Add vectorizer_status for embedding coverage and backlog by dpage · Pull Request #73 · pgEdge/pgedge-vectorizer

dpage · 2026-09-09T11:45:07Z

Summary

Embeddings are generated asynchronously, so a search always runs against a picture of the source that is some way out of date, and there was no way to find out how far. pgedge_vectorizer.vectorizer_status reports, per registered vectorizer, how much of the source is embedded and how much work is still queued.

Coverage is reported two ways, because they answer different questions. source_coverage (source rows with at least one embedded chunk) is the closer match to whether a search over the table can be trusted; chunk_coverage (individual chunks embedded) is the better measure of how much work remains. A large document part-way through embedding is covered on the first and only partly on the second.
Alongside those: queue_pending, queue_processing, queue_failed, oldest_pending_age and last_processed_at for the vectorizer.
Chunk tables are named in the registry rather than joined statically, so the counts come from dynamic SQL in a function that the view wraps. The function takes an optional source table and column, so one vectorizer can be inspected without paying for all of them.

Two choices worth calling out. The function runs as the caller and reports NULL counts for a chunk or source table that has been dropped or that the caller cannot read, rather than failing the whole result set. And a source_coverage above 1 is left visible rather than clamped, because it means the chunk table holds rows for source rows that have gone, which is a real problem worth seeing.

Each row costs a scan of one chunk table and a count of one source table, which is considerably more than the existing queue views cost. docs/monitoring.md says so plainly and frames it as a diagnostic to run deliberately rather than something to poll.

Schema-qualified chunk table names

Review turned up a bug that predates this change and that the new view made visible. enable_vectorization() builds the chunk table's name as source_table || column || '_chunks' and creates it with %I, so for a source table in a schema the dot ends up inside a single identifier rather than separating a schema from a relation. Three to_regclass() lookups passed that name unquoted and so read the dot as qualification:

vectorizer_status(), where the failed lookup left every chunk-derived column NULL whilst the queue columns carried on, reading as a table with no chunks rather than as a lookup that failed;
recreate_chunks(), where it raises Chunk table % does not exist. Use enable_vectorization() first. for a vectorizer that was enabled perfectly correctly, so a rebuild is impossible for any source table outside the search path;
vectorization_truncate_trigger(), where it silently skips the _idf_stats reset, so truncating the source empties every chunk but leaves the corpus statistics describing chunks that have gone.

All three now use quote_ident(). recreate_chunks() was already being redefined by the upgrade script for the token_count change, so it picks the fix up there; the truncate trigger function was not, and the upgrade script now replaces it.

Separately, vectorizer_status() resolved the source table without guarding to_regclass(), which raises insufficient_privilege rather than returning NULL for a qualified name whose schema the caller has no USAGE on. A caller with rights on one vectorizer and not on another's schema therefore got an error for the whole result set instead of the rows it could see. The lookup is now guarded, and the narrowing by source table moved into the loop body for the same reason.

Test plan

New vectorizer_status regression test walks coverage from none through partial to complete, checks failed items are counted apart from the pending backlog, checks narrowing by table and by column, and checks the two degraded cases (coverage above 1 after orphaning, NULL counts after the chunk table is dropped).
Regression coverage for the quoting fixes: maintenance rebuilds a schema-qualified vectorizer, delete_truncate truncates one and asserts the BM25 statistics go with it, and vectorizer_status queries the view as a role with no USAGE on the schema holding one of the registered source tables.
Full suite green against PostgreSQL 18.6: 22 pg_regress tests and 69 TAP tests.
Upgrade path exercised by hand: CREATE EXTENSION ... VERSION '1.1', enable a vectorizer, ALTER EXTENSION ... UPDATE TO '1.2', then query the view, rebuild and truncate against a chunk table created under 1.1.

Note on the base branch

This is stacked on #72, which creates the 1.2 scripts this change also lands in, so the branch is cut from token-count-consistency and the diff below carries that commit too. It targets main rather than the stack parent only because CI is configured to run on main, master and develop alone, so a PR aimed at the parent gets no checks at all. Once #72 merges, the diff here reduces to just this feature. Review the second commit; the first is #72.

Closes #25

codacy-production · 2026-09-09T11:45:54Z

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coderabbitai · 2026-09-09T11:54:07Z

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📝 Walkthrough

Walkthrough

The extension version increases to 1.2. The extension adds C-backed token counting and uses it across chunk processing paths. The 1.2 SQL installation adds vectorization lifecycle functions, queue utilities, monitoring views, and hybrid search. The vectorizer_status function and view report embedding coverage, queue state, and processing timestamps. The changes include a 1.1-to-1.2 migration, documentation, and regression tests.

