chunkhound-index-compactor 0.2.0

Compact a bloated ChunkHound DuckDB index by rebuilding it into a fresh file

ChunkHound Index Compactor

Compact a DuckDB database by rebuilding it into a fresh file. The motivating and supported use case is shrinking a bloated ChunkHound index, whose drop-and-recreate HNSW churn (above its 50-row write-batch threshold) leaves large amounts of orphaned-but-counted blocks. The rebuild pipeline is structurally generic and works on other single-schema DuckDB files, but only ChunkHound-shaped inputs are promised: any shape outside that scope is refused at the front gate (see the Not Supported section below) rather than silently dropped or rebuilt with loss.

That bloat comes back as ChunkHound keeps indexing, so compaction is periodic maintenance rather than a one-time cleanup.

⚡ Quick Start

uvx chunkhound-index-compactor path/to/db.duckdb
# writes path/to/db.duckdb.compacted

uvx chunkhound-index-compactor path/to/db.duckdb --replace
# swaps in the compacted copy and keeps the original at path/to/db.duckdb.bak

uvx chunkhound-index-compactor path/to/db.duckdb --skip-hnsw
# skips rebuilding vector indexes (RAM-flat, smallest output); restore them later
uvx chunkhound-index-compactor restore path/to/db.duckdb.compacted

The source is opened read-only, but an active writer holds the file lock. Close any process writing to the database before running.

🖥️ CLI Usage

$ chunkhound-index-compactor --help
Usage: chunkhound-index-compactor [OPTIONS] COMMAND [ARGS]...

Commands:
  compact  Compact a DuckDB database by rebuilding it into a fresh file. (default)
  restore  Rebuild HNSW vector indexes in a --skip-hnsw artifact, in place.

A bare invocation routes to compact, so chunkhound-index-compactor SOURCE still works:

chunkhound-index-compactor SOURCE [TARGET] [--replace] [--skip-hnsw]
chunkhound-index-compactor restore DATABASE

Argument / Option	Meaning
SOURCE	Path to the existing DuckDB file (required)
TARGET	Path for the compacted output [default: <source>.compacted]
--replace	After success, replace source with the compacted file (original → <source>.bak)
--skip-hnsw	Do not rebuild vector indexes; write a recipe table for later restore

With --skip-hnsw, the output has no vector index and falls back to a brute-force scan (correct, just unaccelerated) until you run restore. Rebuilding the HNSW is the memory-dominant step, so --skip-hnsw lets you compact on a small machine and restore on a RAM-capable one. See docs/benchmarks.md for peak-RAM numbers and docs/architecture.md §RAM cost asymmetry for why.

🐍 Library Usage

from pathlib import Path
from chunkhound_index_compactor import compact_database, restore_indexes, replace_with_compacted

result = compact_database(Path("big.duckdb"), Path("small.duckdb"))
print(f"{result.source_size} -> {result.target_size} ({result.delta_pct:+.1f}%)")

# Small-RAM path: skip the vector index, restore it later on a bigger machine.
compact_database(Path("big.duckdb"), Path("small.duckdb"), skip_hnsw=True)
restored = restore_indexes(Path("small.duckdb"))
print(f"restored: {restored.restored}")

# Optional: swap in place with .bak backup
backup = replace_with_compacted(result.source, result.target)

compact_database() raises:

• ValueError: target resolves to the same path as source, the FK graph has a cycle, or the source has a shape refused at the front gate (see the Not Supported section below).
• FileNotFoundError: source does not exist.
• FileExistsError: target already exists.
• RuntimeError: the bundled vss extension binary cannot be located (only reachable if the source contains an HNSW index).

restore_indexes() raises:

• FileNotFoundError: database does not exist.
• ValueError: database has no _compactor_hnsw_recipe table (not a --skip-hnsw artifact).
• RuntimeError: the bundled vss extension binary cannot be located.

replace_with_compacted() raises:

• FileNotFoundError: source or compacted is missing.
• FileExistsError: <source>.bak already exists (it refuses to overwrite an existing backup).
• OSError: the move from compacted to source fails even via the cross-filesystem fallback (shutil.move).

🚫 Not Supported

The tool fails hard rather than silently dropping anything it cannot reproduce.

• Non-main schemas and views (raise ValueError).
• User-defined types, generated columns, self-referential foreign keys, and HNSW indexes on non-bare-column expressions (raise ValueError).
• Foreign-key cycles among tables (raise ValueError).
• HNSW tuning parameters other than metric (M, M0, ef_construction, ef_search); they are not recoverable from a built index and are rebuilt at the vss defaults.
• Table and column comments are not carried across the rebuild.

See docs/architecture.md for the reasoning, and docs/out-of-scope.md for approaches considered and not pursued.

🏗️ Development

Setup, local checks, CI, and release process: CONTRIBUTING.md.

⚖️ License

MIT

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[!NOTE] Yes, an AI wrote this README. And the code, the docs, the tests, and the .claude/skills it now uses to write the next round. Yes, a human told it to keep the emojis. The human has ADHD, which, as it turns out, means his brain was already doing attention re-routing and context-window thrashing before LLMs made it cool. They call him ... LLMartin. The emojis are a feature.