[Feature] Support vector and full-text search in File Index

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
45/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Active
Tech stack
cpp

Research direction

Start with the existing File Index write path, container format, readers, and the work from #173. Trace how read-context requests reach FileIndexReader and how selected row positions reach the data-file reader. Done means vector and full-text indexes round-trip through write/read paths, support the listed edge cases, and preserve per-file TopK score alignment.

Written by the indexing model from the issue text.

Description

enhancement
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Motivation

Paimon C++ has File Index infrastructure for per-data-file indexes, but does not yet provide an end-to-end File Index search path for vector similarity or full-text queries. Applications should be able to build these indexes with their data files and use them to select matching file-local rows without requiring a Global Index.

Solution

Add Vector Search and Full Text Search support to File Index:

  • Build and serialize vector and full-text index artifacts through the existing File Index write path and container format, and open them through File Index readers.
  • Add file-local search visits to FileIndexReader and route search requests from the read context to the appropriate index reader.
  • Apply returned file-local row positions to the data-file reader. Vector Search should return a TopK result independently for each data file and keep scores aligned with selected rows; expose scores through an explicitly projected _INDEX_SCORE column.
  • Support Full Text Search row selection. Score output for Full Text Search can be handled separately.
  • Add focused tests for write/read round trips, null or empty indexes, multiple data files and batches, score alignment, and columns with more than one File Index type.

The initial implementation can target append-only/raw-file reads. Predicate combination, deletion-vector and row-range pre-filtering, Merge-on-Read/Data Evolution, and cross-file global TopK should be handled in follow-up work so that filtering does not silently change TopK semantics.

Anything else?

This builds on the File Index writing work in #173; it is specifically about vector/full-text index implementations and their search read path.

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Dominant language
C++
Stars
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Forks
29
Avg merge
2d 30m
Merged PRs (30d)
77

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