Among the many things we do with Postgres at work, we use it as a cache for certain kinds of remote requests. Our schema is:
CREATE TABLE IF NOT EXISTS cache (
key VARCHAR(256) PRIMARY KEY,
value TEXT NOT NULL,
ttl TIMESTAMP DEFAULT NULL
);
CREATE INDEX IF NOT EXISTS idx_cache_ttl ON cache(ttl);
This table does not have triggers or foreign keys. Updates are typically:
INSERT INTO cache (key, value, ttl)
VALUES ('Ethan is testing8393645', '"hi6286166"', sec2ttl(300))
ON CONFLICT (key) DO UPDATE
SET value = '"hi6286166"', ttl = sec2ttl(300);
(Where sec2ttl is defined as:)
CREATE OR REPLACE FUNCTION sec2ttl(seconds FLOAT)
RETURNS TIMESTAMP AS $$
BEGIN
IF seconds IS NULL THEN
RETURN NULL;
END IF;
RETURN now() + (seconds || ' SECOND')::INTERVAL;
END;
$$ LANGUAGE plpgsql;
Querying the cache is done in a transaction like this:
BEGIN;
DELETE FROM cache WHERE ttl IS NOT NULL AND now() > ttl;
SELECT value FROM cache WHERE key = 'Ethan is testing6460437';
COMMIT;
There are a few things not to like about this design -- the DELETE happening in cache "reads", the index on cache.ttl is not ascending which makes it kind of useless, (edit: ASC is the default, thanks wargre!) plus the fact that we're using Postgres as a cache at all. But all of that would have been acceptable except that we've started getting deadlocks in production, which tend to look like this:
ERROR: deadlock detected
DETAIL: Process 12750 waits for ShareLock on transaction 632693475; blocked by process 10080.
Process 10080 waits for ShareLock on transaction 632693479; blocked by process 12750.
HINT: See server log for query details.
CONTEXT: while deleting tuple (426,1) in relation "cache"
[SQL: 'DELETE FROM cache WHERE ttl IS NOT NULL AND now() > ttl;']
Investigating the logs more thoroughly indicates that both transactions were performing this DELETE operation.
As far as I can tell:
My transactions are in READ COMMITTED isolation mode.
ShareLocks are grabbed by one transaction to indicate that it wants to mutate rows that another transaction has mutated (i.e. locked).
Based on the output of an EXPLAIN query, the ShareLocks should be grabbed by both DELETE transactions in physical order.
The deadlock indicates that both queries locked rows in a different order.
If all that is correct, then somehow some simultaneous transaction has changed the physical order of rows. I see that an UPDATE can move a row to an earlier or later physical position, but in my application, the UPDATEs always remove rows from consideration by the DELETEs (because they're always extending a row's TTL). If the rows were previously in physical order, and you remove one, then you're still left with physical order. Similarly for DELETE. We're not doing any VACUUM or any other operation which you might expect to reorder rows.
Based on Avoiding PostgreSQL deadlocks when performing bulk update and delete operations, I tried to change the DELETE queries to:
DELETE FROM cache c
USING (
SELECT key
FROM cache
WHERE ttl IS NOT NULL AND now() > ttl
ORDER BY ttl ASC
FOR UPDATE
) del
WHERE del.key = c.key;
However, I'm still able to get deadlocks locally. So generally, how can two DELETE queries deadlock? Is it because they're locking in an undefined order, and if so, how do I enforce a specific order?
