7.8. WITH
Queries (Common Table Expressions)
WITH
provides a way to write auxiliary statements for use in a larger query. These statements, which are often referred to as Common Table Expressions orCTEs, can be thought of as defining temporary tables that exist just for one query. Each auxiliary statement in aWITH
clause can be aSELECT
,INSERT
,UPDATE
, orDELETE
; and theWITH
clause itself is attached to a primary statement that can also be aSELECT
,INSERT
,UPDATE
, orDELETE
.
WITH regional_sales AS ( SELECT region, SUM(amount) AS total_sales FROM orders GROUP BY region), top_regions AS ( SELECT region FROM regional_sales WHERE total_sales > (SELECT SUM(total_sales)/10 FROM regional_sales))SELECT region, product, SUM(quantity) AS product_units, SUM(amount) AS product_salesFROM ordersWHERE region IN (SELECT region FROM top_regions)GROUP BY region, product;
The optionalRECURSIVE
modifier changesWITH
from a mere syntactic convenience into a feature that accomplishes things not otherwise possible in standard SQL. UsingRECURSIVE
, aWITH
query can refer to its own output. A very simple example is this query to sum the integers from 1 through 100:
WITH RECURSIVE t(n) AS ( VALUES (1) UNION ALL SELECT n+1 FROM t WHERE n < 100)SELECT sum(n) FROM t;
The general form of a recursiveWITH
query is always anon-recursive term, thenUNION
(orUNION ALL
), then arecursive term, where only the recursive term can contain a reference to the query's own output. Such a query is executed as follows:
Recursive Query Evaluation
Evaluate the non-recursive term. For
UNION
(but notUNION ALL
), discard duplicate rows. Include all remaining rows in the result of the recursive query, and also place them in a temporaryworking table.So long as the working table is not empty, repeat these steps:
Evaluate the recursive term, substituting the current contents of the working table for the recursive self-reference. For
UNION
(but notUNION ALL
), discard duplicate rows and rows that duplicate any previous result row. Include all remaining rows in the result of the recursive query, and also place them in a temporaryintermediate table.Replace the contents of the working table with the contents of the intermediate table, then empty the intermediate table.
Note
WhileRECURSIVE
allows queries to be specified recursively, internally such queries are evaluated iteratively.
In the example above, the working table has just a single row in each step, and it takes on the values from 1 through 100 in successive steps. In the 100th step, there is no output because of theWHERE
clause, and so the query terminates.
Recursive queries are typically used to deal with hierarchical or tree-structured data. A useful example is this query to find all the direct and indirect sub-parts of a product, given only a table that shows immediate inclusions:
WITH RECURSIVE included_parts(sub_part, part, quantity) AS ( SELECT sub_part, part, quantity FROM parts WHERE part = 'our_product' UNION ALL SELECT p.sub_part, p.part, p.quantity * pr.quantity FROM included_parts pr, parts p WHERE p.part = pr.sub_part)SELECT sub_part, SUM(quantity) as total_quantityFROM included_partsGROUP BY sub_part
When working with recursive queries it is important to be sure that the recursive part of the query will eventually return no tuples, or else the query will loop indefinitely. Sometimes, usingUNION
instead ofUNION ALL
can accomplish this by discarding rows that duplicate previous output rows. However, often a cycle does not involve output rows that are completely duplicate: it may be necessary to check just one or a few fields to see if the same point has been reached before. The standard method for handling such situations is to compute an array of the already-visited values. For example, consider the following query that searches a tablegraph
using alink
field:
WITH RECURSIVE search_graph(id, link, data, depth) AS ( SELECT g.id, g.link, g.data, 1 FROM graph g UNION ALL SELECT g.id, g.link, g.data, sg.depth + 1 FROM graph g, search_graph sg WHERE g.id = sg.link)SELECT * FROM search_graph;
This query will loop if thelink
relationships contain cycles. Because we require a“depth” output, just changingUNION ALL
toUNION
would not eliminate the looping. Instead we need to recognize whether we have reached the same row again while following a particular path of links. We add two columnspath
andcycle
to the loop-prone query:
WITH RECURSIVE search_graph(id, link, data, depth, path, cycle) AS ( SELECT g.id, g.link, g.data, 1, ARRAY[g.id], false FROM graph g UNION ALL SELECT g.id, g.link, g.data, sg.depth + 1, path || g.id, g.id = ANY(path) FROM graph g, search_graph sg WHERE g.id = sg.link AND NOT cycle)SELECT * FROM search_graph;
Aside from preventing cycles, the array value is often useful in its own right as representing the“path” taken to reach any particular row.
In the general case where more than one field needs to be checked to recognize a cycle, use an array of rows. For example, if we needed to compare fieldsf1
andf2
:
WITH RECURSIVE search_graph(id, link, data, depth, path, cycle) AS ( SELECT g.id, g.link, g.data, 1, ARRAY[ROW(g.f1, g.f2)], false FROM graph g UNION ALL SELECT g.id, g.link, g.data, sg.depth + 1, path || ROW(g.f1, g.f2), ROW(g.f1, g.f2) = ANY(path) FROM graph g, search_graph sg WHERE g.id = sg.link AND NOT cycle)SELECT * FROM search_graph;
Tip
Omit theROW()
syntax in the common case where only one field needs to be checked to recognize a cycle. This allows a simple array rather than a composite-type array to be used, gaining efficiency.
