The reproduced test database is as follows:
CREATE TABLE `test_distinct` ( `id` int(11) NOT NULL AUTO_INCREMENT, `a` varchar(50) CHARACTER SET utf8 DEFAULT NULL, `b` varchar(50) CHARACTER SET utf8 DEFAULT NULL, PRIMARY KEY (`id`) ) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=latin1;
The test data in the table is as follows. Now we need to count the number of columns after deduplication of these three columns.
My friend gave me four query statements to locate the problem
SELECT COUNT(*) AS cnt FROM test_distinct; SELECT COUNT(DISTINCT id, a, b) as cnt FROM test_distinct; SELECT id, a, b, COUNT(*) AS cnt FROM test_distinct GROUP BY id, a, b HAVING cnt > 1; SELECT l.id AS l_id, l.a AS l_a, l.b AS l_b, r.id AS r_id, r.a AS r_a, r.b AS r_b FROM test_distinct l LEFT JOIN test_distinct r ON l.id = r.id AND l.a = r.a AND l.b = r.b WHERE r.id is NULL or r.id = 'null';
The query results are as follows:
Notice! ! ! From the test data, we can quickly guess where the problem lies, but it turns out that there are more than 30,000 pieces of data in the table, and it is impossible to view the data with the naked eye.
There are two counterintuitive points in the above query results:
The second piece of data is missing after deduplication statistics, but the result of the third piece of data shows There is no identical data.
When using the same table to do a left outer connection, the driving table has data, but the driven table is empty.
Let’s look at the second question first. The official document has the following explanation:
When using the ON clause, the conditions it contains The expression is the same as that used in the WHERE clause. A common situation is to use the ON clause to specify the join conditions of the table, and use the WHERE clause to limit the rows included in the result set.
If there are no matching rows in the right table for the conditions in the ON or USING part of the LEFT JOIN, then the right table uses all columns set to NULL.
You cannot use arithmetic comparison operators (such as =, < or <>) to compare NULL.
SELECT NULL = NULL; SELECT NULL IS NULL;
So the second problem is that the result of NULL=NULL is always False, which results in the two rows originally Equal data results are not equal.
But this does not solve the first problem: why a piece of data disappeared after deduplication. However, we can guess that the missing data is probably related to the NULL value.
We separate the two operations of count and distinct:
SELECT COUNT(*) as cnt FROM (SELECT DISTINCT id, a, b FROM test_distinct) as tmp;
Huh? The result is correct, which means that the query plan generated by count(distinct expr)
may be different from what we imagined. It is not to remove duplicates first and then count. Use explain to analyze the query plan of the two statements. As shown below:
As you can see from the table, the mysql execution engine directly counts count(distinct expr)
As a query, check the official documentation:
The problem has finally been clarified. There are two ways to solve this problem. The first is to remove duplicates first and then count. The second is to use the IFNULL()
function:
SELECT COUNT(DISTINCT id, a, IFNULL(b, '0')) as cnt FROM test_distinct;
In addition, count( )Use:
SELECT id, a, b, COUNT(*) FROM test_distinct GROUP BY id, a, b; SELECT id, a, b, COUNT(b) FROM test_distinct GROUP BY id, a, b;
You cannot use arithmetic comparison operators (such as =, ) to compare null values;
count(distinct expr) returns the number of distinct and non-empty rows in the expr column;
COUNT() has two distinct uses: it can be used to count the number of values in a column, or it can be used to count the number of rows. When counting column values, the column value is required to be non-empty (NULL is not counted). When a column or expression is specified in parentheses of the COUNT() function, the function counts the number of results that have a value in the expression. Another function of COUNT() is to count the number of rows in the result set. When MySQL confirms that the expression value within the parentheses cannot be empty, it is actually counting the number of rows. The simplest thing is when we use COUNT(). In this case, the wildcard does not expand to all columns as we guessed. In fact, it will ignore all columns and directly count all rows - "High-Performance MySQL";
In InnoDB, SELECT COUNT(*) and SELECT COUNT(1) are processed in the same way, and there is no performance difference.
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