> I don't think the downstream dependencies will let that work without
> rebuilding them as well. The drop fails (without a cascade), and the other
> views and matviews that are built off of this all simply point to x_old.
Wow, ouch. Yeah, I'd neglected to consider dependent objects. Your
only "
> I'm curious if I'm overlooking other possible architectures or tools that
> might make this simpler to manage.
One of the issues with materialized views is that they are based on
views... For a concurrent update, it essentially performs a looped
merge, which can be pretty ugly. That's the price
g use of set theory within a
database, for example, you might be getting 100x less throughput than
you could otherwise attain. If it's not proprietary in some way, or
you can obfuscate it into a test case, we can probably help then. As
it stands, there isn't enough to go on.
--
ct they're not exceptionally
useful anymore. :)
As a side note, using INSERT instead scales almost exactly linearly.
This would be useful, except that INSERT is already at least a
magnitude slower than COPY. Hah.
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t stuck, because this seems incredibly
wrong. I'll keep digging.
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'/tmp/loadtest1.csv'" &>/dev/null &
psql -c "COPY test_copy2 FROM '/tmp/loadtest1.csv'" &>/dev/null &
psql -c "COPY test_copy3 FROM '/tmp/loadtest1.csv'" &>/dev/null &
psql -c "COPY test_copy4 FROM '/tm
e?
I also know 9.5 underwent a lot of locking improvements, so it might not be
relevant. I just haven't gotten a chance to repeat my tests with 9.5 just
yet.
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Alexey,
The issue is not that 8GB is the maximum. You *can* set it higher. What I'm
saying, and I'm not alone in this, is that setting it higher can actually
decrease performance for various reasons. Setting it to 25% of memory on a
system with 512GB of RAM for instance, would be tantamount to
Alexey,
The issue is that the 1/4 memory suggestion hasn't been a recommendation in
quite a while. Now that much larger amounts of RAM are readily available, tests
have been finding out that more than 8GB of RAM in shared_buffers has
diminishing or even worse returns. This is true for any versi
> Yeah, pgTune is pretty badly out of date. It's been on my TODO list, as
> I'm sure it has been on Greg's.
Yeah. And unfortunately the recommendations it gives have been spreading. Take
a look at the online version:
http://pgtune.leopard.in.ua/
I entered a pretty typical 92GB system, and it r
until 3.11+, but the worst
of the behavior was solved before that.
Bugs in kernel cache page aging algorithms are bad, m'kay?
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-9.2 systems
encountered high CPU counts. I somehow doubt Intel would allow their HT
architecture to regress so badly from Nehalem, which is almost
3-generations old at this point. This smells like something in the
software stack, up to and including the Linux kernel.
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n retrieve those
kind of results in a few milliseconds.
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off turbo, or forgot to disable power saving features.
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data and WHERE clause and see if the planner still goes for the
terrible plan. If it does, that would seem like an obvious planner tweak
to me.
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an in that case, depending on how high
random_page_cost is.
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's still doing the
sequence scan, we'll have to dig deeper.
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obvious immediately.
Here's a link for your version:
http://www.postgresql.org/docs/9.0/static/sql-explain.html
You should still consider upgrading to the latest release of 9.0 too.
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any rows, the random seeks are throwing off your performance. Of
course, I can't confirm that without EXPLAIN output.
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_
ally match, which queries
are performing badly, and so on.
Please refer to this page to ask performance related questions:
https://wiki.postgresql.org/wiki/Slow_Query_Questions
Without much of this information, we'd only be speculating.
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Shaun Thomas
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initely much happier since the upgrade, but the
plural of anecdote is not data. :)
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-generic-lts-saucy pseudo-package to at
least get onto the 3.11 instead. The 3.2 kernel is pants-on-head
retarded; we've had a lot more luck with 3.8 and above.
Cheers!
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f the table. I highly recommend reading
up on cardinality and selectivity before creating more indexes. This
page in the documentation does a really good job:
http://www.postgresql.org/docs/9.3/static/row-estimation-examples.html
--
Shaun Thomas
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at(tm). It can
be kinda safe-ish if mounted in sync mode with caching disabled, but I'd
never use it on any of our systems.
We also have this in the Wiki:
http://wiki.postgresql.org/wiki/Shared_Storage
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shing.
This is a pretty well-known issue on Linux systems with large amounts of RAM.
Most VM servers fit that profile, so I'm not surprised it's hurting you.
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ving the indexes around. I can't think of many indexes in our
database where I have the low cardinality value as the first column. Databases
have an easier time managing many shallow buckets of values, than a few deep
ones.
