dev/MultiforaDB
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

results: the M0 gates, measured

Browse Source 
PLAN D7's six items, with the numbers and the command that reproduces each in
tests/e2e/results/m0-gates.txt. Unit tests green in both optimize modes, the
whole e2e matrix green, the spec scorecard byte-identical at 131/161/195, and
the large smoke run at the scale D7.3 asked for:

  21.47 GB collection (1,310,720 x 16 KiB)
  data file                 21.75 GB      (+1.3% over the documents)
  log after the load        2.5 MB        (checkpoints reclaim it)
  kill -9 then reopen       0.5 s         (0.5 s at 4 GB too -- flat)
  RSS after reopen          237 MB        (1.1% of the data)
  count after restart       1,310,720     last document byte-intact
  acked writes after kill   200/200

That is the milestone's claim, measured: an open costs the working set rather
than the size of the database. Before M0 the same measurement was 523 MB
resident for a 512 MB database, because recovering each document's `_id` meant
reading every document at open.

Two gates need reading rather than a tick, and m0-gates.txt says so where a
reader would otherwise take a tick for granted.

The churn gate settles at 1.65x live data (delete-heavy) to 2.47x
(update-heavy), flat, above the ~1.3x amendment A2 hoped for. Rebuild-only
reclamation cannot reach that: it needs a whole second copy of the live data
before the first can be freed. The gate existed to decide whether doc-level
free lists are needed after M0, and that is the answer.

Benchmark parity holds for every read and latency row inside the run-to-run
spread, and bulk insert regresses 24% (732 -> 555 MB/s), reproducibly across
three runs. Risk 1 as written: document bytes now reach the disk uncompressed
on top of the LZ4 log. createIndex improves 62% from the same change.

Three measurement bugs fixed while running the gates, because each would have
put a false number in the README:

  - `compare-run.sh` measured "db on disk" as `du` of the log alone against
    `du` of mongod's whole dbpath. It reported 20 MB for a 1 GB collection --
    the documents had moved to <db>.data. Honest figure, measured: 914 MB of
    allocated blocks against mongod's compressed 85 MB.
  - `big.js` counted "compaction events" as "the log shrank", which is a
    *checkpoint* now. It claimed 12 compaction rewrites during a pure insert
    load, which has no garbage to compact.
  - `big.js` labelled peak RSS "in-memory engine: docs live in RAM" and its
    summary said the collection was held "fully in RAM". Both were true of the
    engine this milestone replaced.

README: the storage section described an all-in-RAM engine; the comparison
table mixed one old run's body with three new rows; and `findOne({_id})` was
documented as a full scan for integer ids, which the ordered `_id_` index made
false (2 ms against 55 s for a scan of the same 21.5 GB collection). The table
is now best-of-three for both servers, with the measured variance stated, since
two runs of the same binary moved the sub-10 ms rows by 27-51%.
This commit is contained in:
Alexey Shakhmatov
2026-08-03 23:09:43 +03:00
parent 4b70ce6da9
commit 504179acd1
9 changed files with 505 additions and 87 deletions
Download Patch File Download Diff File Expand all files Collapse all files

36
tests/e2e/results/bench-20260803-223947.txt Normal file
View File

@@ -0,0 +1,36 @@
# multiforadb vs MongoDB benchmark
# date: 2026-08-03T19:42:00Z git: 5228ed7+dirty
# args: size=1g doc-size=16k wc=j clients=1 4 8 16 32 per-client=2000
# reproduce: bash tests/e2e/bench-run.sh 1g 16k "1 4 8 16 32"
[main]
insertOne (sequential) ×200 0.20 ms 4.9 ms
bulk insert throughput 463.4 MB/s 581.3 MB/s
docs loaded 65,536 65,536
createIndex({k: 1}) 27.9 ms 78.1 ms
countDocuments({}) 2.6 ms 12.8 ms
findOne({_id: <ObjectId>}) 0.64 ms 0.72 ms
findOne({k: 500}) (indexed) 0.59 ms 1.6 ms
find({p: {$gte,$lt}}).count() (scan) 14.1 ms 12.5 ms
find({}).sort({_id:-1}).limit(20) 1.5 ms 2.4 ms
find({}, {proj}).limit(1000) 3.6 ms 4.7 ms
aggregate $group by k 8.4 ms 13.4 ms
updateOne({_id}) ×50 0.15 ms 0.23 ms
updateMany({k: 7}, {$inc}) 1.9 ms 7.0 ms
deleteOne({_id}) + insertOne 0.63 ms 5.8 ms
node client RSS 153 MB 155 MB
[concurrency]
clients 1 8354 204 41.0x
clients 4 465 0.0x
clients 8 978 0.0x
clients 16 1877 0.0x
clients 32 3765 0.0x
[meta]
mfdb_rss_mb 1059
md_rss_mb 1203
mfdb_reopen 0.3s
md_reopen 1.3s
mfdb_disk_mb 20MB
md_disk_mb 83MB

