The log is now a 16-byte file header (magic, version, codec, block
target) plus a sequence of blocks. Each block keeps the pre-existing
record framing unchanged, so Engine.apply_record does not change; records
never straddle blocks (appends accumulate in memory and the block seals
at ~256 KiB). The block header's integrity hash covers the stored payload
bytes exactly as they sit on disk, so the decompressor only ever sees
input already proven intact. Torn tails stay distinguishable from
interior corruption exactly as before: a short read, an impossible
length, or a hash mismatch in the final block truncates cleanly (later
appends overwrite the garbage); a hash mismatch anywhere else is
error.InvalidLog.
The codec is a hand-rolled LZ4 block compressor/decompressor (~1.7 GB/s
measured) with a per-block codec byte falling back to raw when
compression does not help; the header keeps raw legal so zstd can be
swapped in later. Zig 0.16 ships zstd decompression only, and deflate
would cap writes below the insert rate.
Engine.compact goes through the same Log API (deferred sync, one commit)
and compresses for free; sync() seals the pending block before fsyncing,
so the acknowledged-write durability semantics are unchanged (an
unsealed block holds only unacknowledged batch records).
Measured (tests/e2e/results/phase4.txt): db on disk 1025 -> 97 MB, now
smaller than MongoDB's own compressed files; bulk insert 816 -> 722 MB/s
(the accepted compression cost); reopen unchanged at 0.8 s.
Verified: unit suite in all three optimize modes (new LZ4 round-trip,
corrupt-block, and torn-tail truncation tests), the crash pair, e2e6
(kill -9 mid-write), and two full benchmark runs.
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.
Replace Index.entries (one sorted array) with a B+tree so writes into an
already-built index stop being quadratic. Nodes are fixed 4 KiB slotted
pages in a flat u32-addressed ArrayListUnmanaged(Node); records longer
than a quarter page spill to an append-only overflow slab (BSON strings
reach 16 MB). Leaves are doubly linked for ordered iteration; the flat
node array stays one contiguous byte range for a later checkpoint.
Insertion descends by separator and splits leaves/internals upward,
promoting keys via a stable copy (a nested split can otherwise clobber
the promoted-key scratch). Deletion does not rebalance: emptied leaves
are unlinked and dropped from their parent, internal nodes may carry one
child, and dead pages are abandoned in place (node memory peaks at the
tree's peak size, exactly what the old array's capacity did). Lookups
are lower-bound seeks plus leaf-chain band scans, so equal keys may
span leaves freely. Bulk build (append_doc_entries + finish_bulk) sorts
a staging array and packs leaves bottom-up. reserve_for now takes the
built entries and reserves exact overflow bytes plus a worst-case node
count, keeping insert_entries infallible after the log append.
db.zig: TTL sweep now seeks the minimum-datetime encoded key and walks
the contiguous datetime band, stopping at the cutoff or type change.
Measured (tests/e2e/results/phase2.txt): updateMany 17.3 -> 1.8 ms
(2.8x slower than MongoDB -> 3.7x faster), createIndex 62 -> 51 ms.
Verified: unit suite ReleaseFast/ReleaseSafe/Debug (incl. the existing
lookup_range and remove_doc differentials, plus a new incremental
insert/remove differential against a brute-force model), the crash pair,
e2e3/e2e4/e2e6, and dev stress tests for depth-2 splits, full drains,
and spilled records through internal levels.
Five items in dependency order, each sized to land on its own. The design
decisions already settled are recorded so they are not re-derived, and so
are the ordering constraints, which are the part that actually matters --
notably that the _id index must follow the tree, because it updates on
every insert and against a sorted array that is only affordable while ids
happen to append at the end.
Also carries the ground rules the earlier work established: A/B on one
harness rather than trusting a model, mutation-check tests that guard an
invariant, and the two absolutes (an index may only over-approximate; the
database must always open).
Each item names the traps found while investigating it -- deletion being
where B+trees go wrong, listIndexes possibly noticing a real _id_ index,
hashing compressed rather than uncompressed bytes, the fabricated
Document values that break when Document changes meaning, and the
durability guarantee that quietly weakens under group commit.
