9/4/2023 0 Comments Sql cdc![]() Test increasing the threshold parameter until you find a sweet spot for your workload. If possible, run cleanup when there is no other workload active or during the off-peak time. This could degrade the application response time, and it could increase the latency of the change data capture scan job. Notice that especially with big thresholds, a lock escalation on change tables can happen. The configurable threshold value derives the maximum number of delete entries that can be deleted using a single statement on clean-up. This stored procedure starts by extracting the configured retention and threshold values for the cleanup job from _jobs. The cleanup job is initiated by running the parameter less stored procedure sp_MScdc_cleanup_job. And also try to avoid using change data capture to capture changes to tables that have frequent large update transactions. The bottom line is that try to avoid scenarios where a row needs to be updated immediately after insert. This will result in three rows instead of one row that needed to be written to the change table for each insert to the original table. This can happen in the application or by utilizing an INSERT trigger that looks for missing fields and then updates them if necessary. ![]() One UPDATE, however, inserts two rows in the change table.Ī common scenario in applications is that a row is inserted to a table and then immediately updated to fill missing fields. many.įor change data capture, one INSERT only creates one row in the change table. ![]() UPDATE, and whether the DML operations impact one row per transaction vs. The main factors to consider are INSERT/DELETE vs. Workload Behavior Recommendation – 1įor planning a change data capture solution, workloads characteristics are very important. If you do require querying for net changes but change data capture latency grows too big, it can be worthwhile to turn support for net changes off and do the net change detection later in a staging database. If you do not require support for net changes, set 0. Especially if change data capture is just able to keep up with a workload, the additional load that is incurred by maintaining the additional index to support net changes queries can be enough to prevent change data capture from keeping up with the workload. Because this index needs to be maintained, we found that enabling net changes can have negative impact on change data capture performance. When set to 1, an additional non-clustered index will be created on the change table and the net changes query function will be created. The in sys.sp_cdc_enable_table can have significant influence on change data capture performance. We have found that the decreased number of columns captured made a huge difference in overall change data capture performance. By specifying just the columns you need you can improve performance. ![]() When enabling CDC on a table, consider what data elements you are actually interested in capturing the changes for over time. Recommendation – 2Īlways limit the list of columns captured by change data capture to only the columns you really need to track by specifying the in sys.sp_cdc_enable_table. On a system where change data capture can fully keep up with the workload, latency should not be significantly higher than the polling interval, and it should not increase over time. If your latency decreases but is still too high, you can further increase maxtrans, but monitor the performance of your workload, latency and performance of queries to the change tables closely. If change data capture with default parameters cannot keep up with the workload and latency becomes too high, you can increase maxscans and/or maxtrans by a factor of 10, or you can reduce pollinginterval to 1. Change Data Capture Parameters Recommendation – 1 Tuning the scan job parameters, sys.sp_cdc_enable_table parameters can significantly improve change data capture performance under load. Understanding workload characteristics, system I/O usage, and allowable latency is key to tuning change data capture performance without negatively impacting the base workload. There are many ways to tune the performance of change data capture. In this article we offer useful examples while pointing out some of the pitfalls that we have come across while working with the CDC. Change data capture (CDC) provides an easy and high-performing way to capture changes in a set of tables. ![]()
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