PostgreSQL JOIN, under the hood - postgresql

I have question about PostgreSQL join.
Does PostgreSQL create temporary table for JOINed tables or it makes everything
without any temporary tables?
The reason of my question is:
When I make SELECT request with many JOINs, I see IO spike in write operations.
What can be the reason of this issue?
Thanks a lot.

PostgreSQL will temporarily spill result-sets to disk if they get large enough. Unless you have a database smaller than your RAM it doesn't have much choice.
However, you can also see unexpected writes if this is the first time you have read in data pages since they were created. There are "hint bits" set on each page to optimise visibility checks. These get set when vacuuming etc. or when a page is accessed. If you do a large import followed by a table scan you can get a lot of unexpected IO as all the hint bits get set and written out.

Related

How to determine how much "slack" in postgres database?

I've got a postgres database which I recently vacuumed. I understand that process marks space as available for future use, but for the most part does not return it to the OS.
I need to track how close I am to using up that available "slack space" so I can ensure the entire database does not start to grow again.
Is there a way to see how much empty space the database has inside it?
I'd prefer to just do a VACUUM FULL and monitor disk consumption, but I can't lock the table for a prolonged period, nor do I have the disk space.
Running version 13 on headless Ubuntu if that's important.
Just like internal free space is not given back to the OS, it also isn't shared between tables or other relations (like indexes). So having freespace in one table isn't going to help if a different table is the one growing. You can use pg_freespacemap to get a fast approximate answer for each table, or pgstattuple for more detailed data.

Db2 performance - many batch programs inserting rows in the same table

Hi there I'm looking for advice from someone who is good at IBM db2 performance.
I have a situation in which many batch tasks are massively inserting rows in the same db2 table, at the same time.
This situation looks potentially bad. I don't think db2 is able to resolve the many requests quickly enough, causing the concurring tasks to take longer to end and even causing some of them to abend with a -904 or -911 sqlcode.
What do you guys think? Should situations like these be avoided? Are there some sort of techniques that could improve the performance of the batch tasks, keeping them from abending or running too slow?
Thanks.
Inserting should not be a big problem running ETL workloads i.e. with DataStage do this all the time.
I suggest to run an
ALTER TABLE <tabname> APPEND ON
This avoids the free space search - details can be found here
With the errors reported the information provided is not sufficient to get the cause of it.
There are several things to consider. What indexes are on the table is one.
Append mode works well to relieve last page contention, there are also issues where you could see contention with the statement itself for the variation lock. Then you could have issues with the transaction logs if they are not fast enough.
What is the table, indexes and statement and maybe we can come up with how to do it. What hardware are you using and what io subsystem is being used for transaction logs and database tablespaces.

