![]() The last queue in your setup is considered to be your default queue. Adding more queues will let you split the load more evenly, and you can also control the number of queries which can be allocated to each queue for further control. So, if you have one group which you know will need to handle a mixture of large and small queries (or a heavier load in general), you can create more queues to suit that group and spread the load more evenly without affecting your other groups.īy default you will have one queue set up with the ability to run up to 5 concurrent queries. Redshift workload management (WLM) is configured within parameter groups, meaning that you can have different WLM settings for different associated parameter groups. In other words, it’s a great way to make sure that large queries that take a long time to complete don’t clog up the system and prevent smaller queries from being resolved. This allows you to dictate the number of queries which can be running in parallel at any given time which, in turn, means that you can make full use of the resources at your disposal. Workload management is a feature of Amazon Redshift which lets you create and control query queues within your cluster. Source, image used under license CC BY-SA 4.0 So, to get you started with maximizing your query throughput, in this post we’re going to cover: Without workload management it’s highly likely that your queries will be slotted into any old random configuration, with complex queries hogging memory and throttling the speed of others. ![]() In other words, it’s a vital tool in making sure that your Redshift clusters are working at full capacity. Workload management lets you make the most of your clusters by setting up queues you can use to run parallel queries with set memory allocations per query slot. That’s where Redshift’s workload management feature comes in. While some competitors may be in the same field, for companies who likely already have AWS solutions in their stack there’s little point in branching out when Redshift is right there, ready to help you handle your data. Amazon Redshift is a true powerhouse in allowing users to handle and analyze big data data sets. ![]()
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