Aleksey Shakhmatov
58914a69c3
Give every Collection an implicit _id_ index (a normal Index with keys
[_id: 1]) so _id equality, $in, ranges and sorts stop depending on the
docs-map hash or a full scan. Kept out of the secondary indexes list, so
listIndexes/dropIndexes/createIndex and the log format are unchanged (no
index_create record, no double listing) and e2e3.js passes unmodified.
Maintained in upsert through the same reserve-then-insert protocol as
the secondaries, removed in evict_doc, and rebuilt after replay by
build_all_indexes alongside them (never maintained mid-replay, so a
failed add can't leave the index under-approximating). index.plan now
takes it as a separate argument. Its keys are canonical
(bson.encode_key gives int32 1, int64 1 and double 1.0 identical bytes),
so the serialization-guarded docs-map fast path (plan_id,
value_fast_path_safe and friends) is deleted.
Measured (tests/e2e/results/phase3.txt): sort({_id:-1}).limit(20) 6.2 ->
2.4 ms (2.3x slower than MongoDB -> parity); integer/string _id point
lookups, $in and ranges verified against the tree. Unit suite in all
three optimize modes, the crash pair, e2e3/e2e4/e2e6.
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).