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WARNING Don't do this for Sybase; it shows a loss The gain shown is for only six DBMSs
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Here's a final example Query #1 transforms into Query #2:
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Query #1: SELECT * FROM Table1 WHERE Table1column1 IN (SELECT Table2column1 FROM Table2 WHERE Table2column1 IN (SELECT Table3column1 FROM Table3)) Query #2: SELECT * FROM Table1 WHERE Table1column1 IN (SELECT Table2column1 FROM Table2) AND Table1column1 IN (SELECT Table3column1 FROM Table3)
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GAIN: 7/7
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It's better to merge two subqueries into one
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Some DBMSs support a nonstandard SQL extension TOP <number> clause for the SELECT statement TOP (or its equivalent) finds the first [number] rows that match the SELECT requirements For example, Microsoft lets you do this:
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SELECT * FROM Table1 X WHERE Xcolumn1 IN (SELECT TOP 5 Ycolumn1 FROM Table2 Y WHERE Ycolumn2 = Xcolumn2 ORDER BY Ycolumn1 DESC)
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The example looks only for the first five rows that are true for the subquery, then evaluates the rest of the query with that data (Microsoft also allows ORDER BY in a subquery if a TOP clause is in the select list) Table 6-2 shows the TOP equivalent support provided by the Big Eight Table 6-2 DBMSs and TOP Equivalent SELECT clause that limits rows returned FETCH FIRST <number> FIRST <number> No support No support TOP <number> LIMIT <number> SAMPLE (<number>) No support
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IBM Informix Ingres InterBase Microsoft MySQL Oracle Sybase
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Conditions of the form > ALL (subquery) have a slight portability problem If the subquery has zero rows, then most DBMSs correctly say the condition is true but some incorrectly say the condition is false Fortunately, none of the Big Eight have this flaw Be that as it may, > ALL conditions should be replaced by > ANY conditions with a MAX in the subquery For example, Query #1 should be replaced by Query #2:
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Query #1: SELECT * FROM Table1 WHERE column1 > ALL (SELECT column1 FROM Table2) Query #2: SELECT * FROM Table1
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WHERE column1 > ANY (SELECT MAX(column1) FROM Table2) GAIN: 5/7
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The idea in this example is that if Table2column1 is indexed, then the DBMS may have an optimal way to find MAX(column1) (Note that these queries can return different results if Table2 is empty, or if Table2column1 contains NULLs)
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Set Operations
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A subquery is a type of set operation Suppose you have a set of rows from an outer query (OUTER) and a set of rows from an inner query (INNER) For IN subqueries, (OUTER) values must contain (INNER) values For NOT IN subqueries, (OUTER) values must not contain (INNER) values Both of these operations could also be done with explicit set operators, namely INTERSECT and EXCEPT Many DBMSs don't support INTERSECT or EXCEPT, although all DBMSs except MySQL support another set operator: UNION Table 6-3 shows the SQL Standard requirements and the level of support the Big Eight have for the set operators Notes on Table 6-3:
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Oracle and Sybase call EXCEPT the MINUS operator Table 6-3 ANSI/DBMS Support for Set Operators UNION EXCEPT INTERSECT UNION JOIN Yes Yes Yes Yes Yes Yes Yes No Yes No No No Yes No No No Yes No No No Yes No No No No No No No Yes Yes Yes No Yes Yes No No
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ANSI SQL IBM Informix Ingres InterBase Microsoft MySQL Oracle Sybase
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It matters little whether a DBMS supports INTERSECT, but the EXCEPT operator is useful for transforming NOT IN For example, Query #1 can be transformed to Query #2:
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Query #1: SELECT column1 FROM Table1 WHERE Table1column2 NOT IN (SELECT column2 FROM Table2) Query #2: SELECT column1 FROM Table1 EXCEPT SELECT column1 FROM Table1 WHERE Table1column2 IN (SELECT column2 FROM Table2) GAIN: 2/3
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Portability Informix, Ingres, InterBase, and Microsoft don't support EXCEPT The gain shown is for only three DBMSs
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The gain happens because IN conditions use indexes NOT IN conditions don't use indexes
The Bottom Line: Syntax Choices
In general, in-to-out plans occur for subqueries that (a) begin with <comparison operator>
[ANY | ALL] and (b) contain no correlations
If a subquery is in-to-out, then the relationship should be few-rows-to-many The best optimizations are ones that reduce the row count in the driver Add DISTINCT to the inner query, even when it's logically superfluous DISTINCT causes ORDER BY, and it reduces the number of rows in the inner query Scanning is faster if the inner loop happens on a materialized view of the table, which is smaller than the table itself DISTINCT helps here as well Materialization is a factor that discourages the DBMS from flattening If DISTINCT is a do-nothing operator because there's no duplication, then the relation is not one-tomany A join is probably better than a subquery in such cases [NOT] EXISTS subqueries generally contain correlations If you can put a significant restriction on the outer query, that's good even if the restriction has to be repeated in the inner query Because you can't break out of the outer loop when using [NOT] EXISTS, it's more effective to reduce the number of outer-loop iterations Use IN for subqueries when the outer table has many rows and the inner table has few rows Use EXISTS for subqueries when the outer query has a search condition in addition to the subquery condition Use NOT EXISTS for subqueries that have a WHERE NOT outer query Don't write queries that contain two subqueries It's better to merge two subqueries into one Conditions of the form > ALL (subquery) have a portability problem Replace > ALL conditions with > ANY conditions that have a MAX function in the subquery
The EXCEPT operator is useful for transforming NOT IN subqueries EXCEPT provides a gain because it changes NOT IN to IN IN conditions use indexes NOT IN conditions don't use indexes