PostgreSQL: Backend processes are active for a long time

now I am hitting a very big road block.
I use PostgreSQL 10 and its new table partitioning.
Sometimes many queries don't return and at the time many backend processes are active when I check backend processes by pg_stat_activity.
First, I thought theses process are just waiting for lock, but these transactions contain only SELECT statements and the other backend doesn't use any query which requires ACCESS EXCLUSIVE lock. And these queries which contain only SELECT statements are no problem in terms of plan. And usually these work well. And computer resources(CPU, memory, IO, Network) are also no problem. Therefore, theses transations should never conflict. And I thoughrouly checked the locks of theses transaction by pg_locks and pg_blocking_pids() and finnaly I couldn't find any lock which makes queries much slower. Many of backends which are active holds only ACCESS SHARE because they use only SELECT.
Now I think these phenomenon are not caused by lock, but something related to new table partition.
So, why are many backends active?
Could anyone help me?
Any comments are highly appreciated.
The blow figure is a part of the result of pg_stat_activity.
If you want any additional information, please tell me.
EDIT
My query dosen't handle large data. The return type is like this:
uuid UUID
,number BIGINT
,title TEXT
,type1 TEXT
,data_json JSONB
,type2 TEXT
,uuid_array UUID[]
,count BIGINT
Because it has JSONB column, I cannot caluculate the exact value, but it is not large JSON.
Normally theses queries are moderately fast(around 1.5s), so it is absolutely no problem, however when other processes work, the phenomenon happens.
If statistic information is wrong, the query are always slow.
EDIT2
This is the stat. There are almost 100 connections, so I couldn't show all stat.
For me it looks like application problem, not postresql's one. active status means that your transaction still was not commited.
So why do you application may not send commit to database?
Try to review when do you open transaction, read data, commit transaction and rollback transaction in your application code.
EDIT:
By the way, to be sure try to check resource usage before problem appear and when your queries start hanging. Try to run top and iotop to check if postgres really start eating your cpu or disk like crazy when problem appears. If not, I will suggest to look for problem in your application.
Thank you everyone.
I finally solved this problem.
I noticed that a backend process holded too many locks. So, when I executed the query SELECT COUNT(*) FROM pg_locks WHERE pid = <pid>, the result is about 10000.
The parameter of locks_per_transactions is 64 and max_connections is about 800.
So, if the number of query that holds many locks is large, the memory shortage occurs(see calculation code of shared memory inside PostgreSQL if you are interested.).
And too many locks were caused when I execute query like SELECT * FROM (partitioned table). Imangine you have a table foo that is partitioned and the number of the table is 1000. And then you can execute SELECT * FROM foo WHERE partion_id = <id> and the backend process will hold about 1000 table locks(and index locks). So, I change the query from SELECT * FROM foo WHERE partition_id = <id> to SELECT * FROM foo_(partitioned_id). As the result, the problem looks solved.
You say
Sometimes many queries don't return
...however when other processes work, the phenomenon happens. If statistic
information is wrong, the query are always slow.
They don't return/are slow when directly connecting to the Postgres instance and running the query you need, or when running the queries from an application? The backend processes that are running, are you able to kill them successfully with pg_terminate_backend($PID) or does that have issues? To rule out issues with the statement itself, make sure statement_timeout is set to a reasonable amount to kill off long-running queries. After that is ruled out, perhaps you are running into a case of an application hanging and never allowing the send calls from PostgreSQL to finish. To avoid a situation like that, if you are able to (depending on OS) you can tune the keep-alive time: https://www.postgresql.org/docs/current/runtime-config-connection.html#GUC-TCP-KEEPALIVES-IDLE (by default is 2 hours)
Let us know if playing with any of that gives any more insight into your issue.
Sorry for late post, As #Konstantin pointed out, this might be because of your application(which is why I asked for your EDIT2). Adding a few excerpts,
table partition has no effect on these locks, that is a totally different concept and does not hold up locks in your case.
In your application, check if the connection properly close() after read() and is in finally block (From Java perspective). I am not sure of your application tier.
Check if SELECT..FOR UPDATE or any similar statement is written erroneously recently which is causing this.
Check if any table has grown in size recently and the column is not Indexed. This is very important and frequent cause of select statements running for some minutes. I'd also suggest using timeouts for select statements in your application. https://www.postgresql.org/docs/9.5/gin-intro.html This can give you a headstart.
Another thing that is fishy to me is the JSONB column, maybe your Jsonb values are pretty long, or the queries are unnecessarily selecting JSONB value even if not required?
Finally, If you don't need some special features of Jsonb data type, then you use JSON data type which is faster (magical maximum, sometimes 50x!)
It looks like the pooled connections not getting closed properly and a few queries might be taking huge time to respond back. As pointed out in other answers, it is the problem with the application and could be connection leak. Most possibly, it might be because of pending transactions over some already pending and unresolved transactions, leading to a number of unclosed transactions.
In addition, PostgreSQL generally has one or more "helper" processes like the stats collector, background writer, autovaccum daemon, walsender, etc, all of which show up as "postgres" instances.
One thing I would suggest you check in which part of the code you have initiated the queries. Try to DRY run your queries outside the application and have some benchmarking of queries performance.
Secondly, you can keep some timeout for certain queries if not all.
Thirdly, you can do kill the idle transactions after certain timeouts by using:
SET SESSION idle_in_transaction_session_timeout = '5min';
I hope it might work. Cheers!

What about expected performance in Pentaho?

