docs: lead README with the Arrow-native framing#4428
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Rewrite the top two paragraphs of README.md so the value prop leads with the Arrow-native pipeline (operators, expressions, shuffle, and broadcast all in Apache Arrow columnar format) rather than 'native Rust implementations'. The accelerator list grows by one entry to mention the experimental Scala/Java UDF support; shuffle and 'What Comet Accelerates' wording is tightened to match. No other docs are touched in this PR. Contributor-guide and user-guide prose updates for the same vocabulary clean-up (apache#4419) will follow separately.
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mbutrovich
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May 29, 2026
| It uses Apache Arrow for zero-copy data transfer between the JVM and native code. | ||
| Comet replaces Spark operators and expressions with implementations that consume and produce Apache Arrow | ||
| batches. Most run as native Rust code on top of Apache DataFusion; some run as JVM code over Arrow batches. | ||
| Either way the work stays in the Comet pipeline without falling back to Spark's row-based engine. |
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| Either way the work stays in the Comet pipeline without falling back to Spark's row-based engine. | |
| Either way, query execution stays in the Comet pipeline without falling back to Spark's row-based engine. |
mbutrovich
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May 29, 2026
| - **Apache Iceberg**: accelerated Parquet scans when reading Iceberg tables from Spark | ||
| (see the [Iceberg guide](https://datafusion.apache.org/comet/user-guide/iceberg.html)) | ||
| - **Shuffle**: native columnar shuffle with support for hash and range partitioning | ||
| - **Shuffle**: Arrow-IPC columnar shuffle with support for hash and range partitioning, in a native Rust |
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Didn't we add a (not 100% Spark-compatible) round-robin partitioning solution? Should we skip that if it's opt-in?
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May 29, 2026
| map, JSON, hash, and predicate categories | ||
| - **Aggregations**: hash aggregate with support for `FILTER (WHERE ...)` clauses | ||
| - **Joins**: hash join, sort-merge join, and broadcast join | ||
| - **Scala/Java UDFs**: experimental support for keeping Scala/Java scalar UDFs in the Comet pipeline |
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We can drop "experimental" if #4514 merges first.
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Which issue does this PR close?
Part of #4419 (the documentation-only phase, first slice).
Rationale for this change
Comet's documentation conflates several distinct ideas under the word "native": implementation language (Rust vs JVM), pipeline membership (handled by Comet vs falls back to Spark), and data format (Arrow columnar vs Spark rows). Issue #4419 spells out a clearer vocabulary so the docs stop overloading "native" and can scale to a roadmap where some JVM code paths (today Scala UDF codegen; soon Arrow UDFs and hybrid impls) also live inside the Comet pipeline.
The original version of this PR rolled the new vocabulary into ~20 files at once. This revision narrows the scope to a single file — the top-level
README.md— so reviewers can sign off on the framing first. The user-guide and contributor-guide sweeps will follow as separate PRs.What changes are included in this PR?
README.mdonly. The two top paragraphs and the "What Comet Accelerates" list are rewritten:No other docs files are touched. Operator renames (
CometExchange→CometNativeShuffleExchange, etc.) and the user-guide / contributor-guide vocabulary sweep are explicitly out of scope here and will land in follow-on PRs.How are these changes tested?
Documentation only. Verified that the README renders correctly on GitHub and that the new wording matches the vocabulary rules in #4419.