If i understand you correctly, you are only ever querying for the rows
where is_exported = false, and turning them into trues. What this means
is that eventually you will have 1 row in the secondary index table with
350K columns that you will never look at.
It seems to me you that perhaps you should just hold your own "manual
index" cf that points to non exported rows, and just delete those
columns when they are exported.
On 08/28/2012 05:23 PM, Edward Kibardin wrote:
I have a column family with the secondary index. The secondary index
is basically a binary field, but I'm using a string for it. The field
called *is_exported* and can be *'true'* or *'false'*. After request
all loaded rows are updated with *is_exported = 'false'*.
I'm polling this column table each ten minutes and exporting new rows
as they appear.
But here the problem: I'm seeing that time for this query grows pretty
linear with amount of data in column table, and currently it takes
*from 12 to 20 seconds (!!!) to find 5000 rows*. From my
understanding, indexed request should not depend on number of rows in
CF but from number of rows per one index value (cardinality), as it's
just another hidden CF like:
"true" : rowKey1 rowKey2 rowKey3 ...
"false": rowKey1 rowKey2 rowKey3 ...
I'm using Pycassa to query the data, here the code I'm using:
column_family = pycassa.ColumnFamily(cassandra_pool,
column_family_name, read_consistency_level=2)
is_exported_expr = create_index_expression('is_exported', 'false')
clause = create_index_clause([is_exported_expr], count = 5000)
column_family.get_indexed_slices(clause)
Am I doing something wrong, but I expect this operation to work MUCH
faster.
Any ideas or suggestions?
Some config info:
- Cassandra 1.1.0
- RandomPartitioner
- I have 2 nodes and replication_factor = 2 (each server has a full
data copy)
- Using AWS EC2, large instances
- Software raid0 on ephemeral drives
Thanks in advance!
