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Nonclustered Index Seek + Ordered Partial Scan + Lookups
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The access method nonclustered index seek + ordered partial scan + lookups is typically used for small-range queries (including a point query) using a nonclustered index scan that doesn't cover the query. To demonstrate this access method, I will use the following query: SELECT orderid, custid, empid, shipperid, orderdate FROM dbo.Orders WHERE orderid BETWEEN 101 AND 120;
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There's no covering index because the first key column is the filtered column orderid , but we do have a noncovering onethe PK_Orders index. If the query is selective enough, the optimizer would use the index. Selectivity is defined as the percentage of the number of rows returned by the query out of the total number of rows in the table. The term high selectivity refers to a small percentage, while low selectivity refers to a large percentage. Our access method first performs a seek within the index to find the first key in the sought range (orderid = 101 ). The second part of the access method is an ordered partial scan in the leaf level from the first key in the range until the last (orderid = 101 ). The third and last part involves lookups of the corresponding data row for each key. Note that the third part doesn't have to wait for the second part to finish. For each key that is found in the range, SQL Server can already apply a lookup. Remember that a lookup in a heap translates to a single page read, while a lookup in a clustered table translates to as many reads as the number of levels in the clustered index (3 in our case). It is vital for making performance estimations to understand that with this access method the last part involving the lookups typically incurs most of the query's cost; this is because it involves most of the I/O activity. Remember, the lookup translates to a whole page read or one whole seek within the clustered index per sought row, and the lookups are always random I/O (as opposed to sequential ones). To estimate the I/O cost of such a query, you can typically focus on the cost of the lookups. If you want to make more accurate estimations, also taking into consideration the seek within the index and the ordered partial scan, feel free to do so; but these parts will be negligible as the range grows larger. The I/O cost of a seek operation is 3 reads in our case (number of levels in the index). The I/O cost of the ordered partial scan depends on the number of rows in the range (20 in our case) and the number of rows that fit in an index page (more than 600 in our case). For our query, there's actually no additional read involved for the partial scan; that's because all the keys in the range we are after reside in the leaf page that the seek reached, or they might span an additional page if the first key appears close to the end of the page. The I/O cost of the lookup operations will be the number of rows in the range (20 in our case), multiplied by one if the table is a heap, or multiplied by the number of levels in the clustered index (3 in our case) if the table is clustered. So you should expect around 23 logical reads in total if you run the query against a heap, and around 63 logical reads if you run it against a clustered table. Remember that the non-leaf levels of the clustered index typically reside in cache because of all the lookup operations going through it; so you shouldn't concern yourself too much over the seemingly higher cost of the query in the clustered table scenario. Figure 3-32 has an illustration of the access method over a heap, and Figure 3-33 shows the execution plan for the query.
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