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This hint was added in SQL Server 2008. It tells the Query Optimizer that it needs to generate a seek predicate when using an index. There are a few cases when the Query Optimizer can determine that a scan of an index is better than a seek when compiling the query. For example, if a query is compiled while the table is almost empty, the storage engine may store all the existing rows in one page in an index. In this case, a scan is faster than a seek, in terms of I/O, because the storage engine supports scanning from the leaf nodes of a B+ tree, which would avoid one extra page of I/O. This condition might be ephemeral, given that newly created tables are often populated soon after. The hint is effective in avoiding such a scenario if you know that perhaps the table won t have enough rows to trigger a recompile or that the performance impact of this condition would be detrimental enough to the system to warrant the hint. The other scenario where such a hint is interesting is to avoid locks in OLTP applications. This hint precludes an index scan, so it can be effective if you have a high-scale OLTP application where locking is a concern in scaling and concurrency. The hint avoids the possibility of the plan taking more locks than desired. Because the Query Optimizer does not explicitly reason about locking in plan selection (it does not prefer a plan that has fewer locks, but it might prefer a plan that it things will perform faster that also happens to take fewer locks). Care should be taken in hinting high-scale applications only when necessary, as a poor hint can cause the system to behave substantially worse than an unhinted plan.

The Query Optimizer assumes that the user will read every row produced by a query. Although this is often true, some user scenarios, such as manually paging through results, do not follow this pattern in these cases, the client reads some small number of rows and then closes the query result. Often a similar query is submitted in the near future to retrieve another batch of rows from the server. In the costing component, this assumption affects the plan choice. For example, hash joins are more ef cient for larger result sets but have a higher

startup cost (to build a hash table for one side of a join). Nested loops joins have no startup cost but a somewhat higher per-row cost. So, when a client wants only a few rows but does not specify a query that returns only a few rows, the latency of the rst row may be slower due to the startup costs for stop-and-go operators like hash joins, spools, and sorts. The FAST <number_rows> hint supplies the costing infrastructure with a hint from the user about how many rows the user will want to read from a query. Internally, this is called a row goal, and simply provides an input into the costing formulas to help specify what point on the costing function is appropriate for the user s query. The TOP() syntax in SQL Server introduces a row goal as well. Note that if you supply TOP(@param), then the Query Optimizer may not have a good value to sniff from the T-SQL context. In this scenario, you would want to use the OPTIMIZE FOR hint (described later in this section).

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MAXDOP stands for maximum degree of parallelism, which describes the preferred degree of fan-out to be used when this query is run (in SKUs that support parallel query plans). For expensive queries, the Query Optimizer attempts to use multiple threads to reduce the run time of a query. Within the costing functions, this means that some portions of the costs of a query are divided over multiple processor cores, reducing the overall cost compared to an otherwise identical serial plan. Very complex queries can actually have multiple zones of parallelism, meaning that each zone can have up to MAXDOP threads assigned to it during execution. Large queries can consume a nontrivial fraction of the resources available to the system. A parallel query can consume memory and threads, blocking other queries that want to begin execution. In some cases, it is bene cial to the overall health of the system to reduce the degree of parallelism for one or more queries to lower the resources required to run a long-running query. This helps workloads that do not use the resource governor to manage resources. Often a server that services mixed workloads would be a good candidate for considering this hint, when needed.