We routinely put large compressed fastq files into data libraries by that method (linking,
no copy) and it is very fast, since the patch that stopped it decompressing the files.
You should probably make sure you specify the file format (fastqsanger) so Galaxy does not
attempt to sniff the file to learn its datatype.
Sr. Staff Software Engineer
9885 Towne Centre Drive
San Diego, CA 92121
From: galaxy-dev-bounces(a)lists.bx.psu.edu [mailto:email@example.com] On
Behalf Of Jennifer Jackson
Sent: Thursday, September 29, 2011 12:13 PM
To: Roman Valls; Galaxy-Dev
Subject: Re: [galaxy-dev] [galaxy-user] Add library to dataset performance metric:
developer vs production instances
This is a good question for the development community to provide
feedback on, so I'll cross-post your question over to that list.
On 9/19/11 2:30 PM, Roman Valls wrote:
Today I was routinely adding a 27GB Illumina lane on my galaxy instance
running on a cluster node. Just the regular cloned-from-hg type of
instance with set_metadata_externally, no more tuning.
It took more than 10 minutes to have the dataset imported into a data
library via the filesystem path upload method... not copying it into
galaxy, just "linking".
galaxy.jobs INFO 2011-09-19 18:05:08,641 job 120 dispatched
galaxy.jobs DEBUG 2011-09-19 18:16:52,822 job 120 ended
galaxy.datatypes.metadata DEBUG 2011-09-19 18:16:52,824 Cleaning up
external metadata files
Since I cannot add datasets to libraries in usegalaxy.org
and compare, I
was wondering if someone can state an approximated average time *for a
production* galaxy installation to do that operation.
I would like to have some empirical number to show on how a production
deployment could speed things up, as opposed to having individual
galaxy instances per user in a cluster (as per IT policies):
Thanks in advance !
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