at's not how it works, normally. I'd suggest adding an ON TRUNCATE
trigger to the table.
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e rows?
Incidentally, any time I get into deleting large numbers of rows, I
generally find it faster to rebuild the table instead ...
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(any opinions are my own)
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That's nice to hear.
> Will this 1GO restriction is supposed to increase in a near future ?
Not planned, no. Thing is, that's the limit for a field in general, not
just JSON; changing it would be a fairly large patch. It's desireable,
but AFAIK nobody is working on it.
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es for previous threads.
Also see Tomas's correlated stats patch submitted for 9.6.
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On 10/06/2015 02:33 AM, FattahRozzaq wrote:
> @Merlin Moncure, I got the calculation using pg_tune. And I modified
> the shared_buffers=24GB and the effective_cache_size=64GB
I really need to get Greg to take down pg_tune. It's way out of date.
Probably, I should replace it.
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gnificantly, the seqscan query is also
the most complex query run against the replica, so maybe the seqscan is
irrelevant and it's being affected by planner issues?
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only takes 2.5 seconds to execute on the
master. So even if the update is blocking the seq scans on the replica
(and I can't see why it would), it should only block them for < 3 seconds.
Anyone seen anything like this?
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after migration to 9.5.
Thank you for testing!
Can you re-run your tests with the fixed schema? How does it look?
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e that.
I think you have a driver, kernel, Linux memory management, or IO stack
issue.
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on X
and/or Y possibly overwriting the same rows on Z?
* is that autovacuum a regular autovacuum, or is it "to prevent wraparound"?
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To make c
periodically. What does IO throughput look like
before/during/after the stalls?
The last was the cause the last time I dealt with a situation like
yours; it turned out the issue was bad RAID card firmware where the card
would lock up whenever the write-through buffer got too much pressure.
ping a new public benchmark.
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> custom ROWS clause
>
> *) try alternate indexing strategy such as jsonb/jsquery
>
> *) move out of hstore and into more standard relational strucure
You forgot:
*) Fund a PostgreSQL developer to add selectivity estimation and stats
to hstore.
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ld have caused this
particular error. Are you certain that this is a recent problem?
Note that this error affects just one compressed value or row, so you're
not losing other data, unless it's a symptom of an ongoing problem.
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On 05/21/2015 01:39 PM, Andres Freund wrote:
> On 2015-05-21 11:54:40 -0700, Josh Berkus wrote:
>> This has been talked about as a feature, but would require major work on
>> PostgreSQL to make it possible. You'd be looking at several months of
>> effort by a really goo
d hacker, and then a whole bunch of performance
testing. If you have the budget for this, then please let's talk about
it because right now nobody is working on it.
Note that this could be a dead end; it's possible that preallocating
large extents could cause worse problems than the current f
(read-write)
>
>
> performance with 3.18 (pgbench, size 100, 32 clients)
>
> 129 303 transactions per second (read only)
> 16 895 transactions (read-write)
Thanks for that data! I'm glad to see that 3.18 has improved so much.
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nce is literally 2X to 5X different between kernels.
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On 04/07/2015 09:46 AM, Mel Llaguno wrote:
> FYI - all my tests were conducted using Ubuntu 12.04 x64 LTS (which I
> believe are all 3.xx series kernels).
If it's 3.2 or 3.5, then your tests aren't useful, I'm afraid. Both of
those kernels have known, severe, memory managem
d, I can't swap out kernels.
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All,
I currently have access to a matched pair of 20-core, 128GB RAM servers
with SSD-PCI storage, for about 2 weeks before they go into production.
Are there any performance tests people would like to see me run on
these? Otherwise, I'll just do some pgbench and DVDStore.
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On 03/16/2015 11:26 AM, Tom Lane wrote:
> Josh Berkus writes:
>> So ... should I assume my diagnosis is correct? Haven't heard any other
>> suggestions.
>
> I don't see any reason to think this is worth worrying about, or worth
> spending planner cycles on to
ernels 3.0 to 3.8 really needs to upgrade soon.
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So ... should I assume my diagnosis is correct? Haven't heard any other
suggestions.
