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get_json

get_json(url, headers)

Description

GET json data from url

Examples

Call or Deploy get_json ?
Call get_json directly

The easiest way to use bigfunctions

  • get_json function is deployed in 39 public datasets for all of the 39 BigQuery regions.
  • It can be called by anyone. Just copy / paste examples below in your BigQuery console. It just works!
  • (You need to use the dataset in the same region as your datasets otherwise you may have a function not found error)

Public BigFunctions Datasets

Region Dataset
eu bigfunctions.eu
us bigfunctions.us
europe-west1 bigfunctions.europe_west1
asia-east1 bigfunctions.asia_east1
... ...
Deploy get_json in your project

Why deploy?

  • You may prefer to deploy get_json in your own project to build and manage your own catalog of functions.
  • This is particularly useful if you want to create private functions (for example calling your internal APIs).
  • Get started by reading the framework page

Deployment

get_json function can be deployed with:

pip install bigfunctions
bigfun get get_json
bigfun deploy get_json

select bigfunctions.eu.get_json('https://api.github.com/repos/unytics/bigfunctions', null)

select bigfunctions.us.get_json('https://api.github.com/repos/unytics/bigfunctions', null)

select bigfunctions.europe_west1.get_json('https://api.github.com/repos/unytics/bigfunctions', null)

+-------+
| data  |
+-------+
| {...} |
+-------+
Need help or Found a bug using get_json?
Get help using get_json

The community can help! Engage the conversation on Slack

We also provide professional suppport.

Report a bug about get_json

If the function does not work as expected, please

  • report a bug so that it can be improved.
  • or open the discussion with the community on Slack.

We also provide professional suppport.

Use cases

A use case for the get_json function is enriching data in BigQuery with information from an external API.

Scenario: You have a table in BigQuery containing information about GitHub repositories, including their names. You want to enrich this data with details like the number of stars, forks, and open issues for each repository. The GitHub API provides this information in JSON format.

Implementation:

  1. BigQuery Table: Let's assume your BigQuery table is named github_repos and has a column named repo_name containing the names of the repositories (e.g., "unytics/bigfunctions").

  2. BigQuery Query using get_json: You can use the following query to fetch data from the GitHub API and extract the desired information:

SELECT
    repo_name,
    JSON_EXTRACT_SCALAR(get_json(CONCAT('https://api.github.com/repos/', repo_name), NULL), '$.stargazers_count') AS stars,
    JSON_EXTRACT_SCALAR(get_json(CONCAT('https://api.github.com/repos/', repo_name), NULL), '$.forks_count') AS forks,
    JSON_EXTRACT_SCALAR(get_json(CONCAT('https://api.github.com/repos/', repo_name), NULL), '$.open_issues_count') AS open_issues
FROM
    `your-project.your-dataset.github_repos`;

Explanation:

  • CONCAT('https://api.github.com/repos/', repo_name) dynamically constructs the URL for each repository's API endpoint.
  • get_json(..., NULL) fetches the JSON data from the constructed URL. The second argument NULL indicates that no custom headers are needed for this request.
  • JSON_EXTRACT_SCALAR(..., '$.stargazers_count') extracts the value associated with the key stargazers_count from the JSON response. Similarly, we extract forks_count and open_issues_count.
  • Remember to replace your-project.your-dataset.github_repos with the actual path to your BigQuery table and select the correct regional dataset for bigfunctions (e.g., bigfunctions.us, bigfunctions.eu).

Result: This query will produce a new table with the original repo_name and the newly fetched stars, forks, and open_issues columns.

This example demonstrates how get_json can be used to integrate external API data directly into BigQuery for analysis and reporting, avoiding the need for intermediate data extraction and loading steps. You can adapt this pattern to interact with other APIs that provide JSON data.

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