Hi John, I have now read the top-level documentation for LWR, and gone through the sample configurations. I would appreciate if you would answer a few technical questions for me. 1) How exactly is the "staging_directory" in "server.ini.sample" used? Is that intended to be the (final) location at which to put files on the remote server? How is the relative path structure under $GALAXY_ROOT/databases/files handled? 2) What exactly does "persistence_directory" in "server.ini.sample" mean? Where should it be located, how will it be used? 3) What exactly does "file_cache_dir" in "server.ini.sample" mean? 4) Does LWR preserve some relative path (e.g. to GALAXY_ROOT) under the above directories? 5) Are files renamed when cached? If so, are they eventually restored to their original names? 6) Is it possible to customize the DRMAA and/or qsub requests made by LWR, for example to include additional settings such as Project or a memory limit? Is it possible to customize this on a case by case basis, rather than globally? 7) Are there any options for the "queued_drmaa" manager in "job_managers.ini.sample" which are not listed in that file? 8) What exactly are the differences between the "queued_drmaa" manager and the "queued_cli" manager? Are there any options for the latter which are not in the "job_managers.ini.sample" file? 9) When I attempt to run LWR (not having completed all the mentioned preparation steps, namely without setting DRMAA_LIBRARY_PATH), I get a Seg fault. Is this because it can't find DRMAA or is it potentially unrelated? In the latter case, here's the error being output to the console: ./run.sh: line 65: 26277 Segmentation fault paster serve server.ini "$@" Lastly, a simple comment, hopefully helpful. It would be nice if the LWR install docs at least mentioned the dependency of PyOpenSSL 0.13 (or later) on OpenSSL 0.9.8f (or later), maybe even with a comment that "pip" will listen to the environment variables CFLAGS and LDFLAGS in the event one is creating a local installation of the OpenSSL library for LWR to use. Thank you for your time and assistance. Best, Eric ________________________________________ From: jmchilton@gmail.com [jmchilton@gmail.com] on behalf of John Chilton [chilton@msi.umn.edu] Sent: Tuesday, November 05, 2013 11:58 AM To: Paniagua, Eric Cc: Galaxy Dev [galaxy-dev@bx.psu.edu] Subject: Re: [galaxy-dev] Managing Data Locality Hey Eric, I think what you are purposing would be a major development effort and mirrors major development efforts ongoing. There are sortof ways to do this already, with various trade-offs, and none particularly well documented. So before undertaking this efforts I would dig into some alternatives. If you are using PBS, the PBS runner contains some logic for delegating to PBS for doing this kind of thing - I have never tried it. https://bitbucket.org/galaxy/galaxy-central/src/default/lib/galaxy/jobs/runn... In may be possible to use a specially configured handler and the Galaxy object store to stage files to a particular mount before running jobs - not sure it makes sense in this case. It might be worth looking into this (having the object store stage your files, instead of solving it at the job runner level). My recommendation however would be to investigate the LWR job runner. There are a bunch of fairly recent developments to enable something like what you are describing. For specificity lets say you are using DRMAA to talk to some HPC cluster and Galaxy's file data is stored in /galaxy/data on the galaxy web server but not on the HPC and there is some scratch space (/scratch) that is mounted on both the Galaxy web server and your HPC cluster. I would stand up an LWR (http://lwr.readthedocs.org/en/latest/) server right beside Galaxy on your web server. The LWR has a concept of managers that sort of mirrors the concept of runners in Galaxy - see the sample config for guidance on how to get it to talk with your cluster. It could use DRMAA, torque command-line tools, or condor at this time (I could add new methods e.g. PBS library if that would help). https://bitbucket.org/jmchilton/lwr/src/default/job_managers.ini.sample?at=d... On the Galaxy side, I would then create a job_conf.xml file telling certain HPC tools to be sent to the LWR. Be sure to enable the LWR runner at the top (see advanced example config) and then add at least one LWR destination. <destinations> .... <destination id="lwr" runner="lwr"> <param id="url">http://localhost:8913/</param> <!-- Leave Galaxy directory and data indices alone, assumes they are mounted in both places. --> <param id="default_file_action">none</param> <!-- Do stage everything in /galaxy/data though --> <param id="file_action_config">file_actions.json</param> </destination> Then create a file_actions.json file in the Galaxy root directory (structure of this file is subject to change, current json layout doesn't feel very Galaxy-ish). {"paths": [ {"path": "/galaxy/data", "action": "copy"} ] } More details on the structure of this file_actions.json file can be found in the following changeset: https://bitbucket.org/galaxy/galaxy-central/commits/b0b83be30136e2939a4a4f5d... I am really eager to see the LWR gain adoption and tackle tricky cases like this, so if there is anything I can do to help please let me know and contributions in terms of development or documentation would be greatly appreciated as well. Hope this helps, -John On Tue, Nov 5, 2013 at 8:23 AM, Paniagua, Eric <epaniagu@cshl.edu> wrote:
Dear Galaxy Developers,
I administer a Galaxy instance at Cold Spring Harbor Laboratory, which servers around 200 laboratory members. While our initial hardware purchase has scaled well for the last 3 years, we are finding that we can't quite keep up with rising the demand for compute-intensive jobs, such as mapping. We are hesitant to consider buying more hardware to support the load, since we can't expect that solution to scale.
Rather, we are attempting to set up Galaxy to queue jobs (especially mappers) out to the lab's HPCC to accommodate the increasing load. While there is a good number of technical challenges involved in this strategy, I am only writing to ask about one: data locality.
Normally, all Galaxy datasets are stored directly on the private server hosting our Galaxy instance. The HPCC cannot mount our Galaxy server's storage (ie: for the purpose of running jobs reading/writing datasets) for security reasons. However, we can mount a small portion of the HPCC file system to our Galaxy server. Storage on the HPCC is at a premium, so we can't afford to just let newly created (or copied) datasets just sit there. It follows that we need a mechanism for maintaining temporary storage in the (restricted) HPCC space which allows for transfer of input datasets to the HPCC (so they will be visible to jobs running there) and transfer of output datasets back to persistent storage on our server.
I am in the process of analyzing when/where/how exact path names are substituted into tool command lines, looking for potential hooks to facilitate the staging/unstaging of data before/after job execution on the HPCC. I have found a few places where I might try to insert logic for handling this case.
Before modifying too much of Galaxy's core code, I would like to know if there is a recommended method for handling this situation and whether other members of the Galaxy community have implemented fixes or workarounds for this or similar data locality issues. If you can offer either type of information, I shall be most grateful. Of course, if the answer were that there were no recommended or known technique, then that would be valuable information too.
Thank you in advance, Eric Paniagua
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