I'm trying to understand how to lock a row, and only release that lock later.
I have a table like this :
create table testTable (Name varchar(100));
Some test data
insert into testTable (name) select 'Bob';
insert into testTable (name) select 'John';
insert into testTable (name) select 'Steve';
Now, I want to select one of those rows, and prevent other other queries from seeing this row. I achieve that like this :
begin transaction;
select * from testTable where name = 'Bob' for update;
In another window, I do this :
select * from testTable for update skip locked;
Great, I don't see 'Bob' in that result set. Now, I want to do something with the primary retrieved row (Bob), and after I did my work, I want to release that row again. Simple answer would be to do :
commit transaction
However, I am running multiple transactions on the same connection, so I can't just begin and commit transactions all over the show. Ideally I would like to have a "named" transaction, something like :
begin transaction 'myTransaction';
select * from testTable where name = 'Bob' for update;
//do stuff with the data, outside sql then later call ...
commit transaction 'myTransaction';
But postgres doesn't support that. I have found "prepare transaction", but that seems to be a pear-shaped path I don't want to go down, especially as these transaction seem to persist through restarts even.
Is there anyway I can have a reference to commit/rollback for a specific transaction?
You can have only one transaction in a database session, so the question as such is moot.
But I assume that you do not really want to run a transaction, you want to block access to a certain row for a while.
It is usually not a good idea to use regular database locks for such a purpose (the exception are advisory locks, which serve exactly that purpose, but are not tied to table rows). The problem is that long database transactions keep autovacuum from doing its job.
I recommend that you add a status column to the table and change the status rather than locking the row. That would server the same purpose in a more natural fashion and make your problem go away.
If you are concerned that the status flag might not get cleared due to application logic problems, replace it with a visible_from column of type timestamp with time zone that initially contains -infinity. Instead of locking the row, set the value to current_timestamp + INTERVAL '5 minutes'. Only select rows that fulfill WHERE visible_from < current_timestamp. That way the “lock” will automatically expire after 5 minutes.
I would like to lock a table for writing during a period of time, while leaving it available for reading.
Is that possible ?
Ideally I would like to lock the table with a predicate (for example prevent writing rows "where country = france").
If you really want to lock against such inserts, i.e. the query should hang and only continue when you allow it, you would have to place a SHARE lock on the table and keep the transaction open.
This is usually not a good idea.
If you want to prevent any such inserts, i.e. throw an error when such an insert is attempted, create a BEFORE INSERT trigger that throws an exception if the NEW row satisfies the condition.
You can use FOR SHARE lock, which blocks other transactions from performing like UPDATE and DELETE, while allowing SELECT FOR SHARE. (Read the docs for details: https://www.postgresql.org/docs/9.4/explicit-locking.html [13.3.2])
For example, there are 2 processes accessing table user_table, in the following sequence:
Process A: BEGIN;
Process A: SELECT username FROM user_table WHERE country = france FOR SHARE;
Process B: SELECT * FROM user_table FOR SHARE; (In here, process B can still read all the rows of the table)
Process B: UPDATE user_table SET username = 'test' WHERE country = france; (In here, process B is blocked and is waiting for process A to finish its transaction)
Trying to support PostgreSQL DB in my application, found this strange behaviour.
Preparation:
CREATE TABLE test(id INTEGER, flag BOOLEAN);
INSERT INTO test(id, flag) VALUES (1, true);
Assume two concurrent transactions (Autocommit=false, READ_COMMITTED) TX1 and TX2:
TX1:
UPDATE test SET flag = FALSE WHERE id = 1;
INSERT INTO test(id, flag) VALUES (2, TRUE);
-- (wait, no COMMIT yet)
TX2:
SELECT id FROM test WHERE flag=true FOR UPDATE;
-- waits for TX1 to release lock
Now, if I COMMIT in TX1, the SELECT in TX2 returns empty cursor.
It is strange to me, because same experiment in Oracle and MariaDB results in selecting newly created row (id=2).
I could not find anything about this behaviour in PG documentation.
Am I missing something?
Is there any way to force PG server to "refresh" statement visibility after acquiring lock?
PS: PostgreSQL version 11.1
TX2 scans the table and tries to lock the results.
The scan sees the snapshot of the database from the start of the query, so it cannot see any rows that were inserted (or made eligible in some other way) by concurrent modifications that started after that snapshot was taken.
That is why you cannot see the row with the id 2.
For id 1, that is also true, so the scan finds that row. But the query has to wait until the lock is released. When that finally happens, it fetches that latest committed version of the row and performs the check again, so that row is excluded as well.
This “EvalPlanQual” recheck (to use PostgreSQL jargon) is only performed for rows that were found during the scan, but were locked. The second row isn't even found during the scan, so no such processing happens there.
