Software:BigQuery

From HandWiki

BigQuery is a managed, serverless data warehouse product by Google, offering scalable analysis over large quantities of data. It is a Platform as a Service (PaaS) that supports querying using a dialect of SQL and Graph Query Language[1]. It also has built-in machine learning capabilities. BigQuery was announced in May 2010 and made generally available in November 2011.[2]

History

Bigquery originated from Google's internal Dremel technology,[3][4] which enabled quick queries across trillions of rows of data.[5] The product was originally announced in May 2010 at Google I/O.[6] Initially, it was only usable by a limited number of external early adopters due to limitations on the API.[5] However, after the product proved its potential, it was released for limited availability in 2011 and general availability in 2012.[5] After general availability, BigQuery found success among a broad range of customers, including airlines, insurance, and retail organizations.[5]

Design

BigQuery requires all requests to be authenticated, supporting a number of Google-proprietary mechanisms as well as OAuth.

Features

  • Managing data - Create and delete objects such as tables, views, and user defined functions. Import data from Google Storage in formats such as CSV, Parquet, Avro or JSON.
  • Query - Queries are expressed in a 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[9] (e.g. as a bound script in Google Docs), or any language that can work with its REST API or client libraries.[10]
  • Access control - Share datasets with arbitrary individuals, groups, or the world.
  • Machine learning - Create and execute machine learning models using SQL queries.

References

  1. ↑ Saqib Ali (February 25, 2026). "Support for GQL is coming to Google BigQuery!". https://gql.net/support-for-gql-is-coming-to-google-bigquery/. 
  2. ↑ Iain Thomson (November 14, 2011). "Google opens BigQuery for cloud analytics: Dangles free trial to lure doubters". https://www.theregister.co.uk/2011/11/14/google_bigquery_cloud_analytics/. 
  3. ↑ "Dremel: Interactive Analysis of Web-Scale Datasets". Proc. of the 36th International Conference on Very Large Data Bases (VLDB). 2010. https://research.google.com/pubs/pub36632.html. 
  4. ↑ Kazunori Sato (2012). "An Inside Look at Google BigQuery". https://cloud.google.com/files/BigQueryTechnicalWP.pdf. 
  5. ↑ 5.0 5.1 5.2 5.3 Kwek, Ju-Kay. "BigQuery: the unlikely birth of a cloud juggernaut". https://towardsdatascience.com/bigquery-the-unlikely-birth-of-a-cloud-juggernaut-b5ad476525b7. 
  6. ↑ "Google I/O 2010 - BigQuery and Prediction APIs". 26 May 2010. https://www.youtube.com/watch?v=dbkwv1wjs3A. 
  7. ↑ "SQL Reference". https://cloud.google.com/bigquery/docs/reference/standard-sql/. 
  8. ↑ "Quota Policy". https://cloud.google.com/bigquery/quota-policy#queries. 
  9. ↑ "BigQuery Service | Apps Script | Google Developers". March 15, 2018. https://developers.google.com/apps-script/advanced/bigquery. 
  10. ↑ "BigQuery Client Libraries". https://cloud.google.com/bigquery/docs/reference/libraries. 



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