Jq is a program described as " sed for JSON data": JSON stands for JavaScript Object Notation and is nearly ubiquitous as a data format, for its lightweight nature and (relatively) ease of human-readability.
#JQ QUERY HOW TO#
Most of the popular API and data services use the JSON data format, so we'll learn how it's used to serialize interesting information, and how to use the jq to parse it at the command-line. jq is a command-line tool for parsing JSON. | iotc::find(.name = "RangeOfMotion").valueĮxample 4: To manipulate the input message into a tabular format, you can map each exported message into one or more rows.JSON is a lightweight format that is nearly ubiquitous for data-exchange. This query also shows how to import and use the iotc module: import "iotc" as iotc ) | from_entriesĮxample 3: The following JQ query finds the RangeOfMotion telemetry value and converts it from degrees to radians using the formula rad = degree * pi / 180. You can use the Add your input message feature to generate a sample message based on a device template in your application. The structure of the message is similar for other message types but there are some type-specific fields.
All this data is available to your transformation. The following example shows the shape of telemetry message. Each type of data has a specific structure that includes information such as telemetry values, application info, device metadata, and property values. You can export the following streams of data from IoT Central: telemetry, property changes, device connectivity events, device lifecycle events, and device template lifecycle events. To learn more about writing JQ queries, see the JQ manual. For some query examples, see Example transformation queries. To specify a transformation, you write a JQ query, which can use the built-in filters, functions, and features of JQ. The transform engine uses the open-source JQ JSON processor to restructure and format JSON payloads. Then build a transform query to process this message into your required output format.
Then paste the message received by the webhook into 1. as the query to export the message as is to a destination such as a Webhook. If you don't know the format of your input message, use. The following video introduces you to IoT Central data transformations: For example, use a transformation to convert your messages into a tabular format that matches the schema of a destination such as an Azure Data Explorer table. Use transformations to restructure JSON payloads, rename fields, filter out fields, and run simple calculations on telemetry values. Each message passes through the transformation to create an output record that's exported to the destination. You can specify a transformation for each destination in an export definition. Transformations in an IoT Central data export definition let you manipulate the format and structure of the device data before it's exported to a destination. This article shows you how to transform device data as part of a data export definition in an IoT Central application. To use the device data in your IoT solution, you may need to transform your device data before it's exported to other services. IoT devices send data in various formats.
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