It seems to me that you are planning the proverbial search for needles in a haystack.<br>A better approach should be possible by monitoring the harvest while it arrives,<br>one day at a time. (If you have to dig through the past, you still can do it day<br>
by day.) Use rules to keep track of sales events that qualify/disqualify customers.<br>This should reduce the number of facts to a manageable order of magnitude, i.e.,<br>the number of customers.<br><br>-W <br><br><br><div class="gmail_quote">
On 9 September 2010 10:27, bellios <span dir="ltr"><<a href="mailto:carfid@gmail.com">carfid@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
<br>
In my application I would to model the Customers-Sales domain and I thought<br>
that drools could help me to express a set of rules to capture (or execute<br>
on-demand) some "special" customers (e.g. take the customers which not<br>
have/have bought some products of category X in the last 6 months).<br>
<br>
To do this i'm loading the last 6 months sales into WM, afterwards on demand<br>
i execute the rules. This process fails due the memory requirements. I<br>
thought that Drools would use an hibernate/JPA/ or an incremental<br>
mechanisms to load and process the facts.<br>
<br>
@Swindells, Thomas: Do you think that it's the right approach?<br>
<br>
@Michael Anstis-2: I will try to study in deep the event<br>
processing\CEP\streaming methods.<br>
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