Priority: ➖ Normal

Severity of issue fixed: Medium

Merge Risk: 🔵 Low · up to 50d22

The new status reporting behaves as documented. For vectorizers on schema-qualified tables, rebuilding chunks fails with a "does not exist" error, and truncating the source leaves stale BM25 statistics. This problem already exists in 1.1 and is carried forward in the 1.2 functions. It is a small, localized fix that is worth making before release, but it does not block the new status feature.

🚥 Pre-merge checks | ✅ 3 | ❌ 2

❌ Failed checks (2 warnings)

Check name	Status	Explanation	Resolution
Out of Scope Changes check	⚠️ Warning	The whole-PR change set includes concrete functionality unrelated to issue `#25`. Examples include the new `count_tokens()` C and SQL API with token-count integration tests, broad token-count changes, a…	Remove unrelated `count_tokens()` and hybrid-search changes from this pull request, or provide evidence that they are required dependencies of the status feature. Keep only status implementation, required migration wiring, documentation, an…
Docstring Coverage	⚠️ Warning	Docstring coverage is 50.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 2 functions across 2 files. (3 skipped: 3…	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (3 passed)

Check name	Status	Explanation
Linked Issues check	✅ Passed	The PR implements the coding requirements in issue `#25`. It adds `pgedge_vectorizer.vectorizer_status` and the filtering function. The reported metrics include source and chunk coverage, pending, proce…
Title check	✅ Passed	The title clearly identifies the main change: adding vectorizer status reporting for embedding coverage and backlog.
Description check	✅ Passed	The description explains the status metrics, filtering, table-access behavior, schema-qualified name fixes, and test coverage. It is directly related to the changeset.

Full details: Out of Scope Changes check

Explanation

The whole-PR change set includes concrete functionality unrelated to issue #25. Examples include the new count_tokens() C and SQL API with token-count integration tests, broad token-count changes, and new hybrid-search functions and behavior. These changes do not implement or support the vectorizer_status metrics. The summary does not establish that these changes were already present at the merge base.

Resolution

Remove unrelated count_tokens() and hybrid-search changes from this pull request, or provide evidence that they are required dependencies of the status feature. Keep only status implementation, required migration wiring, documentation, and focused tests.

Full details: Docstring Coverage

Explanation

Docstring coverage is 50.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 2 functions across 2 files. (3 skipped: 3 unsupported.)

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In `@sql/pgedge_vectorizer--1.2.sql`:
- Line 1096: Update the chunk-table lookup in vectorizer_status() to pass
quote_ident(v.chunk_table) to to_regclass(), preserving the generated
schema-qualified name as a single identifier. Apply the same change in both SQL
scripts.

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Makefile
docs/api_reference.md
docs/changelog.md
docs/monitoring.md
pgedge_vectorizer.control
sql/pgedge_vectorizer--1.1--1.2.sql
sql/pgedge_vectorizer--1.2.sql
src/pgedge_vectorizer.h
src/tokenizer.c
test/sql/count_tokens.sql
test/sql/vectorizer_status.sql

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enable_vectorization() builds the chunk table's name as source_table || column || '_chunks' and creates it with %I, so for a schema-qualified source table the dot ends up inside a single identifier rather than separating a schema from a relation. Passing that text to to_regclass() as it stands makes it look for a relation in a schema of that name, finds nothing, and leaves every chunk-derived column NULL whilst the queue columns carry on working, which reads as a table with no chunks rather than as a lookup that failed. quote_ident() keeps the name in one piece, matching what quote_identifier() already does for the same value in bm25.c. The source table's name is left alone, since that comes from regclass output and is a genuine qualified reference. Raised by CodeRabbit on #73.

to_regclass() does not return NULL for every name it cannot resolve. Given a qualified name whose schema the caller has no USAGE on, it raises insufficient_privilege instead, so vectorizer_status() failed the entire result set for a caller holding rights on one vectorizer but not on another's schema, and the has_table_privilege() check that was meant to catch exactly that case never ran. Resolve the source table inside a block that traps insufficient_privilege and leaves src_oid NULL, which restores what the comment above the counts promises: a vectorizer the caller cannot read reports NULL counts rather than making the view useless for every other one. The narrowing by p_source_table moves out of the query driving the loop and into the loop body for the same reason, since resolving every registry row in the WHERE clause raises on a vectorizer the caller cannot see even when it asked about a different table. The chunk table lookup needs no guard: quote_ident() makes it a single unqualified name, and an unqualified lookup skips schemas without USAGE rather than erroring. The regression test covers both paths with a role that has no USAGE on the schema holding one of the registered source tables. Raised by Ibrar Ahmed on #73.

