The first category of information that we need to gather about the indexes is the list of available indexes in our database, the list of columns participating in each index and the properties of these indexes.
The classical way of gathering such information about the indexes is expanding the Indexes node under the database tables, then right-clicking on each index, and choose the Properties option as shown below:.
Where you can browse the list of columns participating in the index key and different properties of the selected index. The problem with gathering the indexes information using the UI method is that you need to browse it one index at a time per each table. You can imagine the effort required to check all indexes in a specific database. The list of properties of a selected index can be shown below:. You can see that the columns that are added using the INCLUDE clause as non-key columns will not be listed using that stored procedure.
The third way, and the best for me, to gather metadata information about the index structure is querying the sys. The sys. It is recommended to join sys. A good example of using the sys. The result of the previous query, that includes the table name, the index name, the type of the index and finally the name and the type of key and non-key columns participating in these indexes, will be as shown below:.
The main target of creating an SQL Server index is speeding up the data retrieval performance and enhance the overall performance of the queries. But when the underlying table data is changed or deleted, this change should be replicated to the related table indexes. Over time, and as a result of many inserting, updating, deleting operations, the index will become fragmented, with a large number of unordered pages with free space in these pages, degrading the performance of the queries, due to increasing the number of pages to be scanned in order to retrieve the requested data.
The straight-forward way of getting the fragmentation percentage of an index is from the Fragmentation tab of the index Properties window. Checking the fragmentation percentage of all indexes in a specific database, using the UI method requires a big effort, as you need to check one index at a time. Active Oldest Votes. Improve this answer.
Perfect, that is exactly what I was looking for. For InnoDB, it is a few quick probes. Analyze tabe will not rebuild an index. If the index is faulty it needs a replacement I think. No idea how this can be the accepted answer. It is NOT rebuilding indexes and mysql is known to problems that degenerate index performance over time.
That's factually not correct, it should not be the answer. Speaking of mysql 8. Show 1 more comment. Rick James Rick James k 10 10 gold badges silver badges bronze badges.
I have to disagree with this answer. When going through an old table, of some k rows, I updated a couple of columns that was in an index and the index still contained the old values from before the update. I dropped the index and recreated it and then it worked fine. MySQL 5. Adergaard - How did you 'know' that the index still contained the old values? This may lead to a bug report.
Like Adergaard, I have to disagree, too. In my case a query that uses some fulltext index was very slow looked like full index search was used.
The actual percentage or number of rows the query optimizer samples might not match the percentage or number specified. For example, the query optimizer scans all rows on a data page. SAMPLE is useful for special cases in which the query plan, based on default sampling, is not optimal. In most situations, it is not necessary to specify SAMPLE because the query optimizer uses sampling and determines the statistically significant sample size by default, as required to create high-quality query plans.
Starting with SQL Server The query optimizer will use parallel sample statistics, whenever a table size exceeds a certain threshold. For most workloads, a full scan is not required, and default sampling is adequate. However, certain workloads that are sensitive to widely varying data distributions may require an increased sample size, or even a full scan.
For example, statistics for indexes use a full-table scan for their sample rate. When OFF , statistics sampling percentage will get reset to default sampling in subsequent updates that do not explicitly specify a sampling percentage. The default is OFF.
If the table is truncated, all statistics built on the truncated HoBT will revert to using the default sampling percentage. For example, a table with 1 million rows requires 20, rows updates. It might not be suitable for the query optimizer to generate an efficient execution plan.
SQL Server onwards, it uses dynamic statistics update threshold, and it adjusts automatically according to the number of rows in the table. For example, a table with one million rows we can use the formula to calculate the number of updates after which SQL Server will automatically update statistics. Note: the database compatibility level should be or above to use this dynamic threshold statistics calculations.
SQL Server uses synchronous mode to update the statistics. If query optimizer finds out of date statistics, it updates the SQL Server Statistics first and then prepares the execution plan according to the recently updated statistics. The next executed query takes the benefit of the updated statistics.
Since SQL Server does not wait for the updated statistics, we also call it Asynchronous mode statistics. In the previous section, we learned that SQL Server automatically updates the out-of-date statistics. We can also manually update the statistics for improving the query execution plan and performance on a requirement basis. Employee table. In the following screenshot, we can verify that all the stats get an update at the same time.
Execute the following code.
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