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| Info |
|---|
NOTE: If the job is executed in an environment other than , the job is queued for execution in the environment. Jobs executed on a remote cluster may incur additional overhead to spin up execution nodes, which is typically within 10-15 seconds. During job execution, observes the job in progress and reports progress as needed back into the application. does not control the execution of the job. |
| Tip |
|---|
Tip: Jobs can be scheduled for periodic execution through Flow View page. For more information, see Add Schedule Dialog. |
| Tip |
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Tip: Columns that have been hidden in the Transformer page still appear in the generated output. Before you run a job, you should verify that all currently hidden columns are ok to include in the output. |
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Spark: Executes the job using the Spark running environment.
Dataflow: Executes job on
within the
. This environment is best suited for larger jobs.
...
| Tip |
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Tip: If this limit is exceeded, the job may fail with a job graph too large error. The workaround is to split the job into smaller jobs, such as splitting the recipe into multiple recipes. This is a known limitation of . |
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Automation
Run jobs via API
You can use the available REST APIs to execute jobs for known datasets. For more information, see API Reference.
| D s also |
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| inCQL | true |
|---|
| label | ((label = "job_ui") OR (label = "job")) |
|---|
|