36
tests/e2e/results/bench-20260803-225128.txt Normal file
View File

@@ -0,0 +1,36 @@
# multiforadb vs MongoDB benchmark
# date: 2026-08-03T19:53:01Z git: 4b70ce6+dirty
# args: size=1g doc-size=16k wc=j clients=1 4 8 16 32 per-client=2000
# reproduce: bash tests/e2e/bench-run.sh 1g 16k "1 4 8 16 32"
[main]
insertOne (sequential) ×200 0.22 ms 4.4 ms
bulk insert throughput 555.5 MB/s 738.5 MB/s
docs loaded 65,536 65,536
createIndex({k: 1}) 28.0 ms 70.0 ms
countDocuments({}) 2.8 ms 12.3 ms
findOne({_id: <ObjectId>}) 0.60 ms 0.61 ms
findOne({k: 500}) (indexed) 0.54 ms 1.1 ms
find({p: {$gte,$lt}}).count() (scan) 11.2 ms 13.2 ms
find({}).sort({_id:-1}).limit(20) 1.5 ms 2.0 ms
find({}, {proj}).limit(1000) 3.8 ms 4.3 ms
aggregate $group by k 7.4 ms 15.8 ms
updateOne({_id}) ×50 0.18 ms 0.21 ms
updateMany({k: 7}, {$inc}) 1.9 ms 5.9 ms
deleteOne({_id}) + insertOne 0.67 ms 5.1 ms
node client RSS 163 MB 155 MB
[concurrency]
clients 1 8373 218 38.4x
clients 4 20880 491 42.5x
clients 8 26349 964 27.3x
clients 16 29594 1710 17.3x
clients 32 32235 3389 9.5x
[meta]
mfdb_rss_mb 1059
md_rss_mb 1242
mfdb_reopen 0.3s
md_reopen 1.3s
mfdb_disk_mb 20MB
md_disk_mb 87MB

36
tests/e2e/results/bench-20260803-225322.txt Normal file
View File

@@ -0,0 +1,36 @@
# multiforadb vs MongoDB benchmark
# date: 2026-08-03T19:54:54Z git: 4b70ce6+dirty
# args: size=1g doc-size=16k wc=j clients=1 4 8 16 32 per-client=2000
# reproduce: bash tests/e2e/bench-run.sh 1g 16k "1 4 8 16 32"
[main]
insertOne (sequential) ×200 0.21 ms 4.4 ms
bulk insert throughput 550.4 MB/s 721.6 MB/s
docs loaded 65,536 65,536
createIndex({k: 1}) 28.9 ms 72.5 ms
countDocuments({}) 3.6 ms 11.3 ms
findOne({_id: <ObjectId>}) 0.80 ms 0.76 ms
findOne({k: 500}) (indexed) 0.73 ms 5.4 ms
find({p: {$gte,$lt}}).count() (scan) 14.5 ms 15.4 ms
find({}).sort({_id:-1}).limit(20) 1.9 ms 2.6 ms
find({}, {proj}).limit(1000) 3.8 ms 4.9 ms
aggregate $group by k 11.2 ms 15.5 ms
updateOne({_id}) ×50 0.17 ms 0.21 ms
updateMany({k: 7}, {$inc}) 2.0 ms 6.1 ms
deleteOne({_id}) + insertOne 0.69 ms 4.9 ms
node client RSS 150 MB 156 MB
[concurrency]
clients 1 7709 229 33.7x
clients 4 20122 493 40.8x
clients 8 26210 977 26.8x
clients 16 27794 1895 14.7x
clients 32 32817 3249 10.1x
[meta]
mfdb_rss_mb 1060
md_rss_mb 1178
mfdb_reopen 0.3s
md_reopen 1.3s
mfdb_disk_mb 20MB
md_disk_mb 85MB

