Symbol concatenation with arrow written data

[IvoDD]

Reference Issues/PRs

Monday ref: 18053022100

What does this implement or fix?

Concatenation is made to work with arrow written normalization metadata. Mixing arrow and pandas also works as long as arrow.has_index() == pandas_index.is_physically_stored().

This PR also adds sparse arrow testing for groupby, resampling and concat.

GroupBy and concat work as expected.

Resampling does not and is a non trivial fix. Monday ref to track: 11679866800

Any other comments?

Checklist

Checklist for code changes...

• Have you updated the relevant docstrings, documentation and copyright notice?
• Is this contribution tested against all ArcticDB's features?
• Do all exceptions introduced raise appropriate error messages?
• Are API changes highlighted in the PR description?
• Is the PR labelled as enhancement or bug so it appears in autogenerated release notes?

[claude]

ArcticDB Code Review Summary

API & Compatibility

• No breaking changes to public Python API (Arctic, Library, NativeVersionStore)
• Deprecation protocol followed for removed/renamed parameters
• On-disk format unchanged (or migration path documented)
• Protobuf schema backwards-compatible
• Key types and ValueType enum unchanged (or additive only)

Memory & Safety

• RAII used for all resource management
• No use-after-move or use-after-free patterns
• Buffer size calculations correct (no overflow potential)
• GIL correctly managed at Python-C++ boundary
• No accidental copies of large objects

Correctness

• All ValueType/KeyType switch statements exhaustive
• Edge cases handled (empty data, NaN, Unicode, concurrent access)
• Error codes unique and in correct ErrorCategory
• Storage backend interface fully implemented
• Query clause composition correct

Code Quality

• No duplicated logic (search repo for existing utilities)
• C++ and Python implementations of shared concepts are consistent
• Tests are not duplicating existing test scenarios

Testing

• Behavioural changes have corresponding tests
• Edge cases covered in tests
• Integration tests for storage/version engine changes
• No regression in existing test expectations

Build & Dependencies

• New source files added to CMakeLists.txt
• Dependency changes justified and version-pinned
• Cross-platform compatibility maintained
• vcpkg submodule points to official upstream commit
• vcpkg manifest versions pinned and consistent with submodule baseline
• Custom overlay ports up-to-date with dependency versions
• Conda environment synced with vcpkg dependency versions

Security

• No hardcoded credentials or secrets
• Input validation at system boundaries
• No buffer overflow potential in C++ code

PR Title & Description

• Title is clear, concise, and uses imperative verb
• Title and description are free of typos and grammatical errors
• Description explains what changed and why
• All significant changes in the diff are mentioned in the description
• API/breaking changes explicitly called out in the description
• Linked issues referenced where applicable
• PR labelled appropriately (patch label set)

Documentation

• Public API docstrings accurate
• Breaking changes flagged with appropriate labels

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Summary

This PR adds comprehensive tests for groupby, resample, and concat on sparse Arrow data, fixes concat to accept experimental_arrow normalization metadata, and refactors generate_norm_meta into a pairwise accumulate_norm_metadata helper that handles mixed Arrow+Pandas and Arrow+Arrow cases, plus adds TestMixedArrowPandasConcat integration tests.

Open issues (still unresolved):

Medium — xfail markers missing strict=True (from previous review, unchanged)
Both TestSparseArrowResample (class-level marker) and TestSparseArrowConcat.test_concat_with_resample use @pytest.mark.xfail without strict=True. When sparse resampling is eventually implemented these tests will silently XPASS instead of prompting removal of the marker.

Low — Combined sparse/row-count check in sorted_aggregation.cpp (from previous review, unchanged)
The single schema::check guards two independent invariants (!is_sparse() and row_count() == index_row_count()). A non-sparse column with a mismatched row count would produce the misleading message "Cannot aggregate sparse column".

Informational — _check_query_result Pandas cross-check for resample (from previous review, partially addressed)
The resample (sort_by=None) path compares unsorted results. This is a weaker assertion rather than a correctness bug.

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Latest push (f2fb26d):

• Documentation only: Reorganised comments in accumulate_norm_metadata in clause_utils.cpp. The single block comment that preceded the function header has been split into per-section inline comments (Arrow+Arrow, One arrow/one pandas, Pandas+Pandas), with the Pandas+Pandas section gaining a detailed bullet-list description of the merge rules. No logic changes. No new issues introduced.

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Previously:

• Rename only (fe96b45): common_norm_metadata → accumulate_norm_metadata and parameter first → accumulated in clause_utils.cpp. Pure cosmetic rename — no logic changes.
• test_different_columns had an undefined fixture parameter — index_column removed from method signature.
• test_no_index / test_with_index expected ordering was always arrow-first — Both tests now compute expected correctly respecting the arrow_first parameter.
• PR label — patch label is now set.

[IvoDD]

The Pandas + Pandas code in accumulate_norm_metadata is moved from the previous for loop in generate_norm_meta with the following minor changes:

• Variable renames to be more clear
• A couple more readability changes (non-behavior changing) highlighted in separate comments

[IvoDD]

This comment was moved in favor of another comment in generate_norm_metadata explaining the interaction between non_mathching_name_indices and fake_field_pos

[IvoDD]

This was replaced by an:

            if ((*res_index->mutable_timezone())[idx] != idx_timezone) {
                (*res_index->mutable_timezone())[idx] = "";
            }