Hi Robert comments inline:
On 10/10/2019 20:49, Robert Bradshaw wrote:
On Thu, Oct 10, 2019 at 12:39 AM Etienne Chauchot <[email protected]> wrote:
Hi guys,
You probably know that there has been for several months an work
developing a new Spark runner based on Spark Structured Streaming
framework. This work is located in a feature branch here:
https://github.com/apache/beam/tree/spark-runner_structured-streaming
To attract more contributors and get some user feedback, we think it is
time to merge it to master. Before doing so, some steps need to be achieved:
- finish the work on spark Encoders (that allow to call Beam coders)
because, right now, the runner is in an unstable state (some transforms
use the new way of doing ser/de and some use the old one, making a
pipeline incoherent toward serialization)
- clean history: The history contains commits from November 2018, so
there is a good amount of work, thus a consequent number of commits.
They were already squashed but not from September 2019
I don't think the number of commits should be an issue--we shouldn't
just squash years worth of history away. (OTOH, if this is a case of
this branch containing lots of little, irrelevant commits that would
have normally been squashed away in the normal review process we do
for the main branch, then, yes, some cleanup could be nice.)
+1. yes tiny ones were already squashed except from sept to now.
Regarding status:
- the runner passes 89% of the validates runner tests in batch mode. We
hope to pass more with the new Encoders
- Streaming mode is barely started (waiting for the multi-aggregations
support in spark SS framework from the Spark community)
- Runner can execute Nexmark
- Some things are not wired up yet
- Beam Schemas not wired with Spark Schemas
- Optional features of the model not implemented: state api, timer
api, splittable doFn api, …
WDYT, can we merge it to master once the 2 steps are done ?
I think that as long as it sits parallel to the existing runner, and
is clearly marked with its status, it makes sense to me. How many
changes does it make to the existing codebase (as opposed to add new
code)?
the 2 runners live in the same module but in different java packages.
New runner was re+coded from scratch (cf explanations here
https://www.slideshare.net/EtienneChauchot/etienne-chauchot-spark-structured-streaming-runner).
There is no shared code between the runners (except beam sdk and core of
course :) ).
Etienne
