jiayuasu opened a new issue, #3273:
URL: https://github.com/apache/sedona/issues/3273
Part of #2230.
GeoPandas 1.1 added `GeoSeries.is_valid_coverage` and
`GeoSeries.invalid_coverage_edges` for validating polygonal coverages. A
valid coverage has
non-overlapping polygon interiors and exactly edge-matched shared
boundaries; callers may also
request detection of gaps up to a specified width.
Sedona already depends on JTS 1.20, which provides
`CoveragePolygonValidator`, but validating an
entire distributed GeoSeries cannot be implemented by collecting every
polygon into one task.
The implementation should:
- add a focused native Spark primitive that validates one target geometry
against an explicit
array of neighboring geometries;
- assign a fresh operation-scoped row identifier so duplicate and MultiIndex
rows remain distinct;
- discover candidate neighbors with a distributed spatial self-join using
the target envelope
expanded by `gap_width`, matching JTS coverage-index semantics;
- aggregate only each target's spatial neighbors and run JTS validation on
the executors;
- return one invalid-edge geometry per original row while preserving its
index, order, CRS, and
output naming;
- reduce the distributed invalid-edge result to one Python boolean for
`is_valid_coverage`;
- preserve GeoPandas behavior for valid coverages, overlaps, edge
mismatches, duplicate polygons,
narrow gaps, holes, multipolygons, empty sources, null/empty/non-polygonal
values, and numeric
`gap_width` edge cases; and
- avoid Python UDFs, global geometry collection, and driver materialization
of geometry rows.
The work should be split into two reviewable changes: the native per-target
Spark primitive first,
followed by the distributed GeoPandas APIs and parity/plan coverage.
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