Database Reference
In-Depth Information
Summary
Sometimes you may want to use tools that operate over your raw BigQuery
data or otherwise use BigQuery through other mechanisms than the
BigQuery Web UI or HTTP API. This chapter showed ways to access your
data when you're not using BigQuery directly. You saw how to export your
data from BigQuery via export jobs and via direct download.
You saw how to access your data in parallel because when you deal with
Big Data, you're going to want to take advantage of scale-out parallel
architectures. MapReduce is the most common parallel architecture, and
you saw how to use AppEngine's MapReduce to transform data in parallel.
Google Compute Engine's Hadoop integration was introduced, which you
can also use to perform MapReduces over your BigQuery tables.
Finally, you saw how to run BigQuery queries from two different
spreadsheet programs: Google Spreadsheets and Microsoft Excel. The
spreadsheet integration can be a good launching point for incorporation of
BigQuery data into your own Business Intelligence applications.
The next chapter introduces some third-party tools that have been built on
top of BigQuery that enable you to visualize your data and extend the scope
of BigQuery access and usefulness.
