Working with JSON, Arrays, and Structs in BigQuery
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.
이 실습의 나머지 부분과 기타 사항에 대해 알아보려면 Qwiklabs에 가입하세요.
- Google Cloud Console에 대한 임시 액세스 권한을 얻습니다.
- 초급부터 고급 수준까지 200여 개의 실습이 준비되어 있습니다.
- 자신의 학습 속도에 맞춰 학습할 수 있도록 적은 분량으로 나누어져 있습니다.
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