Hi Andrew! Thanks for your quick response and sorry it took me so long to answer back.
`spawn_blocking` solves the issue: https://gist.github.com/rdettai/d2f9bc59b31785c35dce792878976a19 I am still worried by the amount of thread pools and complexity it creates (1 pool for the outer runtime, 1 pool for spawn_blocking, 1 pool for the inner runtime). As you said, the best thing would be to push async all the way down but it's pretty hard as it propagates through the entire codebase :). For now I settled for adding async fetchers that download the data then sync read from the in-memory buffers. I'll come back to this issue a bit later because it still needs some adjustments. Remi Le ven. 30 oct. 2020 à 11:27, Andrew Lamb <al...@influxdata.com> a écrit : > Tokio has a function `spawn_blocking` > <https://docs.rs/tokio/0.3.2/tokio/task/fn.spawn_blocking.html> that > allows > running synchronous / blocking code as a future on the current runtime. You > can finagle pretty much any combination of sync / async using > spawn_blocking and channels, though the resulting code may not be the most > beautiful. > > Once you introduce `async` into a project or use an `async` library like > rusto, it feels to me like Rust leads you towards pushing async all the way > down and indeed the easiest thing for you, given your described > usecase would be async all the way down. > > I personally think having an async implementation of parquet would be very > valuable, as more and more Rust uses tokio / async IO. Maybe we could > implement an optional async interface on top of the blocking > implementation. > > Likewise, having a sync api and an async api for DataFusion also seems > valuable to to me. > > In my opinion, the biggest benefit from having DataFusion use tokio/async > is a single unified thread pool and execution model for both CPU and IO > work. Prior to being async-ized with the tokio thread pool, DataFusion > spawned / managed threads on its own; Adding additional parallelism without > over subscribing the CPU was likely going to be a significant effort. There > is a thread > < > https://lists.apache.org/thread.html/rbc4535613cb9af3467255234b49222bb8d3e57ef91790ebeff66aa74%40%3Cdev.arrow.apache.org%3E > > > on this mailing list about a similar challenge in the C++ implementation, > to give you a sense of the kinds of issues we are hoping to avoid in > DataFusion with using async > > Andrew > > > On Fri, Oct 30, 2020 at 4:28 AM Rémi Dettai <rdet...@gmail.com> wrote: > > > Hi everyone! > > > > If you are reading this, it means that you felt in the trap of my catchy > > (but meaningless) title! > > > > This discussion somewhat relates to [1]. > > > > DataFusion has recently made its top level "actions" (collect, write...) > > async. The problem is that most of the codebase is not async (in > particular > > Parquet [2]), which means that you have to make an async context work > > together with a sync one. > > > > This works okay... until it doesn't! > > > > I am trying to read into DataFusion from S3, using the AWS Rust SDK > Rusoto. > > The problem is that this SDK is itself async. This means that you end up > > with the following layers: > > DataFusion (async) -> Parquet (sync) -> Rusoto (async) > > As you might now, Tokio does not support blocking on a runtime from > within > > a runtime. > > > > This triggers a set of questions: > > - Does anybody know a way to make such a setup work? > > - Making Parquet async is extremely difficult and breaking, should we try > > to do it [2] ? > > - Is the benefit of having DataFusion async really big? Should we maybe > > have both a sync and an async API ? > > > > Thanks everybody and have a wonderful day. > > > > Regards, > > > > Remi > > > > [1] https://issues.apache.org/jira/browse/ARROW-9464 > > [2] https://issues.apache.org/jira/browse/ARROW-10307 > > >
