In the WLM configuration, the “memory_percent_to_use” represents the actual amount of working memory, assigned to the service class. Note: In this example, the WLM configuration is in JSON format and uses a query monitoring rule (Queue1). "metric_name": "query_temp_blocks_to_disk", Use the STV_WLM_SERVICE_CLASS_CONFIG table to check the current WLM configuration of your Amazon Redshift cluster: [ Resolution Checking your WLM configuration and memory usage To check the concurrency level and WLM allocation to the queues, perform the following steps:ġ.FSPCheck the current WLM configuration of your Amazon Redshift cluster.Ģ.FSPCreate a test workload management configuration, specifying the query queue's distribution and concurrency level.ģ.FSP(Optional) If you are using manual WLM, then determine how the memory is distributed between the slot counts. Note: To define metrics-based performance boundaries, use a query monitoring rule (QMR) along with your workload management configuration. As a result, queries with more resource consumption can run in queues with more resource allocation.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |