ir.translation, import: push the algo. to SQL, improve performance

At a language import (translation files), we want to push a big batch of
translation records into the database. These will need update-or-insert
logic (against existing ones) or even resolution of ir.model.data .
Doing this loop in Python had been slow (invoking 2x read()s, +1 for
ir.model.data, 1 insert or update), triggered the cache (fill and clean
at each iteration).

Instead, follow the old-school db recipe for mass records insertion:
 - create a temporary table w/o indexes or constraints
 - quickly populate the temp with all records of the batch
   (through a dedicated "cursor" object)
 - process the table, doing lookups in collective SQL queries (yes, SQL
   is all about loops of data processing, efficiently)
 - insert all records from temp into ir.model.data
 - call (implicitly) all constraints of ir.model.data at the end of that
   single query.

This improves performance of translation imports by ~3x at least.

bzr revid: xrg@linux.gr-20110608162059-rfy1vvwp8w66ry0i

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