Thomson (November 14, 2011). "Google opens BigQuery for cloud analytics: Dangles free trial to lure doubters". Retrieved August 26, 2016. 
  2. ^ Neil McAllister (September 16, 2014). "Is your data boring? MapR wants you to bore it back with Apache Drill: New release adds support for Google-y SQL-on-Hadoop tech". Retrieved August 26, 2016. 
  3. ^ Simon Sharwood (April 7, 2016). "Google Euro-cloud glitch". Retrieved August 26, 2016. 
  4. ^ Jordan Novet (May 6, 2016). "Google BigQuery now lets you analyze data from Google Sheets". Retrieved August 26, 2016. 
  5. ^ Sergey Melnik; Andrey Gubarev; Jing Jing Long; Geoffrey Romer; Shiva Shivakumar; Matt Tolton; Theo Vassilakis (2010). "Dremel: Interactive Analysis of Web-Scale Datasets". Proc. of the 36th International Conference on Very Large Data Bases (VLDB). 
  6. ^ Kazunori Sato (2012). "An Inside Look at Google BigQuery" (PDF). Google. Retrieved August 26, 2016. 
  7. ^ "SQL Reference". Retrieved 26 June 2017. 
  8. ^ "Quota Policy". Retrieved 26 June 2017. 
  9. ^ "BigQuery Client Libraries". Retrieved 26 June 2017. 

External links[edit]