I have a table in an HDF5 file consisting of 9 columns and just over 6000 rows, and an application which performs updates on these table rows. The application runs hourly and performs updates to the table during each run. No new table rows are added during a run. I perform updates to the table by using row.update() inside a table.where() iterator loop.
I have noticed that after each application run the size of the file increases significantly, and over time the file size balloons from just over 21 MB to well over 750 MB, with no new data being added, just updated. h5repack() run on this file will restore it to its original size with no loss of data. My questions are: 1) What causes the file size increase and 2) is there anything I can do to prevent it? I am using PyTables 2.1.1, HDF5 1.8.3, Python 2.6 under Linux RedHat 5. -- David E. Sallis, Senior Principal Engineer, Software General Dynamics Information Technology NOAA Coastal Data Development Center Stennis Space Center, Mississippi 228.688.3805 david.sal...@gdit.com david.sal...@noaa.gov -------------------------------------------- "Better Living Through Software Engineering" -------------------------------------------- ------------------------------------------------------------------------------ Start uncovering the many advantages of virtual appliances and start using them to simplify application deployment and accelerate your shift to cloud computing. http://p.sf.net/sfu/novell-sfdev2dev _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