This is a bit odd, admitted. But it is not a bug, it is just the way PostgreSQL wirks.
If you want to avoid such anomalies, use the REPEATABLE READ isolation level. Then you will get a serialization error in such a case and can retry the transaction, thus avoiding inconsistencies like that.
I have big stored procedures that handle user actions.
They consist of multiple select statements. These are filtered, most of the times only getting one row. The Selects are copied into temptables or otherwise evaluated.
Finally, a merge-Statement does the needed changes in the DB.
All is encapsulated in a transaction.
I have concurrent input from users, and the selected rows of the select statements should be locked to keep data integrity.
How can I lock the selected Rows of all select statements, so that they aren't updated through other transactions while the current transaction is in process?
Does a table hint combination of ROWLOCK and HOLDLOCK work in a way that only the selected rows are locked, or are the whole tables locked because of the HOLDLOCK?
SELECT *
FROM dbo.Test
WITH (ROWLOCK HOLDLOCK )
WHERE id = #testId
Can I instead use
SET TRANSACTION ISOLATION LEVEL SERIALIZABLE;
right after the start of the transaction? Or does this lock the whole tables?
I am using SQL2008 R2, but would also be interested if things work differently in SQL2012.
PS: I just read about the table hints UPDLOCK and SERIALIZE. UPDLOCK seems to be a solution to lock only one row, and it seems as if UPDLOCK always locks instead of ROWLOCK, which does only specify that locks are row based IF locks are applied. I am still confused about the best way to solve this...
Changing the isolation level fixed the problem (and locked on row level):
SET TRANSACTION ISOLATION LEVEL SERIALIZABLE;
Here is how I tested it.
I created a statement in a blank page of the SQL Management Studio:
begin tran
select
*
into #message
from dbo.MessageBody
where MessageBody.headerId = 28
WAITFOR DELAY '0:00:05'
update dbo.MessageBody set [message] = 'message1'
where headerId = (select headerId from #message)
select * from dbo.MessageBody where headerId = (select headerId from #message)
drop table #message
commit tran
While executing this statement (which takes at last 5 seconds due to the delay), I called the second query in another window:
begin tran
select
*
into #message
from dbo.MessageBody
where MessageBody.headerId = 28
update dbo.MessageBody set [message] = 'message2'
where headerId = (select headerId from #message)
select * from dbo.MessageBody where headerId = (select headerId from #message)
drop table #message
commit tran
and I was rather surprised that it executed instantaneously. This was due to the default SQL Server transaction level "Read Commited" http://technet.microsoft.com/en-us/library/ms173763.aspx . Since the update of the first script is done after the delay, during the second script there are no umcommited changes yet, so the row 28 is read and updated.
Changing the Isolation level to Serialization prevented this, but it also prevented concurrency - both scipts were executed consecutively.
That was OK, since both scripts read and changed the same row (via headerId=28). Changing headerId to another value in the second script, the statements were executed parallel. So the lock from SERIALIZATION seems to be on row level.
Adding the table hint
WITH ( SERIALIZABLE)
in the first select of the first statement does also prevent further reads oth the selected row.
I want to do a large update on a table in PostgreSQL, but I don't need the transactional integrity to be maintained across the entire operation, because I know that the column I'm changing is not going to be written to or read during the update. I want to know if there is an easy way in the psql console to make these types of operations faster.
For example, let's say I have a table called "orders" with 35 million rows, and I want to do this:
UPDATE orders SET status = null;
To avoid being diverted to an offtopic discussion, let's assume that all the values of status for the 35 million columns are currently set to the same (non-null) value, thus rendering an index useless.
The problem with this statement is that it takes a very long time to go into effect (solely because of the locking), and all changed rows are locked until the entire update is complete. This update might take 5 hours, whereas something like
UPDATE orders SET status = null WHERE (order_id > 0 and order_id < 1000000);
might take 1 minute. Over 35 million rows, doing the above and breaking it into chunks of 35 would only take 35 minutes and save me 4 hours and 25 minutes.
I could break it down even further with a script (using pseudocode here):
for (i = 0 to 3500) {
db_operation ("UPDATE orders SET status = null
WHERE (order_id >" + (i*1000)"
+ " AND order_id <" + ((i+1)*1000) " + ")");
}
This operation might complete in only a few minutes, rather than 35.
So that comes down to what I'm really asking. I don't want to write a freaking script to break down operations every single time I want to do a big one-time update like this. Is there a way to accomplish what I want entirely within SQL?
Column / Row
... I don't need the transactional integrity to be maintained across
the entire operation, because I know that the column I'm changing is
not going to be written to or read during the update.
Any UPDATE in PostgreSQL's MVCC model writes a new version of the whole row. If concurrent transactions change any column of the same row, time-consuming concurrency issues arise. Details in the manual. Knowing the same column won't be touched by concurrent transactions avoids some possible complications, but not others.