I am using Pentaho to create ETL's and I am very focused on performance. I develop an ETL process that copy 163.000.000 rows from Sql server 2088 to PostgreSQL and it takes 17h.
I do not know how good or bad is this performance. Do you know how to measure if the time that takes some process is good? At least as a reference to know if I need to keep working heavily on performance or not.
Furthermore, I would like to know if it is normal that in the first 2 minutes of ETL process it load 2M rows. I calculate how long will take to load all the rows. The expected result is 6 hours, but then the performance decrease and it takes 17h.
I have been investigating in goole and I do not find any time references neither any explanations about performance.
Divide and conquer, and proceed by elimination.
First, add a LIMIT to your query so it takes 10 minutes instead of 17 hours, this will make it a lot easier to try different things.
Are the processes running on different machines? If so, measure network bandwidth utilization to make sure it isn't a bottleneck. Transfer a huge file, make sure the bandwidth is really there.
Are the processes running on the same machine? Maybe one is starving the other for IO. Are source and destination the same hard drive? Different hard drives? SSDs? You need to explain...
Examine IO and CPU usage of both processes. Does one process max out one cpu core?
Does a process max out one of the disks? Check iowait, iops, IO bandwidth, etc.
How many columns? Two INTs, 500 FLOATs, or a huge BLOB with a 12 megabyte PDF in each row? Performance would vary between these cases...
Now, I will assume the problem is on the POSTGRES side.
Create a dummy table, identical to your target table, which has:
Exact same columns (CREATE TABLE dummy LIKE table)
No indexes, No constraints (I think it is the default, double check the created table)
BEFORE INSERT trigger on it which returns NULL and drop the row.
The rows will be processed, just not inserted.
Is it fast now? OK, so the problem was insertion.
Do it again, but this time using an UNLOGGED TABLE (or a TEMPORARY TABLE). These do not have any crash-resistance because they don't use the journal, but for importing data it's OK.... if it crashes during the insert you're gonna wipe it out and restart anyway.
Still No indexes, No constraints. Is it fast?
If slow => IO write bandwidth issue, possibly caused by something else hitting the disks
If fast => IO is OK, problem not found yet!
With the table loaded with data, add indexes and constraints one by one, find out if you got, say, a CHECK that uses a slow SQL function, or a FK into a table which has no index, that kind of stuff. Just check how long it takes to create the constraint.
Note: on an import like this you would normally add indices and constraints after the import.
My gut feeling is that PG is checkpointing like crazy due to the large volume of data, due to too-low checkpointing settings in the config. Or some issue like that, probably random IO writes related. You put the WAL on a fast SSD, right?
17H is too much. Far too much. For 200 Million rows, 6 hours is even a lot.
Hints for optimization:
Check the memory size: edit the spoon.bat, find the line containing -Xmx and change it to half your machine memory size. Details varies with java version. Example for PDI V7.1.
Check if the query from the source database is not too long (because too complex, or server memory size, or ?).
Check the target commit size (try 25000 for PostgresSQL), the Use batch update for inserts in on, and also that the index and constraints are disabled.
Play with the Enable lazy conversion in the Table input. Warning, you may produce difficult to identify and debug errors due to data casting.
In the transformation property you can tune the Nr of rows in rowset (click anywhere, select Property, then the tab Miscelaneous). On the same tab check the transformation is NOT transactional.

Does SQL0289N affect other users?

I am getting this error:
com.ibm.db2.jcc.a.SqlException: DB2 SQL Error: SQLCODE=-289, SQLSTATE=57011, SQLERRMC=XXX32KTMP, DRIVER=3.51.90
on a select statement that has a couple of dozen sub-selects.
SQL0289N usually means the current table space size is not enough for allocating new pages for new data.
I want to modify my select such that it does not use as much table space.
While modifying the select I presumably will get this error several more times until I am successful.
My questions are:
A) Does this error only affect my select?
B) Are other users of the database more like to have a problem because I am running this select?
The context of those questions is that I want to know if I have to move my work to a different database to be reasonably sure that I am not impacting other users.
I am wary because the error description is not clear if it is running out of memory that is shared between all users, or memory that is only allocated to my connection.
Note: I am NOT asking how to increase table space or what this error means. I am NOT asking for help modifying my select (hence, I did not show the select). Any answers to that effect would be off topic.
Without knowing how exactly the tablespace in question is defined and why your query needs it it is hard to give you a definite answer.
In the best case the error affects any SQL statement, executed in any session, that requires the use of the same tablespace, especially if it is a system temporary tablespace.
In the worst case, e.g. if it is an SMS tablespace and it shares the file system with other tablespaces and log files, it might even bring the entire DB2 instance down.
Tuning your statement in a different database does not necessarily mean that it will resolve the problem in the original database.