User state is built on top of read, append and clear and not off a read and
write paradigm to allow for blind appends.

The optimization you speak of can be done completely inside the SDK without
any additional protocol being required as long as you clear the state first
and then append all your new data. The Beam Java SDK does this for all
runners when executed portably[1]. You could port the same logic to the
Beam Python SDK as well.


On Tue, Jul 16, 2019 at 5:54 AM Robert Bradshaw <> wrote:

> Python workers also have a per-bundle SDK-side cache. A protocol has
> been proposed, but hasn't yet been implemented in any SDKs or runners.
> On Tue, Jul 16, 2019 at 6:02 AM Reuven Lax <> wrote:
> >
> > It's runner dependent. Some runners (e.g. the Dataflow runner) do have
> such a cache, though I think it's currently has a cap for large bags.
> >
> > Reuven
> >
> > On Mon, Jul 15, 2019 at 8:48 PM Rakesh Kumar <>
> wrote:
> >>
> >> Hi,
> >>
> >> I have been using python sdk for the application and also using
> BagState in production. I was wondering whether state logic has any
> write-through-cache implemented or not. If we are sending every read and
> write request through network then it comes with a performance cost. We can
> avoid network call for a read operation if we have write-through-cache.
> >> I have superficially looked into the implementation and I didn't see
> any cache implementation.
> >>
> >> is it possible to have this cache? would it cause any issue if we have
> the caching layer?
> >>

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