52
tests/e2e/results/bench-latest.txt
View File

@@ -1,36 +1,36 @@
# mongo-lite vs MongoDB benchmark
# date: 2026-08-03T08:53:32Z git: c8d547f+dirty
# multiforadb vs MongoDB benchmark
# date: 2026-08-03T19:54:54Z git: 4b70ce6+dirty
# args: size=1g doc-size=16k wc=j clients=1 4 8 16 32 per-client=2000
# reproduce: bash tests/e2e/bench-run.sh 1g 16k "1 4 8 16 32"
[main]
insertOne (sequential) ×200 0.20 ms 14.8 ms
bulk insert throughput 732.4 MB/s 546.2 MB/s
insertOne (sequential) ×200 0.21 ms 4.4 ms
bulk insert throughput 550.4 MB/s 721.6 MB/s
docs loaded 65,536 65,536
createIndex({k: 1}) 74.4 ms 83.6 ms
countDocuments({}) 3.1 ms 12.4 ms
findOne({_id: <ObjectId>}) 0.59 ms 0.61 ms
findOne({k: 500}) (indexed) 0.56 ms 0.94 ms
find({p: {$gte,$lt}}).count() (scan) 13.0 ms 15.0 ms
find({}).sort({_id:-1}).limit(20) 2.2 ms 2.2 ms
find({}, {proj}).limit(1000) 3.5 ms 4.4 ms
aggregate $group by k 8.3 ms 13.2 ms
updateOne({_id}) ×50 0.14 ms 0.20 ms
updateMany({k: 7}, {$inc}) 1.9 ms 6.4 ms
deleteOne({_id}) + insertOne 0.58 ms 4.9 ms
node client RSS 158 MB 157 MB
createIndex({k: 1}) 28.9 ms 72.5 ms
countDocuments({}) 3.6 ms 11.3 ms
findOne({_id: <ObjectId>}) 0.80 ms 0.76 ms
findOne({k: 500}) (indexed) 0.73 ms 5.4 ms
find({p: {$gte,$lt}}).count() (scan) 14.5 ms 15.4 ms
find({}).sort({_id:-1}).limit(20) 1.9 ms 2.6 ms
find({}, {proj}).limit(1000) 3.8 ms 4.9 ms
aggregate $group by k 11.2 ms 15.5 ms
updateOne({_id}) ×50 0.17 ms 0.21 ms
updateMany({k: 7}, {$inc}) 2.0 ms 6.1 ms
deleteOne({_id}) + insertOne 0.69 ms 4.9 ms
node client RSS 150 MB 156 MB
[concurrency]
clients 1 8435 232 36.4x
clients 4 22480 491 45.8x
clients 8 25920 966 26.8x
clients 16 31079 1842 16.9x
clients 32 34041 3632 9.4x
clients 1 7709 229 33.7x
clients 4 20122 493 40.8x
clients 8 26210 977 26.8x
clients 16 27794 1895 14.7x
clients 32 32817 3249 10.1x
[meta]
ml_rss_mb 553
md_rss_mb 1486
ml_reopen 0.8s
mfdb_rss_mb 1060
md_rss_mb 1178
mfdb_reopen 0.3s
md_reopen 1.3s
ml_disk_mb 97MB
md_disk_mb 106MB
mfdb_disk_mb 20MB
md_disk_mb 85MB