You should instead ignore expired cache entries, so you will not depend on a frequent delete operation for cache expiration:
SELECT value
FROM cache
WHERE
key = 'Ethan is testing6460437'
and (ttl is null or ttl<now());
And have another job that periodically chooses keys to delete skipping already locked keys, which has to either force a well defined order of deleted row, or, better, skip already locked for update rows:
with delete_keys as (
select key from cache
where
ttl is not null
and now()>ttl
for update skip locked
)
delete from cache
where key in (select key from delete_keys);
If you can't schedule this periodically you should run this cleanup like randomly once every 1000 runs of your select query, like this:
create or replace function delete_expired_cache()
returns void
language sql
as $$
with delete_keys as (
select key from cache
where
ttl is not null
and now()>ttl
for update skip locked
)
delete from cache
where key in (select key from delete_keys);
$$;
SELECT value
FROM cache
WHERE
key = 'Ethan is testing6460437'
and (ttl is null or ttl<now());
select delete_expired_cache() where random()<0.001;
You should avoid writes, as they are expensive. Don't delete cache so often.
Also you should use timestamp with time zone type (or timestamptz for short) instead of simple timestamp - especially if you don't know why - a timestamp is not the thing most think it is - blame SQL standard.
Related
I am trying to write an experimentation framework where user can schedule some experiments based on location-ids and time.
my table schema looks like :
TABLE experiment (
id INT NOT NULL PRIMARY KEY,
name varchar(20) NOT NULL,
locationIds varchar[] NOT NULL,
timeStart timestamp NOT NULL,
timeEnd timestamp NOT NULL,
createdAt timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
updatedAt timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP
)
there are insert operations to be done with condition that the location(s) and time should not overlap.
I wanted to know what can be done to avoid in-consistency of data state when there are 2 concurrent inserts taken up where location OR time overlaps,
Ideally I want one of the insert to succeed, but I am fine If both fails and application is supposed to retry again.
Few Approached I tried to think:
Approach:
APPROACH-1
Have an enable column that tells whether certain entry is valid
OR not.
I insert the experiment schedule entry with enable=FALSE
Then I check if there is any other entry which is enabled and is
overlapping with the current Insert.
IF there is such entry then I do nothing and that experiment is not
scheduled. Else I update the entry to enable=TRUE.
Problem : If there is a concurrent conflicting insert, then both will get enable=TRUE when both cleared the step-3.
I gave a thought if I let the transaction-isolation level to be read-uncommitted then also, I can't differentiate the ones in process and the ones already enable=TRUE
Then I thought, If I mark enable as a enum [IN_PROGRESS, ENABLED, DISABLED] then approach will look like this.
APPROACH-2
Have an enable column that tells whether certain entry is [IN_PROGRESS, ENABLED, DISABLED]
I insert the experiment schedule entry with enable=IN_PROGRESS
Then I check if there is any other entry which is enable=ENABLED OR enable=IN_PROGRESS and is overlapping with the current Insert.
IF there is such entry then I update enable=DISABLED and that experiment is not
scheduled. Else I update the entry to enable=ENABLED.
Problem : If there is a concurrent conflicting insert, then both will get enable=DISABLED when both cleared the step-3 and get such overlapping entry.
If the transaction-isolation level is READ-COMMITTED then this will only work IF each step is a transaction, rather whole process as one transaction.
If the transaction-isolation level is READ-UNCOMMITTED then this can be taken up as one transaction, with DISABLED state can be taken as a ROLLBACK step too.
APPROACH-3
Using Trigger Based solution as I am using POSTGRES, I can add a trigger for each insert operation, post insert where I check for such overlapping entry, if there is none, then I update the row to have enable=TRUE
CREATE OR REPLACE FUNCTION enable_if_unique()
RETURNS TRIGGER AS $$
BEGIN
IF (TG_OP = 'INSERT') THEN
UPDATE experiment
SET NEW.enable=true
WHERE (SELECT count(1)
FROM experiment
WHERE enable= true AND location_Ids && OLD.location_ids AND (OLD.timeStart, OLD.timeEnd) OVERLAPS (timeStart, timeEnd)
) = 0;
RETURN NEW;
END IF;
END;
$$ LANGUAGE 'plpgsql';
CREATE TRIGGER enable_if_unique_trigger BEFORE INSERT ON experiment FOR EACH ROW EXECUTE PROCEDURE enable_if_unique();
I am not sure about Approach 3 because I feel it require trigger to act in a serial manner for each insert operation so that one of the Experiment is actually enabled while rest of overlapping ones are disabled.
