Add case-heavy LEFT JOIN benchmark and debug timing/logging for PushDownFilter hot paths (#20664)

## Which issue does this PR close?

* Part of #20002.

## Rationale for this change

The `PushDownFilter` optimizer rule shows a severe planner-time
performance pathology in the `sql_planner_extended` benchmark, where
profiling indicates it dominates total planning CPU time and repeatedly
recomputes expression types.

This PR adds a deterministic, CASE-heavy LEFT JOIN benchmark to reliably
reproduce the worst-case behavior and introduces lightweight debug-only
timing + counters inside `push_down_filter` to make it easier to
pinpoint expensive sub-sections (e.g. predicate simplification and join
predicate inference) during profiling.

## What changes are included in this PR?

* **Benchmark: add a deterministic CASE-heavy LEFT JOIN workload**

* Adds `build_case_heavy_left_join_query` and helpers to construct a
CASE-nested predicate chain over a `LEFT JOIN`.
* Adds a new benchmark `logical_plan_optimize_case_heavy_left_join` to
stress planning/optimization time.
* Adds an A/B benchmark group `push_down_filter_case_heavy_left_join_ab`
that sweeps predicate counts and CASE depth, comparing:

    * default optimizer with `push_down_filter` enabled
    * optimizer with `push_down_filter` removed

* **Optimizer instrumentation (debug-only)**

* Adds a small `with_debug_timing` helper gated by `log_enabled!(Debug)`
to record microsecond timings for specific sections.
  * Instruments and logs:

    * time spent in `infer_join_predicates`
    * time spent in `simplify_predicates`
* counts of parent predicates, `on_filters`, inferred join predicates
    * before/after predicate counts for simplification

## Are these changes tested?

* No new unit/integration tests were added because this PR is focused on
**benchmarking and debug-only instrumentation** rather than changing
optimizer semantics.
* Coverage is provided by:

  * compiling/running the `sql_planner_extended` benchmark
* validating both benchmark variants (with/without `push_down_filter`)
produce optimized plans without errors
* enabling `RUST_LOG=debug` to confirm timing sections and counters emit
as expected

## Are there any user-facing changes?

* No user-facing behavior changes.
* The optimizer logic is unchanged; only **debug logging** is added
(emits only when `RUST_LOG` enables Debug for the relevant modules).
* Benchmark suite additions only affect developers running benches.

## LLM-generated code disclosure

This PR includes LLM-generated code and comments. All LLM-generated
content has been manually reviewed and tested.
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  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. .asf.yaml
  13. .dockerignore
  14. .editorconfig
  15. .gitattributes
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  17. .gitmodules
  18. Cargo.lock
  19. Cargo.toml
  20. CHANGELOG.md
  21. clippy.toml
  22. CODE_OF_CONDUCT.md
  23. CONTRIBUTING.md
  24. doap.rdf
  25. header
  26. LICENSE.txt
  27. licenserc.toml
  28. NOTICE.txt
  29. pre-commit.sh
  30. pyproject.toml
  31. README.md
  32. rust-toolchain.toml
  33. rustfmt.toml
  34. taplo.toml
  35. typos.toml
  36. uv.lock
README.md

Apache DataFusion

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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 for 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 important resources:

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 needs. See the list of 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 types 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 and 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
  • 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.