156
tests/e2e/results/m0-gates.txt Normal file
View File

@@ -0,0 +1,156 @@
# M0 gate results — mmap + WAL storage foundation (PLAN D7)
#
# Machine: Apple Silicon, macOS 25.5.0, 16 KiB system pages, APFS.
# Server: MultiforaDB at the commit named below, ReleaseFast.
# Driver: mongodb@7.5.0 (pinned in tests/e2e/package-lock.json).
# mongod: 8.3.7, for the parity rows.
#
# Read this alongside PLAN.md §5. Every number here is reproducible with the
# command printed under it; where a gate was not met, the number is recorded as
# measured and the reason is stated rather than the workload being tuned until
# it passed.
[D7.1] unit tests, ReleaseFast and ReleaseSafe
zig build test -Doptimize=ReleaseFast 122/122 pass
zig build test -Doptimize=ReleaseSafe 122/122 pass
zig build fuzz fuzz_split, spill, spill2, stress clean
Both modes matter: `protect_stable` (the mprotect belt over the published
image) is comptime-off in ReleaseFast, and `std.posix.mprotect` not existing
in Zig 0.16 was a ReleaseSafe-only compile error.
[D7.2] end-to-end suites — all green
reproduce: zig-out/bin/multiforadb --port 27020 --db /tmp/mfdb-e2e.log \
--ttl-sweep-secs 1 & then node tests/e2e/<suite>
e2e.js CRUD, operators, aggregate, errors 35/35
e2e3.js secondary indexes: unique/sparse/compound 16/16
e2e4.js TTL indexes: expiry and rejected specs 17/17
e2e5.js miscellaneous command surface 3/3
e2e2.js concurrent, 4 writers + 4 readers 2/2
e2e2.js crash-a / crash-b (kill -9, then verify) 1/1 then 3/3
e2e6.js compaction and log growth (own server) 72/72
[D7.3] large-collection smoke — big.js
reproduce: node tests/e2e/big.js --size 20g --doc-size 16k
20g run 4g run
documents 1,310,720 262,144 (x 16 KiB)
live data 21.47 GB 4.29 GB
data file 21.75 GB 4.35 GB (+1.3%, +1.4%)
log file, min -> final 16 B -> 2.5 MB 16 B -> 7.7 MB
bulk insert 411.0 MB/s 560.3 MB/s
peak server RSS during load 18,492 MB 3,318 MB
kill -9 then reopen 0.5 s 0.5 s
RSS after reopen 237 MB (1.1%) 130 MB (3.0%)
count after restart 1,310,720 OK 262,144 OK
last doc intact after restart payload 16254B OK
kill -9 after 200 acked writes 200/200 200/200
This is the milestone's central claim, measured: an open costs the working
set, not the size of the database, and it no longer replays the whole log.
Reopen is flat at 0.5 s from 4 GB to 21.5 GB, and RSS after reopen falls as a
*share* of the data as the database grows — which is what "RSS = working set"
has to mean to be worth anything.
Before M0 the same shape of run reported 523 MB resident after reopen for a
512 MB database, because recovering each document's `_id` meant reading every
document at open. That scan is what the mmap foundation deleted.
Two other things the 20g run shows, honestly. Peak RSS during the *load* is
18.5 GB: writing 21 GB touches 21 GB of pages and the kernel keeps them until
it needs the memory, so a bulk load is not where the mmap win shows up. And a
cold full scan of 21 GB costs ~55 s — countDocuments, the range scan and the
unindexed updateMany all land there, ~390 MB/s off the disk — which is correct
and is the reason M1's cursors and index-only paths matter.
[D7.4] churn gate — doc/slab garbage (PLAN amendment A2 retargets D6.2 here)
40,000 x 16 KiB documents (655 MB live), one secondary index, steady state
measured as data-file size / live data after the ratio stopped moving.
before the fixes after
delete half and refill, 6 rounds 4.10x, climbing 1.65x, flat
random $set over 5x the collection 3.58x, climbing 2.47x, flat
"Climbing" is the whole finding: nothing was being reclaimed at all. Three
bugs, all fixed in `db/pager: reclaim what churn abandons` — a compaction
trigger that had read `log.data_bytes` since before the log was truncated at
every checkpoint, a numeric stable mark that made recycled pages look
published, and a first-fit free list that let one-page requests dismantle
the extents. A fourth fix (a rebuild publishes twice, so the space it frees
is reusable immediately) took the interleaved case from 3.58x to 2.47x.
The gate hoped for ~1.3x and this is above it, structurally: a rebuild needs
a whole second copy of the live data before the first can be freed, and
two-generation retention holds the old copy through two more publishes. The
gate's purpose was to decide whether doc-level free lists are needed after
M0. They are; that is an M1 item. What M0 owes is a bound, and there is one.
[D7.5] benchmark parity vs the pre-mmap engine
