Single INSERT with Multiple Values vs. Multiple Inserts: When Does Batching Become a Bottleneck?

Batch insertion and single insertion of multiple values: When does batch processing become a bottleneck?

A surprising performance comparison shows that executing 1000 INSERT statements alone (290 milliseconds) performs significantly better than inserting 1000 values ​​using a single INSERT statement (2800 milliseconds). To investigate this unexpected result, let's analyze the execution plan and identify potential bottlenecks.

Inspection of the execution plan shows that the single INSERT statement uses an automatic parameterization process to minimize parse/compile time. However, the compilation time of a single INSERT statement suddenly increases at about 250 value clauses, causing the cache plan size to decrease and the compilation time to increase.

Further analysis shows that when compiling a plan for a specific literal value, SQL Server may perform some activities that do not scale linearly, such as sorting. Even without sorting at compile time, adding a clustered index to a table will show an explicit sorting step in the plan.

During the compilation phase, the stack trace of the SQL Server process shows that a lot of time is spent comparing strings. This may be related to the normalization phase (binding or algebraization) of query processing, where the expression parse tree is converted into an algebraic expression tree.

Experiments varying the length and uniqueness of inserted strings have shown that longer strings and fewer duplicates result in worse compile-time performance. This indicates that SQL Server spends more time comparing and identifying duplicates during compilation.

In some cases this behavior can be exploited to improve performance. For example, in a query that uses a duplicate-free column as the primary sort key, SQL Server can skip sorting by the secondary key at runtime and avoid divide-by-zero errors.

So while inserting multiple values ​​using a single INSERT statement may appear to be faster than multiple INSERT statements, the compile time overhead associated with processing large numbers of different values ​​(especially long strings) may cause significant performance degradation in SQL Server decline.

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