Description

UPDATE changes the values of the specified columns in all rows that satisfy the condition. Only the columns to be modified need be mentioned in the SET clause; columns not explicitly modified retain their previous values.

There are two ways to modify a table using information contained in other tables in the database: using sub-selects, or specifying additional tables in the FROM clause. Which technique is more appropriate depends on the specific circumstances.

The optional RETURNING clause causes UPDATE to compute and return value(s) based on each row actually updated. Any expression using the table's columns, and/or columns of other tables mentioned in FROM, can be computed. By default, the new (post-update) values of the table's columns are used, but it is also possible to request the old (pre-update) values. The syntax of the RETURNING list is identical to that of the output list of SELECT.

You must have the UPDATE privilege on the table, or at least on the column(s) that are listed to be updated. You must also have the SELECT privilege on any column whose values are read in the expressions or condition.

Parameters

Outputs

On successful completion, an UPDATE command returns a command tag of the form

UPDATE count

The count is the number of rows updated, including matched rows whose values did not change. Note that the number may be less than the number of rows that matched the condition when updates were suppressed by a BEFORE UPDATE trigger. If count is 0, no rows were updated by the query (this is not considered an error).

If the UPDATE command contains a RETURNING clause, the result will be similar to that of a SELECT statement containing the columns and values defined in the RETURNING list, computed over the row(s) updated by the command.

Notes

When a FROM clause is present, what essentially happens is that the target table is joined to the tables mentioned in the from_item list, and each output row of the join represents an update operation for the target table. When using FROM you should ensure that the join produces at most one output row for each row to be modified. In other words, a target row shouldn't join to more than one row from the other table(s). If it does, then only one of the join rows will be used to update the target row, but which one will be used is not readily predictable.

Because of this indeterminacy, referencing other tables only within sub-selects is safer, though often harder to read and slower than using a join.

In the case of a partitioned table, updating a row might cause it to no longer satisfy the partition constraint of the containing partition. In that case, if there is some other partition in the partition tree for which this row satisfies its partition constraint, then the row is moved to that partition. If there is no such partition, an error will occur. Behind the scenes, the row movement is actually a DELETE and INSERT operation.

There is a possibility that a concurrent UPDATE or DELETE on the row being moved will get a serialization failure error. Suppose session 1 is performing an UPDATE on a partition key, and meanwhile a concurrent session 2 for which this row is visible performs an UPDATE or DELETE operation on this row. In such case, session 2's UPDATE or DELETE will detect the row movement and raise a serialization failure error (which always returns with an SQLSTATE code '40001'). Applications may wish to retry the transaction if this occurs. In the usual case where the table is not partitioned, or where there is no row movement, session 2 would have identified the newly updated row and carried out the UPDATE/DELETE on this new row version.

Note that while rows can be moved from local partitions to a foreign-table partition (provided the foreign data wrapper supports tuple routing), they cannot be moved from a foreign-table partition to another partition.

An attempt of moving a row from one partition to another will fail if a foreign key is found to directly reference an ancestor of the source partition that is not the same as the ancestor that's mentioned in the UPDATE query.

Examples

Change the word Drama to Dramatic in the column kind of the table films:

UPDATE films SET kind = 'Dramatic' WHERE kind = 'Drama';

Adjust temperature entries and reset precipitation to its default value in one row of the table weather:

UPDATE weather SET temp_lo = temp_lo+1, temp_hi = temp_lo+15, prcp = DEFAULT
  WHERE city = 'San Francisco' AND date = '2003-07-03';

Perform the same operation and return the updated entries, and the old precipitation value:

UPDATE weather SET temp_lo = temp_lo+1, temp_hi = temp_lo+15, prcp = DEFAULT
  WHERE city = 'San Francisco' AND date = '2003-07-03'
  RETURNING temp_lo, temp_hi, prcp, old.prcp AS old_prcp;

Use the alternative column-list syntax to do the same update:

UPDATE weather SET (temp_lo, temp_hi, prcp) = (temp_lo+1, temp_lo+15, DEFAULT)
  WHERE city = 'San Francisco' AND date = '2003-07-03';