reproduce: bash tests/e2e/bench-run.sh 1g 16k "1 4 8 16 32"
baseline: tests/e2e/results/phase8.txt (c8d547f, all-in-RAM engine)
M0: three runs, tests/e2e/results/bench-2026080{3-223947,3-225128,3-225322}.txt
Read the range, not a single delta. Two consecutive runs of the *same* binary
moved the sub-10 ms rows by 27-51% on this machine, so any one comparison
reads whatever the noise did that minute. Best-of-three against the baseline:
row pre-mmap M0 min..max best
insertOne (sequential) x200 0.20 ms 0.20..0.22 ms +0%
bulk insert throughput 732.4 MB/s 463.4..555.5 MB/s -24%
createIndex({k: 1}) 74.4 ms 27.9..28.9 ms -62%
countDocuments({}) 3.1 ms 2.6..3.6 ms -16%
findOne({_id: <ObjectId>}) 0.59 ms 0.60..0.80 ms +2%
findOne({k: 500}) (indexed) 0.56 ms 0.54..0.73 ms -4%
find({p: {$gte,$lt}}).count() (scan) 13.0 ms 11.2..14.5 ms -14%
find({}).sort({_id:-1}).limit(20) 2.2 ms 1.5..1.9 ms -32%
find({}, {proj}).limit(1000) 3.5 ms 3.6..3.8 ms +3%
aggregate $group by k 8.3 ms 7.4..11.2 ms -11%
updateOne({_id}) x50 0.14 ms 0.15..0.18 ms +7%
updateMany({k: 7}, {$inc}) 1.9 ms 1.9..2.0 ms +0%
deleteOne({_id}) + insertOne 0.58 ms 0.63..0.69 ms +9%
node client RSS 158 MB 150..163 MB -5%
concurrent durable insertOne, docs/s:
clients 1 8,435 7,709..8,373 -1%
clients 4 22,480 20,122..20,880 -7%
clients 8 25,920 26,210..26,349 +2%
clients 16 31,079 27,794..29,594 -5%
clients 32 34,041 32,235..32,817 -4%
One reproducible regression: bulk insert, -24%, steady across all three runs.
This is PLAN risk 1 exactly as written -- document bytes now reach the disk
uncompressed in the data file on top of the LZ4 log, and that writeback
bandwidth is new. Every other row is inside the run-to-run spread. The gate
as stated was "no phase8 row regressed"; it is met for the read and latency
rows and not for bulk load, which is the trade the milestone makes and which
risk 1 anticipated. Untried mitigations, in the order worth trying:
MADV_HUGEPAGE / a larger growth chunk, and not writing doc bytes twice
(log and slab) for a bulk path that could log an extent reference instead.
createIndex at -62% is the other reproducible number, and it comes from the
same change: a bulk build now packs pages in the mapping instead of growing
an ArrayList.
[D7.6] MongoDB spec-test scorecard
reproduce: bash tests/spec/fetch.sh && node tests/spec/run.js --scorecard
total 131 pass 161 fail 195 skip 175 files 0 errored
Byte-identical to the scorecard recorded before the storage rewrite. That is
the intended result and it is worth stating plainly: M0 replaced the document
store, the node arena and the overflow slab, added copy-on-write, a watermark
and a checkpoint, and moved every index leaf's payload -- and changed no
observable CRUD or aggregate semantics.
# WHAT THE GATES FOUND
# Five bugs, none of which any unit test or e2e suite had reached:
# 1. The compaction trigger had been dead since commit 14 (log truncation
# zeroes the counter it gated on). Nothing reclaimed doc-slab garbage.
# 2. `page_mut_cow` asked `p >= stable_pages`, which is false for a recycled
# page, so every write to one copied and freed it again.
# 3. First fit let copy-on-write's one-page requests shave the extents the
# doc slab needs, so the free list drained every generation and the file
# grew anyway.
# 4. A rebuild's freed space took two unrelated checkpoints to become
# reusable, so the next rebuild grew the file instead of reusing it.
# 5. `reserve_pages`' promise was a single counter on the pager. Two upserts
# on different collections release it independently, so the first to
# finish revoked the second's promise mid-write -- aborting the server at
# four concurrent clients, on the first concurrent benchmark since the
# data file landed. PLAN risk 3, whose mitigation was never built.
# Four of the five are invisible without a workload that runs long enough to
# reach a steady state, or wide enough to have two writers. That is the
# argument for keeping both the churn gate and the concurrent benchmark in the
# gate list rather than treating them as optional.
#
# ONE COMPATIBILITY GAP FOUND, NOT FIXED (out of M0's scope, storage-only)
# `update.apply` (src/update.zig:18) rejects any update document whose first
# key is not `$`, so replacement-style writes -- replaceOne, findOneAndReplace,
# bulkWrite's replaceOne -- fail with "bad update". Found while building the
# churn workload. It is a CRUD feature, not storage, and it is already part of
# what the 161 spec failures cover.