I have the same questions as Christopher. Does this data need to change, or is it write-once? What information do you have when querying? - Will you already have timestamp and msg-id? - If not, you may want to consider aggregating everything into a single key. This is easier of the data isn’t changing. What data will you typically be querying? - Will you typically be looking for a single element of data, or aggregates (graphing or mapping for example)? - If aggregates, what fields are you aggregating on (timestamp, geo, location, etc) and which will be fixed?
The aggregate question may need a little more explanation, so I will use an example. I have been working on time-series data with my key being: <node-id>:<metric-id>:<timestamp> Node-id and metric-id are fixed, they will never be merged in an aggregate way, and I have them before querying. Timestamp is my aggregate value, I may need a single timestamp, or hundreds of thousands of timestamps (to draw a graph). For this reason, I grouped my metrics by 5 minute block instead of one key per timestamp. I also created aggregates with relevant averages and such for 1 hour, 1 day and 1 month to reduce the amount of key lookups for large graphs. So it depends what visualisations you want. If you are going to be mapping the most recent data based on the geo or location, I would include aggregates for that. If you are more interested in timestamp, group by that. Because Riak doesn’t have multi-key consistency though, also choose an canonical source of data. If you store the same data in multiple keys, they will diverge at some point. Decide now which is the real source, and which are derived, it will make your life easier when fixing data later. Also keep in mind typical periods and data size. There was no point for me to create a 1 minute increment since the 5 minute data was an acceptable size. Sure it’s a waste to transmit 4 minutes of data I don’t need, but it’s measured in milliseconds (mainly unserialising JSON in my app), so it doesn’t matter to me and makes larger aggregates much more performant. > On 22 Feb 2015, at 03:44, Christopher Meiklejohn <cmeiklej...@basho.com> > wrote: > > >> On Feb 20, 2015, at 5:35 PM, AM <ams....@gmail.com> wrote: >> >> Hi All. >> >> I am currently looking at using Riak as a data store for time series data. >> Currently we get about 1.5T of data in JSON format that I intend to persist >> in Riak. I am having some difficulty figuring out how to model it such that >> I can fulfill the use cases I have been handed. >> >> The data is provided in several types of log formats with some common fields: >> >> - timestamp >> - geo >> - s/w build # >> - location # >> >> - .... whole bunch of other key value pairs. >> >> For the most part I will need to provide aggregated views based on geo. >> There are some views based on s/w build # and location #. The aggregation >> will be on an hourly basis. >> >> The model that I came up with: >> >> <log-format-type>[<hour>][<timestamp>-<msg-id>]: <json-body> > > Hi AM, > > Additionally, it would be great if you could provide additional information > on how you plan on querying both the original and aggregated values. > Querying is usually the most difficult part to get right in Riak, and your > query pattern will be very important in establishing the best way to lay out > this data on disk. > > - Chris > > Christopher Meiklejohn > Senior Software Engineer > Basho Technologies, Inc. > cmeiklej...@basho.com > > > _______________________________________________ > riak-users mailing list > riak-users@lists.basho.com > http://lists.basho.com/mailman/listinfo/riak-users_lists.basho.com _______________________________________________ riak-users mailing list riak-users@lists.basho.com http://lists.basho.com/mailman/listinfo/riak-users_lists.basho.com
