Comments (2)
I could be mistaken but after skimming the paper (extremely interesting, by the way!) it seems that Weld would need be used at a lower level than Ballista - e.g. at the DataFusion or Arrow levels (I'm not familiar enough to know which). The authors mention comparison to Spark SQL in sections 7 and 8.5:
Spark SQL natively generates Java bytecode, and uses a HyPer-like code generation process to pipeline code from different operators. In our Weld integration, we updated each Spark SQL operator to emit single Weld IR fragment encapsulating its computation, and relied on Weld’s optimizer to fuse and co-optimize these fragments.
It sounds like they're talking about replacing the JIT'd code that Spark uses, which (I think?) corresponds to the code executed in each part of the physical plan. So perhaps Ballista may be responsible for actually calling the Weld optimizer to fuse/co-optimize each fragment produced by DataFusion/Arrow?
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@sd2k I think you may be correct. In any case, integrating with Weld is beyond the scope of this project for the immediate future at least, so I'm closing this for now.
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Related Issues (20)
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- Query fails when there are multiple executors
- Add watch capabilities to ConfigBackendClient
- Move state synchronization to an async task
- Re-run the necessary tasks when an executor dies
- Improve task and job metadata HOT 5
- Use PartitionId in TaskStatus HOT 1
- Add support for Keda
- Make external hostname in executor optional
- Ballista doesn't optimize logical plan HOT 1
- Implement minimal REST API in the scheduler HOT 7
- Windows CI is broken HOT 2
- Create "self-contained" mode in client library
- Add etcd/sled features to scheduler module
- Python CI should run when Rust directory changes
- Update scheduler to support multiple locations per partition HOT 2
- Donate Ballista to Apache Arrow project HOT 31
- why only 1 executor works even I start 2 executors? HOT 1
- tpch convert to multi partitions is frozen
- Ballista Distributed Compute has moved! Please bookmark and star the new repo! HOT 2
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