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Inline comments:
In `@sql/pgedge_vectorizer--1.2.sql`:
- Line 1307: Quote stored generated chunk-table names with quote_ident before
passing them to to_regclass, including the chunk_table_name lookup and the
related _idf_stats lookup. Preserve the existing existence checks while ensuring
each schema-qualified name is resolved as one identifier.

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to_regclass() does not return NULL for every name it cannot resolve. Given a qualified name whose schema the caller has no USAGE on, it raises insufficient_privilege instead, so vectorizer_status() failed the entire result set for a caller holding rights on one vectorizer but not on another's schema, and the has_table_privilege() check that was meant to catch exactly that case never ran. Resolve the source table inside a block that traps insufficient_privilege and leaves src_oid NULL, which restores what the comment above the counts promises: a vectorizer the caller cannot read reports NULL counts rather than making the view useless for every other one. The narrowing by p_source_table moves out of the query driving the loop and into the loop body for the same reason, since resolving every registry row in the WHERE clause raises on a vectorizer the caller cannot see even when it asked about a different table. The chunk table lookup needs no guard: quote_ident() makes it a single unqualified name, and an unqualified lookup skips schemas without USAGE rather than erroring. The regression test covers both paths with a role that has no USAGE on the schema holding one of the registered source tables. Raised by Ibrar Ahmed on #73.

The chunk table's name is generated as source_table || column || '_chunks' and created with %I, so for a schema-qualified source the dot is part of a single identifier. Passing it to to_regclass() unquoted makes the lookup read the dot as qualification and come back NULL for a table that is plainly there, which was fixed for vectorizer_status() earlier in this branch but left in two other places carried over from 1.1. In recreate_chunks() the failed lookup raises 'Chunk table % does not exist. Use enable_vectorization() first.' for a vectorizer that was enabled quite correctly, so the rebuild is impossible for any source table outside the search path. In vectorization_truncate_trigger() it skips the reset of the BM25 statistics table, so truncating the source empties every chunk but leaves the corpus statistics describing chunks that no longer exist, which then skews hybrid search scores until something else rewrites them. recreate_chunks() was already being redefined by the upgrade script for the token_count change, so it picks the fix up there. The truncate trigger function was not, so the upgrade script now replaces it; the trigger itself is unchanged and does not need recreating. Raised by CodeRabbit on #73.

Embeddings are derived data generated asynchronously, so a search is always running against a picture of the source that is some way out of date, and until now there was no way to find out how far. Add a vectorizer_status view giving, per registered vectorizer, how much of the source is embedded and how much work is still queued, so that a user can judge whether a result set reflects recent changes and an operator can see a worker that has stalled or a provider that is rejecting requests. Coverage is reported two ways because they answer different questions. source_coverage, the fraction of source rows with at least one embedded chunk, is the closer match to whether a search over the table can be trusted, whilst chunk_coverage, the fraction of individual chunks embedded, is the better measure of how much work remains. A large document part-way through being embedded is covered on the first and only partly on the second. Alongside those are the pending, processing and failed queue counts for the vectorizer, the age of the oldest pending item and the timestamp of the most recent completion. Chunk tables are named in the registry rather than joined statically, so the counts are gathered with dynamic SQL in a function that the view wraps. The function takes an optional source table and column, so a single vectorizer can be inspected without paying for all of them; that matters because each row costs a scan of one chunk table and a count of one source table, which is a good deal more than the existing queue views cost. The docs say so plainly, and say that this is a diagnostic to run deliberately rather than something to poll. Two deliberate choices. The function runs as the caller and reports NULL counts for a chunk or source table that has been dropped or that the caller cannot read, rather than failing the whole result set, because one inaccessible vectorizer should not make the view useless for the rest. And a source_coverage above 1 is left visible rather than clamped, since it means the chunk table holds rows for source rows that have gone, which is a real problem worth seeing. Closes #25

enable_vectorization() builds the chunk table's name as source_table || column || '_chunks' and creates it with %I, so for a schema-qualified source table the dot ends up inside a single identifier rather than separating a schema from a relation. Passing that text to to_regclass() as it stands makes it look for a relation in a schema of that name, finds nothing, and leaves every chunk-derived column NULL whilst the queue columns carry on working, which reads as a table with no chunks rather than as a lookup that failed. quote_ident() keeps the name in one piece, matching what quote_identifier() already does for the same value in bm25.c. The source table's name is left alone, since that comes from regclass output and is a genuine qualified reference. Raised by CodeRabbit on #73.

