Thread: Efficiently Triggering Autovacuum Analyze?
We have a performance problem accessing one of our tables, I think because the statistics are out of date. The table is fairly large, on the order of 100M rows or so.
The general structure of the table is as follows:
Column | Type | Modifiers
-------------------+--------------------------+------------------------------------------------
id | bigint | not null default nextval('foo_id_seq'::regclass)
record_id | text |
account_id | bigint | not null
-------------------+--------------------------+------------------------------------------------
id | bigint | not null default nextval('foo_id_seq'::regclass)
record_id | text |
account_id | bigint | not null
With indexes:
"foo_pkey" PRIMARY KEY, btree (id)
"uq_account_id_record_id" UNIQUE CONSTRAINT, btree (account_id, record_id)
This table is almost always queried using a combination of (account_id, record_id) and is generally pretty fast. However, under certain loads, the query becomes slower and slower as time goes on. The workload that causes this to happen is when data for a new account_id is being inserted into the table. This will happen in rapid succession and may insert millions of rows over the course of several hours.
The pattern that I notice when this happens is that the CPU on DB will be pegged much higher than usual, and the query to lookup records for the (account_id, record_id) combo will steadily rise from <1ms to more then 2 or 3 seconds over time.
The fix I have employed to restore the speed of the query after I notice it is happening is to manually issue a VACUUM ANALYZE on the table. After the analyze is done, the query returns to its normal speed.
I am looking for suggestions for how to tune, or perhaps automatically detect this pattern, so that I don't have to manually intervene whenever this happens.
Here are my autovacuum settings:
name | setting | unit
-------------------------------------+-----------+------
autovacuum | on |
autovacuum_analyze_scale_factor | 0.05 |
autovacuum_analyze_threshold | 50 |
autovacuum_freeze_max_age | 200000000 |
autovacuum_max_workers | 3 |
autovacuum_multixact_freeze_max_age | 400000000 |
autovacuum_naptime | 30 | s
autovacuum_vacuum_cost_delay | 20 | ms
autovacuum_vacuum_cost_limit | -1 |
autovacuum_vacuum_scale_factor | 0.1 |
autovacuum_vacuum_threshold | 50 |
autovacuum_work_mem | -1 | kB
We're using 9.4.4 (RDS)
Cory Tucker <cory.tucker@gmail.com> writes: > This table is almost always queried using a combination of (account_id, > record_id) and is generally pretty fast. However, under certain loads, the > query becomes slower and slower as time goes on. The workload that causes > this to happen is when data for a new account_id is being inserted into the > table. This will happen in rapid succession and may insert millions of > rows over the course of several hours. Are those insertions happening in one enormous transaction, or even just a few very large ones? > The pattern that I notice when this happens is that the CPU on DB will be > pegged much higher than usual, and the query to lookup records for the > (account_id, record_id) combo will steadily rise from <1ms to more then 2 > or 3 seconds over time. I'm suspicious that this is not autovacuum's fault but reflects the cost of checking uncommitted tuples to see if they've become committed yet. If so, there may be little you can do about it except break the insertion into smaller transactions ... which might or might not be all right from a data consistency standpoint. regards, tom lane
On 12/30/2015 11:09 AM, Cory Tucker wrote: > We have a performance problem accessing one of our tables, I think > because the statistics are out of date. The table is fairly large, on > the order of 100M rows or so. > The fix I have employed to restore the speed of the query after I notice > it is happening is to manually issue a VACUUM ANALYZE on the table. > After the analyze is done, the query returns to its normal speed. > autovacuum_analyze_scale_factor | 0.05 | > autovacuum_analyze_threshold | 50 | > autovacuum_vacuum_scale_factor | 0.1 | > autovacuum_vacuum_threshold | 50 | With this scenario you can expect an autoanalyze every 5 million rows and autovacuum every 10 million. In my experience (and based on your description, yours as well) this is not often enough. Not only that, when it does run it runs longer than you would like, causing an I/O hit while it does. You probably should tune this table specifically, e.g. ALTER TABLE foo SET (autovacuum_vacuum_threshold=100000, autovacuum_vacuum_scale_factor=0); ALTER TABLE foo SET (autovacuum_analyze_threshold=100000, autovacuum_analyze_scale_factor=0); That will cause autovac and autoanalyze to run every 100k records changed (pick your own number here, but I have used this very successfully in the past). This way not only will the table remain well vacuum analyzed, when they run they will finish quickly and have minimal impact. HTH, Joe -- Crunchy Data - http://crunchydata.com PostgreSQL Support for Secure Enterprises Consulting, Training, & Open Source Development
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On Wed, Dec 30, 2015 at 11:20 AM Tom Lane <tgl@sss.pgh.pa.us> wrote:
Cory Tucker <cory.tucker@gmail.com> writes:
> This table is almost always queried using a combination of (account_id,
> record_id) and is generally pretty fast. However, under certain loads, the
> query becomes slower and slower as time goes on. The workload that causes
> this to happen is when data for a new account_id is being inserted into the
> table. This will happen in rapid succession and may insert millions of
> rows over the course of several hours.
Are those insertions happening in one enormous transaction, or even just
a few very large ones?
No, one transaction per row insert.
> The pattern that I notice when this happens is that the CPU on DB will be
> pegged much higher than usual, and the query to lookup records for the
> (account_id, record_id) combo will steadily rise from <1ms to more then 2
> or 3 seconds over time.
I'm suspicious that this is not autovacuum's fault but reflects the cost
of checking uncommitted tuples to see if they've become committed yet.
If so, there may be little you can do about it except break the insertion
into smaller transactions ... which might or might not be all right from
a data consistency standpoint.
regards, tom lane
On 12/30/15 1:31 PM, Joe Conway wrote: > On 12/30/2015 11:09 AM, Cory Tucker wrote: > With this scenario you can expect an autoanalyze every 5 million rows > and autovacuum every 10 million. In my experience (and based on your > description, yours as well) this is not often enough. Not only that, > when it does run it runs longer than you would like, causing an I/O hit > while it does. > > You probably should tune this table specifically, e.g. Another option is to explicitly analyze then SELECT from the table after you're done inserting into it. The advantage is it doesn't tie up an autovac worker and you can ensure that the newly added tuples get properly hinted. You can run the ANALYZE immediately after your insert finishes. The reason to do that is to get up-to-date statistics for other queries to use. That can be particularly important if the new rows have values significantly outside what was in the table before. That's common with things like sequence IDs and timestamp data. The SELECT is a bit trickier; you want to ensure that there is no transaction still running in the database that's older than the transaction that added all the new data. You can check that by comparing the xmin field of one of your new rows with txid_snapshot_xmin(txid_current_snapshot()). Note that because of wraparound you can't do a simple comparison; txid 3 is actually greater than txid 2^32. The whole point of this SELECT is to get the new tuples hinted while the pages are still hot in cache. If you don't do that, the next query that reads the tuple will have to set the hints, which also dirties the page. VACUUM does that too, but there's really no point in having vacuum run through the entire table just to set hints on less than 1% of it. -- Jim Nasby, Data Architect, Blue Treble Consulting, Austin TX Experts in Analytics, Data Architecture and PostgreSQL Data in Trouble? Get it in Treble! http://BlueTreble.com