menu
arrow_back

Working with JSON, Arrays, and Structs in BigQuery

Working with JSON, Arrays, and Structs in BigQuery

1 jam 15 menit 5 Kredit

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.

Bergabunglah dengan Qwiklabs untuk membaca tentang lab ini selengkapnya... beserta informasi lainnya!

  • Dapatkan akses sementara ke Google Cloud Console.
  • Lebih dari 200 lab mulai dari tingkat pemula hingga lanjutan.
  • Berdurasi singkat, jadi Anda dapat belajar dengan santai.
Bergabung untuk Memulai Lab Ini
Skor

—/100

Create a new dataset and table to store the data

Jalankan Langkah

/ 20

Execute the query to see how many unique products were viewed

Jalankan Langkah

/ 15

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

Jalankan Langkah

/ 15

Create a dataset and a table to ingest JSON data

Jalankan Langkah

/ 20

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

Jalankan Langkah

/ 10

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

Jalankan Langkah

/ 10

Execute the query to see which runner ran fastest lap time

Jalankan Langkah

/ 10