SELECT COUNT(*)(SELECT DISTINCT a.my_id, a.last_name, a.first_name, b.temp_val. FROM Table_A a INNER JOIN Table_B b on a.a_id
select{. selectFields = count(uid) AS count.
For example: SELECT COUNT(*) FROM (SELECT 'Dummy' AS [Dummy] WHERE 1 = 0) DummyTable. Will return one record with the value '0', where as: SELECT COUNT(*) FROM (SELECT 'Dummy' AS [Dummy] WHERE 1 = 0) DummyTable GROUP BY [Dummy].
This is basically the same thing as a PIVOT function in some RDBMS: SELECT distributor_id, count(*) AS total, sum(case when level = 'exec' then 1 else 0 end) AS ExecCount, sum(case when level = 'personal' then 1 else 0 end) AS PersonalCount FROM yourtable GROUP BY distributor_id.
SELECT count( * ) as total_record FROM student. Output of above query is here.
Is there any official documentation which statement should process a SELECT faster that I expect to return only one.
Processing SELECT COUNT(*) statements takes some time if index records are not entirely in the buffer pool. For a faster count, create a counter table and let your application update it according to the inserts and deletes it does. However, this method may not scale well in situations where thousands of...
Consequently, SELECT COUNT(*) statements only count rows visible to the current transaction. As of MySQL 8.0.13, SELECT COUNT(*) FROM tbl_name query performance for InnoDB tables is
SELECT COUNT(*) FROM count_demos; This example uses the COUNT(*) function with a WHERE clause to specify a condition to count only rows whose value in
In general, these types of “select the extreme from each group” queries can be solved with the same techniques.