In this one case we had to change all of the items in the
listproperty. In our most common case we might have to add and delete
a couple items to the list property every once in a while. That would
still cost us well over $1,000 each time.

Most of the reasons for this type of data in our product is to
compensate for the fact that there isn't full text search yet. I know
they are beta testing full text, but I'm still worried that that also
might be too expensive per write.

On Jan 5, 6:54 am, Richard Watson <richard.wat...@gmail.com> wrote:
> A couple thoughts.
>
> Maybe the GAE team should borrow the idea of spot prices from Amazon.
> That's a great way to have lower-priority jobs that can run when there are
> instances available. We set the price we're willing to pay, if the spot
> cost drops below that, we get the resources. It creates a market where more
> urgent jobs get done sooner and Google makes better use of quiet periods.
>
> On your issue:
> Do you need to update every entity when you do this? How many items on the
> listproperty need to be changed? Could you tell us a bit more of what the
> data looks like?
>
> I'm thinking that 14 million entities x 18 items each is the amount of
> entries you really have, each distributed across at least 3 servers and
> then indexed. That seems like a lot of writes if you're re-writing
> everything.  It's likely a bad idea to rely on an infrastructure change to
> fix this (recurring) issue, but there is hopefully a way to reduce the
> amount of writes you have to do.
>
> Also, could you maybe run your mapreduce on smaller sets of the data to
> spread it out over multiple days and avoid adding too many instances? Has
> anyone done anything like this?

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