A few notable things about Redshift Workload Management, The principal mechanism that allows the management of resources is the definition of priorities queues for the execution of queries. Our initial recommendation is for 2 WLM queues: a queue for the segment query group with a concurrency of 10. leave the default queue with a concurrency of 5 Though, it doesn't say that the default queue can't have any User or Query groups. Usage limit for Redshift Spectrum – Redshift Spectrum usage limit. Usage limit for concurrency scaling – Concurrency scaling usage limit. It resulted in multiplying the concurrent connections to Redshift by two, and a high load on the queue dedicated to analysts, neither fitting the current WLM strategy, therefore breaking our SLAs. Design a better WLM strategy and monitor it thoroughly. Query throughput per WLM queue – The average number of queries completed per second for a WLM queue. The Redshift WLM has two fundamental modes, automatic and manual. Any queries that are not routed to other queues run in the default queue. If you want to setup your own dynamic WLM, then this blog will help you. Query duration per WLM queue – The average length of time to complete a query for a WLM queue. Intermediate Storage. The closest I could find was this. There is a solution already available on AWS’s RedShift utilities, but its not a sperate package. the rate for all the queues adds up to 100%. From AWS docs, In each queue, WLM creates a number of query slots equal to the queue’s concurrency level. Within the intermix.io dashboard, viewing Recommendations for an individual query will surface the exact touched tables and how to update them, as well as how much memory the query used and the amount of memory capacity in the WLM queue. The maximum concurrency that Redshift supports is 50 across all query groups, and resources like memory are distributed evenly across all those queries. For us, the sweet spot was under 75% of disk used. But yeah, I agree that the Redshift documentation lacks clarity on this. In Redshift, when scanning a lot of data or when running in a WLM queue with a small amount of memory, some queries might need to use the disk. SELECT * FROM wlm_queue_state_vw; This is the default queue setup and what you would see on a stock Redshift cluster: Here is what a custom queue would look like: The custom queue is a three-queue setup that allows for a timeout (max_time) on the fastest queue and moves anything slower to a second queue. By default, Amazon Redshift defines two queues One Superuser queue, which is reserved only for the superuser role and it cannot be configured. The default queue must be the last queue in the WLM configuration. We identified a few levers. How AWS handles this dynamic WLM? Improve our schema design: Be sure to keep enough space on disk so those queries can complete successfully. you have the option of changing the percentage of memory assigned to each queue by setting wlm memory percent parameter. It comes with many other things. Amazon Redshift WLM Queue Time and Execution Time Breakdown - Further Investigation Broken Down by Hour Posted by Tim Miller Once you have determined a day that has shown significant load on your WLM Queue, let’s break it down further to determine a time of the day. The automatic mode provides some tuning functionality, like setting priority levels for different queues, but Redshift tries to automate the processing characteristics for workloads as much as possible. That Redshift supports is 50 across all query groups agree that the WLM. It does n't say that the default queue queues adds up to 100.. But its not a sperate package maximum concurrency that Redshift supports is 50 across all query.! 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