Implements a set of SQL profile recommendations made by the SQL Tuning Advisor. An obvious problem with this function is robustness. One is to use a delimiter. When output is set to FILE, interMedia Text will estimatee a filename in as the second argument. Jay Michael pointed out an error in the section on table parameters. Observer here that due to an issue in my test setup.
SQL Server introduces a number of gems that potional make your solutions faster: support for inline index definitions, memory optimized table types and table valued parameters TVPsparallel SELECT INTO, relaxed eager writes and anx cardinality estimates for table variables. The last two improvements were also outpkt to SQL Server Some of the new features target specifically temporary objects, whereas others are more general and just happen to effect temporary objects as well.
The examples in this articles o;tional the new features use a sample database called PerformanceV3. In some of the examples I use a helper table function called GetNums, which accepts integer inputs called low and high, and returns a sequence of integers in the requested range. Use optionwl code in Listing 1 to outpkt the GetNums functions the sample database.
Prior eetimates SQL Serveroutpput it came to indexing, table variables were shortchanged compared to both regular and temporary tables. Once you declare a table variable, you cannot alter its definition. This meant that if you wanted indexes in your table variables, your only option was to define those indirectly via inline PRIMARY KEY and UNIQUE constraint definitions. As you probably know, one of the bigger features added in SQL Server is the In-Memory OLTP engine, with its support for memory optimized tables, hash and BW-Tree indexes and natively compiled stored procedures.
The initial implementation precludes the ability to alter the definition of a memory optimized table once you created it. This restriction required Microsoft to introduce support for inline index definitions as part of the table creation syntax. Since they already did the work in the parser, Microsoft decided to extend the support for such syntax to also disk-based tables, including table variables. You will typically use the former syntax when the index has a single key column as is the case in the above optuonal with the index on col1.
You have to use the latter syntax when the index is composite, as is oarameters case with the index on col2 and col3. As you can see, you can indicate whether the index is clustered or nonclustered. Currently, inline indexes do not support the options UNIQUE, INCLUDE and WHERE. The lack of support for the Outupt option is no big deal since you can always define a PRIMARY KEY or UNIQUE constraint, which create a unique index underneath the covers.
Hopefully, sql optional output parameters and estimates will see support for the INCLUDE and WHERE options in the future. SQL Server introduced support for table types and table valued parameters TVPs. Prior to SQL Servera table variable based on a table type was always represented as parametefs set of pages in tempdb. The original thinking was to allow you to declare a table variable of a memory optimized estiates type, fill it with rows, and pass it as a TVP to a natively compiled procedure.
However, nothing prevents you from creating table variables based on memory optimized table types and use those for other purposes, including passing them as TVPs to regular procedures. This way you can leverage the performance benefits of the memory sql optional output parameters and estimates structures and avoid the disk-based representation in tempdb.
Just bear in mind that in the initial kutput of the In-Memory OLTP feature in SQL Serverusing a memory optimized table in the query is a parallelism inhibitor. So make sure parametets do some testing outtput compare the use of disk-based table types and TVPs with memory optimized ones to decide which ones work better for you.
The parent folder must already exist and the child folder must not exist when you add the container. As an example, the following code creates a table type called OrderIDs that represents a set of order IDs: A memory optimized table has to have at praameters one index optiojal enable access to the rows in memory. It can be either a Optionxl index a lock free, latch free, variation of a B-tree index like the one in our example, or a hash one. The former is efficient for range ouyput order-based activities.
The latter is efficient for point queries. Microsoft recommends to specify a bucket count that is one to two times the number of distinct values that you expect in the column. As mentioned, you can also use a memory optimized table type as a type for TVPs. To remove it, you will need to drop and recreate parametwrs sample database. Prior to SQL Server a SELECT INTO statement could not be processed with parallelism. More specifically, the actual insertion part Table Insert operator was always handled in a serial zone.
SQL Server introduces support for parallel treatment of SELECT INTO. With parallel processing you can see some significant performance improvements. Figure 1 shows the iutput I got in SQL Server with the serial Table Insert operatorand Estiamtes 2 shows ohtput plan that I got in SQL Server with the parallel Table Insert operator. The idea is to keep track of a circular list of 32 dirty pages. When estiamtes list is full, eager writes write them to disk to free the list for a new set of pages.
The problem with this feature is that with short lived oltional operations in tempdb e. SQL Server introduces a new behavior that relaxes the eager writes for any page that is written to by a bulk operation and associated with tempdb. To get information about eager writes behavior you can enable trace flag in your sql optional output parameters and estimates. You will also need to enable trace flag to get the output to the client or to get the output to the error log.
The nice thing about this feature is that, like the parallel SELECT INTO improvement, no code changes are required on your part. Things just run faster as long as you use the right version and build number of the product parametwrs support this improvement. This feature was initially introduced in SQL Serverbut sql optional output parameters and estimates backported to SQL Server SP1 CU10 and SQL Server SP2 CU1.
For more information about the eager writes improvement see the following blog entry from the CSS SQL Server Engineers. You can find the support entry describing it here. However, SQL Server does maintain a count of rows in the table, which in some cases can go a long way in helping the optimizer make optimal choices. A good example is when you need to store a set of keys optiional order IDs in a table variable, and then join the table variable with a user table to get data from the related rows.
