Each branch node may have up to 16 sub-items - currently, these are
given VertexID based when they are first needed leading to a
mostly-random order of vertexid for each subitem.
Here, we pre-allocate all 16 vertex ids such that when a branch subitem
is filled, it already has a vertexid waiting for it. This brings several
important benefits:
* subitems are sorted and "close" in their id sequencing - this means
that when rocksdb stores them, they are likely to end up in the same
data block thus improving read efficiency
* because the ids are consequtive, we can store just the starting id and
a bitmap representing which subitems are in use - this reduces disk
space usage for branches allowing more of them fit into a single disk
read, further improving disk read and caching performance - disk usage
at block 18M is down from 84 to 78gb!
* the in-memory footprint of VertexRef reduced allowing more instances
to fit into caches and less memory to be used overall.
Because of the increased locality of reference, it turns out that we no
longer need to iterate over the entire database to efficiently generate
the hash key database because the normal computation is now faster -
this significantly benefits "live" chain processing as well where each
dirtied key must be accompanied by a read of all branch subitems next to
it - most of the performance benefit in this branch comes from this
locality-of-reference improvement.
On a sample resync, there's already ~20% improvement with later blocks
seeing increasing benefit (because the trie is deeper in later blocks
leading to more benefit from branch read perf improvements)
```
blocks: 18729664, baseline: 190h43m49s, contender: 153h59m0s
Time (total): -36h44m48s, -19.27%
```
Note: clients need to be resynced as the PR changes the on-disk format
R.I.P. little bloom filter - your life in the repo was short but
valuable
Currently, computed hash keys are stored in a separate column family
with respect to the MPT data they're generated from - this has several
disadvantages:
* A lot of space is wasted because the lookup key (`RootedVertexID`) is
repeated in both tables - this is 30% of the `AriKey` content!
* rocksdb must maintain in-memory bloom filters and LRU caches for said
keys, doubling its "minimal efficient cache size"
* An extra disk traversal must be made to check for existence of cached
hash key
* Doubles the amount of files on disk due to each column family being
its own set of files
Here, the two CFs are joined such that both key and data is stored in
`AriVtx`. This means:
* we save ~30% disk space on repeated lookup keys
* we save ~2gb of memory overhead that can be used to cache data instead
of indices
* we can skip storing hash keys for MPT leaf nodes - these are trivial
to compute and waste a lot of space - previously they had to present in
the `AriKey` CF to avoid having to look in two tables on the happy path.
* There is a small increase in write amplification because when a hash
value is updated for a branch node, we must write both key and branch
data - previously we would write only the key
* There's a small shift in CPU usage - instead of performing lookups in
the database, hashes for leaf nodes are (re)-computed on the fly
* We can return to slightly smaller on-disk SST files since there's
fewer of them, which should reduce disk traffic a bit
Internally, there are also other advantages:
* when clearing keys, we no longer have to store a zero hash in memory -
instead, we deduce staleness of the cached key from the presence of an
updated VertexRef - this saves ~1gb of mem overhead during import
* hash key cache becomes dedicated to branch keys since leaf keys are no
longer stored in memory, reducing churn
* key computation is a lot faster thanks to the skipped second disk
traversal - a key computation for mainnet can be completed in 11 hours
instead of ~2 days (!) thanks to better cache usage and less read
amplification - with additional improvements to the on-disk format, we
can probably get rid of the initial full traversal method of seeding the
key cache on first start after import
All in all, this PR reduces the size of a mainnet database from 160gb to
110gb and the peak memory footprint during import by ~1-2gb.
This kind of data is not used except in tests where it is used only to
create databases that don't match actual usage of aristo.
Removing simplifies future optimizations that can focus on processing
specific leaf types more efficiently.
A casualty of this removal is some test code as well as some proof
generation code that is unused - on the surface, it looks like it should
be possible to port both of these to the more specific data types -
doing so would ensure that a database written by one part of the
codebase can interact with the other - as it stands, there is confusion
on this point since using the proof generation code will result in a
database of a shape that is incompatible with the rest of eth1.
* Add missing leaf cache update when a leaf turns to a branch with two
leaves (on merge) and vice versa (on delete) - this could lead to stale
leaves being returned from the cache causing validation failures - it
didn't happen because the leaf caches were not being used efficiently :)
* Replace `seq` with `ArrayBuf` in `Hike` allowing it to become
allocation-free - this PR also works around an inefficiency in nim in
returning large types via a `var` parameter
* Use the leaf cache instead of `getVtxRc` to fetch recent leaves - this
makes the vertex cache more efficient at caching branches because fewer
leaf requests pass through it.
* pre-allocate `blobify` data and remove redundant error handling
(cannot fail on correct data)
* use threadvar for temporary storage when decoding rdb, avoiding
closure env
* speed up database walkers by avoiding many temporaries
~5% perf improvement on block import, 100x on database iteration (useful
for building analysis tooling)
* Provide portal proof functions in `aristo_api`
why:
So it can be fully supported by `CoreDb`
* Fix prototype in `kvt_api`
* Fix node constructor for account leafs with storage trees
* Provide simple path check based on portal proof functionality
* Provide portal proof functionality in `CoreDb`
* Update TODO list
* Extracted `test_tx.testTxMergeProofAndKvpList()` => separate file
* Fix serialiser
why:
Typo lead to duplicate rlp-encoded nodes in chain
* Remove cruft
* Implemnt portal proof nodes generators `partXxxTwig()`
* Add unit test for portal proof nodes generator `partAccountTwig()`
* Cosmetics
* Simplify serialiser return code format
* Fix proof generator for extension nodes
why:
Code was simply bonkers, not detected before the unit tests were
adapted to check for just this.
* Implemented portal proof nodes verifier `partUntwig()`
* Cosmetics
* Fix `testutp` cli poblem
Jacek Sieka
tersec
andri lim
Jordan Hrycaj