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Working with JSON, Arrays, and Structs in BigQuery

Working with JSON, Arrays, and Structs in BigQuery

1시간 15분 크레딧 5개

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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  • 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.
이 실습을 시작하려면 가입하세요
점수

—/100

Create a new dataset and table to store the data

단계 진행

/ 20

Execute the query to see how many unique products were viewed

단계 진행

/ 15

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

단계 진행

/ 15

Create a dataset and a table to ingest JSON data

단계 진행

/ 20

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

단계 진행

/ 10

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

단계 진행

/ 10

Execute the query to see which runner ran fastest lap time

단계 진행

/ 10