to_regclass() does not return NULL for every name it cannot resolve. Given a qualified name whose schema the caller has no USAGE on, it raises insufficient_privilege instead, so vectorizer_status() failed the entire result set for a caller holding rights on one vectorizer but not on another's schema, and the has_table_privilege() check that was meant to catch exactly that case never ran. Resolve the source table inside a block that traps insufficient_privilege and leaves src_oid NULL, which restores what the comment above the counts promises: a vectorizer the caller cannot read reports NULL counts rather than making the view useless for every other one. The narrowing by p_source_table moves out of the query driving the loop and into the loop body for the same reason, since resolving every registry row in the WHERE clause raises on a vectorizer the caller cannot see even when it asked about a different table. The chunk table lookup needs no guard: quote_ident() makes it a single unqualified name, and an unqualified lookup skips schemas without USAGE rather than erroring. The regression test covers both paths with a role that has no USAGE on the schema holding one of the registered source tables. Raised by Ibrar Ahmed on #73.

The chunk table's name is generated as source_table || column || '_chunks' and created with %I, so for a schema-qualified source the dot is part of a single identifier. Passing it to to_regclass() unquoted makes the lookup read the dot as qualification and come back NULL for a table that is plainly there, which was fixed for vectorizer_status() earlier in this branch but left in two other places carried over from 1.1. In recreate_chunks() the failed lookup raises 'Chunk table % does not exist. Use enable_vectorization() first.' for a vectorizer that was enabled quite correctly, so the rebuild is impossible for any source table outside the search path. In vectorization_truncate_trigger() it skips the reset of the BM25 statistics table, so truncating the source empties every chunk but leaves the corpus statistics describing chunks that no longer exist, which then skews hybrid search scores until something else rewrites them. recreate_chunks() was already being redefined by the upgrade script for the token_count change, so it picks the fix up there. The truncate trigger function was not, so the upgrade script now replaces it; the trigger itself is unchanged and does not need recreating. Raised by CodeRabbit on #73.

ibrarahmad

Ran fresh 1.2 and an upgraded 1.1 -> 1.2 side by side: vectorizer_status returns the same counts on both, and recreate_chunks() on a schema-qualified source table now returns rather than raising, which is the bug the quote_ident() change was for.

Also pointed the view at a table named ev il""tbl to exercise the dynamic SQL over an identifier that needs quoting. It comes back correctly, so the generated names are being quoted properly.

setup, vectorizer_status, delete_truncate and maintenance pass.

Nothing blocking from me.

dpage changed the base branch from token-count-consistency to main September 9, 2026 11:45

dpage closed this Sep 9, 2026

dpage reopened this Sep 9, 2026

dpage force-pushed the fix/issue-25-vectorizer-status branch from 80db550 to 5c7d625 Compare September 9, 2026 11:47

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Comment thread sql/pgedge_vectorizer--1.2.sql Outdated

This was referenced Sep 9, 2026

Let each vectorizer choose its own provider and model #74

Merged

Changing pgedge_vectorizer.model silently re-points every inheriting vectorizer #75

Open

Record and repair embedding model drift #77

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ibrarahmad reviewed Sep 15, 2026

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dpage force-pushed the fix/issue-25-vectorizer-status branch from 2ff6fc7 to 50d22c2 Compare September 23, 2026 09:18

dpage requested a review from ibrarahmad September 23, 2026 09:18

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dpage force-pushed the fix/issue-25-vectorizer-status branch from 50d22c2 to 294a71f Compare September 23, 2026 09:26

dpage added 4 commits September 23, 2026 12:19

dpage force-pushed the fix/issue-25-vectorizer-status branch from a36532b to 87707d1 Compare September 23, 2026 11:22

dpage changed the base branch from main to token-count-consistency September 23, 2026 11:22

ibrarahmad approved these changes Sep 24, 2026

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dpage merged commit 3fed6db into token-count-consistency Oct 1, 2026
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Stop one provider's trouble becoming every provider's #79

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Add vectorizer_status for embedding coverage and backlog - #73

Add vectorizer_status for embedding coverage and backlog#73
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Summary

Schema-qualified chunk table names

Test plan

Note on the base branch

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Up to standards ✅

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