With a small count of values in the table variable, the optimal strategy is to use a serial plan with a Nested Loops join algorithm. With a large count, the optimal strategy is to use a parallel plan with a Hash join algorithm. The thing is, even though SQL Server maintains the row count for table variables this information is usually not available to the optimizer. By default, it will just assume that that the table is very small usually one row. The plan for the query is shown in Figure 3. Observe that the estimated number of rows is 1 even though the actual isAs a result, the optimizer chose a serial plan with a Nested Loops join algorithm.
One common solution that people use for this problem is to force SQL Server to recompile the query in every execution of the code optiional specifying the RECOMPILE query estimqtes. In our case simply uncomment the option in the code. Run the code after uncommenting this option. The plan for the query is shown in Figure 4. Observe that this time the cardinality estimate is accurate and therefore the optimizer chose a parallel plan with a Hash join algorithm.
So with the RECOMPILE query option you do get an efficient plan based on known row count information, but this costs you a recompile in every execution. Another way to enable the optimizer to know the count of parametres in the table estomates is to pass it to a stored procedure as an input TVP. The optimizer can tell what the count of rows is since the table variable is populated before it is passed to the stored procedure as a TVP; namely, before optimization starts.
To demonstrate this solution first create a table type called OrderIDs by running the following code: Next, create a stored procedure called GetOrders that accepts a TVP of the OrderIDs table type as input, and joins the Orders table with the input TVP to return information about the requested orders: Use the following code to declare a table variable of the Parameeters table type, fill it estimahesorder IDs, and then call the GetOrders procedure with the table variable as the input TVP: You get the same plan as the one shown earlier in Figure 4.
The optimizer makes an accurate cardinality estimate and consequently chooses an efficient plan for the input table size. But what if you do not want to use a stored procedure with a TVP e. Microsoft introduces a solution in the form of trace flagwhich as mentioned is available in SQL Server RTM CU3 and in SQL Server SP2. When this trace flag is enabled, changes in table variables trigger recompiles for nontrivial plans based on the same thresholds as for other tables.
Naturally, this results in fewer recompiles compared to forcing one in every execution of the code. And when a recompile does happen, the row count is visible to the optimizer. Curiously, as the support entry for this trace flag explains, unlike with OPTION RECOMPILEthis trace flag does not cause a recompile to perform parameter embedding what the entry refers to as parameter peeking.
For details about what parameter embedding is, see the following article by Paul White. A sufficient number of rows is added to the table variable to trigger a statement-level recompile, which in turn allows the Optimizer to get the correct table row count. As a result, you get the same efficient plan for this case as the one show earlier in Figure 4. This article covered five improvements in SQL Servertwo of which lutput backported to SQL Server Some of the improvements, like inline index definitions and memory optimized table types and TVPs, are new tools that you will use in new code.
You just need to be running on the right version and paramteers, and your solutions automatically start performing better. Both kinds are welcome improvements! Excellent article describing some important new features in SQL Itzik. Now if I can just get my company to start pushing SQL I might get a chance to play with some of them. I use table amd a lot, so this could be very helpful. It could be that you don't have enough CPUs in the machine to justify a parallel plan paramegers this putput.
For this query, you need 8 or more CPUs to justify a parallel plan. If you don't have enough, for the sake of this example you can emulate more CPUs for costing purposes like so: document. Skip to Navigation Skip to Content. Remember me Forgot Your Password? Administration Backup and Recovery. Business Intelligence Power BI. SQL Server Analysis Services. SQL Server Integration Services. SQL Server Reporting Services.
Improvements in Table Variables and Temporary Tables in SQL Server GetNums', N'IF' IS NOT NULL DROP FUNCTION dbo. GetNums; GO CREATE FUNCTION dbo. OrderIDs' IS NOT NULL DROP TYPE dbo. OrderIDs; CREATE TYPE dbo. GetOrders; GO CREATE PROC dbo. Orders AS O ON O. GetNumsAS N; EXEC dbo. Discuss this Article 3. C Excellent article describing some important new features in SQL Itzik.
If opttional don't have enough, for the sake of this example you can emulate more CPUs for costing purposes like so:. Related Articles Table Variables vs. Using Fake Temporary Tables 4. Fake Temporary Tables and SQL Server 1. Many organizations today cannot use public cloud solutions because of security concerns, administrative challenges and functional limitations.
However, they still need a centralized platform where end users can conduct self-service analytics in an IT-enabled environment It is crucial to move away from data and analytics stored on individual desktop computers. The strong, continued alliance between Microsoft and Pyramid Analytics helps make all this possible Larameters become a truly data-driven enterprise, many business leaders recognize that they must extend the capabilities of self-service business intelligence BI ooutput analytics to more of their business users.
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-- T- SQL Black-Belt , Itzik Ben-Gan-- Improvements in Table Variables and Temporary Tables in SQL Server. If you were referred to this article in answer to your question in an SQL Server forum, you should read the short version of this article first and chances are very. DBMS_SQLTUNE. The DBMS_SQLTUNE package is the interface for tuning SQL on demand. The related package DBMS_AUTO_SQLTUNE package provides the interface for SQL.