APPROACH-4
From online search for other possible solution, I See Inserts taken up using Select Statement and the WHERE clause helping to add the required condition.
INSERT INTO experiment(id, name, locationIds, timeStart, timeEnd)
SELECT 1, 'exp-1', ARRAY[123,234,345], '2020-03-13 12:00:00'
WHERE (
SELECT count(1)
FROM EXPERIMENT
WHERE enable= true
AND
location_Ids && OLD.location_ids
AND
(OLD.timeStart, OLD.timeEnd) OVERLAPS (timeStart, timeEnd)
) = 0;
I feel there is still possibility of consistency issue as both concurrent operations will not be able to read each in the SELECT statement checking the constraint.
Final APPROACH : APPROACH-2
I like to know following things :
Which is the best approach in terms of scalability and high-throughput ?
Which approach is actually making the sure the data consistency is maintained?
Any Other Approach that I could have used and missed here!!!
Newbie To POSTGRES, Will APPRECIATE example OR links
as mentioned by #a_horse_with_no_name
we can use exclusion constraint :
-- this prevents overlaps in the locationids AND the time range
alter table experiment
add constraint no_overlap
exclude using gist (locationids with &&, tsrange(timestart, timeend) with &&);
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.
In PostgreSQL (9.3) I have a table defined as:
CREATE TABLE charts
( recid serial NOT NULL,
groupid text NOT NULL,
chart_number integer NOT NULL,
"timestamp" timestamp without time zone NOT NULL DEFAULT now(),
modified timestamp without time zone NOT NULL DEFAULT now(),
donotsee boolean,
CONSTRAINT pk_charts PRIMARY KEY (recid),
CONSTRAINT chart_groupid UNIQUE (groupid),
CONSTRAINT charts_ichart_key UNIQUE (chart_number)
);
CREATE TRIGGER update_modified
BEFORE UPDATE ON charts
FOR EACH ROW EXECUTE PROCEDURE update_modified();
I would like to replace the chart_number with a sequence like:
CREATE SEQUENCE charts_chartnumber_seq START 16047;
So that by trigger or function, adding a new chart record automatically generates a new chart number in ascending order. However, no existing chart record can have its chart number changed and over the years there have been skips in the assigned chart numbers. Hence, before assigning a new chart number to a new chart record, I need to be sure that the "new" chart number has not yet been used and any chart record with a chart number is not assigned a different number.
How can this be done?
Consider not doing it. Read these related answers first:
Gap-less sequence where multiple transactions with multiple tables are involved
Compacting a sequence in PostgreSQL
If you still insist on filling in gaps, here is a rather efficient solution:
1. To avoid searching large parts of the table for the next missing chart_number, create a helper table with all current gaps once:
CREATE TABLE chart_gap AS
SELECT chart_number
FROM generate_series(1, (SELECT max(chart_number) - 1 -- max is no gap
FROM charts)) chart_number
LEFT JOIN charts c USING (chart_number)
WHERE c.chart_number IS NULL;
2. Set charts_chartnumber_seq to the current maximum and convert chart_number to an actual serial column:
SELECT setval('charts_chartnumber_seq', max(chart_number)) FROM charts;
ALTER TABLE charts
ALTER COLUMN chart_number SET NOT NULL
, ALTER COLUMN chart_number SET DEFAULT nextval('charts_chartnumber_seq');
ALTER SEQUENCE charts_chartnumber_seq OWNED BY charts.chart_number;
Details:
How to reset postgres' primary key sequence when it falls out of sync?
Safely and cleanly rename tables that use serial primary key columns in Postgres?
