The primary reason for using a lateral join is that the inner subquery can refer to the fields of the row from the table reference and use that to determine what rows to return. The rows returned by the inner subquery are then added to the result of the lateral join. The above query will iterate through each row in the table reference and evaluate the inner subquery for each row, exactly like a foreach loop would. (For context, a table reference is either a table or a subquery.) The simplest form, which is the one you probably want looks like the following: There are actually two different ways of writing a lateral join. I also find it surprising there are no good explanations of lateral joins online given how simple they are.Ī lateral join is simply a foreach loop in SQL. I find it surprising lateral joins were only introduced into Postgres four years ago given how useful they are. They are simple, while at the same time they let you write queries that would be nearly impossible to write otherwise. The following table shows similarities, differences, and key migration considerations.Personally, lateral joins are one of my favorite Postgres features. You can rewrite these statements using INNER JOIN LATERAL and LEFT JOIN LATERAL.įind Items that were never ordered. Find the differences following.įULL OUTER JOIN and OUTER JOIN using the pre-ANSI SQL 92 syntax aren’t supported, but you can use workarounds.ĬROSS APPLY and OUTER APPLY aren’t supported. Syntax FROMįor most JOIN statements, the syntax should be equivalent and no rewrites should be needed. You can replace them with INNER JOIN LATERAL and LEFT JOIN LATERAL. PostgreSQL doesn’t support APPLY options. Every JOIN starts as a Cartesian product. Results in a Cartesian product of the two sets. PostgreSQL UsageĪmazon Aurora PostgreSQL-Compatible Edition (Aurora PostgreSQL) supports all types of joins in the same way as SQL Server. Col1 COl2 Col1 COl2įor more information, see FROM clause plus JOIN, APPLY, PIVOT (Transact-SQL) in the SQL Server documentation. The preceding example produces the following results. SELECT I.ItemįULL OUTER JOIN CREATE TABLE T1(Col1 INT, COl2 CHAR(2)) ) INSERT INTO OrderItems (OrderID, Item, Quantity)įind Items that were never ordered. ('3/8" Bolt', 'Imperial Bolts', 'Brass') CREATE TABLE OrderItems ('M8 Washer', 'Metric Washers', 'Stainless Steel'), ('M8 Nut', 'Metric Nuts', 'Stainless Steel'), ('M8 Bolt', 'Metric Bolts', 'Stainless Steel'), ) INSERT INTO Items (Item, Category, Material) For more information, see Deprecated Database Engine Features in SQL Server 2008 R2 in the SQL Server documentation.Įven though INNER JOIN using the ANSI SQL 89 syntax is still supported, they are highly discouraged due to being notorious for introducing hard-to-catch programming bugs. To perform a FULL OUTER JOIN, asterisks were placed on both sides of the equality sign of the join predicate.Īs of SQL Server 2008R2, outer joins using this syntax have been deprecated. T-SQL supported outer joins by adding an asterisk to the left or the right of equality sign of the join predicate to designate the reserved table. SELECT * FROM Table1,Īlthough the ANSI standard didn’t specify outer joins at the time, most RDBMS supported them in one way or another. To perform an INNER JOIN, you only needed to add the JOIN predicate as part of the WHERE clause. The ANSI syntax for a CROSS JOIN operator was to list the sets in the FROM clause using commas as separators. Up until version 2008R2, SQL Server also supported the old-style JOIN syntax including LEFT and RIGHT OUTER JOIN. In that case, NULL is assigned to all columns of. Similar to a LEFT OUTER JOIN in the sense that rows from are returned even if the sub query for produces an empty set. Similar to a CROSS JOIN in the sense that every row from is matched with every row from. This functionality isn’t possible with any type of standard JOIN operator. However, APPLY operators enable the creation of a correlation between and such that may consist of a sub query, a VALUES row value constructor, or a table valued function that is evaluated for each row of where the query can reference columns from the current row in. SQL Server also supports the APPLY operator, which is somewhat similar to a join. Designates both sets as reserved and adds non-matching rows from both, similar to a LEFT OUTER JOIN and a RIGHT OUTER JOIN. RIGHT OUTER JOIN ON Adds to the INNER JOIN all the rows from the reserved right set with NULL for all the columns that come from the left set. Adds to the INNER JOIN all the rows from the reserved left set with NULL for all the columns that come from the right set. Filters the Cartesian product to only the rows where the join predicate evaluates to TRUE.
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