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Working with JSON, Arrays, and Structs in BigQuery

Working with JSON, Arrays, and Structs in BigQuery

1 hour 15 minutes 5 Credits

GSP416

Google Cloud Self-Paced Labs

Overview

BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

This lab is an in-depth walkthrough of working with semi-structured data (ingesting JSON, Array data types) inside of BigQuery. Denormalizing your schema into a single table with nested and repeated fields can yield performance improvements, but the SQL syntax for working with array data can be tricky. You will practice loading, querying, troubleshooting, and unnesting various semi-structured datasets.

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Score

—/100

Create a new dataset and table to store the data

Run Step

/ 20

Execute the query to see how many unique products were viewed

Run Step

/ 15

Execute the query to use the UNNEST() on array field

Run Step

/ 15

Create a dataset and a table to ingest JSON data

Run Step

/ 20

Execute the query to COUNT how many racers were there in total

Run Step

/ 10

Execute the query that will list the total race time for racers whose names begin with R

Run Step

/ 10

Execute the query to see which runner ran fastest lap time

Run Step

/ 10