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From Gianluca Borello <>
Subject Performance issues with "many" CQL columns
Date Sun, 14 Feb 2016 22:22:20 GMT

I've just painfully discovered a "little" detail in Cassandra: Cassandra
touches all columns on a CQL select (related issues,,

My data model is fairly simple: I have a bunch of "sensors" reporting a
blob of data (~10-100KB) periodically. When reading, 99% of the times I'm
interested in a subportion of that blob of data across an arbitrary period
of time. What I do is simply splitting those blobs of data in about 30
logical units and write them in a CQL table such as:

create table data (
id bigint,
ts bigint,
column1 blob,
column2 blob,
column3 blob,
column29 blob,
column30 blob
primary key (id, ts)

id is a combination of the sensor id and a time bucket, in order to not get
the row too wide. Essentially, I thought this was a very legit data model
that helps me keep my application code very simple (because I can work on a
single table, I can write a split sensor blob in a single CQL query and I
can read a subset of the columns very efficiently with one single CQL

What I didn't realize is that Cassandra seems to always process all the
columns of the CQL row, regardless of the fact that my query asks just one
column, and this has dramatic effect on the performance of my reads.

I wrote a simple isolated test case where I test how long it takes to read
one *single* column in a CQL table composed of several columns (at each
iteration I add and populate 10 new columns), each filled with 1MB blobs:

10 columns: 209 ms
20 columns: 339 ms
30 columns: 510 ms
40 columns: 670 ms
50 columns: 884 ms
60 columns: 1056 ms
70 columns: 1527 ms
80 columns: 1503 ms
90 columns: 1600 ms
100 columns: 1792 ms

In other words, even if the result set returned is exactly the same across
all these iteration, the response time increases linearly with the size of
the other columns, and this is really causing a lot of problems in my

By reading the JIRA issues, it seems like this is considered a very minor
optimization not worth the effort of fixing, so I'm asking: is my use case
really so anomalous that the horrible performance that I'm experiencing are
to be considered "expected" and need to be fixed with some painful column
family splitting and messy application code?


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