Index
To avoid being diverted to an offtopic discussion, let's assume that
all the values of status for the 35 million columns are currently set
to the same (non-null) value, thus rendering an index useless.
When updating the whole table (or major parts of it) Postgres never uses an index. A sequential scan is faster when all or most rows have to be read. On the contrary: Index maintenance means additional cost for the UPDATE.
Performance
For example, let's say I have a table called "orders" with 35 million
rows, and I want to do this:
UPDATE orders SET status = null;
I understand you are aiming for a more general solution (see below). But to address the actual question asked: This can be dealt with in a matter milliseconds, regardless of table size:
ALTER TABLE orders DROP column status
, ADD column status text;
The manual (up to Postgres 10):
When a column is added with ADD COLUMN, all existing rows in the table
are initialized with the column's default value (NULL if no DEFAULT
clause is specified). If there is no DEFAULT clause, this is merely a metadata change [...]
The manual (since Postgres 11):
When a column is added with ADD COLUMN and a non-volatile DEFAULT
is specified, the default is evaluated at the time of the statement
and the result stored in the table's metadata. That value will be used
for the column for all existing rows. If no DEFAULT is specified,
NULL is used. In neither case is a rewrite of the table required.
Adding a column with a volatile DEFAULT or changing the type of an
existing column will require the entire table and its indexes to be
rewritten. [...]
And:
The DROP COLUMN form does not physically remove the column, but
simply makes it invisible to SQL operations. Subsequent insert and
update operations in the table will store a null value for the column.
Thus, dropping a column is quick but it will not immediately reduce
the on-disk size of your table, as the space occupied by the dropped
column is not reclaimed. The space will be reclaimed over time as
existing rows are updated.
Make sure you don't have objects depending on the column (foreign key constraints, indices, views, ...). You would need to drop / recreate those. Barring that, tiny operations on the system catalog table pg_attribute do the job. Requires an exclusive lock on the table which may be a problem for heavy concurrent load. (Like Buurman emphasizes in his comment.) Baring that, the operation is a matter of milliseconds.
If you have a column default you want to keep, add it back in a separate command. Doing it in the same command applies it to all rows immediately. See:
Add new column without table lock?
To actually apply the default, consider doing it in batches:
Does PostgreSQL optimize adding columns with non-NULL DEFAULTs?
General solution
dblink has been mentioned in another answer. It allows access to "remote" Postgres databases in implicit separate connections. The "remote" database can be the current one, thereby achieving "autonomous transactions": what the function writes in the "remote" db is committed and can't be rolled back.
This allows to run a single function that updates a big table in smaller parts and each part is committed separately. Avoids building up transaction overhead for very big numbers of rows and, more importantly, releases locks after each part. This allows concurrent operations to proceed without much delay and makes deadlocks less likely.
If you don't have concurrent access, this is hardly useful - except to avoid ROLLBACK after an exception. Also consider SAVEPOINT for that case.
Disclaimer
First of all, lots of small transactions are actually more expensive. This only makes sense for big tables. The sweet spot depends on many factors.
If you are not sure what you are doing: a single transaction is the safe method. For this to work properly, concurrent operations on the table have to play along. For instance: concurrent writes can move a row to a partition that's supposedly already processed. Or concurrent reads can see inconsistent intermediary states. You have been warned.
Step-by-step instructions
The additional module dblink needs to be installed first:
How to use (install) dblink in PostgreSQL?
Setting up the connection with dblink very much depends on the setup of your DB cluster and security policies in place. It can be tricky. Related later answer with more how to connect with dblink:
Persistent inserts in a UDF even if the function aborts
Create a FOREIGN SERVER and a USER MAPPING as instructed there to simplify and streamline the connection (unless you have one already).
Assuming a serial PRIMARY KEY with or without some gaps.
CREATE OR REPLACE FUNCTION f_update_in_steps()
RETURNS void AS
$func$
DECLARE
_step int; -- size of step
_cur int; -- current ID (starting with minimum)
_max int; -- maximum ID
BEGIN
SELECT INTO _cur, _max min(order_id), max(order_id) FROM orders;
-- 100 slices (steps) hard coded
_step := ((_max - _cur) / 100) + 1; -- rounded, possibly a bit too small
-- +1 to avoid endless loop for 0
PERFORM dblink_connect('myserver'); -- your foreign server as instructed above
FOR i IN 0..200 LOOP -- 200 >> 100 to make sure we exceed _max
PERFORM dblink_exec(
$$UPDATE public.orders
SET status = 'foo'
WHERE order_id >= $$ || _cur || $$
AND order_id < $$ || _cur + _step || $$
AND status IS DISTINCT FROM 'foo'$$); -- avoid empty update
_cur := _cur + _step;
EXIT WHEN _cur > _max; -- stop when done (never loop till 200)
END LOOP;
PERFORM dblink_disconnect();
END
$func$ LANGUAGE plpgsql;
Call:
SELECT f_update_in_steps();
You can parameterize any part according to your needs: the table name, column name, value, ... just be sure to sanitize identifiers to avoid SQL injection:
Table name as a PostgreSQL function parameter
Avoid empty UPDATEs:
How do I (or can I) SELECT DISTINCT on multiple columns?