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in. This will
pretty much never be fast, especially with 2M rows involved.
I could be wrong about this, and the back-end folks might have a different
answer, but I wouldn't hold my breath.
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312-
> On most machines the limit is higher than you'd ever want to set it. I
> have a set of servers with 1TB RAM and shared buffers on them is set
> to 10G and even that is probably higher than it needs to be. The old
> 1/4 of memory advice comes from the days when db server memory
> was in the 1 to
n extreme cases. Optimization fences are truly
forever. Unless of course they're removed. In which case, a bunch of
queries that exploited them will suddenly perform a whole lot worse,
causing organizations to delay upgrading PostgreSQL.
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> What are your thoughts on the right way to use SSDs in a RAID to
> enhance postgres I/O performance? In an earlier reply, you
> indicated one of a "RAID1+0 consisting of several spindles,
> NVRAM-based solution (SSD or PCIe card), or a SAN"
Well, it's a tiered approach. If you can identify yo
he results
of the insert.
WITH saved AS (
INSERT INTO dst
SELECT * FROM src WHERE ...
RETURNING *
)
DELETE FROM src
WHERE ...;
I'll admit yours is cleaner, though. :)
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table middle ground
with 240GB.
Of course, don't forget to buy modules in multiples of four, otherwise
you're not taking advantage of all the CPU's memory channels. :)
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d to a
separate set of disks for a workload of this volume. The amount of
writes here will constantly degrade read IO and further increase fetch
times.
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stho
couple versions. There are also a ton of considerations regarding new
Linux kernel settings.
Greg, go tell Packt they need to pay you to write the second edition. ;)
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only scans. So
theoretically, you might actually see some benefit there. If it were me
and I had spindles available, I would just increase the overall size of
the pool. It's a lot easier than managing multiple tablespaces.
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users have that setup. You're much more
likely to get meaningful feedback if you follow the herd. :)
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nt records are?
Add an index to the createdAt column:
CREATE INDEX idx_log_createdat ON "Log" (createdAt DESC);
Using that, it should get the ten most recent Log records almost
immediately, including associated article content.
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solution. Your
'-s 2000' test was probably running mostly from memory, while the '-s
4000' did not.
What you're seeing is the speed your records are being supplied from
disk, plus whatever cache effects are there when records are read before
they are flushed in favor of m
mind that the dead tuples are still in the table, but reusable.
The free_space column and free_percent is a better description of table
bloat from data turnover cleaned up by autovacuum.
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h more controller
chips can (purportedly) push upwards of 6GB/s, which is a tad faster
than the 800MB/s (measured) of our ancient gen-1 cards.
Too many variables. -_-
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of this will probably pan out, but I need to see the limits of how
badly I can abuse the database.
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ld tables has a
low cost, but it's not zero. With about a dozen of them, query times
increase from 0.130ms to 0.280ms for my test case. Not a lot in the long
run, but in a OLTP system, it can be fairly noticeable.
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telling devs to use current_date instead of ORM
injections, then. Hopefully we can track down and tweak the affected
queries on the tables we're partitioning without too much work and QA.
Thanks, Tom!
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31
pg_proc
SET provolatile = 'i'
WHERE proname = 'date_in';
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apparently detrimental to query execution.
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ong, and I can't seem to come up with
a workaround other than, "Ok devs, hard code dates into all of your
queries from now on."
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, and we were getting some really bad query plans unless we
*strongly* suggested RPC was cheap. I was afraid I'd have to go lower,
but 1 seemed to do the trick.
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ce
* 2 years, 3 months in operation
* 1.29PB written
* 1.75PB read
The load on our system right now is 3.7 on a 24 CPU box while serving
4100 TPS after active trading hours. The FusionIO drive is basically the
only reason we can do all of that without a lot of excessive contortions.
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Shaun Thomas
that would run
into performance problems with a (relatively inexpensive) setup like this.
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read queue, which
suggests a firmware issue.
Often this is because the device was optimized for sequential reads and
post lower IOPS than is theoretically possible so they can advertise
higher numbers alongside consumer-grade disks. They're Greg's disks
though. :)
--
Shaun Thomas
ZIL would compare. It's still disk-based, but the
transparent SSD layer acting as a gigantic passive read and write cache
intrigue me. It seems like it would also make a good middle-ground
concerning cost vs. performance.
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Shaun Thomas
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ut those situations are few and far between in a
heavy transactional setting. Having used NVRAM/SSDs, I could never go
back so long as the budget allows us to procure them.