On 02/27/2015 05:28 PM, Josh Berkus wrote:
> All:
>
> This got posted to pgsql-bugs, but got no attention there[1], so I'm
> sending it to this list.
>
> Test case:
>
> cr
the planner returns a fictitious cost for the whole query.
Or is there something else at work here?
[1]
http://www.postgresql.org/message-id/20150225194953.2546.86...@wrigleys.postgresql.org
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> carefully, it also seems to work with index scan partially in case of
> equality comparisons.
Seems like a good use for SP-GiST. Go for it!
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fact, I am just today dismantling an EAV database and normalizing
it, and so far application throughput is up 500%)
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On 02/02/2015 05:48 PM, Jim Nasby wrote:
> On 2/1/15 3:08 PM, Josh Berkus wrote:
>> I'm not clear on what you're suggesting here. I'm discussing how the
>> stats for a JSONB field would be stored and accessed; I don't understand
>> what that has to d
On 01/30/2015 05:34 PM, Jim Nasby wrote:
> On 1/30/15 2:26 PM, Josh Berkus wrote:
>> This would probably work because there aren't a lot of data structures
>> where people would have the same key:value pair in different locations
>> in the JSON, and care about it stats-w
Seq Scan on articles (cost=0.00..2289.21 rows=33 width=427)"
> " Filter: (data @> '{"locked": true}'::jsonb)"
> ---
Please send us the output of EXPLAIN ( ANALYZE ON, BUFFERS ON ) so that
we can see what the query is actually doing, rather than just wha
On 01/28/2015 03:50 PM, Peter Geoghegan wrote:
> On Wed, Jan 28, 2015 at 3:42 PM, Josh Berkus wrote:
>> jsonb_col @> '[ "key1" ]'
>> or jsonb_col ? 'key1'
>> if in MCE, assign % from MCE
>> otherwise assign 1% of non-MCE
On 01/28/2015 03:34 PM, Peter Geoghegan wrote:
> On Wed, Jan 28, 2015 at 3:03 PM, Josh Berkus wrote:
>> We already have most_common_elem (MCE) for arrays and tsearch. What if
>> we put JSONB's most common top-level keys (or array elements, depending)
>> in the MCE a
On 01/28/2015 11:48 AM, Tomas Vondra wrote:
> On 27.1.2015 08:06, Josh Berkus wrote:
>> Folks,
>>
> ...
>>
>> On a normal column, I'd raise n_distinct to reflect the higher
>> selecivity of the search terms. However, since @> uses contsel,
>
; '["math", "physics"]'::jsonb)
Planning time: 0.093 ms
Execution time: 7.632 ms
On a normal column, I'd raise n_distinct to reflect the higher
selecivity of the search terms. However, since @> uses contsel,
n_distinct is ignored. Anyone know a clever
uspect that it's the
other issue with Tom mentioned, which is that 9.2 really doesn't take
physical index size into account.
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To make changes to yo
can on
> file_state. Apologies for the confusion.
>
> I'm thinking that I'm seeing the effect Tom has just mentioned.
It's not using a bitmapscan in either case; it's a straight indexscan.
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ecause the same query, using
file_state, is 20X to 50X slower, because that index frequently gets
pushed out of memory.
What am I missing? Or is this potentially a planner bug for costing?
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variadic return times from a function which don't match
variadic input types. Returning a value as an actual numeric from JSONB
would require returning a numeric from a function whose input type is
text or json. So a known issue but one which would require a lot of
replumbing to fix.
-
o I'll
need to do some work to recreate the original bad plan circumstances.
I'll keep you posted on how the patch works for that setup.
It would be great to come up with a generic/public test for a bad
abort-early situation. Ideas?
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ne or libedit libraries for
your platform. How did you build PostgreSQL?
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enced by a foreign key constraint".
Oh, come on. We had hardly any problems with that patch!
