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Table 2-6. Information about Query Plans Extracted from Cache
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The query optimizer must take care of several specific issues when optimizing INSERT, UPDATE, and DELETEor, in other words, data modifying statements. Here I will describe the techniques employed by the SQL Server to process these statements. The IUD (shorthand I will use for "INSERT, UPDATE, and DELETE") plans have two stages. The first stage is read only , and it determines which rows need to be inserted/updated/deleted by generating a data stream describing the changes to be made. For INSERTs, the data stream contains column
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values; for DELETEs, it has the table keys; and for UPDATEs, it has both the table keys and the values of changed columns. The second stage applies changes in the data stream to the table; additionally, it takes actions necessary to preserve data integrity by performing constraint validation, it maintains nonclustered indexes and indexed views, and it fires triggers if they exist. Usually the UPDATE and DELETE query plans contain two references to the target table: the first reference is used to identify the affected rows and the second to perform the change. The INSERT plans contain only one reference to the target table unless the same target table also participates in generating the inserted rows. In some simple cases, SQL Server merges the read and write stages of the IUD plans together. This is the case, for example, when inserting values directly into a table (a process known as a scalar insert ) or updating/deleting rows identified by a value of a primary key on the target table. The Assert operator is automatically included in the query plans in the second phase if SQL Server needs to perform constraint validation. SQL Server validates the CHECK constraints for INSERTs and UPDATEs by evaluating a usually inexpensive scalar expression on each affected row and column. Foreign key constraints are enforced on INSERTs and UPDATEs to the table containing the foreign key constraint, and they're enforced on UPDATEs and DELETEs to the table containing the referenced key. The related table that is not the target of the IUD operation is scanned to verify the constraint; therefore, data access is involved. Declaring a primary key automatically creates a unique index on the key columns, but this is not the case for a foreign key. UPDATEs and DELETEs of referenced keys must access the foreign key table for each updated or deleted primary key value, either to validate nonexistence of the removed key or to propagate the change if it is a cascading referential integrity constraint. Therefore, you should ensure there is an index on the foreign key if you plan to perform UPDATEs affecting the key values or DELETEs from the primary table. In addition to performing the IUD operation on the clustered index or heap, processing of the INSERT and DELETE queries also maintains all nonclustered indexes, and the UPDATE queries maintain indexes containing the modified columns. Because nonclustered indexes include the clustered index and partitioning keys to allow efficient access to the table row, updating columns that participate in the clustered index or in the partitioning key is expensive because it requires maintenance of all indexes. Updating the partitioning key might also cause rows to move between partitions. Therefore, when you have a choice, choose clustering and partitioning keys that you don't plan to update.
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SQL Server 2005 restricts the partitioning keys to a single column; therefore, "partitioning key" and "partitioning column" are synonyms.
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In general, the performance of IUD statements is closely tied to the number of maintained indexes that include the target columns, because those must all be modified. Performing single-row INSERT and DELETE operations to an index requires a single index-tree traversal. SQL Server implements update to an index or partitioning key as a DELETE followed by an INSERTtherefore, it is roughly twice as expensive as a nonkey UPDATE. The query optimizer considers and costs two different strategies for IUD statements: per-row and per-index maintenance. These two strategies are demonstrated in the plans for queries 1 and 2, respectively, in Figure 2-12 . With per-row maintenance, SQL Server maintains the indexes and the base table together for each row affected by the query. The updates to all nonclustered indexes are performed in conjunction with each single row update on the base table (which might be a heap or a
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clustered index). The plan for Query 1 DELETE FROM dbo.Orders WHERE OrderDate='2002-01-01' (the top one in Figure 2-12 ) is an example of a per-row maintenance. Query 1is deleting only 24 rows in the Orders table in the Performance database that is generated by Listing 3-1 from 3 . The plan for Query 1 does not show any deletes performed on the secondary indexes because they are carried out together with the deletes of the clustered index rows one row at a time.
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