nimbus-eth1/nimbus/db/aristo/aristo_compute.nim

204 lines
6.7 KiB
Nim

# nimbus-eth1
# Copyright (c) 2023-2024 Status Research & Development GmbH
# Licensed under either of
# * Apache License, version 2.0, ([LICENSE-APACHE](LICENSE-APACHE) or
# http://www.apache.org/licenses/LICENSE-2.0)
# * MIT license ([LICENSE-MIT](LICENSE-MIT) or
# http://opensource.org/licenses/MIT)
# at your option. This file may not be copied, modified, or distributed
# except according to those terms.
{.push raises: [].}
import
std/strformat,
chronicles,
eth/common,
results,
"."/[aristo_desc, aristo_get, aristo_serialise],
./aristo_desc/desc_backend
type WriteBatch = tuple[writer: PutHdlRef, count: int, depth: int, prefix: uint64]
# Keep write batch size _around_ 1mb, give or take some overhead - this is a
# tradeoff between efficiency and memory usage with diminishing returns the
# larger it is..
const batchSize = 1024 * 1024 div (sizeof(RootedVertexID) + sizeof(HashKey))
func progress(batch: WriteBatch): string =
# Return an approximation on how much of the keyspace has been covered by
# looking at the path prefix that we're currently processing
&"{(float(batch.prefix) / float(uint64.high)) * 100:02.2f}%"
func enter(batch: var WriteBatch, nibble: int) =
batch.depth += 1
if batch.depth <= 16:
batch.prefix += uint64(nibble) shl ((16 - batch.depth) * 4)
func leave(batch: var WriteBatch, nibble: int) =
if batch.depth <= 16:
batch.prefix -= uint64(nibble) shl ((16 - batch.depth) * 4)
batch.depth -= 1
proc putKeyAtLevel(
db: AristoDbRef,
rvid: RootedVertexID,
key: HashKey,
level: int,
batch: var WriteBatch,
): Result[void, AristoError] =
## Store a hash key in the given layer or directly to the underlying database
## which helps ensure that memory usage is proportional to the pending change
## set (vertex data may have been committed to disk without computing the
## corresponding hash!)
# Only put computed keys in the database which keeps churn down by focusing on
# the ones that do not change - the ones that don't require hashing might as
# well be loaded from the vertex!
if level == -2:
if key.len == 32:
let be = db.backend
if batch.writer == nil:
doAssert be != nil, "source data is from the backend"
# TODO long-running batch here?
batch.writer = ?be.putBegFn()
be.putKeyFn(batch.writer, rvid, key)
batch.count += 1
if batch.count mod batchSize == 0:
if batch.count mod (batchSize * 100) == 0:
info "Writing computeKey cache",
count = batch.count, accounts = batch.progress
else:
debug "Writing computeKey cache",
count = batch.count, accounts = batch.progress
?be.putEndFn batch.writer
batch.writer = nil
ok()
else:
db.deltaAtLevel(level).kMap[rvid] = key
ok()
func maxLevel(cur, other: int): int =
# Compare two levels and return the topmost in the stack, taking into account
# the odd reversal of order around the zero point
if cur < 0:
max(cur, other) # >= 0 is always more topmost than <0
elif other < 0:
cur
else:
min(cur, other) # Here the order is reversed and 0 is the top layer
proc computeKeyImpl(
db: AristoDbRef, # Database, top layer
rvid: RootedVertexID, # Vertex to convert
batch: var WriteBatch,
): Result[(HashKey, int), AristoError] =
## Compute the key for an arbitrary vertex ID. If successful, the length of
## the resulting key might be smaller than 32. If it is used as a root vertex
## state/hash, it must be converted to a `Hash32` (using (`.to(Hash32)`) as
## in `db.computeKey(rvid).value.to(Hash32)` which always results in a
## 32 byte value.
db.getKeyRc(rvid).isErrOr:
# Value cached either in layers or database
return ok value
let (vtx, vl) = ?db.getVtxRc(rvid, {GetVtxFlag.PeekCache})
# Top-most level of all the verticies this hash compution depends on
var level = vl
# TODO this is the same code as when serializing NodeRef, without the NodeRef
var writer = initRlpWriter()
case vtx.vType
of Leaf:
writer.startList(2)
writer.append(vtx.pfx.toHexPrefix(isLeaf = true).data())
case vtx.lData.pType
of AccountData:
let
stoID = vtx.lData.stoID
skey =
if stoID.isValid:
let (skey, sl) = ?db.computeKeyImpl((stoID.vid, stoID.vid), batch)
level = maxLevel(level, sl)
skey
else:
VOID_HASH_KEY
writer.append(
encode Account(
nonce: vtx.lData.account.nonce,
balance: vtx.lData.account.balance,
storageRoot: skey.to(Hash32),
codeHash: vtx.lData.account.codeHash,
)
)
of RawData:
writer.append(vtx.lData.rawBlob)
of StoData:
# TODO avoid memory allocation when encoding storage data
writer.append(rlp.encode(vtx.lData.stoData))
of Branch:
template writeBranch(w: var RlpWriter) =
w.startList(17)
for n in 0 .. 15:
let vid = vtx.bVid[n]
if vid.isValid:
batch.enter(n)
let (bkey, bl) = ?db.computeKeyImpl((rvid.root, vid), batch)
batch.leave(n)
level = maxLevel(level, bl)
w.append(bkey)
else:
w.append(VOID_HASH_KEY)
w.append EmptyBlob
if vtx.pfx.len > 0: # Extension node
var bwriter = initRlpWriter()
writeBranch(bwriter)
writer.startList(2)
writer.append(vtx.pfx.toHexPrefix(isleaf = false).data())
writer.append(bwriter.finish().digestTo(HashKey))
else:
writeBranch(writer)
let h = writer.finish().digestTo(HashKey)
# Cache the hash int the same storage layer as the the top-most value that it
# depends on (recursively) - this could be an ephemeral in-memory layer or the
# underlying database backend - typically, values closer to the root are more
# likely to live in an in-memory layer since any leaf change will lead to the
# root key also changing while leaves that have never been hashed will see
# their hash being saved directly to the backend.
?db.putKeyAtLevel(rvid, h, level, batch)
ok (h, level)
proc computeKey*(
db: AristoDbRef, # Database, top layer
rvid: RootedVertexID, # Vertex to convert
): Result[HashKey, AristoError] =
var batch: WriteBatch
let res = computeKeyImpl(db, rvid, batch)
if res.isOk:
if batch.writer != nil:
if batch.count >= batchSize * 100:
info "Writing computeKey cache", count = batch.count, progress = "100.00%"
else:
debug "Writing computeKey cache", count = batch.count, progress = "100.00%"
?db.backend.putEndFn batch.writer
batch.writer = nil
ok (?res)[0]
# ------------------------------------------------------------------------------
# End
# ------------------------------------------------------------------------------