Postgres uses MVCC (multi-version concurrency control), thus avoiding any locking if you are the only writer; any number of concurrent readers can work on the table, and there won't be any locking.
So if it really takes 5h, it must be for a different reason (e.g. that you do have concurrent writes, contrary to your claim that you don't).
You should delegate this column to another table like this:
create table order_status (
order_id int not null references orders(order_id) primary key,
status int not null
);
Then your operation of setting status=NULL will be instant:
truncate order_status;
First of all - are you sure that you need to update all rows?
Perhaps some of the rows already have status NULL?
If so, then:
UPDATE orders SET status = null WHERE status is not null;
As for partitioning the change - that's not possible in pure sql. All updates are in single transaction.
One possible way to do it in "pure sql" would be to install dblink, connect to the same database using dblink, and then issue a lot of updates over dblink, but it seems like overkill for such a simple task.
Usually just adding proper where solves the problem. If it doesn't - just partition it manually. Writing a script is too much - you can usually make it in a simple one-liner:
perl -e '
for (my $i = 0; $i <= 3500000; $i += 1000) {
printf "UPDATE orders SET status = null WHERE status is not null
and order_id between %u and %u;\n",
$i, $i+999
}
'
I wrapped lines here for readability, generally it's a single line. Output of above command can be fed to psql directly:
perl -e '...' | psql -U ... -d ...
Or first to file and then to psql (in case you'd need the file later on):
perl -e '...' > updates.partitioned.sql
psql -U ... -d ... -f updates.partitioned.sql
I am by no means a DBA, but a database design where you'd frequently have to update 35 million rows might have… issues.
A simple WHERE status IS NOT NULL might speed up things quite a bit (provided you have an index on status) – not knowing the actual use case, I'm assuming if this is run frequently, a great part of the 35 million rows might already have a null status.
However, you can make loops within the query via the LOOP statement. I'll just cook up a small example:
CREATE OR REPLACE FUNCTION nullstatus(count INTEGER) RETURNS integer AS $$
DECLARE
i INTEGER := 0;
BEGIN
FOR i IN 0..(count/1000 + 1) LOOP
UPDATE orders SET status = null WHERE (order_id > (i*1000) and order_id <((i+1)*1000));
RAISE NOTICE 'Count: % and i: %', count,i;
END LOOP;
RETURN 1;
END;
$$ LANGUAGE plpgsql;
It can then be run by doing something akin to:
SELECT nullstatus(35000000);
You might want to select the row count, but beware that the exact row count can take a lot of time. The PostgreSQL wiki has an article about slow counting and how to avoid it.
Also, the RAISE NOTICE part is just there to keep track on how far along the script is. If you're not monitoring the notices, or do not care, it would be better to leave it out.
Are you sure this is because of locking? I don't think so and there's many other possible reasons. To find out you can always try to do just the locking. Try this:
BEGIN;
SELECT NOW();
SELECT * FROM order FOR UPDATE;
SELECT NOW();
ROLLBACK;
To understand what's really happening you should run an EXPLAIN first (EXPLAIN UPDATE orders SET status...) and/or EXPLAIN ANALYZE. Maybe you'll find out that you don't have enough memory to do the UPDATE efficiently. If so, SET work_mem TO 'xxxMB'; might be a simple solution.
Also, tail the PostgreSQL log to see if some performance related problems occurs.
I would use CTAS:
begin;
create table T as select col1, col2, ..., <new value>, colN from orders;
drop table orders;
alter table T rename to orders;
commit;
Some options that haven't been mentioned:
Use the new table trick. Probably what you'd have to do in your case is write some triggers to handle it so that changes to the original table also go propagated to your table copy, something like that... (percona is an example of something that does it the trigger way). Another option might be the "create a new column then replace the old one with it" trick, to avoid locks (unclear if helps with speed).
Possibly calculate the max ID, then generate "all the queries you need" and pass them in as a single query like update X set Y = NULL where ID < 10000 and ID >= 0; update X set Y = NULL where ID < 20000 and ID > 10000; ... then it might not do as much locking, and still be all SQL, though you do have extra logic up front to do it :(
PostgreSQL version 11 handles this for you automatically with the Fast ALTER TABLE ADD COLUMN with a non-NULL default feature. Please do upgrade to version 11 if possible.
An explanation is provided in this blog post.