![]() Workload management is a piece of configuration with big potential and there is another proof of it, the one that is enabled by default – Short Query Acceleration (SQA). For every query monitoring rule you can specify one of the following actions: log, abort or change query priority. Using predicates you can build your custom rules using basic math operations like ‘ ’ and ‘ =’ on them or take advantage of one of the predefined templates. The metrics listed above are called predicates, you can find the table with a detailed description here. With QMR you can match queries by user group or query group (label) to control it with the rules that you’ll specify, these can be related to: These restrictions are called Query Monitoring Rules (QMR) and this part of Redshift configuration, in my opinion, deserves some attention. With custom WLM JSON configuration you can modify the processing rules of the default queue or add more queues with some restrictions applied. Default configuration contains one, default queue that can run up to 5 queries concurrently – no other restrictions applied. ![]() The most powerful parameter though is WLM JSON configuration that is used to define query queues and associated processing rules. You can find the full list of the parameters here. To introduce some changes you need to create a new, custom parameter group and assign it to the cluster. Every cluster has a default configuration that cannot be modified. WLM JSON configuration is part of the Redshift cluster parameter group. User groups are important in the context of Query Monitoring Rules (QMR) that are part of Redshift’s WorkLoad Management (WLM). They can be used to differentiate users’ privileges related to so-called CRUD operations. Database access is based on users and user groups. When managing the database backend one of the things to take care of is access management. However, do you know all the possibilities that it brings? In this article, I would like to describe how to improve the way your database is queried in order to take care of its health, performance and user experience. Definitely, it may even be your first choice for Big Data management in the cloud. Amazon Redshift is a well-known data warehouse solution with PostgreSQL background.
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