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Kirill Smelkov
mariadb
Commits
a3ae37ed
Commit
a3ae37ed
authored
Dec 10, 2001
by
jani@hynda.mysql.fi
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Added information about floating point numbers.
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Docs/manual.texi
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Docs/manual.texi
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a3ae37ed
...
@@ -44369,6 +44369,7 @@ the server runs, for example, in @code{safe_mysqld} or @code{mysql.server}.
...
@@ -44369,6 +44369,7 @@ the server runs, for example, in @code{safe_mysqld} or @code{mysql.server}.
* Problems with alias:: Problems with @code{alias}
* Problems with alias:: Problems with @code{alias}
* Deleting from related tables:: Deleting Rows from Related Tables
* Deleting from related tables:: Deleting Rows from Related Tables
* No matching rows:: Solving Problems with No Matching Rows
* No matching rows:: Solving Problems with No Matching Rows
* Problems with float:: Problems with floating point comparison
@end menu
@end menu
@node Case sensitivity, Using DATE, Query Issues, Query Issues
@node Case sensitivity, Using DATE, Query Issues, Query Issues
...
@@ -44611,7 +44612,7 @@ id's per query if the @code{related_column} is an index. If the
...
@@ -44611,7 +44612,7 @@ id's per query if the @code{related_column} is an index. If the
number of arguments in the @code{IN} clause.
number of arguments in the @code{IN} clause.
@node No matching rows,
, Deleting from related tables, Query Issues
@node No matching rows,
Problems with float
, Deleting from related tables, Query Issues
@appendixsubsec Solving Problems with No Matching Rows
@appendixsubsec Solving Problems with No Matching Rows
@cindex no matching rows
@cindex no matching rows
...
@@ -44639,16 +44640,10 @@ the table that was last removed from the query.
...
@@ -44639,16 +44640,10 @@ the table that was last removed from the query.
@item
@item
If you are comparing @code{FLOAT} or @code{DOUBLE} columns with numbers that
If you are comparing @code{FLOAT} or @code{DOUBLE} columns with numbers that
have decimals, you can't use @code{=}! This problem is common in most
have decimals, you can't use @code{'='}. This problem is common in most
computer languages because floating-point values are not exact values:
computer languages because floating-point values are not exact values.
In most cases, changing the @code{FLOAT} to a @code{DOUBLE} will fix this.
@example
@xref{Problems with float}.
mysql> SELECT * FROM table_name WHERE float_column=3.5;
->
mysql> SELECT * FROM table_name WHERE float_column between 3.45 and 3.55;
@end example
In most cases, changing the @code{FLOAT} to a @code{DOUBLE} will fix this!
@item
@item
If you still can't figure out what's wrong, create a minimal test that can
If you still can't figure out what's wrong, create a minimal test that can
...
@@ -44666,6 +44661,128 @@ shell> mysql test2 < query.sql
...
@@ -44666,6 +44661,128 @@ shell> mysql test2 < query.sql
Post the test file using @code{mysqlbug} to @email{mysql@@lists.mysql.com}.
Post the test file using @code{mysqlbug} to @email{mysql@@lists.mysql.com}.
@end enumerate
@end enumerate
@node Problems with float, , No matching rows, Query Issues
@appendixsubsec Problems with floating point comparison
Floating point numbers cause confusion sometimes, because these numbers
are not stored as exact values inside computer architecture. What one
can see on the screen usually is not the exact value of the number.
Field types @code{FLOAT} and @code{DECIMAL} are such.
@example
CREATE TABLE t1 (i int, d1 decimal(9,2), d2 decimal(9,2));
INSERT INTO t1 values (1, 101.40, 21.40), (1, -80.00, 0.00), (2, 0.00, 0.00),
(2, -13.20, 0.00), (2, 59.60, 46.40), (2, 30.40, 30.40), (3, 37.00, 7.40),
(3, -29.60, 0.00), (4, 60.00, 15.40), (4, -10.60, 0.00), (4, -34.00, 0.00),
(5, 33.00, 0.00), (5, -25.80, 0.00), (5, 0.00, 7.20), (6, 0.00, 0.00),
(6, -51.40, 0.00);
mysql> SELECT i, SUM(d1) AS a, SUM(d2) AS b FROM t1 GROUP BY i HAVING a <> b;
+------+--------+-------+
| i | a | b |
+------+--------+-------+
| 1 | 21.40 | 21.40 |
| 2 | 76.80 | 76.80 |
| 3 | 7.40 | 7.40 |
| 4 | 15.40 | 15.40 |
| 5 | 7.20 | 7.20 |
| 6 | -51.40 | 0.00 |
+------+--------+-------+
@end example
The result is correct. Although the first five records look like they
shouldn't pass the comparison test, they may do so because the
difference between the numbers show up around tenth decimal, or so
depending on computer architecture.