;-)
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On 11/10/2014 01:40 PM, Alvaro Herrera wrote:
> Josh Berkus wrote:
>> All,
>>
>> pg version: 9.3.5
>> RHEL 6.5
>> 128GB/32 cores
>> Configured with shared_buffers=16GB
>> Java/Tomcat/JDBC application
>>
>> Server has an issue that whenever
ven that I'm seeing preposterously long BIND times (like
50 seconds), I don't think that's explained just by bad plans.
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27;ll have more
information when I do: for example, is it ALL queries which are slow or
just some of them?
However, I thought this list would have some other ideas where to look.
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On 11/10/2014 11:11 AM, Tom Lane wrote:
> Josh Berkus writes:
>> On 11/10/2014 10:59 AM, Jeff Janes wrote:
>>> On Mon, Nov 10, 2014 at 10:48 AM, Josh Berkus wrote:
>>>> Did this patch every make it in? Or did it hang waiting for verification?
&g
On 11/10/2014 10:59 AM, Jeff Janes wrote:
> On Mon, Nov 10, 2014 at 10:48 AM, Josh Berkus wrote:
>
>> On 12/31/2013 09:55 AM, Tom Lane wrote:
>>> Josh Berkus writes:
>>>> Tom,
>>>>> There's an abbreviated version of this argument in
Tory,
Do you know if your workload involves a lot of lock-blocking,
particularly blocking on locks related to FKs? I'm tracing down a
problem which sounds similar to yours.
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On 12/31/2013 09:55 AM, Tom Lane wrote:
> Josh Berkus writes:
>> Tom,
>>> There's an abbreviated version of this argument in the comments in
>>> my proposed patch at
>>> http://www.postgresql.org/message-id/11927.1384199...@sss.pgh.pa.us
>>
that was on older versions of Postgres).
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.
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672.821433 (excluding connections establishing)
I suspect this is due to the improvements in writing less to WAL. If
so, good work, guys!
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To make changes to your su
ing else?
RH probably backpatches our fixes as they come out. They did in the
past, anyway.
I just had the impression from your original post that this was a new
system; if so, it would make sense to build it on a version of Postgres
which wasn't already EOL.
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On 10/10/2014 04:16 AM, Greg Stark wrote:
> On Thu, Oct 2, 2014 at 8:56 PM, Josh Berkus wrote:
>> Yes, it's only intractable if you're wedded to the idea of a tiny,
>> fixed-size sample. If we're allowed to sample, say, 1% of the table, we
>> can get a MU
kend ever used more than 3X work_mem. This is
partly because the level of parallelism in postgres is extremely
limited, so we can't actually sort 8 partitions at the same time.
BTW, 8.4 is EOL. Maybe time to upgrade?
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where underestimating
n_distinct produced a penalty. Now we do, and we ought to change algos.
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ing cost estimates based on what
the worst case cost looks like, correct? That seemed to be your
proposal from an earlier post. If so, we're in violent agreement here.
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On 09/26/2014 01:06 AM, Simon Riggs wrote:
> On 23 September 2014 00:56, Josh Berkus wrote:
>
>> We've hashed that out a bit, but frankly I think it's much more
>> profitable to pursue fixing the actual problem than providing a
>> workaround like "ris
ual problem than providing a
workaround like "risk", such as:
a) fixing n_distinct estimation
b) estimating stacked quals using better math (i.e. not assuming total
randomness)
c) developing some kind of correlation stats
Otherwise we would be just providing users with another knob there
On 09/19/2014 11:38 PM, Greg Stark wrote:
>
> On 19 Sep 2014 19:40, "Josh Berkus" <mailto:j...@agliodbs.com>> wrote:
>>
>> On 09/19/2014 10:15 AM, Merlin Moncure wrote:
>> > On Wed, Sep 17, 2014 at 7:11 PM, Josh Berkus <mailto:j...@agliodbs.com
due to transmission time, not disk
IO. Otherwise, please post your schema (well, a truncated version) and
your queries.
BTW, in cases like yours I've used a INT array instead of 500 columns to
good effect; it works slightly better with PostgreSQL's compression.
