How do I do large non-blocking updates in PostgreS

问题:

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?

回答1:

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;

Per documentation:

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...

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. (These statements do not apply when dropping the system oid column; that is done with an immediate rewrite.)

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. Since it only takes a few milliseconds, you should still be fine.

If you have a column default you want to keep, add it back in a separate command. Doing it in the same command would apply it to all rows immediately, voiding the effect. You could then update the existing columns in batches. Follow the documentation link and read the Notes in the manual.

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

About avoiding empty UPDATE:

• How do I (or can I) SELECT DISTINCT on multiple columns?

回答2:

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;

回答3:

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;

回答4:

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

回答5:

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).

回答6:

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.

回答7:

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.

回答8:

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 :(

回答9:

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.