A data warehouse? Maybe spindles still have a place there. Heavy
transactional system? Not a chance.
--
Shaun Thomas
factor of 1000, which is the actual problem.
The other reason I tried the combined index was that there was some
noise a while back about having the planner check for possible column
correlations on composite indexes. Clearly that ended up not being the
case, but it was worth examination.
--
Shaun
with functional indexes. It would
definitely be nice to override the stats with known correlations when
possible.
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but never any consensus. Anyone
care to comment?
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th
27;t complete enough, so it thinks there
are few matches. If that doesn't work and you want a quick, but ugly fix
for this, you can create the following index:
CREATE INDEX event_20130406_id_desc_tstamp_utc_idx
ON event_20130406 (id DESC, tstamp_utc);
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Settings that are new, and could assist in setting up streaming or backups:
wal_level
max_wal_senders
People are getting more and more vocal about increasing cpu_tuple_cost,
as the default is apparently too low in practice.
Everything else? Salt to taste.
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autogrouping and increasing sched_migration_cost. If the completely fair
scheduler has less locking contention with this patch-set, those tweaks
may not even be necessary. I need to see if I can find a system to test on.
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ms to work
without major adverse effects. Apparently the tiny table really will be
tiny in actual use, so impact should be minimal.
I just really don't like using subselects that way. :)
Thanks, Tom!
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sure what's going on here. I
sense an optimization fence, but I can't see where.
Thanks in advance!
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ly ones who ran into this, too. You settled on
a much higher setting than we did, but the end result was the same. I
wonder how prevalent this will become as more servers are switched over
to newer kernels in the next couple of years. Hopefully more people
start complaining so they fix
y prefer PostgreSQL's approach...
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squat about internal kernel mechanics. Anyone who
actually *isn't* talking out of his ass is free to interject. :)
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itself or combined with Linux terms is tremendously unhelpful.
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s with the
Completely Fair Scheduler, as opposed to the O(1) scheduler. For all
intents and purposes, this means 3.0 kernels and above.
With a 2.6 kernel, you're fine.
Effectively these changes fix what is basically a performance regression
compared to older kernels.
--
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Optio
scheduler settings
should be modified under different usage scenarios.
I just figured I'd share, since we found this info so beneficial.
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y this, because frankly, I find it difficult to believe.
If legit, high-connection systems would benefit greatly.
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x27;m still curious why only recent 3.2's cause it, but 3.4 don't. That's
mighty odd.
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4
levels, but that's expected. I haven't checked 3.0, but other threads
I've read suggest it had less problems. Sorry if I wasn't clear.
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3.4, but still happens.
If anyone has tested against 3.6 or 3.7, I'd love to hear your input.
Inconsistent load reports are one thing... strangled performance and
inflated CPU usage are quite another.
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own tests prove beneficial.
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er
eclectic and a little wonky, or that nailing down load calculations went
awry since the NOHZ stuff started, or both. At this point, I wish we'd
stayed on CentOS.
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read IO by reducing shared_buffers to 4GB.
Without as many reads, your writes should be much less disruptive.
You'll need to restart PG to adopt that change.
But I encourage you to keep iostat running in a terminal window so you
can watch it for a while. It's very revealing.
--
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er. You should also use sar. Just a plain:
sar 1 100
Will give you a lot of info on what the CPU is doing. You want that
%iowait column to be as low as possible.
Keep us updated.
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7;s some
other write stream happening we're not privy to.
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t
The rest of this is fine, except that you probably should have added:
sudo chown -R postgres:postgres /ssd/pg_xlog/*
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. Increase that to a few hundred, and my TPS drops down to
30k. Simply having the clients there kills performance.
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e performance of the master does it?
Only if you're using synchronous replication. From what I saw in the
config, that isn't the case.
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the kernel
decides to write out dirty memory. That can make checkpoints take
minutes to commit in some cases, which basically stops all write traffic
to your database entirely.
That should get you going, anyway. You still need more/better disks so
you can move your pg_xlog directory. With you
spec three years ago, and
unsuited to database use simply due to the 2-disk RAID.
Is the only way out of this really a SSD disk?
No. There are many, many steps you can and should take before going this
route. You need to know the problem you're solving before making
potentially expensive
mp tables because I know that's how they work.
But I'd be more than willing to modify my syntax one way or the other to
adopt non-materialized CTEs, provided there's some way to get the
current behavior.
