On Jul 19, 2010, at 9:52 AM, Adrian Price-Whelan wrote: > Hi, > > I was just wondering at first whether there was a known issue with > ARRAY types, but here is the query: > spectra = > session.query(Spectrum).join(SpectrumHeader).filter(SpectrumHeader.filename > == spPlateFilename).all() > > It should return ~1000 objects equaling about 120MB of data. In > Python, this query takes >10 minutes to complete, but as a SQL query > (copying and pasting the echo'd command) it takes a few seconds: > SELECT spectrum.pk AS spectrum_pk, spectrum.ra AS spectrum_ra, > spectrum.dec AS spectrum_dec, spectrum.values AS spectrum_values, > spectrum.spectrum_header_pk AS spectrum_spectrum_header_pk, > spectrum.fiber_number AS spectrum_fiber_number, spectrum.inv_var AS > spectrum_inv_var, spectrum.and_mask AS spectrum_and_mask, > spectrum.or_mask AS spectrum_or_mask FROM spectrum JOIN > spectrum_header ON spectrum_header.pk = spectrum.spectrum_header_pk > WHERE spectrum_header.filename = 'spPlate-3586-55181.fits' > > autoflush and autocommit are both set to False. > > It seems like a straightforward query so I'm confused as to what could > be getting hung up.
does it take a few seconds to fully fetch all the results and it only gets 1000 rows ? or is that just to get the initial result? these are different things. also if any of the individual columns are very large BLOBs or perhaps very large PG arrays that would add to the overhead of a fetch. You can also try writing a DBAPI-only script that runs the query, as well as running engine.execute(myquery.statement) and fetching rows that way to see if some in-object process is the factor (which is unlikely). > > Thanks for any insight, > > Adrian > > On Jul 16, 10:24 pm, Michael Bayer <mike...@zzzcomputing.com> wrote: >> You absolutely need to turn in echoing and locate the specific SQL query >> which causes the issue. Queries can take excessive time for a very wide >> variety of reasons. >> >> On Jul 16, 2010, at 12:56 PM, Adrian Price-Whelan wrote: >> >> >> >>> Hello -- >> >>> I'm working with a database populated with data originally from a file >>> structure of files that are ~150MB each. We are dealing with a lot of data >>> that is being stored in the database using the 'ARRAY' datatype, >>> specifically numeric[]. After loading some of the data into the database I >>> tried performing a query to get back some data, and comparing it with code >>> that reads directly from the file system - but the database query took ~50 >>> times longer to complete. For instance, to retrieve 100 records that >>> contain a few 4000 element arrays each using the code that reads the >>> filesystem it took less than a second, but the query on the database took >>> around 25 seconds to complete. Has anyone else had issues with array types >>> slowing down queries or does this sound more like another issue? >> >>> Thanks! >>> Adrian >> >>> -- >>> You received this message because you are subscribed to the Google Groups >>> "sqlalchemy" group. >>> To post to this group, send email to sqlalch...@googlegroups.com. >>> To unsubscribe from this group, send email to >>> sqlalchemy+unsubscr...@googlegroups.com. >>> For more options, visit this group >>> athttp://groups.google.com/group/sqlalchemy?hl=en. > > -- > You received this message because you are subscribed to the Google Groups > "sqlalchemy" group. > To post to this group, send email to sqlalch...@googlegroups.com. > To unsubscribe from this group, send email to > sqlalchemy+unsubscr...@googlegroups.com. > For more options, visit this group at > http://groups.google.com/group/sqlalchemy?hl=en. > -- You received this message because you are subscribed to the Google Groups "sqlalchemy" group. To post to this group, send email to sqlalch...@googlegroups.com. To unsubscribe from this group, send email to sqlalchemy+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/sqlalchemy?hl=en.