3. While chart_gap is not empty fetch the next chart_number from there.
To resolve possible race conditions with concurrent transactions, without making transactions wait, use advisory locks:
WITH sel AS (
SELECT chart_number, ... -- other input values
FROM chart_gap
WHERE pg_try_advisory_xact_lock(chart_number)
LIMIT 1
FOR UPDATE
)
, ins AS (
INSERT INTO charts (chart_number, ...) -- other target columns
TABLE sel
RETURNING chart_number
)
DELETE FROM chart_gap c
USING ins i
WHERE i.chart_number = c.chart_number;
Alternatively, Postgres 9.5 or later has the handy FOR UPDATE SKIP LOCKED to make this simpler and faster:
...
SELECT chart_number, ... -- other input values
FROM chart_gap
LIMIT 1
FOR UPDATE SKIP LOCKED
...
Detailed explanation:
Postgres UPDATE ... LIMIT 1
Check the result. Once all rows are filled in, this returns 0 rows affected. (you could check in plpgsql with IF NOT FOUND THEN ...). Then switch to a simple INSERT:
INSERT INTO charts (...) -- don't list chart_number
VALUES (...); -- don't provide chart_number
In PostgreSQL, a SEQUENCE ensures the two requirements you mention, that is:
No repeats
No changes once assigned
But because of how a SEQUENCE works (see manual), it can not ensure no-skips. Among others, the first two reasons that come to mind are:
How a SEQUENCE handles concurrent blocks with INSERTS (you could also add that the concept of Cache also makes this impossible)
Also, user triggered DELETEs are an uncontrollable aspect that a SEQUENCE can not handle by itself.
In both cases, if you still do not want skips, (and if you really know what you're doing) you should have a separate structure that assign IDs (instead of using SEQUENCE). Basically a system that has a list of 'assignable' IDs stored in a TABLE that has a function to pop out IDs in a FIFO way. That should allow you to control DELETEs etc.
But again, this should be attempted, only if you really know what you're doing! There's a reason why people don't do SEQUENCEs themselves. There are hard corner-cases (for e.g. concurrent INSERTs) and most probably you're over-engineering your problem case, that probably can be solved in a much better / cleaner way.
Sequence numbers usually have no meaning, so why worry? But if you really want this, then follow the below, cumbersome procedure. Note that it is not efficient; the only efficient option is to forget about the holes and use the sequence.
In order to avoid having to scan the charts table on every insert, you should scan the table once and store the unused chart_number values in a separate table:
CREATE TABLE charts_unused_chart_number AS
SELECT seq.unused
FROM (SELECT max(chart_number) FROM charts) mx,
generate_series(1, mx(max)) seq(unused)
LEFT JOIN charts ON charts.chart_number = seq.unused
WHERE charts.recid IS NULL;
The above query generates a contiguous series of numbers from 1 to the current maximum chart_number value, then LEFT JOINs the charts table to it and find the records where there is no corresponding charts data, meaning that value of the series is unused as a chart_number.
Next you create a trigger that fires on an INSERT on the charts table. In the trigger function, pick a value from the table created in the step above:
CREATE FUNCTION pick_unused_chart_number() RETURNS trigger AS $$
BEGIN
-- Get an unused chart number
SELECT unused INTO NEW.chart_number FROM charts_unused_chart_number LIMIT 1;
-- If the table is empty, get one from the sequence
IF NOT FOUND THEN
NEW.chart_number := next_val(charts_chartnumber_seq);
END IF;
RETURN NEW;
END;
$$ LANGUAGE plpgsql;
CREATE TRIGGER tr_charts_cn
BEFORE INSERT ON charts
FOR EACH ROW EXECUTE PROCEDURE pick_unused_chart_number();
Easy. But the INSERT may fail because of some other trigger aborting the procedure or any other reason. So you need a check to ascertain that the chart_number was indeed inserted:
CREATE FUNCTION verify_chart_number() RETURNS trigger AS $$
BEGIN
-- If you get here, the INSERT was successful, so delete the chart_number
-- from the temporary table.
