Working with JSON, Arrays, and Structs in BigQuery




Create a new dataset and table to store the data

Execute the query to see how many unique products were viewed

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

Create a dataset and a table to ingest JSON data

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

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

Execute the query to see which runner ran fastest lap time

Working with JSON, Arrays, and Structs in BigQuery

1 godz. 15 godz. Punkty: 5


Google Cloud Self-Paced Labs


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.

In this lab you will work in-depth 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.

Dołącz do Qwiklabs, aby zapoznać się z resztą tego modułu i innymi materiałami.

  • Uzyskaj tymczasowy dostęp do Google Cloud Console.
  • Ponad 200 modułów z poziomów od początkującego do zaawansowanego.
  • Podzielono na części, więc można uczyć się we własnym tempie.
Dołącz, aby rozpocząć ten moduł