item Change type Description PD patrol- �→ region- �→ interval �→ Modified Controls the running frequency at which repli- caChecker checks the health state of a Region. The smaller this value is, the faster instance. server tidb-1 10.9.18.229:4000 check inter 2000 rise 2 fall 3 # Detects �→ port 4000 at a frequency of once every 2000 milliseconds. If it is �→ detected as successful twice, the server is considered server tidb-1 10.9.18.229:4000 check inter 2000 rise 2 fall 3 # Detects 68 �→ port 4000 at a frequency of once every 2000 milliseconds. If it is �→ detected as successful twice, the server is considered

indexes to greatly improve query perfor- mance • Improve the accuracy of optimizer cardinality estimation to help to select optimal execution plans • Announce the general availability (GA) for the Lock User document, #25882 • Improve the accuracy of optimizer cardinality estimation – Improve the accuracy of TiDB’s estimation of TopN/Limit. For example, for pagination queries on a large table that select the right index and reduce query response time. 36 – Improve the accuracy of out-of-range estimation. For example, even if the statis- tics for a day have not been updated, TiDB can accurately select

TiDB server. tidb_enforce_mpp �→ Newly added Controls whether to ignore the optimizer’s cost estimation and to forcibly use the MPP mode for query execution. The data type of this variable is BOOL and that might occur in the large data volume caused by hash conflicts in Version 1 and maintains the estimation accuracy in most scenarios. User document 2.2.2.2 Transaction • Support the Lock View feature seconds slow of NTP time Last offset : -0.000041040 seconds RMS offset : 0.000053422 seconds Frequency : 2.286 ppm slow Residual freq : -0.000 ppm Skew : 0.012 ppm Root delay : 0.012706812 seconds

the TiDB optimizer automatically determines whether to use TiFlash replicas based on the cost estimation. To check whether or not a TiFlash replica is selected, you can use the desc or explain analyze alleviates the pressure on the database write. In practice, you can also adjust the step to control the frequency of database updates. Finally, note that the IDs generated by the above two solutions are not random seconds slow of NTP time Last offset : -0.000041040 seconds RMS offset : 0.000053422 seconds Frequency : 2.286 ppm slow Residual freq : -0.000 ppm Skew : 0.012 ppm Root delay : 0.012706812 seconds

issue of batch-client in client-go #47691 @crazycs520 • Fix the issue of incorrect memory usage estimation in INDEX_LOOKUP_HASH_JOIN #47788 @SeaRise • Fix the issue of uneven workload caused by the rejoining the TiDB optimizer automatically determines whether to use TiFlash replicas based on the cost estimation. To check whether or not a TiFlash replica is selected, you can use the desc or explain analyze alleviates the pressure on the database write. In practice, you can also adjust the step to control the frequency of database updates. Finally, note that the IDs generated by the above two solutions are not random

issue that the optimizer does not use the best multi-column statistics information for row count estimation when the query contains filter conditions like (... AND ...)OR (... AND ...)... #54323 @time-and-fate the TiDB optimizer automatically determines whether to use TiFlash replicas based on the cost estimation. To check whether or not a TiFlash replica is selected, you can use the desc or explain analyze results. Unlike traditional full-text search, which relies on exact keyword matching and word frequency, vector search converts various data types (such as text, images, or audio) into high- dimensional

automatic ANALYZE tasks that are running outside the set time window #55283 @hawkingrei • Adjust estimation results from 0 to 1 for equality conditions that do not hit TopN when statistics are entirely composed the TiDB optimizer automatically determines whether to use TiFlash replicas based on the cost estimation. To check whether or not a TiFlash replica is selected, you can use the desc or explain analyze alleviates the pressure on the database write. In practice, you can also adjust the step to control the frequency of database updates. Finally, note that the IDs generated by the above two solutions are not random

the TiDB optimizer automatically determines whether to use TiFlash replicas based on the cost estimation. To check whether or not a TiFlash replica is selected, you can use the desc or explain analyze alleviates the pressure on the database write. In practice, you can also adjust the step to control the frequency of database updates. Finally, note that the IDs generated by the above two solutions are not random seconds slow of NTP time Last offset : -0.000041040 seconds RMS offset : 0.000053422 seconds Frequency : 2.286 ppm slow 630 Residual freq : -0.000 ppm Skew : 0.012 ppm Root delay : 0.012706812 seconds

instance. server tidb-1 10.9.18.229:4000 check inter 2000 rise 2 fall 3 # Detects �→ port 4000 at a frequency of once every 2000 milliseconds. If it is �→ detected as successful twice, the server is considered instance. server tidb-1 10.9.18.229:4000 check inter 2000 rise 2 fall 3 # Detects �→ port 4000 at a frequency of once every 2000 milliseconds. If it is �→ detected as successful twice, the server is considered the TiDB optimizer automatically determines whether to use TiFlash replicas based on the cost estimation. To check whether or not a TiFlash replica is selected, you can use the desc or explain analyze

issue that the optimizer does not use the best multi-column statistics information for row count estimation when the query contains filter conditions like (... AND ...)OR (... AND ...)... #54323 @time-and-fate the TiDB optimizer automatically determines whether to use TiFlash replicas based on the cost estimation. To check whether or not a TiFlash replica is selected, you can use the desc or explain analyze results. Unlike traditional full-text search, which relies on exact keyword matching and word frequency, vector search converts various data types (such as text, images, or audio) into high- dimensional