We am doing a system redesigning and due to the change in design we need to import data from multiple similar source tables into one table. For this same, I am running a loop which have the list of tables and importing all the data. However, due to massive amount of data, I got out of memory error after execution of around 12 hours and 20 tables. Now I discovered that the loop runs in a single transaction which I don't need since the system which is filling the data is suspended for that time. Having this transaction thing, I believe, it is taking longer time also. My requirement is to run my query without any transaction.
DO $$DECLARE r record;
BEGIN
FOR r IN SELECT '
INSERT INTO dbo.tb_requests
(node_request_id, request_type, id, process_id, data, timestamp_d1, timestamp_d2, create_time, is_processed)
SELECT lpad(A._id, 32, ''0'')::UUID, (A.data_type + 1) request_type, B.id, B.order_id, data_value, timestamp_d1, timestamp_d2, create_time, TRUE
FROM dbo.data_store_' || id || ' A
JOIN dbo.tb_new_processes B
ON A.process_id = B.process_id
WHERE A._id != ''0'';
' as log_query FROM dbo.list_table
ORDER BY line_id
LOOP
EXECUTE r.log_query;
END LOOP;
END$$;
This is a sample code block. It is not the actual code block but I think, it will give the idea.
Error Message(Translation from Original Japanese error Message):
ERROR: Out of memory
DETAIL: Request for size 32 failed in memory context "ExprContext".
SQL state: 53200
You cannot to run any statement on server side without transaction. For some modern Postgres releases you can run commit statement inside DO statement. It is closes current transaction and starts new transactions. This can breaks very long transaction, and can solve the problem with memory leak - Postgres releasing some memory at transaction end.
Or use shell scripts instead (bash) if it is possible.
I got a weird error while I was writing to my Postgres database over Aurora PostgreSQL on AWS
PostgreSQL version 9.6.11
my tries to fix that issue on table admin_user
Vacuum admin_user
Vacuum Freeze admin_user
I couldn't recreate the table as it's connected to all other tables and will cause a big mess
Update question
I cant access the table
For reasons that we probably cannot fathom here (could be a PostgreSQL software bug that might have been fixed by 9.6.19, could be a hardware problem), you have suffered data corruption.
Since you are using a hosted database and have no access to the database except through SQL, your options are limited.
The best is probably to use subtransactions to lift as many data as you can from the table (called test in this example):
/* will receive salvaged rows */
CREATE TABLE test_copy (LIKE test);
You can run something like this code:
DO
$$DECLARE
c CURSOR FOR SELECT * FROM test;
r test;
cnt bigint := 0;
BEGIN
OPEN c;
LOOP
cnt := cnt + 1;
/* block to start a subtransaction for each row */
BEGIN
FETCH c INTO r;
EXIT WHEN NOT FOUND;
EXCEPTION
WHEN OTHERS THEN
/* there was data corruption fetching the row */
RAISE WARNING 'skipped corrupt data at row number %', cnt;
NOVE c;
CONTINUE;
END;
/* row is good, salvage it */
INSERT INTO test_copy VALUES (r.*);
END LOOP;
END;$$;
Good luck.
I have 2 tables (1 staging table and 1 main operational table).
Both tables have the same structure.
For my solution,
I am using DB2Copy in program to insert 10000 records into staging table (4 seconds)
From the staging table, will move the data into main table using stored procedure (10 seconds)
However, it will lock the main table when running stored procedure.
I am suspecting because of the BEGIN and END which cause the stored procedure to act like a transaction.
I do not want the table to be locked when running stored procedure. (any suggestion?) Prefer: Stored procedure insert record by record into main table without transaction behavior.
Below is my code:
CREATE PROCEDURE SP_NAME ( )
LANGUAGE SQL
NOT DETERMINISTIC
CALLED ON NULL INPUT
EXTERNAL ACTION
OLD SAVEPOINT LEVEL
MODIFIES SQL DATA
INHERIT SPECIAL REGISTERS
BEGIN
--DECLARE TEMP VARIABLES
BEGIN
DECLARE MYCURSOR CURSOR WITH RETURN TO CALLER FOR
--SELECT STAGING TABLE
DECLARE CONTINUE HANDLER FOR NOT FOUND SET AT_END = 1;
OPEN MYCURSOR;
-- FETCH MYCURSOR INTO TEMP VARIABLES
WHILE AT_END = 0 DO
-- INSERT MAIN TABLE
-- FETCH MYCURSOR INTO TEMP VARIABLES
END WHILE;
CLOSE MYCURSOR;
END;
END;
My Environment
I have a program "A" which is trying to insert 10k records into main table (A lot of indexes and high volume of data) which takes 10 minutes ++.
About main operational table
High number of read but minimum updates and inserts at front end.
At back end, another program will frequently insert record into this table.
Only 1 instance of the back end program is allowed to run at one time
When you create the procedure, make sure your commitment-control setting is *NONE (a.k.a. autocommit). This should not lock your whole table
Adding the example
CREATE PROCEDURE userS.SP_TEST (
IN col_DATA Varchar(10) )
LANGUAGE SQL
SPECIFIC userS.SP_TEST
NOT DETERMINISTIC
MODIFIES SQL DATA
SET OPTION COMMIT = *NONE
BEGIN INSERT INTO userS.TABLE1 VALUES(col_DATA);
END
I recently inherited an application that uses PostgreSQL and I have been troubleshooting issues relating to saving records in the database.
I know that PostgreSQL allows me to record the transaction ID in the log by including the special value of %x in the log_line_prefix. What I noticed, however, is that the first statement that occurs within a transaction always gets logged with a zero.
If I perform the following operations in psql,
begin;
insert into numbers (1);
insert into numbers (2);
commit;
the query log will contain the following entries:
2016-09-20 03:07:40 UTC 0 LOG: statement: begin;
2016-09-20 03:07:53 UTC 0 LOG: statement: insert into numbers values (1);
2016-09-20 03:07:58 UTC 689 LOG: statement: insert into numbers values (2);
2016-09-20 03:08:03 UTC 689 LOG: statement: commit;
My log format is %t %x and as you can see, the transaction ID for the first insert statement is 0, but it changes to 689 when I execute the second insert.
Can anyone explain why after starting a transaction PostgreSQL doesn't log the right transaction ID on the first statement? Or if I'm just doing this wrong, is there a more reliable way of identifying which queries were part of a single transaction by looking at the log file?
The transaction ID is assigned after the statement starts, so log_statement doesn't capture it. BEGIN doesn't assign a transaction ID, it's delayed until the first write operation.
Use the virtual txid instead, which is assigned immediately. The placeholder is %v. These are assigned immediately, but are not persistent and are backend-local.
I find it useful to log both. The txid because it matches up to xmin and xmax system column contents, etc; the vtxid to help me group up operations done in transactions.
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.