interesting! might just work. We will try it out.
E.g. A chance of 500 V's. V has fields a, b, c, (b=foo on all records) and
some client app wants to run a continuous query on all V where b=foo, or was
=foo but now is not following the update.
The writer updates 100 V's, by setting b=bar on all records, and some
incrementing version int N
The datastreamer transformer mutates V by adding a new field called
"changes" which contains b=foo to denote that only the field b was changed,
and it's old value was foo. (e.g. a set of {fieldname, oldvalue}, {.... )
The writer updates the V_signal cache to denote a change was made, with
version N.
The client continuous query listens to the V_signal cache. When it receives
an update (denoting V updates have occurred), it does a scanquery on V in
the transformer, (scan query filters the records that were updated as part
of version N, and either the fields we care about match our predicate, or
the "changes" field are one of the ones we are interested in and match the
predicate).
These are batched up as a collection and returned to the client. Does this
seem like a reasonable approach?
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