Data Lake Compute provides Spark-based batch and flow computing capabilities for you to perform complex data processing and ETL operations through data jobs.
Currently, data jobs support the following versions:
Before starting a data job, you need to create a data access policy to ensure data security as instructed in Configuring Data Access Policy.
Currently, only CKafka data source is supported for data job configuration, with more data sources to come in the future.
A data job is billed by the data engine usage. Currently, pay-as-you-go and monthly subscription billing modes are supported. For more information, see Data Engine Overview.
Note:As a data job differs from a SQL job in terms of the compute engine type, you need to purchase a separate data engine for Spark jobs; otherwise, you can’t run data jobs on a SparkSQL data engine.
On the Data job management page, you can create, start, modify, and delete a data job.
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