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BigQuery

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BigQuery
Type of site
Infrastructure as a service
Available inEnglish
OwnerGoogle
URLcloud.google.com/products/bigquery/
RegistrationRequired

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

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

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

  • 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 SQL dialect and the results are returned in JSON with a maximum reply length of approximately 64 MB.[7] There are some limitations to the usual SQL queries. For example, BigQuery supports joins, but one of the two JOINed tables must be small enough or use the JOIN EACH keyword instead.
  • Integration - BigQuery can be used from Google Apps Script, Google Spreadsheets, or any language that can work with its REST API.
  • Access control - is possible to share datasets with arbitrary individuals, groups, or the world.

References

  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. ^ "Google BigQuery API Overview (V2)". Retrieved 1 July 2012.
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