On 05/15/2017 10:54 AM, Zsolt Ero wrote:
Thanks, it is all clear now. Just out of interest, what is the point
of synchronize_session='fetch'?
that will do a SELECT and get the new value back and update your ORM
object in memory. Set synchronize_session=False if you don't care.
For me all it does is a simple SELECT maps.id AS maps_id FROM maps
WHERE maps.id = %(id_1)s
All I get as a return value is 0: not successful (probably id didn't
exist), while 1: successful. It is the same behaviour both with
'fetch' and False.
Zsolt
On 15 May 2017 at 16:33, mike bayer <mike...@zzzcomputing.com> wrote:
On 05/15/2017 10:31 AM, Zsolt Ero wrote:
I'm trying to run your example, but it doesn't work:
from sqlalchemy import func
m = request.dbsession.query(models.Map).get(3)
m.screenshots = func.jsonb_set(m.screenshots, '{key}', '"value"')
request.dbsession.flush()
It ends up in a (psycopg2.ProgrammingError) can't adapt type 'dict'.
jsonb_set(models.Map.screenshots, ...)
because this works against the column, not the value
Also, from the generated SQL it seems to me that it's also doing the
full JSONB update from client side, not just inserting a key into the
database server side.
UPDATE maps SET screenshots=jsonb_set(%(jsonb_set_1)s,
%(jsonb_set_2)s, %(jsonb_set_3)s) WHERE maps.id = %(maps_id)s
{'maps_id': 3, 'jsonb_set_3': '"value"', 'jsonb_set_2': '{key}',
'jsonb_set_1': {u'small': u'2ad139ee69cdcd9e.jpg', u'full':
u'68b3f51491ff1501.jpg'}}
On 15 May 2017 at 16:18, Zsolt Ero <zsolt....@gmail.com> wrote:
Thanks for the answer. My use case is the following:
I have an object (map_obj), which has screenshots in two sizes. I'm
using JSONB columns to store the screenshot filenames.
Now, the two screenshot sizes are generated in parallel. The code is
like the following:
map_obj = query(...by id...)
filename = generate_screenshot(size) # long running screenshot
generation
try:
dbsession.refresh(map_obj, ['screenshots'])
map_obj.screenshots = dict(map_obj.screenshots, **{size: filename})
except Exception as e:
logger.warning(...)
It worked well for 99.9% of the cases. The problem is that in the rare
case when both screenshots got rendered within a few milliseconds, one
of the screenshots got lost.
The simple solution was to add lockmode='update' to the refresh, so
this way the refreshes are blocking until the other finishes the
update.
But since this means locking a full row, I was thinking a simple JSONB
insertion would probably be better, since I can avoid locking the row.
Zsolt
On 15 May 2017 at 15:58, mike bayer <mike...@zzzcomputing.com> wrote:
On 05/15/2017 09:32 AM, Zsolt Ero wrote:
In PostgreSQL 9.5+ it is finally possible to modify a single key inside
a
JSONB column. Usage is something like this:
update maps set screenshots=jsonb_set(screenshots, '{key}', '"value"')
where id = 10688
Is it possible to write this query using the ORM somehow? If not,
please
take it as a feature request.
You can use that function directly:
my_object = session.query(Maps).get(5)
my_object.screenshots = func.jsonb_set(my_object.screenshots, '{key}',
'"value"')
session.flush()
as far as "transparent" ORM use of that, like this:
my_object.screenshots[key] = "value"
right now that is a mutation of the value, and assuming you were using
MutableDict to detect this as an ORM change event, the ORM considers
"screenshots" to be a single value that would be the target of an
UPDATE,
meaning the whole JSON dictionary is passed into the UPDATE. There is no
infrastructure for the ORM to automatically turn certain column updates
into
finely-detailed SQL function calls. I can imagine that there might be
some
event-based way to make this happen transparently within the flush,
however,
but I'd need to spend some time poking around to work out how that might
work.
I'm not familiar with what the advantage to jsonb_set() would be and I
can
only guess it's some kind of performance advantage. I'd be curious to
see
under what scenarios being able to set one element of the JSON vs.
UPDATEing
the whole thing is a performance advantage significant compared to the
usual
overhead of the ORM flush process; that is, Postgresql is really fast,
and
for this optimization to be significant, you probably need to be calling
the
Core function directly anyway rather than going through the whole ORM
flush
process. But this is all based on my assumption as to what your goal
of
using this function is.
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