My underlying question is about the effects of the partitioning key on compaction. Specifically, would having date as part of the partitioning key make compaction easier (because compaction wouldn't have to merge wide rows over multiple days)? According to the person on irc, it wouldn't make much difference.
We care mostly about read times. If read times were all we cared about, we'd use a CQL primary key of ((customer_id,type) date), especially since it lets us efficiently iterate over all dates for a given customer and type. I also care about compaction time, and if the other primary key form decreased compaction time, I might go for it. We have terabytes of data. I don't think we ever have to query all types for a given customer or date. That is, we are always given a specific customer and type, plus usually but not always a date. Thanks, Don From: Jonathan Lacefield [mailto:jlacefi...@datastax.com] Sent: Wednesday, March 26, 2014 11:20 AM To: user@cassandra.apache.org Subject: Re: Question about how compaction and partition keys interact Don, What is the underlying question? Are trying to figure out what's going to be faster for reads or are you really concerned about storage? The recommendation typically provided is to suggest that tables are modeled based on query access, to enable the fastest read performance. In your example, will your app's queries look for 1) customer interactions by type by day, with the ability to - sort by day within a type - grab ranges of dates for at type quickly - or pull all dates (and cell data) for a type or 2) customer interactions by date by type, with the ability to - sort by type within a date - grab ranges of types for a date quickly - or pull all types data for a date We also typically recommend that partitions stay within ~100k of columns or ~100MB per partition. With your first scenario, wide row, you wouldn't hit the number of columns for ~273 years :) What's interesting in your modeling scenario is that, with the current options, you don't have the ability to easily pull all dates for a customer without specifying the type, specific dates, or using ALLOW FILTERING. Did you ever consider partitioning simply on customer and using date and type as clustering keys? Hope that helps. Jonathan Jonathan Lacefield Solutions Architect, DataStax (404) 822 3487 [Image removed by sender.]<http://www.linkedin.com/in/jlacefield> [Image removed by sender.]<http://www.datastax.com/what-we-offer/products-services/training/virtual-training> On Wed, Mar 26, 2014 at 1:22 PM, Donald Smith <donald.sm...@audiencescience.com<mailto:donald.sm...@audiencescience.com>> wrote: 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<tel:425.201.3900%20x%203866> C: (206) 819-5965<tel:%28206%29%20819-5965> F: (646) 443-2333<tel:%28646%29%20443-2333> dona...@audiencescience.com<mailto:dona...@audiencescience.com> [AudienceScience]
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