![]() If you want to dig deeper, provide SHOW CREATE TABLE (so we can see the index(es), etc), EXPLAIN SELECT (so we can discuss what the Optimizer decided on) and, if possible EXPLAIN FORMAT=JSON SELECT. The simplest way to force the join order is to put the tables in the correct order in the FROM clause and use SELECT STRAIGHTJOIN like so: SELECT STRAIGHTJOIN SUM (City.Population) FROM Country,City WHERE City.CountråodeCountry.Code AND Country. Note that your "0.005 seconds" was "luck". The Optimizer would see that as something worth optimizing. Your first query might be sped up by using WHERE EXISTS (. (Note: The table size is based on row estimates and may not be correct every time.) Without a WHERE clause, the Optimizer usually starts with the smaller table. If that's the same table as the ORDER BY, then the above discussion may kick in. ![]() Usually (not always), a WHERE clause (on one table) tells the Optimizer "pick me". With two tables, the Optimizer chooses one table, finds what it can there, then does a Nested Loop Join to the other table. If all columns in ORDER BY and GROUP BY clauses come from the same. When you JOIN two (or more) tables, it gets messier. 11.The best join combination for joining the tables is found by trying all possibilities. (This assumes no GROUP BY, or the GROUP BY and ORDER BY are identical.) In general, if the WHERE, and ORDER BY can be completely satisfied, then LIMIT n can be optimized. If there is no suitable index on SALEDATE for a pipelined order by, the database must read and sort the entire table. It will need to pick up all the rows with a>12, sort by x, then deliver one row. No problem - Look in the index for a=12 pick the first item. With an inner join of two tables, there are usually seven choices: PostgreSQL can opt for a nested loop, hash or merge join, and for the first two of these, the order of the tables makes a difference as well. If not, then it could have to scan the entire table to find the one row ! Given INDEX(a, x) I mentioned above that the optimizer rearranges the join order of a query. Were able to narrow our searches as usual using a WHERE clause, and we can specify how the tables are. May also use the index, and hope that some early row is satisfied by the WHERE. A LEFT JOIN in MySQL combines rows from two tables. If a table is determined to be nullable, some optimizations will degenerate. Null rows can be propagated according to the JOIN relationship (topjoinlist). Will conveniently use the index and pick off the first item Given INDEX(x) 2.1 Pass the List of Inner Tables from null to join (propagatenullability) The prepare function first processes nullable table, which refers to the table that may contain null rows.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |