E-MapReduce:Manage notebook computes

Create a notebook compute

After you create a notebook compute, you can select it when you develop a notebook.

1. Go to the Notebook Compute tab.

   1. Log on to the EMR console.

   2. In the left-side navigation pane, choose EMR Serverless > Spark.

   3. On the Spark page, click the name of the workspace that you want to manage.

   4. In the left-side navigation pane of the EMR Serverless Spark page, click Compute.

   5. Click the Notebook Compute tab.

2. On the Notebook Compute tab, click Create Notebook Compute.

3. On the Create Notebook Compute page, configure the parameters described in the following table and click Create.

   Important

   We recommend that you ensure the maximum number of concurrent compute units (CUs) for the selected resource queue to at least the number of CUs required by the notebook compute. The available values for the maximum concurrency are displayed in the console.

   Parameter	Description
   Name	The notebook compute name. The name must be 1 to 64 characters in length and can contain letters, digits, hyphens (-), underscores (_), and spaces.
   Resource Queue	The resource queue in which the notebook compute is deployed. Select a resource queue from the drop-down list. Only resource queues that are available in the development environment or resource queues that are available in both the development and production environments are displayed in the drop-down list. For more information about resource queues, see Manage resource queues.
   Engine Version	The version of the engine that is used by the notebook compute. For more information about engine versions, see Engine versions.
   Automatic Stop	By default, this feature is enabled. By default, the system automatically stops the notebook compute if the notebook compute has not been used for the last 120 minutes.
   spark.driver.cores	The number of CPU cores that are used by the driver of the Spark application. Default value: 1 CPU.
   spark.driver.memory	The size of memory that is available to the driver of the Spark application. Default value: 3.5 GB.
   spark.executor.cores	The number of CPU cores that can be used by each executor. Default value: 1 CPU.
   spark.executor.memory	The size of memory that is available to each executor. Default value: 3.5 GB.
   spark.executor.instances	The number of executors that are allocated to the Spark application. Default value: 2.
   Dynamic Resource Allocation	By default, this feature is disabled. After you enable this feature, you must configure the following parameters: Minimum Number of Executors: Default value: 2. Maximum Number of Executors: If you do not configure spark.executor.instances, the default value 10 is used.
   More Memory Configurations (Click to Show)	spark.driver.memoryOverhead: the size of non-heap memory that is available to each driver. Default value: 1 GB. spark.executor.memoryOverhead: the size of non-heap memory that is available to each executor. Default value: 1 GB. spark.memory.offHeap.size: the size of off-heap memory that is available to the Spark application. Default value: 1 GB. This parameter is valid only if spark.memory.offHeap.enabled is set to true. By default, spark.memory.offHeap.enabled is set to true and spark.memory.offHeap.size is set to 1 GB if the Fusion engine is used.
   Spark Configuration	The Spark configurations. Separate the configurations with spaces. For example, set the value to spark.sql.catalog.paimon.metastore dlf.

4. Click Start in the Actions column of the notebook compute that you created.

References

• For information about operations related to resource queues, see Manage resource queues.

• For information about the permissions that each role has on notebook computes, see Manage users and roles.

• For more information about how to develop a notebook, see Get started with notebook development.