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From Donald Smith <Donald.Sm...@audiencescience.com>
Subject Question about how compaction and partition keys interact
Date Wed, 26 Mar 2014 17:22:22 GMT
In CQL we need to decide between using ((customer_id,type),date) as the CQL primary key for
a reporting table, versus ((customer_id,date),type).

We store reports for every day.  If we use (customer_id,type) as the partition key (physical
key), then we have  a WIDE ROW where each date's data is stored in a different column. Over
time, as new reports are added for different dates, the row will get wider and wider, and
I thought that might cause more work for compaction.

So, would a partition key of (customer_id,date) yield better compaction behavior?

Again, if we use (customer_id,type) as the partition key, then over time, as new columns are
added to that row for different dates, I'd think that compaction would have to merge new data
for a given physical row from multiple sstables. That would make compaction expensive.  But
if we use (customer_id,date) as the partition key, then new data will be added to new physical
rows, and so compaction would have less work to do????

My question is really about how compaction interacts with partition keys.  Someone on the
Cassandra irc channel, http://webchat.freenode.net/?channels=#cassandra, said that when partition
keys overlap between sstables, there's only "slightly" more work to do than when they don't,
for merging sstables in compaction.  So he thought the first form,  ((customer_id,type),date),
 would be better.

One advantage of the first form, ((customer_id,type),date) ,  is that we can get all report
data for all dates for a given customer and type in a single wide row  -- and we do have a
(uncommon) use case for such reports.

If we used a primary key of ((customer_id,type,date)), then the rows would be un-wide; that
wouldn't take advantage of clustering columns and (like the second form) wouldn't support
the (uncommon) use case mentioned in the previous paragraph.

Thanks, Don

Donald A. Smith | Senior Software Engineer
P: 425.201.3900 x 3866
C: (206) 819-5965
F: (646) 443-2333
donalds@AudienceScience.com<mailto:donalds@AudienceScience.com>

[AudienceScience]


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