Tip
The recursive query evaluation algorithm produces its output in breadth-first search order. You can display the results in depth-first search order by making the outer queryORDER BY
a“path” column constructed in this way.
A helpful trick for testing queries when you are not certain if they might loop is to place aLIMIT
in the parent query. For example, this query would loop forever without theLIMIT
:
WITH RECURSIVE t(n) AS ( SELECT 1 UNION ALL SELECT n+1 FROM t)SELECT n FROM t LIMIT 100;
This works becausePostgres Pro's implementation evaluates only as many rows of aWITH
query as are actually fetched by the parent query. Using this trick in production is not recommended, because other systems might work differently. Also, it usually won't work if you make the outer query sort the recursive query's results or join them to some other table, because in such cases the outer query will usually try to fetch all of theWITH
query's output anyway.
A useful property ofWITH
queries is that they are evaluated only once per execution of the parent query, even if they are referred to more than once by the parent query or siblingWITH
queries. Thus, expensive calculations that are needed in multiple places can be placed within aWITH
query to avoid redundant work. Another possible application is to prevent unwanted multiple evaluations of functions with side-effects. However, the other side of this coin is that the optimizer is less able to push restrictions from the parent query down into aWITH
query than an ordinary subquery. TheWITH
query will generally be evaluated as written, without suppression of rows that the parent query might discard afterwards. (But, as mentioned above, evaluation might stop early if the reference(s) to the query demand only a limited number of rows.)
The examples above only showWITH
being used withSELECT
, but it can be attached in the same way toINSERT
,UPDATE
, orDELETE
. In each case it effectively provides temporary table(s) that can be referred to in the main command.
7.8.2. Data-Modifying Statements inWITH
You can use data-modifying statements (INSERT
,UPDATE
, orDELETE
) inWITH
. This allows you to perform several different operations in the same query. An example is:
WITH moved_rows AS ( DELETE FROM products WHERE "date" >= '2010-10-01' AND "date" < '2010-11-01' RETURNING *)INSERT INTO products_logSELECT * FROM moved_rows;
This query effectively moves rows fromproducts
toproducts_log
. TheDELETE
inWITH
deletes the specified rows fromproducts
, returning their contents by means of itsRETURNING
clause; and then the primary query reads that output and inserts it intoproducts_log
.
A fine point of the above example is that theWITH
clause is attached to theINSERT
, not the sub-SELECT
within theINSERT
. This is necessary because data-modifying statements are only allowed inWITH
clauses that are attached to the top-level statement. However, normalWITH
visibility rules apply, so it is possible to refer to theWITH
statement's output from the sub-SELECT
.
Data-modifying statements inWITH
usually haveRETURNING
clauses (seeSection 6.4), as shown in the example above. It is the output of theRETURNING
clause,not the target table of the data-modifying statement, that forms the temporary table that can be referred to by the rest of the query. If a data-modifying statement inWITH
lacks aRETURNING
clause, then it forms no temporary table and cannot be referred to in the rest of the query. Such a statement will be executed nonetheless. A not-particularly-useful example is:
WITH t AS ( DELETE FROM foo)DELETE FROM bar;
This example would remove all rows from tablesfoo
andbar
. The number of affected rows reported to the client would only include rows removed frombar
.
Recursive self-references in data-modifying statements are not allowed. In some cases it is possible to work around this limitation by referring to the output of a recursiveWITH
, for example:
WITH RECURSIVE included_parts(sub_part, part) AS ( SELECT sub_part, part FROM parts WHERE part = 'our_product' UNION ALL SELECT p.sub_part, p.part FROM included_parts pr, parts p WHERE p.part = pr.sub_part)DELETE FROM parts WHERE part IN (SELECT part FROM included_parts);
This query would remove all direct and indirect subparts of a product.
Data-modifying statements inWITH
are executed exactly once, and always to completion, independently of whether the primary query reads all (or indeed any) of their output. Notice that this is different from the rule forSELECT
inWITH
: as stated in the previous section, execution of aSELECT
is carried only as far as the primary query demands its output.
The sub-statements inWITH
are executed concurrently with each other and with the main query. Therefore, when using data-modifying statements inWITH
, the order in which the specified updates actually happen is unpredictable. All the statements are executed with the samesnapshot (seeChapter 13), so they cannot“see” one another's effects on the target tables. This alleviates the effects of the unpredictability of the actual order of row updates, and means thatRETURNING
data is the only way to communicate changes between differentWITH
sub-statements and the main query. An example of this is that in
WITH t AS ( UPDATE products SET price = price * 1.05 RETURNING *)SELECT * FROM products;
the outerSELECT
would return the original prices before the action of theUPDATE
, while in
WITH t AS ( UPDATE products SET price = price * 1.05 RETURNING *)SELECT * FROM t;
the outerSELECT
would return the updated data.
Trying to update the same row twice in a single statement is not supported. Only one of the modifications takes place, but it is not easy (and sometimes not possible) to reliably predict which one. This also applies to deleting a row that was already updated in the same statement: only the update is performed. Therefore you should generally avoid trying to modify a single row twice in a single statement. In particular avoid writingWITH
sub-statements that could affect the same rows changed by the main statement or a sibling sub-statement. The effects of such a statement will not be predictable.
At present, any table used as the target of a data-modifying statement inWITH
must not have a conditional rule, nor anALSO
rule, nor anINSTEAD
rule that expands to multiple statements.