ANSI SQL IBM Informix Ingres InterBase Microsoft MySQL Oracle Sybase in Java

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ANSI SQL IBM Informix Ingres InterBase Microsoft MySQL Oracle Sybase
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Notes on Table 4-1:
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Basic GROUP BY column This column is "Yes" if the DBMS supports basic GROUP BY syntax like:
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SELECT column1, MIN(column2) FROM Table1 GROUP BY column1
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Expressions column This column is "Yes" if the DBMS supports expressions in GROUP BY, like this:
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SELECT UPPER(column1) FROM Table1 GROUP BY UPPER(column1)
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CREATE VIEW column This column is "Yes" if the DBMS lets you put GROUP BY in a CREATE VIEW statement, like this:
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CREATE VIEW View1 AS SELECT column1, COUNT(column1) FROM Table1 GROUP BY column1
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COLLATE Clause column This column is "Yes" if the DBMS supports ANSI SQL-style COLLATE clauses, or Oraclestyle NLSSORT() function calls, or a CAST to a different character set with a different collation in GROUP BY, like this:
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SELECT column1, MIN(column2) FROM Table1 GROUP BY column1 COLLATE SQL_Latin1_General
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CUBE/ROLLUP column This column is "Yes" if the DBMS supports CUBE and ROLLUP for summarizing, like this:
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SELECT column1, column2 FROM Table1 GROUP BY CUBE (column1, column2)
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Max Columns column Shows how many columns may be listed in the GROUP BY clause For Sybase, our tests showed it was possible to group at least 20 columns This differs from Sybase's response to JDBC's getMaxColumnsInGroupBy call, which returns 16
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Max Bytes column Shows the maximum allowed length, in bytes, of grouped values
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Optimal GROUP BY Clauses
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We've already mentioned that GROUP BY performs better if you keep the number of grouping columns small One way you can do so is to avoid grouping redundant columns, as in this example:
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SELECT secondary_key_column, primary_key_column, COUNT(*) FROM Table1 GROUP BY secondary_key_column, primary_key_column
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Because primary key columns are unique and may not contain NULL by definition, the mention of secondary_key_column in this example is redundant The problem is that if you take secondary_key_column out of the GROUP BY clause, you'll get an error message All DBMSs except MySQL and Sybase will tell you that you can't have secondary_key_column in the select list if it's not also in the GROUP BY list This is how to write a query that's legal and that's faster:
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SELECT MIN(secondary_key_column), primary_key_column, COUNT(*) FROM Table1
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GROUP BY primary_key_column GAIN: 4/7
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WARNING Don't do this for Ingres; it shows a loss The gain shown is for only seven DBMSs
Here are two ways to speed up GROUP BY when you're joining tables
Reduce before you expand
GROUP BY tends to reduce row counts, and JOIN tends to expand row counts Because a DBMS must evaluate FROM and WHERE clauses before GROUP BY clauses, this tip is not easy to put into practice, but there is a way You can make a join happen late by replacing it with a set operator (The SQL Standard set operators are UNION, EXCEPT, and INTERSECT) For example, replace Statement #1 with Statement #2:
Statement #1: SELECT SUM(Table1column2), SUM(Table2column2) FROM Table1 INNER JOIN Table2 ON Table1column1 = Table2column1 GROUP BY Table1column1 Statement #2: SELECT column1, SUM(column2), 0 FROM Table1 GROUP BY column1 INTERSECT SELECT column1, 0, SUM(column2) FROM Table2 GROUP BY column1 GAIN: 2/2
Portability Informix, Ingres, InterBase, Microsoft, MySQL, and Sybase don't support INTERSECT The gain shown is for only two DBMSs
GROUP on the same table
When you're grouping joined tables, the GROUP BY column should be from the same table as the column(s) on which you're applying a set function We're passing this advice along because some vendors think it's important enough to mention in their documentation
Also to do with joins and GROUP BY, you can improve performance by avoiding joins altogether Consider this SELECT:
SELECT COUNT(*) FROM Table1, Table2 WHERE Table1column1 = Table2column1
If Table1column1 is unique, you could replace the join with a subquery Transform the SELECT to:
SELECT COUNT(*) FROM Table2 WHERE Table2column1 IN (SELECT Table1column1 FROM Table1) GAIN: 4/6
WARNING Don't do this for Oracle; it shows a loss The gain shown is for only six DBMSs (see Portability note)
Portability MySQL doesn't support subqueries The gain shown is for only six DBMSs
HAVING
Most DBMSs do not merge WHERE and HAVING clauses This means the following statements are logically the same but won't run at the same speed:
Query with WHERE and HAVING: SELECT column1 FROM Table1 WHERE column2 = 5 GROUP BY column1 HAVING column1 > 6 Query with WHERE only: SELECT column1 FROM Table1 WHERE column2 = 5 AND column1 > 6 GROUP BY column1 GAIN: 3/8
The "Query with WHERE only" runs faster on three of the Big Eight You should use this type of query except in the rare cases where you need to defer the filtering implied by column1 > 6 for example, if the comparison is hard to evaluate