For sanity, I ran the same python script with the same row ids again today and
it was 10x faster. Must be something going wrong intermittently in my cluster.
-Allan
On April 11, 2014 at 11:02:11 AM, Allan C (alla...@gmail.com) wrote:
It’s a fairly standard relational-like CF. Description is the only field
that’s potentially big (can be up to 1k).
CREATE COLUMN FAMILY 'Event' WITH
key_validation_class = 'UTF8Type' AND
comparator = 'UTF8Type' AND
default_validation_class = 'UTF8Type' AND
bloom_filter_fp_chance = 0.1 AND
compaction_strategy = 'LeveledCompactionStrategy' AND
compaction_strategy_options = {sstable_size_in_mb:160} AND
compression_options =
{sstable_compression:SnappyCompressor,chunk_length_kb:64} AND
-- key_alias = 'eventId' AND
column_metadata = [
{column_name: 'createdAt', validation_class: 'DateType'},
{column_name: 'creatorId', validation_class: 'UTF8Type'},
{column_name: 'creatorName', validation_class: 'UTF8Type'},
{column_name: 'description', validation_class: 'UTF8Type'},
{column_name: 'privacy', validation_class: 'UTF8Type'},
{column_name: 'location', validation_class: 'UTF8Type'},
{column_name: 'locationId', validation_class: 'UTF8Type'},
{column_name: 'endTime', validation_class: 'DateType'},
{column_name: 'name', validation_class: 'UTF8Type'},
{column_name: 'picture', validation_class: 'UTF8Type'},
{column_name: 'startTime', validation_class: 'DateType'},
{column_name: 'updatedAt', validation_class: 'DateType'},
{column_name: 'lat', validation_class: 'UTF8Type'},
{column_name: 'lng', validation_class: 'UTF8Type'},
{column_name: 'street', validation_class: 'UTF8Type'},
{column_name: 'city', validation_class: 'UTF8Type'},
{column_name: 'state', validation_class: 'UTF8Type'},
{column_name: 'zip', validation_class: 'UTF8Type'},
{column_name: 'country', validation_class: 'UTF8Type'},
{column_name: '~lastSync', validation_class: 'DateType'},
{column_name: '~nextSync', validation_class: 'DateType'},
{column_name: '~syncBlock', validation_class: 'IntegerType'},
{column_name: 'noCount', validation_class: 'IntegerType'},
{column_name: 'invitedCount', validation_class: 'IntegerType'},
{column_name: 'maybeCount', validation_class: 'IntegerType'},
{column_name: 'yesCount', validation_class: 'IntegerType'},
{column_name: '~version', validation_class: 'IntegerType'}
];
-Allan
On April 10, 2014 at 4:49:34 PM, Tyler Hobbs (ty...@datastax.com) wrote:
On Thu, Apr 10, 2014 at 6:26 PM, Allan C <alla...@gmail.com> wrote:
Looks like the amount of data returned has a big effect. When I only return one
column, python reports only 20ms compared to 150ms when returning the whole
row. Rows are each less than 1k in size, but there must be client overhead.
That's a surprising amount of overhead in pycassa. What's your schema like for
this CF?
--
Tyler Hobbs
DataStax
