GCP BigQuery

BigQuery is one of the most popular data warehouses in the world. Webhook Relay functions allow directly inserting data into them.

Webhook Relay to BigQuery

Prerequisites:

• Google Cloud Platform account (free trial available)

• Google Cloud project with BigQuery enabled (there’s a generous free tier available for BigQuery)

• Dataset and table in BigQuery - https://cloud.google.com/bigquery/docs/tables

Webhook Relay provides a helper package bigquery that can stream writes into Google Cloud BigQuery. To start ingesting data from webhooks straight into your BigQuery table, create a new Function and just import ‘bigquery’ package:

-- Import BigQuery helper package
local bigquery = require('bigquery')

A new tab should appear that will ask you to set up credentials:

Configure GCP credentials

Go to that tab and it will ask you to:

1. Create new service accounts with BigQuery Editor permissions

2. Download the JSON file. Once you have the JSON file

3. Copy & paste contents into the form and click save.

Streaming data to GCP BigQuery

-- Import BigQuery helper package
local bigquery = require('bigquery')
local json = require("json")

-- Parsing payload
local rowData, err = json.decode(r.RequestBody)
if err then error(err) end

-- Initializing BigQuery client
err = bigquery.initialize('your-project-id', 'dataset-id', 'table-id')
if err then error(err) end

-- Receiving payload:
-- {
--     "hub_user_id": "user-id-here",
--     "category": "signup",
--     "action": "click",
--     "label": "github auth"
-- }

-- Insert row:
err = bigquery.insert(rowData)
if err then error(err) end

Check if record exists

A simple query to check whether a row exists by matching a column with a value:

bigquery = require('bigquery')
err =	bigquery.initialize('your-project-id', 'dataset-id', 'table-id')
if err then error(err) end

local exists, err = bigquery.record_exists('name', 'john')
if err then error(err) end

if exists then
  -- OK
else
  error('Record not found')
end

Execute any command

To execute any SQL command on your table:

bigquery = require('bigquery')
err =	bigquery.initialize('your-project-id', 'dataset-id', 'table-id')
if err then error(err) end

-- Delete old records of the matching category. Method 'exec' can take an arbitrary 
-- number of arguments, depending on how many ? you have in your query.
err = bigquery.exec('DELETE dataset-id.table-id WHERE category = ? AND country = ?', 'movies', 'US')
if err then error(err) end

BigQuery package API reference

At the moment there’s a single client method that bigquery package exposes:

Method name	Parameter Type	Description
insert(rowData)	Table	A table [key]value that represents a row data.
record_exists(column, value)	String, String	Checks if a row with the matching column exists

Limitations

Currently our package doesn’t support nested objects. That means that a table with a JSON structure such as:

{
    "hub_user_id": "user-id-here",
    "category": "signup",
    "action": "click",
    "label": "github auth",
    "nested_data": {
      "location": "GB",
      "date": "2020-05-10"
    }
}

will not be successfully inserted. Therefore, flatten the structure in the function before inserting it.

Troubleshooting

Few things to note:

• Ensure that project ID, dataset ID and table ID are there.

• BigQuery table schema is defined by the user. You don’t have to write all the fields (most of the can be nullable) but if you try to write a field that doesn’t exist, BigQuery will refuse to write.