# Various join joins for SQL

Source: Internet
Author: User
Tags joins

For SQL joins, learning may be a bit confusing. We know that the join syntax for SQL has a lot of inner, outer, left, and sometimes it's not very clear what the result set looks like for a select. There is an article on Coding horror (it is not clear why Coding horror was also the wall) through the Venturi diagram Venn diagrams explained the join of SQL. I feel clear and understandable, turn around.

Suppose we have two tables, table A is the one on the left and table B is the one on the right. What is the Venetian Macao?

Each of them has four records, of which two records are the same, as follows:

 `1` `id ``name``id  ``name`
 `2` `-- ----       --  ----`
 `3` `1  Pirate     1   Rutabaga`
 `4` `2  Monkey     2   Pirate`
 `5` `3  Ninja      3   Darth Vader`
 `6` `4  Spaghetti  4   Ninja`

Let's look at the results of different joins.

 `1` `SELECT``* ``FROM` `TableA ``INNER``JOIN``TableB`
 `2` `ON``TableA.``name``= TableB.``name`
 `3` `id  ``name``id   ``name`
 `4` `--  ----       --   ----`
 `5` `1   Pirate     2    Pirate`
 `6` `3   Ninja      4    Ninja`

Inner Join
The resulting set of results is the intersection of a and B.

 `01` `SELECT``* ``FROM` `TableA ``FULL``OUTER` `JOIN``TableB`
 `02` `ON``TableA.``name``= TableB.``name`
 `03` `id    ``name``id    ``name`
 `04` `--    ----       --    ----`
 `05` `1     Pirate     2     Pirate`
 `06` `2     Monkey     ``null``null`
 `07` `3     Ninja      4     Ninja`
 `08` `4     Spaghetti  ``null``null`
 `09` `null``null``1     Rutabaga`
 `10` `null``null``3     Darth Vader`

The full outer join produces a and B's set. It is important to note, however, that for records that do not have a match, NULL is the value.

 `1` `SELECT``* ``FROM` `TableA ``LEFT``OUTER` `JOIN` `TableB ``ON``TableA.``name``= TableB.``name`
 `2` `id  ``name``id    ``name`
 `3` `--  ----       --    ----`
 `4` `1   Pirate     2     Pirate`
 `5` `2   Monkey      ``null``null`
 `6` `3   Ninja      4     Ninja`
 `7` `4   Spaghetti   ``null``null`

The left outer join produces a full set of table A, whereas a match in B table has a value, and no match is substituted with a null value.

 ` 1 ` `select *  from  tablea   left outer  join  tableb  on tablea. name  = TableB. name where  tableb.id  is  null `
 `2` `id  ``name``id     ``name`
 `3` `--  ----       --     ----`
 `4` `2   Monkey  ``null``null`
 `5` `4   Spaghetti   ``null``null`

Produces a collection that is available in table A and not in the B table.

 ` 1 ` `select *  from  tablea   full outer  join  tableb  on tablea. name  = TableB. name where  tablea.id  is  null  or tableb.id   is  null `
 `2` `id    ``name``id    ``name`
 `3` `--    ----       --    ----`
 `4` `2     Monkey    ``null``null`
 `5` `4     Spaghetti ``null``null`
 `6` `null``null``1     Rutabaga`
 `7` `null``null``3     Darth Vader`

produce datasets that do not appear in both A and B tables.

It is also necessary to register that we also have a cross join of "cross-set", which is not represented by Wenshitu because it is a n*m combination of the data of table A and table B, that is, the Cartesian product. The expression is as follows:

 `1` `SELECT``* ``FROM``TableA`
 `2` `CROSS``JOIN``TableB`

This Cartesian product produces 4 x 4 = 16 records, which, in general, are seldom used in this syntax. But we have to be careful, if you do not use nested SELECT statements, the general system will produce a Cartesian product and then filter. This is very dangerous for performance, especially when the table is very large.

Various join joins for SQL

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