Re: [galaxy-dev] data collections - workflow - bug?
Torsten - thanks for reporting this. This bug was reported a few more times - and after several false starts I think we have finally found a fix (with a lot of help from Marius van den Beek, Philip Mabon, Aaron Petkau, and Franklin Bristow - big thanks to each of them). Pull Request with Fix: https://github.com/galaxyproject/galaxy/pull/52 Trello Card Tracking Progress: https://trello.com/c/I0n23JEP Thanks for the patience all, -John On Tue, Jan 27, 2015 at 12:35 PM, Torsten Houwaart houwa...@informatik.uni-freiburg.de wrote: I will try to build a smaller testcase that fails and talk about the job handlers with Björn tomorrow. I tried this with quite a big workflow which I built from scratch (in the editor). I'll get back to you. Best, Torsten On 27.01.2015 18:25, John Chilton wrote: Sorry again about this mixup (bringing conversation back on channel). Does this happen everytime you run a workflow with collections? Do you know how many job handlers Galaxy is configured with? -John On Mon, Jan 26, 2015 at 11:24 AM, John Chilton jmchil...@gmail.com wrote: Ugh misread sqlalchemy as sqlite. I will work on this. -John On Mon, Jan 26, 2015 at 11:16 AM, Torsten Houwaart houwa...@informatik.uni-freiburg.de wrote: Hi John, i ran this on the Galaxy server in Freiburg: galaxy.uni-freiburg.de Björn (who sits immediately opposite of my desk :) ) told me it's a Postres database and that shouldn't be the problem. Best, Torsten On 26.01.2015 16:48, John Chilton wrote: Hey, Really intensive database operations including datasest collections but other things too like multi-running tools or workflows over many individual datasets for instance - can very easily overwhelm the default sqlite database. This is frustrating and shouldn't happen - but it does unfortunately. I would recommend using a postgres database when testing out dataset collections. The good news is that it is easier than ever to get a fully fledged production-quality server thanks to Bjoern's docker server (https://github.com/bgruening/docker-galaxy-stable) - it comes bundled with Postgres and Slurm so it should be able to handle the collection operations. If you need to run Galaxy on a non-containerized server (for instance because that is where the software is) more information on setting up Galaxy can be found here https://wiki.galaxyproject.org/Admin/Config/Performance/ProductionServer. Here is a Trello card to track progress on the database optimization efforts if you are interested https://trello.com/c/UPLsMKQI. Very sorry. -John -John On Mon, Jan 26, 2015 at 9:35 AM, Torsten Houwaart houwa...@informatik.uni-freiburg.de wrote: Hello Galaxy Devs, I was using data collections (for the first time) for a new workflow of ours and I ran into this problem. There was no complaint by the workflow-editor and I could start the workflow but then see below happened. If you need more information about the workflow or otherwise let me know. Best, Torsten H. job traceback: Traceback (most recent call last): File /usr/local/galaxy/galaxy-dist/lib/galaxy/jobs/runners/__init__.py, line 565, in finish_job job_state.job_wrapper.finish( stdout, stderr, exit_code ) File /usr/local/galaxy/galaxy-dist/lib/galaxy/jobs/__init__.py, line 1250, in finish self.sa_session.flush() File /usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/scoping.py, line 114, in do return getattr(self.registry(), name)(*args, **kwargs) File /usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/session.py, line 1718, in flush self._flush(objects) File /usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/session.py, line 1789, in _flush flush_context.execute() File /usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/unitofwork.py, line 331, in execute rec.execute(self) File /usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/unitofwork.py, line 475, in execute uow File /usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/persistence.py, line 59, in save_obj mapper, table, update) File /usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/persistence.py, line 485, in _emit_update_statements execute(statement, params) File /usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/engine/base.py, line 1449, in execute params) File /usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/engine/base.py, line 1584, in _execute_clauseelement compiled_sql, distilled_params File
Re: [galaxy-dev] data collections - workflow - bug?
Hey,
Really intensive database operations including datasest collections
but other things too like multi-running tools or workflows over many
individual datasets for instance - can very easily overwhelm the
default sqlite database. This is frustrating and shouldn't happen -
but it does unfortunately. I would recommend using a postgres database
when testing out dataset collections. The good news is that it is
easier than ever to get a fully fledged production-quality server
thanks to Bjoern's docker server
(https://github.com/bgruening/docker-galaxy-stable) - it comes bundled
with Postgres and Slurm so it should be able to handle the collection
operations. If you need to run Galaxy on a non-containerized server
(for instance because that is where the software is) more information
on setting up Galaxy can be found here
https://wiki.galaxyproject.org/Admin/Config/Performance/ProductionServer.
Here is a Trello card to track progress on the database optimization
efforts if you are interested https://trello.com/c/UPLsMKQI.
Very sorry.
-John
-John
On Mon, Jan 26, 2015 at 9:35 AM, Torsten Houwaart
houwa...@informatik.uni-freiburg.de wrote:
Hello Galaxy Devs,
I was using data collections (for the first time) for a new workflow of ours
and I ran into this problem. There was no complaint by the workflow-editor
and I could start the workflow but then see below happened.
If you need more information about the workflow or otherwise let me know.
Best,
Torsten H.
job traceback:
Traceback (most recent call last):
File /usr/local/galaxy/galaxy-dist/lib/galaxy/jobs/runners/__init__.py,
line 565, in finish_job
job_state.job_wrapper.finish( stdout, stderr, exit_code )
File /usr/local/galaxy/galaxy-dist/lib/galaxy/jobs/__init__.py, line
1250, in finish
self.sa_session.flush()
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/scoping.py,
line 114, in do
return getattr(self.registry(), name)(*args, **kwargs)
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/session.py,
line 1718, in flush
self._flush(objects)
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/session.py,
line 1789, in _flush
flush_context.execute()
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/unitofwork.py,
line 331, in execute
rec.execute(self)
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/unitofwork.py,
line 475, in execute
uow
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/persistence.py,
line 59, in save_obj
mapper, table, update)
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/orm/persistence.py,
line 485, in _emit_update_statements
execute(statement, params)
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/engine/base.py,
line 1449, in execute
params)
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/engine/base.py,
line 1584, in _execute_clauseelement
compiled_sql, distilled_params
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/engine/base.py,
line 1698, in _execute_context
context)
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/engine/base.py,
line 1691, in _execute_context
context)
File
/usr/local/galaxy/galaxy-dist/eggs/SQLAlchemy-0.7.9-py2.7-linux-x86_64-ucs2.egg/sqlalchemy/engine/default.py,
line 331, in do_execute
cursor.execute(statement, parameters)
DBAPIError: (TransactionRollbackError) deadlock detected
DETAIL: Process 3144 waits for ShareLock on transaction 2517124; blocked by
process 3143.
Process 3143 waits for ShareLock on transaction 2517123; blocked by process
3144.
HINT: See server log for query details.
'UPDATE workflow_invocation SET update_time=%(update_time)s WHERE
workflow_invocation.id = %(workflow_invocation_id)s' {'update_time':
datetime.datetime(2015, 1, 26, 14, 20, 4, 155440), 'workflow_invocation_id':
5454}
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