Aleksey Shakhmatov
570900a6ef
Documents live as canonical BSON bytes in a segmented per-collection slab (fixed 8 MiB segments keep capacity slack under one segment); the docs map holds flat offsets that stay valid across segment growth, and removed documents leave garbage bytes until compaction rewrites. The per-document ArenaAllocator and its second full Pair-tree copy are gone. The matcher walks the stored bytes directly, skipping by length any field the filter does not name (a new bson byte-walker: element_key, skip_value, read_value with borrowed leaves, get_at, and a borrowed spine parse). The byte matcher is differential-tested against the tree matcher on a corpus and shares its operator logic. Stored documents are never materialized on the scan path or in aggregate $match; $group reads group keys and sums straight off the bytes. Sort, projection, findAndModify, updates and index entry generation use a borrowed spine into the slab (or the byte collector, which also replaced collect_values in build_entries). The compaction threshold now counts uncompressed data volume, since a compressed log would otherwise never trigger. Measured (tests/e2e/results/phase5.txt): server RSS 1979 -> 539 MB (2.4x smaller than MongoDB; phase1 baseline 2.0 GB), range-scan 22.5 -> ~12 ms (parity, best run faster than MongoDB), proj 4.1 -> 3.4 ms, createIndex parity. Verified: unit suite in all three modes with zero leaks, the crash pair, e2e6, and the stress/spill programs.
End-to-end tests with the official MongoDB Node.js driver
These exercise mongo-lite from a real driver over TCP: full CRUD, query operators, aggregation, error codes, concurrent clients, crash recovery, and the whole lifecycle including server restarts.
Setup
cd tests/e2e
npm init -y >/dev/null
npm install mongodb
Run
Most suites expect a server running on port 27020:
zig build
zig-out/bin/mongo-lite --port 27020 --db /tmp/ml-e2e.log --ttl-sweep-secs 1 &
node tests/e2e/e2e.js # CRUD + operators + aggregate + errors (29 checks)
node tests/e2e/e2e2.js concurrent # 8 clients: 4 writers + 4 readers (2 checks)
node tests/e2e/e2e2.js crash-a # write 50 docs, then kill -9 the server
node tests/e2e/e2e2.js crash-b # restart and verify all 50 survived
node tests/e2e/e2e3.js # secondary indexes: unique/sparse/compound (16 checks)
node tests/e2e/e2e4.js # TTL indexes: expiry + rejected specs (15 checks)
e2e4.js needs the server started with --ttl-sweep-secs 1 (the default is
60 seconds); the other suites do not care about the flag.
e2e6.js is the full-lifecycle suite and is self-contained: it spawns its
own server on port 27220 with a fresh log, runs the whole feature surface,
restarts the server twice (graceful SIGTERM, then kill -9 mid-write) and
verifies everything survived:
node tests/e2e/e2e6.js # 73 checks, ~15 s, needs no running server
E2E6_PORT=27300 node tests/e2e/e2e6.js # different port if 27220 is taken
Rebuild with zig build after any change under src/ before restarting the
server: zig build test compiles the test binary only and leaves
zig-out/bin/mongo-lite stale, so the suites keep running against the old
rules and report failures that the source no longer explains.
e2e2.js concurrent is safe to repeat against a running server (it drops its
collection first); crash-a/crash-b are two halves of one scenario.
Multi-GB collections: big.js
big.js is a load harness, not a pass/fail suite: it spawns a server, bulk
loads up to ~5 GB, and reports insert throughput, the compaction behavior,
server RSS, per-operation latencies, reopen (replay) time, and kill -9
durability.
node tests/e2e/big.js --quick # 268 MB smoke run
node tests/e2e/big.js --size 5g --doc-size 128k --oid --batch 200 \
--compact-threshold 2g # ~5 GB, 40k docs
Options: --size/--doc-size/--batch (k/m/g suffixes), --oid
(ObjectId _ids — see below), --index <field> (secondary index before
loading), --compact-threshold <bytes> (passed to the server),
--port, --keep (keep the db file).
Measured behavior (all documented in the top-level README):
- Build in ReleaseFast —
zig builddefaults to it; a Debug server is 10-200x slower on every path. - Insert throughput collapses under the default 16 MiB compaction
threshold: every ~16 MB of writes rewrites the whole log with one fsync
per record (O(n²) total). With
--compact-threshold 2gthe rate stays flat (hundreds of MB/s at 128 KB docs in ReleaseFast). Raise the threshold for bulk loads. findOne({_id})is O(1) only for ObjectId_ids. Integer_ids are serialization-ambiguous (int32/int64/double compare equal but hash differently), so the docs-map fast path is skipped and every lookup is a full scan. Use the driver's default ObjectId ids on big collections.- The engine holds everything in RAM: ~1-1.2x the data size at 128 KB docs (more at 16 KB docs, where per-document arena overhead dominates). A 5 GB collection needs roughly 6-7 GB of RAM.
- Reopen of a 5 GB log replays in ~10 s (ReleaseFast); every committed write survives kill -9.
Comparing against real MongoDB: compare.js + compare-run.sh
bash tests/e2e/compare-run.sh [size] [doc-size] # e.g. 1g 16k
Starts mongod (brew install mongodb-community) on :27018 and mongo-lite
on :27019, runs the same driver workload against each (durable writes:
mongo-lite fsyncs per command, mongod runs with j: true), measures kill -9
reopen for both, and prints a side-by-side table. compare.js alone runs
one side (see its --help-style header comment).