|From:||Scott Volkers <scottvolkers(at)gmail(dot)com>|
|To:||Jeff Janes <jeff(dot)janes(at)gmail(dot)com>|
|Subject:||Re: BUG #16148: Query on Large table hangs in ETL flows and gives out of memory when run in pgAdmin4|
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I may not have explained this well.
The long and the short of it is this where clause
FROM "elliedb"."documentlog" WHERE dcmodifiedutc>(extract(epoch from
TIMESTAMP '2019-11-15 11:30:51')*1000)
causes and out of memory error in PGAdmin. The query will not run. I am
testing it there because the same query will not run in Informatica ETL
task flow. It hangs our processes. No error returns in the Informatica
My reference to aggregation is the presumption of what Postgres Sql engine
is doing with the production of a result set.
On Wed, Dec 4, 2019 at 5:05 PM Jeff Janes <jeff(dot)janes(at)gmail(dot)com> wrote:
> On Wed, Dec 4, 2019 at 9:20 AM PG Bug reporting form <
> noreply(at)postgresql(dot)org> wrote:
>> The following bug has been logged on the website:
>> Bug reference: 16148
>> Logged by: Scott Volkers
>> Email address: scottvolkers(at)gmail(dot)com
>> PostgreSQL version: 9.5.15
>> Operating system: PostgreSQL 9.5.15 on x86_64-pc-linux-gnu, compiled
>> We have a large table and the error occurs with this where clause:
>> FROM "elliedb"."documentlog" WHERE dcmodifiedutc>(extract(epoch from
>> TIMESTAMP '2019-11-15 11:30:51')*1000)
>> When we reduce the scope to current time - 4 hours the query works within
>> where dcmodifiedutc > '1575282651000'
>> Is this expected? Is this a version issue being only 9.5?
> From "Now minus 4" hours to now covers 100 fold less time than from
> 2019-11-15 11:30:51 until now does. Assuming your data is evenly
> distributed over the past and doesn't have data from the future, then I
> think that yes, selecting 100 time more data is expected to take more time
> and more memory. pgAdmin4 is not well suited to loading giant data sets
> into memory. You can extract large data sets directly into files. This
> will not depend on the version.
>> It seems the
>> timestamp conversion would be done once and applied to the filter, but it
>> seems to ballooning the query result being aggregated for the where
> Is aggregation being used? You haven't shown any aggregation.
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