We are considering using Riak and I am looking for some advice on best practices for updating a large number of records. Our problem is that we have a large number of unique sets of results, each of which represent a schedule for multiple people on a particular day or set of days.
For example, we would have a result set for Mondays from 11/01 - 11/28 and another for 11/29 and then a third on Mondays from 11/30 onwards if one person's schedule was edited for 11/29. So when a person's schedule changes, we need to update the related result sets. The issue is that there are likely to be a large number of result sets that need to be updated for each change to a person's schedule and I would like to process them in parallel. From what I have seen, the only way to do this is to write a MapReduce (or map really I guess) function in Erlang, though the forum thread I found seemed to discourage this approach. Is that correct or am I missing something? This seems like a relatively common use-case for sharded data, so I am hoping that Riak offers a good solution for us. Thanks in advance, Dan Langevin
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