On Jan 5, 2017, at 1:38 PM, Rémi Cura wrote:
>
> Hey,
> 1 sec seems really good in this case,
> and I'm assuming you tuned postgres so the main index fits into ram (work_mem
> and all other stuff).
>
> You could avoid a CTE by mixing both cte.
>
> WITH pts AS (
>
Ah, yes indeed. Upping the segment length to 1,000 brings the execution time down to 642 ms, and further upping it to 10,000 brings the execution time down again to 442.104 ms. I'll have to play around with it and see where the minimum is. Would that be likely to vary depending on initial path
Hey,
1 sec seems really good in this case,
and I'm assuming you tuned postgres so the main index fits into ram
(work_mem and all other stuff).
You could avoid a CTE by mixing both cte.
WITH pts AS (
SELECT (pt).geom, (pt).path[1] as vert
FROM
ST_DumpPoints(
ST_Segmentize(
Varying the segment length upwards might have a salutary effect for a
while, as the efficiency improvement of fewer inner loops battles with the
inefficiency of having more points selected by the index filter. Worth an
experiment.
P
On Thu, Jan 5, 2017 at 1:00 PM, Israel Brewster
Hi,
I got this scenario:
master01
--> slave01 ---> slave02 -> slave03 ---> slave04
As you can see, slave03 replicates from slave02 and slave04 from slave03.
I'm promoting slave03 into a master, and trying to make slave04 to be able
to connect to its new master.
AS i'm using PostgreSQL
=?UTF-8?Q?Torsten_F=C3=B6rtsch?= writes:
> This hex string decodes to something sensible:
> $ perl -le 'print pack "H*", shift'
> 246c69626469722f757466385f616e645f69736f383835395f31
> $libdir/utf8_and_iso8859_1
> Maybe it rings a bell.
Hah, that's pretty suggestive. So
This hex string decodes to something sensible:
$ perl -le 'print pack "H*", shift'
246c69626469722f757466385f616e645f69736f383835395f31
$libdir/utf8_and_iso8859_1
Maybe it rings a bell.
On Thu, Jan 5, 2017 at 7:57 PM, BRUSSER Michael
wrote:
> I see this with
> On Jan 5, 2017, at 10:38 AM, Paul Ramsey wrote:
>
> Yes, you did. You want a query that spits out a tupleset of goemetries (one
> each for each wee segment), and then you can join that set to your main table
> using st_dwithin() as the join clause.
> So start by
Yes, you did. You want a query that spits out a tupleset of goemetries (one
each for each wee segment), and then you can join that set to your main
table using st_dwithin() as the join clause.
So start by ditching the main table and just work on a query that generates
a pile of wee segments.
On
On Jan 5, 2017, at 8:50 AM, Paul Ramsey wrote:
>
> The index filters using bounding boxes. A long, diagonal route will have a
> large bounding box, relative to the area you actually care about (within a
> narrow strip of the route). Use ST_Segmentize() to add points
On Wed, Jan 4, 2017 at 8:49 AM, Kevin Grittner wrote:
> On Wed, Dec 28, 2016 at 10:58 AM, Steven Grimm wrote:
>
>> WHERE ((e.timeStamp > '2016-12-19T20:34:22.315Z')
>> OR (e.timeStamp = '2016-12-19T20:34:22.315Z'
>> AND
On 01/05/2017 11:46 AM, Adrian Klaver wrote:
On 01/05/2017 08:31 AM, Rob Sargent wrote:
On 01/05/2017 05:44 AM, vod vos wrote:
I finally figured it out as follows:
1. modified the corresponding data type of the columns to the csv file
2. if null values existed, defined the data type to
I see this with PostgreSQL 9.4.7 and some 8.x versions running on Linux Red Hat.
Older versions "supposedly" do not exhibit this behavior, but I didn't check.
$ psql
Password:
psql: FATAL: could not access file
"\x246c69626469722f757466385f616e645f69736f383835395f31": No such file or
directory
On 01/05/2017 08:31 AM, Rob Sargent wrote:
On 01/05/2017 05:44 AM, vod vos wrote:
I finally figured it out as follows:
1. modified the corresponding data type of the columns to the csv file
2. if null values existed, defined the data type to varchar. The null
values cause problem too.
so
The index filters using bounding boxes. A long, diagonal route will have a
large bounding box, relative to the area you actually care about (within a
narrow strip of the route). Use ST_Segmentize() to add points to your
route, ST_DumpPoints() to dump those out as point and ST_MakeLine to
generate
I have a database (PostgreSQL 9.6.1) containing 62,702,675 rows of latitude (numeric), longitude(numeric), elevation(integer) data, along with a PostGIS (2.3.0) geometry column (location), running on a CentOS 6.8 box with 64GB RAM and a RAID10 SSD data drive. I'm trying to get the maximum
Job writes:
> Could you please help me?
There's advice here on how to ask this type of question with enough
detail to get answers:
https://wiki.postgresql.org/wiki/Slow_Query_Questions
regards, tom lane
--
Sent via pgsql-general mailing
On 01/05/2017 10:18 AM, Job wrote:
Hello guys,
a very strange thing: after upgrading from 8.4.22 to 9.6.1 i noticed,
under heavy beanchmarks, a really slowdown of Postgresql 9.6.1, with
the machine really "without breath".
By replacing Postgresql 8.4.22 evberything returns working fine.
Hello guys,
a very strange thing: after upgrading from 8.4.22 to 9.6.1 i noticed, under
heavy beanchmarks, a really slowdown of Postgresql 9.6.1, with the machine
really "without breath".
By replacing Postgresql 8.4.22 evberything returns working fine.
With three days of investigation, i come
On 01/05/2017 05:44 AM, vod vos wrote:
I finally figured it out as follows:
1. modified the corresponding data type of the columns to the csv file
2. if null values existed, defined the data type to varchar. The null
values cause problem too.
so 1100 culumns work well now.
This problem
Hi,
there is something happening in my replication that is not clear to me. I
think I'm missing something.
I've two server, red and blue.
red is primary blue is standby, async repl.
Now:
1 cleanly stop red
2 promote blue
3 insert tuples in blue
4 from red site, pg_rewind from blue to red dir.
5
On 01/05/2017 04:44 AM, vod vos wrote:
I finally figured it out as follows:
1. modified the corresponding data type of the columns to the csv file
2. if null values existed, defined the data type to varchar. The null
values cause problem too.
Did you change the NULLs to something else?
As
2017-01-05 13:44 GMT+01:00 vod vos :
> I finally figured it out as follows:
>
> 1. modified the corresponding data type of the columns to the csv file
>
> 2. if null values existed, defined the data type to varchar. The null
> values cause problem too.
>
int, float, double can
Well, unfortunately i am not seeing much difference. I shaved off maybe a
second of worst case run.
I guess i should just split the db into smaller ones, since tmpstats are
now per-db. Are there any other things i could try?
2017-01-05 8:18 GMT+01:00 marcin kowalski :
>
I finally figured it out as follows:
1. modified the corresponding data type of the columns to the csv file
2. if null values existed, defined the data type to varchar. The null values
cause problem too.
so 1100 culumns work well now.
This problem wasted me three days. I have lots of
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