Google BigQuery

Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service (PaaS) that supports querying using ANSI SQL.It was designed for analyzing data on the order of billions of rows, using a SQL-like syntax. It runs on the Google Cloud Storage infrastructure and can be accessed with a REST-oriented application program interface (API).

Connecting to Google Account

Mammoth allows you to connect to Google account and get the data into Mammoth.

  1. Select API & Databases from the add menu and click on Google BigQuery.

    Google BigQuery selection
  2. Click on New Connection and log in into your Google account.

    Google BigQuery login
  3. Select the desired ProjectID - Dataset and click on Next.

    Google BigQuery profile

Once your Google account is connected with Mammoth, you will be presented with a list of tables and views in that database.

  • Select the desired table to get a preview.

  • Write your own SQL query or run a test query and preview the result.

  • Click on Next .

    Google BigQuery profile

After you have selected the table you want to work on, you get options to configure it as follows -

  • Rename it in the data pull scheduling window.

  • Save it in a desired location in the the Data Library from Adding file to option.

Scheduling your Data Pulls

You can start retrieving the data now or at a specific time according to your choice. You can also schedule the data pull in order to get the latest data from your Database at a certain time interval - daily, weekly or monthly.

On every data pull from your Database, you also have an option to either replace the older data or combine with older data.

BigQuery data pull

On choosing Combine with older data option, you will get an option to choose a unique sequence column. Using this column, on refresh, Mammoth will pick up all the rows that have greater value in this column than the previous data pull.