JSON JQ Transform Task

"type" : "JSON_JQ_TRANSFORM"

Introduction

The JSON_JQ_TRANSFORM task is a System task that allows the processing of JSON data that is supplied to the task by using the popular JQ processing tool’s query expression language.

Check the JQ Manual and the JQ Playground for more information on JQ.

Use Cases

JSON is a popular format of choice for data interchange. It is widely used in web and server applications, document storage, API I/O, etc. It’s also used within Conductor to define workflow, task definitions and pass data and state between tasks and workflows. This makes a tool like JQ a natural fit for processing task-related data. Some common usages within Conductor include, working with HTTP tasks, JOIN tasks or standalone tasks that try to transform data from one task's output to another's input.

Configuration

Here is an example of a JSON_JQ_TRANSFORM task. The inputParameters attribute is expected to have a value object with the following.

1. A list of key-value pair objects denoted key1/value1, key2/value2 in the example below. Note the key1/value1 are arbitrary names used in this example.

2. A key with the name queryExpression, whose value is a JQ expression. The expression will operate on the value of the inputParameters attribute. In the example below, the inputParameters have two inner objects named by attributes key1 and key2, each of which has an object that is named value1 and value2. They have an associated array of strings as values, "a", "b" and "c", "d". The expression key3: (.key1.value1 + .key2.value2) concatenates the 2 string arrays into a single array against an attribute named key3.

{
  "name": "jq_example_task",
  "taskReferenceName": "my_jq_example_task",
  "type": "JSON_JQ_TRANSFORM",
  "inputParameters": {
    "key1": {
      "value1": [
        "a",
        "b"
      ]
    },
    "key2": {
      "value2": [
        "c",
        "d"
      ]
    },
    "queryExpression": "{ key3: (.key1.value1 + .key2.value2) }"
  }
}

The execution of this example task above will provide the following output. The resultList attribute stores the full list of the queryExpression result. The result attribute stores the first element of the resultList. An optional error attribute along with a string message will be returned if there is an error processing the query expression.

{
  "result": {
    "key3": [
      "a",
      "b",
      "c",
      "d"
    ]
  },
  "resultList": [
    {
      "key3": [
        "a",
        "b",
        "c",
        "d"
      ]
    }
  ]
}

Input Configuration

Attribute	Description
name	Task Name. A unique name that is descriptive of the task function
taskReferenceName	Task Reference Name. A unique reference to this task. There can be multiple references of a task within the same workflow definition
type	Task Type. In this case, JSON_JQ_TRANSFORM
inputParameters	The input parameters that will be supplied to this task. The parameters will be a JSON object of at least 2 attributes, one of which will be called queryExpression. The others are user-named attributes. These attributes will be accessible by the JQ query processor
inputParameters/user-defined-key(s)	User-defined key(s) along with values.
inputParameters/queryExpression	A JQ query expression

Output Configuration

Attribute	Description
result	The first results returned by the JQ expression
resultList	A List of results returned by the JQ expression
error	An optional error message indicating that the JQ query failed to process

Example JQ transforms

Cleaning up a JSON response

This excerpt is from the Simple ETL Codelab.

An HTTP Task makes an API call to GitHub to request a list of "stargazers" (users who have starred a repository). The API response (for just one user) looks like this:

The snippet of ${hundred_stargazers_ref.output}

  
"body":[
  {
  "starred_at":"2016-12-14T19:55:46Z",
  "user":{
    "login":"lzehrung",
    "id":924226,
    "node_id":"MDQ6VXNlcjkyNDIyNg==",
    "avatar_url":"https://avatars.githubusercontent.com/u/924226?v=4",
    "gravatar_id":"",
    "url":"https://api.github.com/users/lzehrung",
    "html_url":"https://github.com/lzehrung",
    "followers_url":"https://api.github.com/users/lzehrung/followers",
    "following_url":"https://api.github.com/users/lzehrung/following{/other_user}",
    "gists_url":"https://api.github.com/users/lzehrung/gists{/gist_id}",
    "starred_url":"https://api.github.com/users/lzehrung/starred{/owner}{/repo}",
    "subscriptions_url":"https://api.github.com/users/lzehrung/subscriptions",
    "organizations_url":"https://api.github.com/users/lzehrung/orgs",
    "repos_url":"https://api.github.com/users/lzehrung/repos",
    "events_url":"https://api.github.com/users/lzehrung/events{/privacy}",
    "received_events_url":"https://api.github.com/users/lzehrung/received_events",
    "type":"User",
    "site_admin":false
  }
}
]

We only need the starred_at and login parameters for users who starred the repository after a given date (provided as an input to the workflow ${workflow.input.cutoff_date}). We'll use the JQ Transform to simplify the output:

{
          "name": "jq_cleanup_stars",
          "taskReferenceName": "jq_cleanup_stars_ref",
          "inputParameters": {
            "starlist": "${hundred_stargazers_ref.output.response.body}",
            "queryExpression": "[.starlist[] | select (.starred_at > \"${workflow.input.cutoff_date}\") |{occurred_at:.starred_at, member: {github:  .user.login}}]"
          },
          "type": "JSON_JQ_TRANSFORM",
          "decisionCases": {},
          "defaultCase": [],
          "forkTasks": [],
          "startDelay": 0,
          "joinOn": [],
          "optional": false,
          "defaultExclusiveJoinTask": [],
          "asyncComplete": false,
          "loopOver": []
        }

The JSON is stored in starlist. The queryExpression reads in the JSON, selects only entries where the starred_at value meets the date criteria, and generates output JSON of the form:

{
  "occurred_at": "date from JSON",
  "member":{
    "github" : "github Login from JSON"
  }
}

The entire expression is wrapped in [] to indicate that the response should be an array.

Creating Dynamic Fork Inputs

Dynamic Forks require multiple JSON inputs that are created on demand. JQ Transforms are ideal for this and are used in the Order Fulfillment Codelab.