pl sql performance tuning techniques

be sorted, or it can be added to a column (like joins or additions). Any non-indexed item in the ORDER BY statement, or a computed expression, will slow down the query. Double-check the order BY statement to find non-indexed items or expressions that degrade performance. The solution to this problem is to rewrite the order BY statement to use the index, or you can establish another index for the column you are using, and you should absolutely avoid u

The failure effect is described above. Just want to explain that in the performance tunning aspect can only according to the situation to seek the reason and solves. This is an interesting process. Great principles are experiences that help us make fewer mistakes. Therefore, poor design inevitably leads to performance problems. Inexperienced programmers are bound to write bad code. But a good design can mak

union and UnionAll. UnionAll Good 18, pay attention to using distinct, do not use when not necessary, it will make the query slower than the union. Duplicate records are not a problem in the query. 19. Do not return rows or columns that are not required when querying 20. Use sp_configure ' query governor cost limit ' or setquery_governor_cost_limit to limit the resources consumed by the query. When an estimate query consumes more resources than the limit, the server automatically cancels the qu

index, the TPS from the previous 110 to 6000 such. Two. The SQL statement index does not work: When performing a performance test, the server is running under the circumstances: The CPU of the database is up to 90%-99.9%, and the CPU of the application is low; Sufficient memory (free memory >20m); Network normal; Disk input/output is normal; CPU-High Monitor diagram The logs a

Label:Original address: Http://social.technet.microsoft.com/wiki/contents/articles/4995.sql-server-columnstore-performance-tuning.aspxSQL Server's Columnstore index is a new version of SQL Server release that improves query performance for the Data Warehouse, and this article explains the

an execution plan, and stored in a database of SQL statements, is a collection of control flow language, the speed of course fast. 48, the return value of the function is not too large, this overhead is very large. A user-defined function that executes as a cursor consumes a large amount of resources if a large result is returned with a stored procedure. 49, as far as possible to avoid repeated access to the same or several tables, especially the lar

released, the data page will not be in the memory of the data cache, This causes the memory problem to be the bottleneck of the disk. PAGEIOLATCH_EX is write data, this is generally the disk write speed obviously keep up, and memory is not directly related. Here is the resource wait time for query pageiolatch_x: Select Wait_type, waiting_tasks_count, Wait_time_ms, Max_wait_time_ms, Signal_wait_time_ms from sys.dm_os_wait_stats wherelike' pageiolatch%' order by Wait_type Through the above

1. Check the database space usage to see which tables are consuming larger disk spaceExecute the following statement:SelectO.name, SUM (p.reserved_page_count) asReserved_page_count, SUM (p.used_page_count) asUsed_page_count, SUM ( CaseWhen (p.index_id2) Then (p.in_row_data_page_count+P.lob_used_page_count+p.row_overflow_used_page_count)Elsep.lob_used_page_count+P.row_overflow_used_page_count End) asDataPages, SUM ( CaseWhen (p.index_id2) then Row_countElse 0end) asrowcounts fromsys.dm_db_partiti

DISTINCTdatabase_id,object_idFrom Sys.dm_db_missing_index_details) as Ddmid on ddmid.database_id = ddios.database_idand ddmid.object_id = ddios.object_idWHERE Ddios.page_lock_wait_in_ms > 0 and object_name (ddios.[ OBJECT_ID]) like ' Pos_transmst 'ORDER by Ddios.page_lock_wait_count DESC;/*******************************************************************************************--page IO Latch Wait *******************************************************************************************/ SEL

not in with not existsIn a subquery, the NOT IN clause performs an internal sort and merge, in either case, not in is the least effective because it performs a full table traversal of the table in the subquery, and in order to avoid using not, it can be written as an outer join (Outer Joins) or not EXISTSLow efficiencySELECT *FROM dbo. OrdersWHERE id_p>0 and Id_p not in (SELECT IdFROM dbo. Persons)EfficientSELECT *From OrdersWHERE id_p >0 and not EXISTS (SELECT IdFrom Persons WHERE persons.id =

, one is not perfect function also dare to take Out (2000) The second functional architecture of the outstanding design makes the function has a strong continuity and Scalability (2005 2000 of the function to retain and improve). The optimization tool is simple to use 1: Use SQL Server Porfiler (Event Viewer) to record all the steps of the operation database in the business system and save it as a working file. 2: Open sql2005 's database Engine

] + ' (' + ISNULL (equality_columns, ') + case when equality_columns are not Null and Inequality_columns is isn't NULL then ', ' ELSE ' END + ISNULL (inequality_columns, ') + ') ' + Isnul L (' INCLUDE (' + included_columns + ') ', ') as Create_index_syntaxfrom sys.dm_db_missing_index_groups as Ginner JOIN Sys.dm_db_missing_index_group_stats as Gson gs.group_handle = G.index_group_handleinner JOIN sys.dm_db_missing_index_ Details as DON g.index_handle = D.index_handleorder by possibleimprovement

Tags: default int query full table scan condition index default policy wildcard1. Building an Index2. Avoid full table scanAvoid using is null, which is not NULL, so that writing discards the index of the field.If this is the case, try to set the default value when designing the tableCompare operators in! = Use less intLike wildcards try to put wildcards behind "qw%" and do not use fuzzy queries, which use the indexwhere L = R use less function operations, arithmetic operations, and other expres

By changing the vast majority of SQL queries into stored procedures, such operations can undoubtedly improve some of the performance. All operations using "SELECT * from XXX" are specific to the required fields. A query that uses joins to connect more than 2 large amounts of data, and queries that have little variation on the underlying datasheet, uses the view and indexes the view. The reason comes from th