andygrove opened a new pull request, #218:
URL: https://github.com/apache/datafusion-site/pull/218

   Draft announcement for Ballista 56.0.0, written ahead of the release from 
what has merged to `main` since 55.0.0. It focuses on performance, memory 
usage, adaptive query execution and robustness.
   
   Contents:
   
   - **Performance**: TPC-H SF1000 results on the same cluster as the 55.0.0 
post. Ballista is now 2.2x faster than Spark 4.1.3 (up from 1.79x) and 1.12x 
faster than Spark + Comet 1.1.0 (from 1.10x slower), and 3.4x faster than Spark 
with the new experimental pipelined mode. Includes the changes behind the gain 
and the same caveats as before.
   - **Memory usage**: the smallest executor memory at which TPC-H q18 
finishes, for Ballista (8 GiB), Spark (12 GiB) and Spark + Comet 1.2.0 (20 
GiB), and how each engine's time changes as memory shrinks. From 
apache/datafusion-ballista#2855.
   - **AQE**: HyperLogLog distinct counts on shuffles, measuring joins before 
broadcasting them, exchange reuse, physical plans through AQE, partition 
coalescing and skew-join splitting (opt-in), and the groundwork for runtime 
filters.
   - **Robustness**: graceful shutdown, the standalone result service, plans 
that used to return wrong results silently, and the merge-queue test suites.
   - **Python**, other changes, and upgrading notes.
   
   Charts are copied from the Ballista docs (`tpch_sf1000_total.svg` from 
`main`, the two memory charts from apache/datafusion-ballista#2855).
   
   To do before publishing (also listed in a comment at the top of the post):
   
   - [ ] Set the date to the release date (front matter and file name).
   - [ ] Update the commit and contributor counts and the thank-you list from 
the 56.0.0 changelog (currently 189 commits from 20 authors on `main`).
   - [ ] Confirm the DataFusion version 56.0.0 ships with.
   - [ ] Merge apache/datafusion-ballista#2855 so the memory usage page link 
resolves.
   
   🤖 Generated with [Claude Code](https://claude.com/claude-code)
   


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