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  1. Preface
  2. Informatica Intelligent Cloud Services REST API
  3. Platform REST API version 2 resources
  4. Platform REST API version 3 resources
  5. Data Integration REST API
  6. Mass Ingestion Files REST API
  7. Mass Ingestion Streaming REST API
  8. RunAJob utility
  9. ParamSetCli utility
  10. REST API codes
  11. REST API resource quick references

REST API Reference

REST API Reference

CodeTask

CodeTask

Use the
code task
API to submit Spark code written in Scala to an
advanced cluster
. You can use the CodeTask resource to create, start, and cancel a
code task
job. You can also access session logs, view job details and job status of a
code task
.
Consider the following guidelines when you use the
code task
resource:
  • Write your
    code task
    in Scala.
  • Submit your code in a JAR file using the
    code task
    APIs.
  • Use an AWS serverless or non-serverless environment.
  • Use the following base URL:
    <server URL>/disnext/api/v1/<API name>
  • Use the following request header format:
    <METHOD> <server URL>/<URI> HTTP/<HTTP version> Content-Type: application/json Accept: application/json IDS-SESSION-ID: <IDS_SESSION_ID>
  • Ensure that you have the permission to create, execute, and view the
    code task
    APIs.
  • Use the following persisted variables as needed for the
    code task
    APIs:
    • IDS_SESSION_ID
    • ORG_ID
    • CODE_TASK_ID
    • CODE_TASK_JOB_ID
If you use a tool such as Postman that automatically includes the HTTP version, do not enter the HTTP version in the URL. If the HTTP version appears twice in the URL, the request fails.
Complete the following tasks to submit Scala code in a JAR file and manage and monitor
code task
jobs:
  • Send login information to get the session ID using Login.
  • Create the
    code task
    and get the
    code task
    ID using Create.
  • Start the
    code task
    and get the job ID using Start.
  • View
    code task
    details using View.
  • Check on the job status for the
    code task
    using Status.
  • Cancel the
    code task
    job using Cancel.
  • Access the session logs for the
    code task
    using Session logs.
  • Access the Spark task results for the
    code task
    using Task results.

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