Is this possible? I\'m interested in finding out which columns were specified in the UPDATE
request regardless of the fact that the new value that is being sent
I have obtained another solution to similar problem almost naturally, because my table contained a column with semantics of 'last update timestamp' (lets call it UPDT).
So, I decided to include new values of source and UPDT in any update only at once (or none of them). Since UPDT is intended to change on every update, with such a policy one can use condition new.UPDT = old.UPDT
to deduce that no source was specified with current update and substitute the default one.
If one already has 'last update timestamp' column in his table, this solution will be simpler, than creating three triggers. Not sure if it is better idea to create UPDT, when it is not needed already. If updates are so frequent that there is risk of timestamp similarity, a sequencer can be used instead of timestamp.
If a "source" doesn't "send an identifier", the column will be unchanged. Then you cannot detect whether the current UPDATE
was done by the same source as the last one or by a source that did not change the column at all. In other words: this does not work properly.
If the "source" is identifiable by any session information function, you can work with that. Like:
NEW.column = session_user;
Unconditionally for every update.
I found a way how to solve the original problem. The column will be set to a default value in any update where the column is not updated (not in the SET
list of the UPDATE
).
Key element is a per-column trigger introduced in PostgreSQL 9.0 - a column-specific trigger using the UPDATE OF
column_name
clause.
The trigger will only fire if at least one of the listed columns is mentioned as a target of the
UPDATE
command.
That's the only simple way I found to distinguish whether a column was updated with a new value identical to the old, versus not updated at all.
One could also parse the text returned by current_query(). But that seems tricky and unreliable.
I assume a column col
defined NOT NULL
.
Step 1: Set col
to NULL
if unchanged:
CREATE OR REPLACE FUNCTION trg_tbl_upbef_step1()
RETURNS trigger AS
$func$
BEGIN
IF OLD.col = NEW.col THEN
NEW.col := NULL; -- "impossible" value
END IF;
RETURN NEW;
END
$func$ LANGUAGE plpgsql;
Step 2: Revert to old value. Trigger will only be fired, if the value was actually updated (see below):
CREATE OR REPLACE FUNCTION trg_tbl_upbef_step2()
RETURNS trigger AS
$func$
BEGIN
IF NEW.col IS NULL THEN
NEW.col := OLD.col;
END IF;
RETURN NEW;
END
$func$ LANGUAGE plpgsql;
Step 3: Now we can identify the lacking update and set a default value instead:
CREATE OR REPLACE FUNCTION trg_tbl_upbef_step3()
RETURNS trigger AS
$func$
BEGIN
IF NEW.col IS NULL THEN
NEW.col := 'default value';
END IF;
RETURN NEW;
END
$func$ LANGUAGE plpgsql;
The trigger for Step 2 is fired per column!
CREATE TRIGGER upbef_step1
BEFORE UPDATE ON tbl
FOR EACH ROW
EXECUTE PROCEDURE trg_tbl_upbef_step1();
CREATE TRIGGER upbef_step2
BEFORE UPDATE OF col ON tbl -- key element!
FOR EACH ROW
EXECUTE PROCEDURE trg_tbl_upbef_step2();
CREATE TRIGGER upbef_step3
BEFORE UPDATE ON tbl
FOR EACH ROW
EXECUTE PROCEDURE trg_tbl_upbef_step3();
Trigger names are relevant, because they are fired in alphabetical order (all being BEFORE UPDATE
)!
The procedure could be simplified with something like "per-not-column triggers" or any other way to check the target-list of an UPDATE
in a trigger. But I see no handle for this.
If col
can be NULL
, use any other "impossible" intermediate value and check for NULL
additionally in trigger function 1:
IF OLD.col IS NOT DISTINCT FROM NEW.col THEN
NEW.col := '#impossible_value#';
END IF;
Adapt the rest accordingly.
In plpgsql you could do something like this in your trigger function:
IF NEW.column IS NULL THEN
NEW.column = 'default value';
END IF;
Another way is to exploit JSON/JSONB functions that come in recent versions of PostgreSQL. It has the advantage of working both with anything that can be converted to a JSON object (rows or any other structured data), and you don't even need to know the record type.
To find the differences between any two rows/records, you can use this little hack:
SELECT pre.key AS columname, pre.value AS prevalue, post.value AS postvalue
FROM jsonb_each(to_jsonb(OLD)) AS pre
CROSS JOIN jsonb_each(to_json(NEW)) AS post
WHERE pre.key = post.key AND pre.value IS DISTINCT FROM post.value
Where OLD
and NEW
are the built-in records found in trigger functions representing the pre and after state respectively of the changed record. Note that I have used the table aliases pre
and post
instead of old
and new
to avoid collision with the OLD and NEW built-in objects. Note also the use of IS DISTINCT FROM
instead of a simple !=
or <>
to handle NULL
values appropriately.
Of course, this will also work with any ROW constructor such as ROW(1,2,3,...)
or its short-hand (1,2,3,...)
. It will also work with any two JSONB objects that have the same keys.
For example, consider an example with two rows (already converted to JSONB for the purposes of the example):
SELECT pre.key AS columname, pre.value AS prevalue, post.value AS postvalue
FROM jsonb_each('{"col1": "same", "col2": "prediff", "col3": 1, "col4": false}') AS pre
CROSS JOIN jsonb_each('{"col1": "same", "col2": "postdiff", "col3": 1, "col4": true}') AS post
WHERE pre.key = post.key AND pre.value IS DISTINCT FROM post.value
The query will show the columns that have changed values:
columname | prevalue | postvalue
-----------+-----------+------------
col2 | "prediff" | "postdiff"
col4 | false | true
The cool thing about this approach is that it is trivial to filter by column. For example, imagine you ONLY want to detect changes in columns col1
and col2
:
SELECT pre.key AS columname, pre.value AS prevalue, post.value AS postvalue
FROM jsonb_each('{"col1": "same", "col2": "prediff", "col3": 1, "col4": false}') AS pre
CROSS JOIN jsonb_each('{"col1": "same", "col2": "postdiff", "col3": 1, "col4": true}') AS post
WHERE pre.key = post.key AND pre.value IS DISTINCT FROM post.value
AND pre.key IN ('col1', 'col2')
The new results will exclude col3
from the results even if it's value has changed:
columname | prevalue | postvalue
-----------+-----------+------------
col2 | "prediff" | "postdiff"
It is easy to see how this approach can be extended in many ways. For example, say you want to throw an exception if certain columns are updated. You can achieve this with a universal trigger function, that is, one that can be applied to any/all tables, without having to know the table type:
CREATE OR REPLACE FUNCTION yourschema.yourtriggerfunction()
RETURNS TRIGGER AS
$$
DECLARE
immutable_cols TEXT[] := ARRAY['createdon', 'createdby'];
BEGIN
IF TG_OP = 'UPDATE' AND EXISTS(
SELECT 1
FROM jsonb_each(to_jsonb(OLD)) AS pre, jsonb_each(to_jsonb(NEW)) AS post
WHERE pre.key = post.key AND pre.value IS DISTINCT FROM post.value
AND pre.key = ANY(immutable_cols)
) THEN
RAISE EXCEPTION 'Error 12345 updating table %.%. Cannot alter these immutable cols: %.',
TG_TABLE_SCHEMA, TG_TABLE_NAME, immutable_cols;
END IF;
END
$$
LANGUAGE plpgsql VOLATILE
You would then register the above trigger function to any and all tables you want to control via:
CREATE TRIGGER yourtiggername
BEFORE UPDATE ON yourschema.yourtable
FOR EACH ROW EXECUTE PROCEDURE yourschema.yourtriggerfunction();