8/2/2023 0 Comments Sqlite inner join explained![]() In this particular case these will be the rows that were preserved as they had no match in the right hand table and the query returns the single red row not matched in table B. This simply restricts the previous result to only return the rows where B.Colour IS NULL. SELECT A.Colour, B.Colour FROM A LEFT OUTER JOIN B ON A.Colour = B.Colour WHERE B.Colour IS NULL Outer Joins are logically evaluated in the same way as inner joins except that if a row from the left table (for a left join) does not join with any rows from the right hand table at all it is preserved in the result with NULL values for the right hand columns. SELECT A.Colour, B.Colour FROM A LEFT OUTER JOIN B ON A.Colour = B.Colour I won't repeat the picture of the 16 rows again. The join condition evaluates to true for all rows in the cross join result so this is just the same as a cross join. SELECT A.Colour, B.Colour FROM A INNER JOIN B ON 1 =1 Evaluating A.Colour NOT IN ('Green','Blue') on each row of the cross join returns. The inner join condition need not necessarily be an equality condition and it need not reference columns from both (or even either) of the tables. SELECT A.Colour, B.Colour FROM A INNER JOIN B ON A.Colour NOT IN ('Green','Blue') SELECT A.Colour, B.Colour FROM A INNER JOIN B ON A.Colour = B.Colour Same as inner join then preserve left non matched rows as in left outer join and right non matching rows as per right outer join. Same as inner join then for any rows in the right table that did not match anything output these with NULL values for the left table columns. Same as inner join then for any rows in the left table that did not match anything output these with NULL values for the right table columns. Evaluate the condition in the "ON" clause for all rows in the cross join result. Inner and Outer joins have an "ON" clause predicate. ![]() SELECT A.Colour, B.Colour FROM A CROSS JOIN B This does not have an ON clause and simply returns every combination of rows from the two tables. Further explanation follows.įirst start with a CROSS JOIN (AKA Cartesian Product). I'll start off with an animated version of a full outer join. (NB: In practice the query optimiser may find more efficient ways of executing the query than the purely logical description above but the final result must be the same) (For outer joins only) add back in any outer rows that were lost in step 2.Evaluate the on clause against all rows from step 1 keeping those where the predicate evaluates to true.There is no substitute for understanding the logical processing and it is relatively straightforward to grasp anyway. They don't show any distinction between a cross join and an inner join, for example, or more generally show any distinction between different types of join predicate or provide a framework for reasoning about how they will operate. The Venn diagrams don't really do it for me. ![]() select * from a FULL OUTER JOIN b on a.a = b.b If something in A doesn't have a corresponding datum in B, then the B portion is null, and vice versa. Select a.*, b.* from a,b where a.a(+) = b.b Ī full outer join will give you the union of A and B, i.e. select * from a RIGHT OUTER JOIN b on a.a = b.b Select a.*, b.* from a,b where a.a = b.b(+) Ī right outer join will give all rows in B, plus any common rows in A. select * from a LEFT OUTER JOIN b on a.a = b.b Select a.*, b.* from a,b where a.a = b.b Ī left outer join will give all rows in A, plus any common rows in B. select * from a INNER JOIN b on a.a = b.b Note that (1,2) are unique to A, (3,4) are common, and (5,6) are unique to B.Īn inner join using either of the equivalent queries gives the intersection of the two tables, i.e. Suppose you have two tables, with a single column each, and data as follows: A B the inner part of a Venn diagram intersection.Īn outer join of A and B gives the results of A union B, i.e. Assuming you're joining on columns with no duplicates, which is a very common case:Īn inner join of A and B gives the result of A intersect B, i.e.
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