![]() ![]() 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. Sometimes, using UNION instead of UNION ALL can accomplish this by discarding rows that duplicate previous output rows. 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. That column will implicitly be added to the output rows of the CTE. ![]() The SEARCH clause specifies whether depth- or breadth first search is wanted, the list of columns to track for sorting, and a column name that will contain the result data that can be used for sorting. This syntax is internally expanded to something similar to the above hand-written forms. ) SEARCH BREADTH FIRST BY id SET ordercol SELECT * FROM search_tree ORDER BY ordercol There is built-in syntax to compute a depth- or breadth-first sort column. The order of the rows within each level is certainly undefined, so some explicit ordering might be desired in any case. However, this is an implementation detail and it is perhaps unsound to rely on it. The recursive query evaluation algorithm produces its output in breadth-first search order. SELECT t.id, t.link, t.data, path || ROW(t.f1, t.f2) For example, if we needed to track fields f1 and f2: In the general case where more than one field needs to be used to identify a row, use an array of rows. ![]() SELECT t.id, t.link, t.data, path || t.id WITH RECURSIVE search_tree(id, link, data, path) AS ( To add depth-first ordering information, you can write this: WITH RECURSIVE search_tree(id, link, data) AS ( For example, consider the following query that searches a table tree using a link field: To create a depth-first order, we compute for each result row an array of rows that we have visited so far. This approach merely provides a convenient way to order the results afterwards. Note that this does not actually control in which order the query evaluation visits the rows that is as always in SQL implementation-dependent. This can be done by computing an ordering column alongside the other data columns and using that to sort the results at the end. Refer to the manual on UPDATE for details.When computing a tree traversal using a recursive query, you might want to order the results in either depth-first or breadth-first order. If you want different values to be used for different rows of C, you'll have to join the 3 tables (using JOIN - ON and WHERE) It then uses the values from that arbitrary row to update all rows of table C. without any joining condition) and then choosing an arbitrary row ( LIMIT 1 without ORDER BY). Your derived table is cross joining A and B (i.e. Ypercube already gave a basic explanation in his comment (now removed): The last WHERE clause is optional to avoid empty updates that would not change anything (but still write a new row version at full cost). (A.column1, B.column2, A.column1 + B.column2) WHERE C.id = A.id - ? not specified in question!ĪND (C.column1, C.column2, C.column3) IS DISTINCT FROM JOIN B ON A.id = B.id - ? not specified in question! The proper form would be (assuming current pg version 9.3 for lack of information): UPDATE C ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |