Why Cassandra secondary indexes are so slow on just 350k rows?

4
votes

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!

1
performancecassandraindexingpycassa
Have you tried 1.2.x? They've made improvements to secondary index support. – Aaron

1 Answers

1
votes

I don't know the internals of indexing in Cassandra but I'm under the assumption it behaves in a similar fashion to PostgreSQL / MySQL, were indexing boolean, true/false columns is redundant in many scenarios. If cardinality is low (true & false = 2 unique values) and data is distributed quite evenly, e.g. ~50% true and ~50% false, then the database engine will likely perform a full table scan (which doesn't utilize the indexes).

The linear relationship between query execution and data set size would further support that Cassandra is performing a full table (keyspace) scan.