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https://issues.apache.org/jira/browse/CASSANDRA-10050?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15429358#comment-15429358
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Robert Stupp commented on CASSANDRA-10050:
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As far as I understand this ticket, it would require at least a schema change.
Changing the order of the keys would require that the token is encoded in the
internal 2i tables. I.e. instead of _partition-key=index-value +
clustering-key=base-primary-key_ it would be _partition-key=index-value +
clustering-key=token-of-base-partition-key+base-primary-key_ ; also, "token"
would depend on the partitioner. Quite irrelevant for BOP, but random and
murmur3 partitioner would require the token to be included.
Not sure, whether the current implementation (i.e. returning the rows in key
order) is something that people rely on. Means, would it be worth to add an
option to internal 2i that says: _store in token order_?
> Secondary Index Performance Dependent on TokenRange Searched in Analytics
> -------------------------------------------------------------------------
>
> Key: CASSANDRA-10050
> URL: https://issues.apache.org/jira/browse/CASSANDRA-10050
> Project: Cassandra
> Issue Type: Improvement
> Environment: Single node, macbook, 2.1.8
> Reporter: Russell Spitzer
> Fix For: 3.x
>
>
> In doing some test work on the Spark Cassandra Connector I saw some odd
> performance when pushing down range queries with Secondary Index filters.
> When running the queries we see huge amount of time when the C* server is not
> doing any work and the query seem to be hanging. This investigation led to
> the work in this document
> https://docs.google.com/spreadsheets/d/1aJg3KX7nPnY77RJ9ZT-IfaYADgJh0A--nAxItvC6hb4/edit#gid=0
> The Spark Cassandra Connector builds up token range specific queries and
> allows the user to pushdown relevant fields to C*. Here we have two indexed
> fields (size) and (color) being pushed down to C*.
> {code}
> SELECT count(*) FROM ks.tab WHERE token("store") > $min AND token("store") <=
> $max AND color = 'red' AND size = 'P' ALLOW FILTERING;{code}
> These queries will have different token ranges inserted and executed as
> separate spark tasks. Spark tasks with token ranges near the Min(token) end
> up executing much faster than those near Max(token) which also happen to
> through errors.
> {code}
> Coordinator node timed out waiting for replica nodes' responses]
> message="Operation timed out - received only 0 responses."
> info={'received_responses': 0, 'required_responses': 1, 'consistency': 'ONE'}
> {code}
> I took the queries and ran them through CQLSH to see the difference in time.
> A linear relationship is seen based on where the tokenRange being queried is
> starting with only 2 second for queries near the beginning of the full token
> spectrum and over 12 seconds at the end of the spectrum.
> The question is, can this behavior be improved? or should we not recommend
> using secondary indexes with Analytics workloads?
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