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From "Hiller, Dean" <>
Subject Re: Selecting rows efficiently from a Cassandra CF containing time series data
Date Tue, 11 Dec 2012 15:08:58 GMT
We use PlayOrm to do something similar

We have an object like this(typing all this from memory)….

TimeSeries {

   private long beginOfMonth;
   Private long timestamp;


Then we just use the ScalableSQL to query into the partition itself.  This is all on random
partitioner as well.  We could partition by day if we had way more of a dataload, but we tend
not to need that.  The query looks something like this  "PARTITIONS s(:beginOfMonth) select
s from TimeSeries as s";  OR "PARTITIONS s(:beginOfMonth) select s from TimeSeries as s where
s.time > :start and s.time < :end"


From: Chin Ko <<>>
Reply-To: "<>" <<>>
Date: Tuesday, December 11, 2012 7:23 AM
To: "<>" <<>>
Subject: Selecting rows efficiently from a Cassandra CF containing time series data

I would like to get some opinions on how to select an incremental range of rows efficiently
from a Cassandra CF containing time series data.

We have a web application that uses a Cassandra CF as logging storage. We insert a row into
the CF for every "event" of each user of the web application. The row key is timestamp+userid.
The column values are unstructured data. We only insert rows but never update or delete any
rows in the CF.

Data volume:
The CF grows by about 0.5 million rows per day. We have a 4 node cluster and use the RandomPartitioner
to spread the rows across the nodes.

There is a need to transfer the Cassandra data to another relational database periodically.
Due to the large size of the CF, instead of truncating the relational table and reloading
all rows into it each time, we plan to run a job to select the "delta" rows since the last
run and insert them into the relational database.

We would like to have some flexibility in how often the data transfer job is done. It may
be run several times each day, or it may be not run at all on a day.

Options considered:
- We are using RandomPartitioner, so range scan by row key is not feasible.
- Add a secondary index on the timestamp column, but reading rows via secondary index still
requires an equality condition and does not support range scan.
- Add a secondary index on a column containing the date and hour of the timestamp. Iterate
each hour between the time job was last run and now. Fetch all rows of each hour.

I would appreciate any ideas of other design options of the Cassandra CF to enable extracting
the rows efficiently.

Besides Java, has anyone used any ETL tools to do this kind of delta extraction from Cassandra?


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