If you do not monitor the size of the HLL, this will cause performance regression over time, as well as higher resource consumption, slower and inconsistent SELECT statement performance, and an increase in storage.
Even if the purge threads are unable to keep up with changes on the DB, HLL can remain high. Note: Long running transactions are not the only cause of HLL spikes. If your workload demands a lot of long running or open transactions, then you can expect to see a high HLL on the database. The InnoDB history list length represents the number of unflushed changes. But when a transaction is not committed for a long time, due to growth of the undo segments, then history list length (HLL) increases. This means that once you have committed a transaction, then InnoDB purges the older copies. MVCC maintains multiple copies of the same record to preserve read-consistency. InnoDB uses a concept called Multi-version-concurrency control (MVCC). If you are using the MySQL 5.6 compatible version, use the MySQL Performance Schema to monitor performance of queries on an ongoing basis. Enable slow query logging for your DB cluster to record these queries and take action later. If BufferCacheHitRatio drops and your SELECT statement is slow, then you're processing the query from underlying volumes.Īnother important resource to identify slow SELECT statements is the slow query log. VolumeReadsIOPS: This metric is the number of billed volume level read operations and should be as low as possible.īufferCacheHitRatio: This metric is the percentage of requests that the buffer cache serves, and should be as high as possible. This project is for tools/scripts that can be used to extract information from Optimizer Trace generated by the MySQL Query Optimizer. Use the metrics below to check if you are serving a particular query from disk or from memory: This means that next time the database needs the same block of data, it can fetch from the memory rather than going to the disk. To minimize the disk I/O, the database engine tries to cache the block read from the disk. SELECT queries can also run slowly due to disk seeks. You can also monitor your load bearing queries and SQLs by waits, and identify the users that cause the maximum waits. Enable Performance insights for your DB instance and then check if your load is exceeding the Max vCPU.
Cost estimation for full table scan and index scan on a single table.You should always monitor your CPU utilization and free memory on your Amazon Aurora cluster. "rows_estimation": [-Logic optimization, estimate the number of tuples in each table. "equals": "`b`.`sid`", -connected equivalent field "ref_optimizer_key_uses": [-Logic optimization, find alternative indexes "row_may_be_null": false, -whether there is a null value, and if there is no false Avoid including events that occur frequently. For more information, see sptracecreate (Transact-SQL). Using a graphical user interface hinders performance. "table_dependencies": [-Logic optimization, to find out the interdependencies between tables. To minimize the performance cost incurred by a trace, try the following: Consider using the command prompt to run traces. "join_preparation":, -Logic optimization, conditional simplification, end