Github user haohui closed the pull request at:
https://github.com/apache/storm/pull/796
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Github user haohui commented on the pull request:
https://github.com/apache/storm/pull/796#issuecomment-148433347
Thanks for the feedback. The architecture will be flexible to allow
pluggable code generation.
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Github user arunmahadevan commented on the pull request:
https://github.com/apache/storm/pull/796#issuecomment-148294057
Thanks, I get it now. I think it would be good to leave some hooks to
plugin other approaches to bytecode generation in future if needed.
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Github user haohui commented on the pull request:
https://github.com/apache/storm/pull/796#issuecomment-148118238
The main motivation is performance -- The code that generated by Calcite
has a lot of down casts which can potentially have a visible impact, as the
targeted throughput is
Github user arunmahadevan commented on the pull request:
https://github.com/apache/storm/pull/796#issuecomment-147949951
Curious to know why LLVM with C++ was chosen ? Calcite spark adapter
appears to be using Janino to compile the generated java code.
https://github.com/apache/incuba
Github user harshach commented on the pull request:
https://github.com/apache/storm/pull/796#issuecomment-147737771
+1
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GitHub user haohui opened a pull request:
https://github.com/apache/storm/pull/796
STORM-1105. Compile the logical plans into LLVM functions.
This PR compiles three logical operators, tablescan, filter and projection
to LLVM functions.
You can merge this pull request into a Git rep
