Db2 performance - many batch programs inserting rows in the same table - db2

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.

Related

What could be causing high cpu in google spanner databases? (unresponsive table)

I'm facing an issue where 2 out of 10 spanner databases are showing a high CPU usage (above 40%) whereas the others are around %1 each, with almost identical or more data.
I notice one of our tables has become "unresponsive" no queries work against it. We shutdown all apps that connect to those dbs, and we also deleted all current sessions using gcloud sessions list and then gcloud session delete.
However the table is still unresponsive. A simple select like select id from mytable where name = 'test' is not responding (when tested from an app, and also from gcloud web interface), it only happens with that table, which has only a few columns with normal data and no more than 2000 records. We identified the query that could have been the source of the problem, however the table seems to be locked (only count(*) without any where clause works).
I was wondering if there is any way to "unlock" the table, kill those "transactions" that might be causing the issue, or restart those specific spanner databases, or in the worst case scenario restarting the spanner instance.
I have seen the monitoring high cpu documentation, but even if we can identify the cpu is high, we don't really know how to restart or make it back to normal before reviewing the query/ies that could have caused the issue (if that was the case).
High CPU can be caused by user initiated queries, from different types of operations. It is important to notice that your instance is where you allocate resources to be used by the underlying Cloud Spanner databases. This means, that if all of your databases are in the same instance and if some of your databases are hogging the CPU, all your other databases will struggle.
In terms of a locked table, I would be very surprised if a deadlock is the problem here, since Spanner mitigates those issues using "wound-wait" algorithm. What I suspect might be happening is that a long time is necessary to perform the query in that table and it times out. It would be nice to investigate a bit more on your problem:
How long did you wait for your query on the problematic table (before you deemed to be stuck)? It might be a problem where your query just takes long and you are timing out before getting the results. It might be a problem where there are hotspots in your table and transactions are getting aborted often, preventing you from getting results.
What error did you get when performing the query on the table? The error code can tell you more about what might be happening.
Have you tried doing a stale read on the table to see if any data is returned? If lock contention is the problem, this should succeed and return results faster for you. Thus, you can further investigate the lock usage with the statistics table (as shown below).
Inspect query statistics: you can list the queries with the highest CPU usage, find the average latency for a query and find out the queries that timeout the most. There is much more you can do, as seen here. You can also view the query statistics in cloud console. What I would verify is, by reducing the overall CPU, does your query come back without any issues? You might need more resources if so. Or you might need to reduce hotspots in your database.
Inspect Lock statistics: you can investigate lock conflicts in your rows and tables. I think that an interesting query for your problem would be Discovering which row keys and columns had long lock wait times during the selected period. You can then see if your query is reading those row keys and columns and act accordingly.

Time-consuming queries to PostgreSQL Database are duplicated

After restoring db-server from snapshot something strange started happening with our database. Basically it can be described as all time-consuming queries are seems to be duplicated. At least as pg_stat_activity shows it
These lines are almost equal except for their PIDs and client addresses.
Usually I'd think that that's just a mistake of dev team (multiple equal queries at a time in code, cron misconfiguration, etc), but one of those time-consuming selects comes from PowerBI which I believe to be quite reliable in terms of loading data.
Has anybody ever stumbled upon this problem?
Turned out that's the way pg_stat_activity shows parallel workers processing single query. You can make sure that's the case by getting backend_type of these records.

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!

TimescalDB is slower than pure PostgreSQL

I setup TimescaleDB and Postgresql for testing performance on time-serial data. I have successful setup the hyper table. I test with inserted 2M rows from my C# program. But the TimescaleDB is process totally slower than pure Postgresql. Even with the TimescaleDB my program did not response after it insert some hundred records. I don't know why. Can anyone give me a hint? Or am I missing something?
We will need a bit more information in order to pinpoint what issues you're running into. If TimescaleDB is not responding at all after inserting a few hundred records, it sounds like something is definitely misconfigured, either on the database or the system level. Is the client simply timing out, or is it accompanied with some kind of error? If the process is hanging, do you have any insight into what the system is doing during this time (e.g., is there a lot of IO, is CPU maxed out?). Are you seeing any locks in contention when this happens (see Postgres Lock Monitoring? It would also be good to see your data model and how your TimescaleDB hypertable was created.
Also, note that TimescaleDB will not necessarily outperform Postgres with a low number of rows and single row inserts. TimescaleDB shines when you hit tens of millions of rows or more and insert in batches. See the PostgreSQL vs TimescaleDB Blog Post for more information.

PostgreSQL JOIN, under the hood

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.