![]() ![]() For example, you can use a query monitoring rule to hop or cancel a long-running query.Determining how much time your queries are spending either in the Workload Management (WLM) Queue or executing on your Amazon Redshift source can go a long way to improving your cluster’s performance. (Optional) Create and define a query monitoring rule to manage queries that reach metric boundaries.WLM dynamic memory configuration helps you prioritize your workload according to memory usage. Use WLM dynamic memory allocation to configure the amount of memory allocated to each queue.Queries that aren't assigned run in the default queue. Note: Queries are assigned according to user or query group. Create and define a query assignment rule.Then, choose Switch WLM mode to switch to Manual WLM. Choose Edit workload queues to edit the WLM configuration. (Optional) If your WLM parameter group is set to Automatic WLM mode, modify the WLM configuration for your parameter group.(Optional) If your WLM parameter group is set to Manual WLM mode, then no updates are required.To prioritize your workload in Amazon Redshift using manual WLM, perform the following steps: If you're managing multiple WLM queues, you can configure workload management (WLM) queues to improve query processing. A queue's memory is divided equally amongst the queue's query slots. When you enable manual WLM, each queue is allocated a portion of the cluster's available memory. For example, you can set your query monitoring rule to change a query's priority status if a running query exceeds 40 seconds. (Optional) Create a WLM query monitoring rule to define performance boundaries (such as time limits or concurrency levels) for queries and queues.If a workload is marked as "Critical" priority, only one of its queries can be run at each time. Note: Superusers can apply a "Critical" priority status (the highest priority level) to a query. By default, each queue is assigned a "Normal" priority status. Configure the priority status for your queue.You can create separate queues (with a maximum of eight queues) for each workload, associating queues with user groups or query groups. Choose Add queue to add additional workload queues.Then, choose Switch WLM mode to switch to Automatic WLM. (Optional) If your WLM parameter group is set to Manual WLM mode, modify the WLM configuration for your parameter group.(Optional) If your WLM parameter group is set to Automatic WLM mode, then no updates are required.Choose the Workload management tab to view the current WLM configuration.Choose the parameter group that you want to modify.From the navigation menu, choose CONFIG.To prioritize your workload in Amazon Redshift using automatic WLM, perform the following steps: Note: It's a best practice to test automatic WLM on existing queries or workloads before moving the configuration to production. Concurrency is adjusted according to your workload. When you enable automatic WLM, Amazon Redshift automatically determines how resources are allocated to each query. To prioritize your queries, choose the WLM configuration that best fits your use case. Use manual WLM if you want to manage your own workload or manually assign resources to queries. For manual WLM, the default concurrency value is five queries and memory allocation is divided equally. For both automatic and manual WLM, you can create separate query queues. With manual WLM, you must specify values for WLM query concurrency slots and memory allocation properties. Manual WLM: Manual WLM is used to manage multiple WLM queues in Amazon Redshift.Unlike manual WLM, automatic WLM allows you to set a query priority value to indicate the relative priority of workloads. Amazon Redshift determines the amount of resources that queries need, and adjusts the amount accordingly. Automatic WLM: When you enable automatic WLM, your query concurrency and memory allocation are managed by Amazon Redshift.Amazon Redshift supports the following WLM configurations: To prioritize your queries, use Amazon Redshift workload management (WLM). ![]() Queries can be prioritized according to user group, query group, and query assignment rules. In Amazon Redshift, you can create extract transform load (ETL) queries, and then separate them into different queues according to priority.
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