Order search scans large histories through JavaScript UDFs #1185

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Bug description / summary

GET /api/orders?search=... does register orders_search_contains and orders_search_digits_contains again for each non-empty search. The registration itself is not a meaningful performance problem: on the tested runtime, re-registering the pair took a median 1.155 microseconds, and request timings with registration enabled/disabled showed no consistent difference. Repeated searches after one registration returned identical results.

The reproducible large-history cost is the search scan: a no-match query scans orders in created_at order and invokes the JavaScript orders_search_contains callback for each order number and each linked customer name. The synchronous .all() runs in the order route. At 300,000 synthetic orders, the actual API response took about 235 ms at p50 and invoked the callback 540,300 times. This is a performance finding about the UDF-per-row scan, not a claim that repeated registration is the cause.

Steps to reproduce

1. On the tested revision, initialize a temporary database with the current schema/indexes and seed synthetic histories of 1,000, 10,000, 100,000, and 300,000 orders. The benchmark used 1,000 customers, 80.1% customer-linked orders, and one target customer on every 1,000th order; no real customer data was used.
2. Send repeated authenticated requests to GET /api/orders?per_page=50&search=benchmark-not-found-token.
3. Repeat the same search after registering the functions once on that database connection, but skip subsequent db.function() calls. Compare results and timings.

Expected behavior

Search results and pagination should preserve current matching behavior while large histories do not require a JavaScript callback for every historical row when the query has no/very few matches. The 50-row page limit should bound returned/hydrated rows; today it does not bound rows examined for selective searches.

Actual behavior

The query plan scans orders using the created_at index, evaluates the custom search predicates, and uses only the customer primary-key index for the correlated customer lookup. A no-match search examines the full history. Searching for one old order-number match likewise cannot stop after finding that single result because the query must continue to establish whether there are 51 matches.

Tested revision and benchmark environment

• Branch: main
• Commit: 7ca68a0a14e8be8557d0038af4977f144251320a
• FloCafe package version: 3.13.0
• Runtime: Node v26.9.0, macOS arm64, better-sqlite3 13.0.3, SQLite 3.53.4
• Method: current Express route over local HTTP, current migrations/schema and indexes, temporary SQLite DB, repeated warm requests. No tracked files, migrations, indexes, app settings, or customer records were changed.

There were five API samples per registration mode at each size; the differences are inconsistent and dominated by scan/runtime variation. Direct repeated registration of both production-equivalent callbacks measured p50 1.155 microseconds per pair. For the letter-containing no-match query, both functions are registered each request but orders_search_digits_contains is not invoked. The 300k phone query (+1 (555) 222-0199) returned 50 rows plus a cursor after an early match; it invoked orders_search_contains 91,851 times and orders_search_digits_contains 81,651 times.

As a diagnostic only, a scan-only SQLite instr(lower(...), lower(?)) query with the same plan and an ASCII no-match term measured p50 171.304 ms at 300k versus 235.923 ms for the JavaScript-UDF scan. This is not a drop-in replacement: SQLite's built-in lower() does not preserve the current Unicode case-insensitive behavior.

Query plan and source

Both the text and phone search plans were:

SCAN orders USING INDEX idx_orders_created
CORRELATED SCALAR SUBQUERY 1
SEARCH search_customer USING INDEX sqlite_autoindex_customers_1 (id=?)

The phone plan does not use idx_customers_phone_digits_unique; the search wraps phone fields in a substring UDF. The current order-number/name/phone substring predicates have no searchable B-tree index.

• UDF registration, normalization, and predicates: main/routes/orders.ts
• Search query, order-by, limit, and synchronous .all(): main/routes/orders.ts
• Existing order/customer indexes: main/db.ts, main/db.ts
• Search request debounce and API parameters: frontend orders page, filter debounce
• Existing API regression tests: tests/orders-search-api.test.ts

Concrete impact

At 100,000 orders (roughly one year at 300 orders/day), a no-match search took about 83 ms p50. At 300,000 orders (about 2.7 years at that rate), it took about 235 ms p50, with p90 about 251 ms in the registration-enabled samples. The search filter waits 300 ms before issuing a request, so an older-history search can take roughly half a second from a filter change to response on this benchmark machine, before other UI/network work. Because this route uses synchronous SQLite access, the backend event loop is occupied for the scan. Slower machines may take longer.

Suggested minimal change

Do not treat moving registration as the performance fix: that only saves about 1 microsecond/request. For the actual scan, evaluate indexed candidate retrieval (for example, an FTS5 trigram path for eligible order-number/name substrings) and run the existing UDF as the final verifier. Keep the current fallback for short queries and phone normalization unless candidate retrieval is proven complete for those inputs. The tested SQLite runtime supports FTS5 trigram, but packaged targets must be checked. Do not replace the matcher with SQLite lower() without preserving Unicode behavior, and do not mark the UDF deterministic as a substitute for reducing scanned rows.

Correctness-preserving acceptance criteria and regression tests

• Keep result sets, case-insensitive Unicode/name matching, order-number substring matching, phone digit fragments across punctuation, mixed text-plus-digits behavior, null-customer behavior, and cursor pagination identical.
• Add a repeated-request/connection-reopen test showing functions remain available when installed once per database connection; do not require re-registration per request.
• Add a reproducible temporary-database benchmark at 100k and 300k rows with EXPLAIN QUERY PLAN, p50/p95 latency, and callback counts. Show that the indexed path reduces rows/callbacks materially without a full scan for eligible searches; avoid flaky wall-clock assertions in the ordinary unit suite.
• Keep existing API coverage passing: npx ts-node --transpile-only -P tests/tsconfig.json tests/orders-search-api.test.ts passed on the tested commit. Additional synthetic API probes passed for order number, Unicode zoë, case-insensitive apostrophe name, punctuated and fragment phone searches, mixed alphanumeric input, and searches after registration was skipped.

Reference: ARCH-009b. Related earlier issues: #719 (customer-name/phone search), #1074 (order pagination), and #208 (large-history performance findings).

Environment

• Operating System: macOS arm64 (benchmark harness)
• Installation Method: Source / development build
• FloCafe version: 3.13.0 at 7ca68a0a14e8be8557d0038af4977f144251320a