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ur X5675's perform about 40-50% better with HT
enabled. Not the 2x you might expect by doubling the amount of
"processors", but it definitely didn't make things worse.
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using HASH indexes, though. They're not WAL
logged, so they can't be replicated, and they're also not crash safe.
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erved in their own private pool or something.
I mean... a pool is basically a proxy server. I don't have 12 individual
proxy servers for 12 webservers.
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stho...@option
same. So it
would be very helpful to also see the actual CREATE TABLE, and CREATE
INDEX statements for those tables.
We can't help you with this limited information. Sorry.
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OptionsHouse | 141 W. Jackson Blvd. | Suite 500 | Chicago IL, 60604
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ilar with
8.2. Even 8.3 is on the way to retirement. You're *six* major versions
behind the main release.
At the very least, you need to upgrade PostgreSQL from 8.1.17 to 8.1.23.
You're still on a version of PG that's almost 7-years old, but at least
you'd have the most rec
ws a
heavy preference for freeing memory from proc 0. It seems to only do it
on this node, so we're going to switch nodes soon and see if the problem
reappears. We may have to perform a node hardware audit if this persists.
Thanks for your input, though. :)
--
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OptionsHouse | 141
performance.
I mean, I get it. I just wonder if this particular tweak isn't more of a
regression than initially thought.
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S
That really bit us in the ass until
EnterpriseDB sent us a patch. From browsing the threads, didn't someone
say a similar problem existed in PG core?
--
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OptionsHouse | 141 W. Jackson Blvd. | Suite 500 | Chicago IL, 60604
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g else. I was trying to produce a clean-room to showcase this.
But I'm seeing it everywhere I test, even with sane settings.
Our EDB server is doing the same thing on much beefier hardware and
correspondingly increased settings, which is what prompted me to test it
in plai
eed.
It took us days to figure this out, so I figured I'd share.
Thanks, everyone!
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ish, really.
Or is there some embedded magic in streaming replication that requires
start/stop backup? I've never had problems starting slaves built from an
rsync before.
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On 10/24/2012 02:31 PM, Shaun Thomas wrote:
The main flaw with my example is that it's random. But I swear I'm not
making it up! :)
And then I find a way to make it non-random. Hooray:
CREATE TABLE date_test (
id SERIAL,
col1 varchar,
col2 numeric,
action_date TIMESTAMP WI
nc on date_test
(cost=0.00..9.37 rows=1 width=23) (actual time=77.046..77.046 rows=0
loops=1)
Index Cond: (date_trunc('day'::text, action_date) >=
'2012-10-24 00:00:00'::timestamp without time zone)
Filter: (((col1)::text = 'S:96'::text) AND (col2 =
erriding problem seems to be two-fold:
1. Is there any way to specifically set stats on a functional index?
2. Why is the planner so ridiculously optimistic with functional
indexes, even in the case of much higher selectivity as reported by
pg_stats on the named columns?
Thanks!
n case someone else encounters this.
Yes, even if that answer is "reboot." :)
Thanks again!
--
Shaun Thomas
OptionsHouse | 141 W. Jackson Blvd. | Suite 500 | Chicago IL, 60604
312-444-8534
stho...@optionshouse.com
__
See http://www.peak6.c
after the market closes to see if the
unallocated chunk shrinks.
--
Shaun Thomas
OptionsHouse | 141 W. Jackson Blvd. | Suite 500 | Chicago IL, 60604
312-444-8534
stho...@optionshouse.com
__
See http://www.peak6.com/email_disclaimer/ for terms and con
y segments directly to any large block. With MySQL, it's not
uncommon to dedicate over 50% of RAM to the MySQL process itself, but I
don't often see PG systems with more than 8GB in shared_buffers.
All the rest should be available for random allocation in general. At
least, in theor
2 4 6 8 10 12 14 16 18 20 22
node 0 size: 36853 MB
node 0 free: 13816 MB
node 1 cpus: 1 3 5 7 9 11 13 15 17 19 21 23
node 1 size: 36863 MB
node 1 free: 751 MB
node distances:
node 0 1
0: 10 20
1: 20 10
Looks like CPU 0 is hoarding memory. :(
--
Shaun Thomas
OptionsHouse | 141 W. J
t, anywhere from
20-60% disk utilization that's mostly reads.
It's pretty aggressively keeping that 14GB free, and it's driving me
nuts. :)
--
Shaun Thomas
OptionsHouse | 141 W. Jackson Blvd. | Suite 500 | Chicago IL, 60604
312-444-8534
stho...@optionshouse.com
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