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apache / datafusion / 3f2b6ebd2599daf2a98dd19a2b4be3358023e81d
commit3f2b6ebd2599daf2a98dd19a2b4be3358023e81d[log] [tgz]
authorAlex Huang <huangweijun1001@gmail.com>Sat Nov 08 12:08:42 2025 +0200
committerGitHub <noreply@github.com>Sat Nov 08 10:08:42 2025 +0000
tree2c741907736b3b1dd94aebd191b6ead966a41bcf
parentf470914c9e780a02e97039640da349e4f2333e74 [diff]
feat: Enhance `array_slice` functionality to support `ListView` and `LargeListView` types (#18432)

## Which issue does this PR close?

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- Closes #18351

## Rationale for this change

`array_slice` accepts `ListView` / `LargeListView` inputs.

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Why are you proposing this change? If this is already explained clearly
in the issue then this section is not needed.
Explaining clearly why changes are proposed helps reviewers understand
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## What changes are included in this PR?


- Extend array_slice_inner to handle `ListView`/`LargeListView` arrays
directly.
- Share the stride/bounds logic between list and list‑view
implementations via a new `SlicePlan`.



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## Are these changes tested?
Yes

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## Are there any user-facing changes?

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Yes. `array_slice` now accepts `ListView` and `LargeListView` arrays
without requiring an explicit cast.
2 files changed
tree: 2c741907736b3b1dd94aebd191b6ead966a41bcf
  1. .devcontainer/
  2. .github/
  3. benchmarks/
  4. ci/
  5. datafusion/
  6. datafusion-cli/
  7. datafusion-examples/
  8. dev/
  9. docs/
  10. python/
  11. test-utils/
  12. datafusion-testing
  13. parquet-testing
  14. testing
  15. .asf.yaml
  16. .dockerignore
  17. .editorconfig
  18. .gitattributes
  19. .gitignore
  20. .gitmodules
  21. Cargo.lock
  22. Cargo.toml
  23. CHANGELOG.md
  24. clippy.toml
  25. CODE_OF_CONDUCT.md
  26. CONTRIBUTING.md
  27. doap.rdf
  28. header
  29. LICENSE.txt
  30. licenserc.toml
  31. NOTICE.txt
  32. pre-commit.sh
  33. README.md
  34. rust-toolchain.toml
  35. rustfmt.toml
  36. taplo.toml
  37. typos.toml
README.md

Apache DataFusion

Crates.io Apache licensed Build Status Commit Activity Open Issues Discord chat Linkedin Crates.io MSRV

Website | API Docs | Chat

DataFusion is an extensible query engine written in Rust that uses Apache Arrow as its in-memory format.

This crate provides libraries and binaries for developers building fast and feature rich database and analytic systems, customized to particular workloads. See use cases for examples. The following related subprojects target end users:

“Out of the box,” DataFusion offers SQL and Dataframe APIs, excellent performance, built-in support for CSV, Parquet, JSON, and Avro, extensive customization, and a great community.

DataFusion features a full query planner, a columnar, streaming, multi-threaded, vectorized execution engine, and partitioned data sources. You can customize DataFusion at almost all points including additional data sources, query languages, functions, custom operators and more. See the Architecture section for more details.

Here are links to some important information

What can you do with this crate?

DataFusion is great for building projects such as domain specific query engines, new database platforms and data pipelines, query languages and more. It lets you start quickly from a fully working engine, and then customize those features specific to your use. Click Here to see a list known users.

Contributing to DataFusion

Please see the contributor guide and communication pages for more information.

Crate features

This crate has several features which can be specified in your Cargo.toml.

Default features:

  • nested_expressions: functions for working with nested type function such as array_to_string
  • compression: reading files compressed with xz2, bzip2, flate2, and zstd
  • crypto_expressions: cryptographic functions such as md5 and sha256
  • datetime_expressions: date and time functions such as to_timestamp
  • encoding_expressions: encode and decode functions
  • parquet: support for reading the Apache Parquet format
  • sql: Support for sql parsing / planning
  • regex_expressions: regular expression functions, such as regexp_match
  • unicode_expressions: Include unicode aware functions such as character_length
  • unparser: enables support to reverse LogicalPlans back into SQL
  • recursive_protection: uses recursive for stack overflow protection.

Optional features:

  • avro: support for reading the Apache Avro format
  • backtrace: include backtrace information in error messages
  • parquet_encryption: support for using Parquet Modular Encryption
  • pyarrow: conversions between PyArrow and DataFusion types
  • serde: enable arrow-schema's serde feature

DataFusion API Evolution and Deprecation Guidelines

Public methods in Apache DataFusion evolve over time: while we try to maintain a stable API, we also improve the API over time. As a result, we typically deprecate methods before removing them, according to the deprecation guidelines.

Dependencies and Cargo.lock

Following the guidance on committing Cargo.lock files, this project commits its Cargo.lock file.

CI uses the committed Cargo.lock file, and dependencies are updated regularly using Dependabot PRs.