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On 09/19/2014 10:15 AM, Merlin Moncure wrote:
> On Wed, Sep 17, 2014 at 7:11 PM, Josh Berkus wrote:
>> This is the core issue with abort-early plans; they depend on our
>> statistics being extremely accurate, which we know they are not. And if
>> they're wrong, the exec
which is a < 1MB database, and one client and 1
thread, which is an interesting test I wouldn't necessarily have done
myself. I'll throw the same test on one of my machines and see how it does.
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climbs by 1000X or more. Abort-early
plans are inherently riskier than other types of query plans.
What I'm not clear on is why upgrading from 9.1 to 9.3 would bring about
this change. The stats are no more than 10% different across the
version change.
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nality of ddet_id, it might actually be slower to
use the index).
In addition, other folks on this thread have already pointed out the
memory settings issues to you.
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On 08/22/2014 07:02 AM, Andres Freund wrote:
> On 2014-08-21 14:02:26 -0700, Josh Berkus wrote:
>> On 08/20/2014 07:40 PM, Bruce Momjian wrote:
>>> Not sure how you can make such a blanket statement when so many people
>>> have tested and shown the benefits of hyper-thr
On 08/21/2014 04:08 PM, Steve Crawford wrote:
> On 08/21/2014 03:51 PM, Josh Berkus wrote:
>> On 08/21/2014 02:26 PM, Scott Marlowe wrote:
>>> I'm running almost the exact same setup in production as a spare. It
>>> has 4 of those CPUs, 256G RAM, and is currently
g a 3.2 kernel right now. I could probably get a later
> model kernel on it even.
You know about the IO performance issues with 3.2, yes?
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On 08/21/2014 02:11 PM, Bruce Momjian wrote:
> On Thu, Aug 21, 2014 at 02:02:26PM -0700, Josh Berkus wrote:
>> On 08/20/2014 07:40 PM, Bruce Momjian wrote:
>>> On Wed, Aug 20, 2014 at 12:13:50PM -0700, Josh Berkus wrote:
>>>> On a read-write test, it
On 08/20/2014 07:40 PM, Bruce Momjian wrote:
> On Wed, Aug 20, 2014 at 12:13:50PM -0700, Josh Berkus wrote:
>> On a read-write test, it's 10% faster with HT off as well.
>>
>> Further, from their production machine we've seen that having HT on
>> causes the ma
rther, from their production machine we've seen that having HT on
causes the machine to slow down by 5X whenever you get more than 40
cores (as in 100% of real cores or 50% of HT cores) worth of activity.
So we're definitely back to "If you're using PostgreSQL, turn off
Hyperthr
Mark,
Is the 60-core machine using some of the Intel chips which have 20
hyperthreaded virtual cores?
If so, I've been seeing some performance issues on these processors.
I'm currently doing a side-by-side hyperthreading on/off test.
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Folks,
So one thing we tell users who have chronically long IN() lists is that
they should create a temporary table and join against that instead.
Other than not having the code, is there a reason why PostgreSQL
shouldn't do something like this behind the scenes, automatically?
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Explained here:
https://www.usenix.org/system/files/conference/fast13/fast13-final80.pdf
13 out of 15 tested SSD's had various kinds of corruption on a power-out.
(thanks, Neil!)
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e! Any idea when it will be available? Our community could
really use some updated benchmark tooling ...
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ation do I need ? How much RAM ?
> - If not, would it be better to think about a cluster or other ?
> - (Have you any idea to optimize this table ?)
Consider also trying cstore_fdw: https://github.com/citusdata/cstore_fdw
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Linux kernel module.
NFS on Solaris/Illumos is a different story. Not sure about FreeBSD.
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AM?
2) is this a DW workload, where most writes are large writes?
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d run some different
sizes of pgbench.
I'd be particularly interested in the performance of ZFS tuning options
on Linux ...
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we probably would have done more design changes!"
HFS+ was written in about 6 months, and is largely unimproved since its
release in 1995. Ext2 doesn't perform too well, either; the difference
is that Linux users have alternative filesystems available.
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f a buffer of ready
connections to deal with the next peak when it comes in.
That also means that even if the pool is a fixed size, you want to
rotate in and out the actual sessions, so that they don't hang onto
maximum virtual memory indefinitely.
