Introduction to Google's BigQuery

BigQuery

A BigQuery is a web-based tool that allows us to execute SQL-like queries and enables interactive analysis of massively large datasets at outstanding speeds working in conjunction with Google Storage.

BigQuery pricing

Charges are rounded to the nearest MB, with a minimum 10 MB data processed per table referenced by the query. The first 1 TB of data processed per month is free of charge. Other operations, such as saving a table to the cloud, requires you to set up billing. Setting up billing requires a cost ($0.026 per GB, per month) and for small queries, you won't need it.

Setting Up BigQuery

For setting up a BigQuery obviously you need a Google account. We can start a sample project by going through Google API Consloe.

Procedure

Step 1

After signing into the Google API Console, click on Create Project. Provide a name for your project. At this step the project will be created.



Step 2

A Dashboard will appear, click on Try BigQuery that will be in the top-left corner.



Step 3

After clicking on Try BigQuery a page will appear where you have some data to query. Click on Compose Query to query with sample data.



Getting Data for BigQuery

There are 2 ways to do this, either query sample data or load your own data.

Let's start with sample data.

After clicking on Try BigQuery a page will appear. In that page in the left pane click on the publicdata:samples dropdown list. It will show some sample databases. When you click on any database it will show the structure of the database.

Querying Data

To create your first query, click Compose Query in the top-left. A query box should show up at the top of your screen and whichever dataset you have selected should be below it. To start, let's work with the shakespeare data.

Example of Querying Data

SELECT word, SUM(word_count) as count
FROM (publicdata:samples.shakespeare)
WHERE word = "swagger"
OR word = "bedazzled"
GROUP BY word
ORDER BY count DESC

This query will return the "swagger" and "bedazzled" words counts in the shakespeare database.



Implementation of BigQuery: Boo-box

https://cloud.google.com/files/BooBox.pdf

Safari Books Online

https://developers.google.com/bigquery/case-studies/safari-books

redBus

https://cloud.google.com/files/Redbus.pdf

Crystalloids

https://cloud.google.com/files/Crystalloids.pdf

Claritics

https://cloud.google.com/files/Claritics.pdf

Conclusion

Day by day advancement is continuing in the field of BigData. Giant companies like Google, Microsoft, Yahoo and Amazon are the market leaders and compete with each other. Let's see what else develops with BigData in the near future.

This is a brief article about BigQuery but BigQuery is quite large in fact. I skipped the portion components of BigQuery. For that you can refer to the following link.

https://cloud.google.com/bigquery/what-is-bigquery

This is my first effort in the article section on c-sharpcorner, I hope you will like it a little bit. ;-)