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