Increment the sales count of the salesperson who manages the account for Acme Corporation, using the FROM clause syntax:

UPDATE employees SET sales_count = sales_count + 1 FROM accounts
  WHERE accounts.name = 'Acme Corporation'
  AND employees.id = accounts.sales_person;

Perform the same operation, using a sub-select in the WHERE clause:

UPDATE employees SET sales_count = sales_count + 1 WHERE id =
  (SELECT sales_person FROM accounts WHERE name = 'Acme Corporation');

Update contact names in an accounts table to match the currently assigned salespeople:

UPDATE accounts SET (contact_first_name, contact_last_name) =
    (SELECT first_name, last_name FROM employees
     WHERE employees.id = accounts.sales_person);

A similar result could be accomplished with a join:

UPDATE accounts SET contact_first_name = first_name,
                    contact_last_name = last_name
  FROM employees WHERE employees.id = accounts.sales_person;

However, the second query may give unexpected results if employees.id is not a unique key, whereas the first query is guaranteed to raise an error if there are multiple id matches. Also, if there is no match for a particular accounts.sales_person entry, the first query will set the corresponding name fields to NULL, whereas the second query will not update that row at all.

Update statistics in a summary table to match the current data:

UPDATE summary s SET (sum_x, sum_y, avg_x, avg_y) =
    (SELECT sum(x), sum(y), avg(x), avg(y) FROM data d
     WHERE d.group_id = s.group_id);

Attempt to insert a new stock item along with the quantity of stock. If the item already exists, instead update the stock count of the existing item. To do this without failing the entire transaction, use savepoints:

BEGIN;
-- other operations
SAVEPOINT sp1;
INSERT INTO wines VALUES('Chateau Lafite 2003', '24');
-- Assume the above fails because of a unique key violation,
-- so now we issue these commands:
ROLLBACK TO sp1;
UPDATE wines SET stock = stock + 24 WHERE winename = 'Chateau Lafite 2003';
-- continue with other operations, and eventually
COMMIT;

Change the kind column of the table films in the row on which the cursor c_films is currently positioned:

UPDATE films SET kind = 'Dramatic' WHERE CURRENT OF c_films;

Updates affecting many rows can have negative effects on system performance, such as table bloat, increased replica lag, and increased lock contention. In such situations it can make sense to perform the operation in smaller batches, possibly with a VACUUM operation on the table between batches. While there is no LIMIT clause for UPDATE, it is possible to get a similar effect through the use of a Common Table Expression and a self-join. With the standard PostgreSQL table access method, a self-join on the system column ctid is very efficient:

WITH exceeded_max_retries AS (
  SELECT w.ctid FROM work_item AS w
    WHERE w.status = 'active' AND w.num_retries > 10
    ORDER BY w.retry_timestamp
    FOR UPDATE
    LIMIT 5000
)
UPDATE work_item SET status = 'failed'
  FROM exceeded_max_retries AS emr
  WHERE work_item.ctid = emr.ctid;

This command will need to be repeated until no rows remain to be updated. Use of an ORDER BY clause allows the command to prioritize which rows will be updated; it can also prevent deadlock with other update operations if they use the same ordering. If lock contention is a concern, then SKIP LOCKED can be added to the CTE to prevent multiple commands from updating the same row. However, then a final UPDATE without SKIP LOCKED or LIMIT will be needed to ensure that no matching rows were overlooked.

Compatibility

This command conforms to the SQL standard, except that the FROM and RETURNING clauses are PostgreSQL extensions, as is the ability to use WITH with UPDATE.

Some other database systems offer a FROM option in which the target table is supposed to be listed again within FROM. That is not how PostgreSQL interprets FROM. Be careful when porting applications that use this extension.

According to the standard, the source value for a parenthesized sub-list of target column names can be any row-valued expression yielding the correct number of columns. PostgreSQL only allows the source value to be a row constructor or a sub-SELECT. An individual column's updated value can be specified as DEFAULT in the row-constructor case, but not inside a sub-SELECT.