Loading Data Into BigQuery From Cloud Storage. Complete Guide.

Loading data into BigQuery using Cloud Functions in 20 minutes.

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In this article, we will build a streaming real-time analytics pipeline using Google Client Libraries. We will create a Cloud Function to load data from Google Storage into BigQuery. This is a complete guide on how to work with tables, different file formats, and schemas.

Our Cloud function is built on top of the hybrid solution using both AWS and Google Cloud Platform.

Let’s assume we have all our source files in Google Storage. Using the techniques that we’ll cover for this part, you will have a foundation to build any sort of table in BigQuery Data Warehouse.

We will also be going over the details of wiring up a simple data loading system, along with covering some guidelines for schemas, different file formats and BigQuery Python API components, e.g. load_table_from_json, load_table_from_file and load_table_from_dataframe.

Before trying this article, follow the Python setup instructions in the BigQuery Quickstart Using Client Libraries.

Prerequisites:

• Google developer account.
• Google Command Line Interface. Follow this article to install it…