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Use cases

The purpose of the jsonToDifferentTableFields transform is to take a JSON document stored in the "source_payload" field or one of the transform fields in an integration table, extract values from the JSON properties, and put these values into fields in another integration table.

The primary use case for extracting values from JSON properties and putting them in table fields is to enable SQL queries to use the collected data for analytics, machine learning, troubleshooting, queries, reporting, sending data to Thingworx, and supporting ETL jobs to send data to external systems, and so forth.


The SQL examples in this section show how SQL can add value to collected data.

Return records where the temperature is greater than 60

SQL can filter records based on field values.

SELECT temperature_whole 
FROM air_quality_sensor 
WHERE temperature_whole > 60;

Combine the whole and fractional parts of a temperature to compute a temperature value

SQL can create calculated values from fields. This example returns records where the computed temperature is greater than 80.

SELECT (temperature_whole + temperature_fraction) AS temperature 
FROM air_quality_sensor
WHERE (temperature_whole + temperature_fraction) > 80;

Create the integration table named air_quality_sensor.

If you want to run the previous SQL examples, you can use this JSON action.

  "api": "hub",
  "authToken": "replaceWithAuthTokenFromServer",
  "action": "createIntegrationTable",
  "params": {
    "databaseName": "faircom",
    "tableName": "air_quality_sensor",
    "fields": [
        "name": "temperature_whole",
        "type": "integer"
        "name": "temperature_fraction",
        "type": "integer"
    "metadata": {"description": "Custom integration table for air quality"},
    "retentionPeriod": 30,
    "retentionUnit": "day"

Add a record to this table

Run these SQL insert statements to add records to this table.

INSERT INTO air_quality_sensor 
(temperature_whole, temperature_fraction) VALUES(70,3);

INSERT INTO air_quality_sensor 
(temperature_whole, temperature_fraction) VALUES(80,9);


You may also run the JSON to external table transform tutorials to learn how to create a transform that automatically creates an integration table and inserts transformed records into it when the source integration table receives records.