El dc 18 de 04 del 2007 a les 11:38 +0100, en/na Michael Hoffman va escriure: > What is the I/O block size that PyTables uses? I ask because on my > Lustre system, reading blocks of less than 2 MB results in degraded > performance.
Yes, for chunked datasets (all except for Array), you can compute the chunksize in the next way (using 2.0 here): # For arrays >>> reduce(lambda x, y: x*y, array.chunkshape)*array.atom.size 4096L # 4 KB # For tables >>> table.chunkshape[0]*table.description._v_itemsize 4032L # almost 4 KB > Is there a way to change the I/O block size? Yup, you can in 2.0 by passing the desired value in new argument 'chunkshape' in constructors (remember to divide by the size of your atom first). HTH, -- Francesc Altet | Be careful about using the following code -- Carabos Coop. V. | I've only proven that it works, www.carabos.com | I haven't tested it. -- Donald Knuth ------------------------------------------------------------------------- This SF.net email is sponsored by DB2 Express Download DB2 Express C - the FREE version of DB2 express and take control of your XML. No limits. Just data. Click to get it now. http://sourceforge.net/powerbar/db2/ _______________________________________________ Pytables-users mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/pytables-users