DELETE FROM charts_unused_chart_number WHERE unused = NEW.chart_number;
END;
$$ LANGUAGE plpgsql;
CREATE TRIGGER tr_charts_verify
AFTER INSERT ON charts
FOR EACH ROW EXECUTE PROCEDURE verify_chart_number();
At a certain point the table with unused chart numbers will be empty whereupon you can (1) ALTER TABLE charts to use the sequence instead of an integer for chart_number; (2) delete the two triggers; and (3) the table with unused chart numbers; all in a single transaction.
While what you want is possible, it can't be done using only a SEQUENCE and it requires an exclusive lock on the table, or a retry loop, to work.
You'll need to:
LOCK thetable IN EXCLUSIVE MODE
Find the first free ID by querying for the max id then doing a left join over generate_series to find the first free entry. If there is one.
If there is a free entry, insert it.
If there is no free entry, call nextval and return the result.
Performance will be absolutely horrible, and transactions will be serialized. There'll be no concurrency. Also, unless the LOCK is the first thing you run that affects that table, you'll face deadlocks that cause transaction aborts.
You can make this less bad by using an AFTER DELETE .. FOR EACH ROW trigger that keeps track of entries you delete by INSERTing them into a one-column table that keeps track of spare IDs. You can then SELECT the lowest ID from the table in your ID assignment function on the default for the column, avoiding the need for the explicit table lock, the left join on generate_series and the max call. Transactions will still be serialized on a lock on the free IDs table. In PostgreSQL you can even solve that using SELECT ... FOR UPDATE SKIP LOCKED. So if you're on 9.5 you can actually make this non-awful, though it'll still be slow.
I strongly advise you to just use a SEQUENCE directly, and not bother with re-using values.
Here is a table that has fields id, id_user, order_id.
Required when creating a record to find the last number of user and insert the following in order.
I wrote a stored procedure that takes the next order number to the user, but even it does not provide a unique order number.
CREATE OR REPLACE FUNCTION get_next_order()
RETURNS TRIGGER
LANGUAGE plpgsql
AS $function$
DECLARE
next_order_num bigint;
BEGIN
select order_id + 1 INTO next_order_num
from payment_out
where payment_out.id_usr = NEW.id_usr
and payment_out.order_id is not null
order by payment_out.order_id desc
limit 1;
-- if payments does't exist, return 1
NEW.order_id = coalesce(next_order_num, 1);
return NEW;
END;
$function$
CREATE TRIGGER get_next_order
BEFORE INSERT
ON payment_out
FOR EACH ROW EXECUTE
PROCEDURE get_next_order()
How can I avoid duplicate order numbers?
For this to work in the presence of multiple concurrent transactions inserting orders for the same user, you need a lock on a particular record to make them wait and execute serially.
e.g., before the first SELECT, you might:
PERFORM 1 FROM "users" where id_user = NEW.id_user FOR UPDATE;
where you lock the parent "users" record that owns the orders.
Otherwise, multiple concurrent transactions could execute your procedure at the same time, but they can't see each others' inserted values, so they'll pick the same numbers.
However, beware: A foreign key constraint will cause a SHARE lock to be taken on the users entry already, when you insert into a table that depends on it. Your trigger will try to upgrade that into an UPDATE lock, but multiple transactions might already hold the SHARE lock, so this will block. You'll land up with transactions all waiting for each other, until PostgreSQL kills all but one of them in a deadlock abort error. The only way to avoid this is for the application to SELECT 1 FROM users WHERE id_user = blahblah FOR UPDATE before it creates the orders for that user.
A variant is to keep a next_order_id field in users and do an UPDATE users SET next_order_id = next_order_id + 1 RETURNING next_order_id, and use the result of that to set the order ID. The same lock upgrade problem applies.
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.