The problem cannot be solved by using ROUND() (or similar function),
because the result is still a floating point number. Example:
@example
mysql> SELECT i, ROUND(SUM(d1), 2) AS a, ROUND(SUM(d2), 2) AS b FROM t1 GROUP BY i HAVING a <> b;
+------+--------+-------+
| i | a | b |
+------+--------+-------+
| 1 | 21.40 | 21.40 |
| 2 | 76.80 | 76.80 |
| 3 | 7.40 | 7.40 |
| 4 | 15.40 | 15.40 |
| 5 | 7.20 | 7.20 |
| 6 | -51.40 | 0.00 |
+------+--------+-------+
@end example
This is what the numbers in row 'a' look like:
@example
mysql> SELECT i, ROUND(SUM(d1), 2)*1.0000000000000000 AS a, ROUND(SUM(d2), 2) AS b FROM t1 GROUP BY i HAVING a <> b;
+------+----------------------+-------+
| i | a | b |
+------+----------------------+-------+
| 1 | 21.3999999999999986 | 21.40 |
| 2 | 76.7999999999999972 | 76.80 |
| 3 | 7.4000000000000004 | 7.40 |
| 4 | 15.4000000000000004 | 15.40 |
| 5 | 7.2000000000000002 | 7.20 |
| 6 | -51.3999999999999986 | 0.00 |
+------+----------------------+-------+
@end example
Depending on the computer architecture you may or may not see similar results.
Each CPU may evaluate floating point numbers differently. For example in
some machines you may get 'right' results by multiplaying both arguments
with 1, an example follows.
@strong{WARNING: NEVER TRUST THIS METHOD IN YOUR APPLICATION, THIS IS
AN EXAMPLE OF A WRONG METHOD!!!}
@example
mysql> SELECT i, ROUND(SUM(d1), 2)*1 AS a, ROUND(SUM(d2), 2)*1 AS b FROM t1 GROUP
BY i HAVING a <> b;
+------+--------+------+
| i | a | b |
+------+--------+------+
| 6 | -51.40 | 0.00 |
+------+--------+------+
@end example
The reason why the above example seems to be working is that on the
particular machine where the test was done, the CPU floating point
arithmetics happens to round the numbers to same, but there is no
rule that any CPU should do so, so it cannot be trusted.
The correct way to do floating point number comparison is to first
decide on what is the wanted tolerance between the numbers and then do
the comparsion against the tolerance number. For example, if we agree on
that floating point numbers should be regarded the same, if they are
same with precision of one of ten thousand (0.0001), the comparsion
should be done like this:
@example
mysql> SELECT i, SUM(d1) AS a, SUM(d2) AS b FROM t1 GROUP BY i HAVING ABS(a - b) > 0.0001;
+------+--------+------+
| i | a | b |
+------+--------+------+
| 6 | -51.40 | 0.00 |
+------+--------+------+
1 row in set (0.00 sec)
@end example
And vice versa, if we wanted to get rows where the numbers are the same,
the test would be:
@example
mysql> SELECT i, SUM(d1) AS a, SUM(d2) AS b FROM t1 GROUP BY i HAVING ABS(a - b) < 0.0001;
+------+-------+-------+
| i | a | b |
+------+-------+-------+
| 1 | 21.40 | 21.40 |
| 2 | 76.80 | 76.80 |
| 3 | 7.40 | 7.40 |
| 4 | 15.40 | 15.40 |
| 5 | 7.20 | 7.20 |
+------+-------+-------+
@end example
@node Table Definition Issues, , Query Issues, Problems
@node Table Definition Issues, , Query Issues, Problems
@appendixsec Table Definition Related Issues
@appendixsec Table Definition Related Issues
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