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Data Lake Compute
Creating Data Job
Last updated: 2024-07-17 17:45:32
Creating Data Job
Last updated: 2024-07-17 17:45:32

Preparations

Before creating a data job, you need to configure the CAM role arn to secure the data access from the data job. For detailed directions, see Configuring Data Access Policy.

Directions

1. Log in to the Data Lake Compute console and select Data job on the left sidebar.
2. Click Create job.


Configure parameters as follows:
Parameter
Description
Job name
It can contain up to 40 letters, digits, and underscores.
Job type
In batch: Batch data jobs based on Spark JAR
In flow: Flow data jobs based on Spark Streaming
Data source connection
Data source for In batch data jobs. Currently, it can only be CKafka, which needs to be configured in advanced in Job configuration.
Data engine
It can be a Spark job data engine for which you have the permission.
If you select Data source, you can only select a data engine connected to the data source.
Program package
The JAR format is supported.
You can select a local file of up to 5 MB in size or a file in COS. If the local file exceeds 5 MB, upload it to COS for use. You can directly enter a COS path.
Dependency JAR resource
The JAR format is supported. You can select multiple resources.
You can select a local file of up to 5 MB in size or a file in COS. If the local file exceeds 5 MB, upload it to COS for use. You can directly enter multiple COS paths and separate them by semicolon.
Dependency file resource
You can select a local file of up to 5 MB in size or a file in COS. If the local file exceeds 5 MB, upload it to COS for use. You can directly enter multiple COS paths and separate them by semicolon.
CAM role arn
The data access policy configured in Job configuration, which specifies the scope of data accessible to a data job. For more information, see Configuring Data Access Policy.
Main class
JAR package parameter in the main class. Separate multiple parameters by space.
Job parameter
-config information of the job, which starts with spark. in the format of k=v. Separate multiple parameters by line break.
Example: spark.network.timeout=120s
Resource configuration
The engine resources that can be configured with the data job, the number of which cannot exceed the specifications of the selected data engine. Resource description: 1 CU ≈ 1-core 4 GB MEM
Billable CUs = executor resource * executor quantity + driver resource
Pay-as-you-go data engines are billed by the billable CUs.
3. After configuring the parameters, click Save.
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