BigQuery: Difference between revisions
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*[http://code.google.com/p/bigquery-linkeddata/ BigQuery Endpoint] (an unofficial) [[Google App Engine]] application for issuing queries |
*[http://code.google.com/p/bigquery-linkeddata/ BigQuery Endpoint] (an unofficial) [[Google App Engine]] application for issuing queries |
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*[http://cran.r-project.org/web/packages/googlebigquery/ R client library] for communicating with Google BigQuery |
*[http://cran.r-project.org/web/packages/googlebigquery/ R client library] for communicating with Google BigQuery |
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*[https://github.com/ApacheDrill ApacheDrill] - Incubator for an Open Source version of BigQuery |
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{{Cloud computing}} |
{{Cloud computing}} |
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Revision as of 14:00, 30 August 2012
Type of site | Infrastructure as a service |
|---|---|
| Available in | English |
| Owner | |
| URL | code.google.com/apis/bigquery |
| Registration | Required |
BigQuery for Developers 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 complementary with MapReduce.
Design
BigQuery (BQ) is reportedly based on Dremel[1], 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 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 [2] . BigQuery does not currently support joins.
- Integration - BigQuery can be used from Google Apps Script and Google Spreadsheets.
- Access Control - is done via Google Storage.
Notes
- ^ 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).
{{cite web}}: CS1 maint: multiple names: authors list (link) - ^ "Google BigQuery API Overview (V2)". Retrieved 1 July 2012.
References
External links
- Official website
- BigQuery discuss Discussion Group
- Intro to new Google cloud technologies: Google Storage, Prediction API, BigQuery slideshare presentation by Chris Schalk (Developer Advocate at Google)
- BigQuery, meet Google Spreadsheets
- OpenDremel: Google BigQuery / Dremel implementation
- BigQuery Endpoint (an unofficial) Google App Engine application for issuing queries
- R client library for communicating with Google BigQuery
- ApacheDrill - Incubator for an Open Source version of BigQuery