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vel did test it and reported that it successfully alleviates his
> real-world problem. So I'm now inclined to commit this. Objections?
None from me.
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environment.
Beyond that, I can't speculate.
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I'm really not clear on what you're trying to measure here. If you're
doing "time" from your PC, then network transmission time completely
dominates your reponse time ... and that can be affected by all kinds of
random variables.
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for separate
databases. This will mean lots of additional storage space -- the
per-DB overhead by itself will be 100GB -- but otherwise you'll be
grappling with the issues involved in having a million tables, which Joe
Conway outlined. But if you don't have shared tables, your huge s
we were entertaining the idea of running our Postgres database
> on our VM farm alongside our application vm's. We are planning to run a
> few Postgres synchronous replication nodes.
Biggest pitfall here is IO performance configuration. I can't give you
specific advice without knowing
their problems. We can't really determine
> what to do without that information.
Unfortunately, the original reporter of this issue will not be available
for testing for 2-3 weeks, and I haven't been able to devise a synthetic
test which clearly shows the issue.
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gt; max_connections = 350
> shared_buffers = 8GB
Try dropping shared_buffers to 2GB. We've seen some issues on certain
systems with 8GB shared buffers.
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To make c
table grew. However -- I'm not 100% sure of this, but it seems to have
> jumped recently (from 3-4 minutes to 7 minutes).
> *
> http://www.postgresql.org/message-id/20030323112241.w14634-100...@megazone23.bigpanda.com
Probably the table just got larger than RAM.
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Josh Berkus
Postgre
What did you find?
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Josh Berkus
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ght be right here.
Any thoughts on a fix for this we could get into 9.2.5?
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Josh Berkus
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llowed to check the clog until after
> you verify the transaction is no longer in progress, otherwise you open up
> race conditions.
In this particular case, I'd argue that we don't care about race
conditions -- it's a plan estimate. We certainly care about them a lot
less than l
On 09/19/2013 01:47 PM, Josh Berkus wrote:
> Test:
>
> 1. create a table with a range type column.
> 2. insert 1000 identical values into that column.
> 3. analyze
> 4. n-distinct will still be listed as -1 (unique) for the column.
>
> Why?
>
Anyone?
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Josh Be
ystem-wide contention, because it takes the
> ProcArrayLock, once per row which needs to be checked. So you have 20
> processes all fighting over the ProcArrayLock, each doing so 1000
times per
> query.
Why do we need a procarraylock for this? Seems like the solution would
be not to take
Test:
1. create a table with a range type column.
2. insert 1000 identical values into that column.
3. analyze
4. n-distinct will still be listed as -1 (unique) for the column.
Why?
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Josh Berkus
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f the index" optimization?
It's the story of our lives: we can't optimize anything without
deoptimizing something else. Dammit.
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Josh Berkus
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To
sure
about. Does that mean that 8.4 was unsafe, or that this is something
which *could* be fixed in later versions?
I'm also confused as to why this would affect BIND time rather than
EXECUTE time.
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Josh Berkus
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> We are using Hibernate in Java to interact with Postgres 9.1.
>
> Can you please suggest some test cases or some issues which may hamper us?
Port your application and run your smoke tests?
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Josh Berkus
PostgreSQL Experts Inc.
http://pgexperts.com
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for page 10,000 is a bot
screen-scraping your site, anyway.
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Josh Berkus
PostgreSQL Experts Inc.
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repeatedly. Per earlier on this
thread, that can bloat to 200X time required for a BIND, and it's
definitely PostgreSQL-side.
I'm trying to produce a test case which doesn't involve the user's
application. However, hints on other things to analyze would be keen.
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Josh Berkus
Po
| 0.00
bgwriter_halt_potential | 0.00
buffer_allocation_ratio | 0.288
And your query, with some rounding added:
-[ RECORD 1 ]---+--
alloc_mbps | 0.116
checkpoint_mbps | 0.340
clean_mbps | 0.000
backend_mbps| 0.056
write_mbps | 0.396
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Josh Berkus
PostgreSQL Experts
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