nimbus-eth1/fluffy/content_db.nim

311 lines
11 KiB
Nim

# Nimbus
# Copyright (c) 2021-2022 Status Research & Development GmbH
# Licensed and distributed under either of
# * MIT license (license terms in the root directory or at https://opensource.org/licenses/MIT).
# * Apache v2 license (license terms in the root directory or at https://www.apache.org/licenses/LICENSE-2.0).
# at your option. This file may not be copied, modified, or distributed except according to those terms.
{.push raises: [Defect].}
import
std/[options, heapqueue],
eth/db/kvstore,
eth/db/kvstore_sqlite3,
stint,
./network/state/state_content
export kvstore_sqlite3
# This version of content db is the most basic, simple solution where data is
# stored no matter what content type or content network in the same kvstore with
# the content id as key. The content id is derived from the content key, and the
# deriviation is different depending on the content type. As we use content id,
# this part is currently out of the scope / API of the ContentDB.
# In the future it is likely that that either:
# 1. More kvstores are added per network, and thus depending on the network a
# different kvstore needs to be selected.
# 2. Or more kvstores are added per network and per content type, and thus
# content key fields are required to access the data.
# 3. Or databases are created per network (and kvstores pre content type) and
# thus depending on the network the right db needs to be selected.
const
# Maximal number of ObjInfo objects held in memory per database scan. 100k
# objects should result in memory usage of around 7mb which should be
# appropriate for even low resource devices
maxObjPerScan = 100000
type
RowInfo = tuple
contentId: array[32, byte]
payloadLength: int64
ObjInfo* = object
contentId*: array[32, byte]
payloadLength*: int64
distFrom*: UInt256
ContentDB* = ref object
kv: KvStoreRef
maxSize: uint32
sizeStmt: SqliteStmt[NoParams, int64]
unusedSizeStmt: SqliteStmt[NoParams, int64]
vacStmt: SqliteStmt[NoParams, void]
getAll: SqliteStmt[NoParams, RowInfo]
PutResultType* = enum
ContentStored, DbPruned
PutResult* = object
case kind*: PutResultType
of ContentStored:
discard
of DbPruned:
furthestStoredElementDistance*: UInt256
fractionOfDeletedContent*: float64
numOfDeletedElements*: int64
# Objects must be sorted from largest to closest distance
proc `<`(a, b: ObjInfo): bool =
return a.distFrom < b.distFrom
template expectDb(x: auto): untyped =
# There's no meaningful error handling implemented for a corrupt database or
# full disk - this requires manual intervention, so we'll panic for now
x.expect("working database (disk broken/full?)")
proc new*(T: type ContentDB, path: string, maxSize: uint32, inMemory = false): ContentDB =
let db =
if inMemory:
SqStoreRef.init("", "fluffy-test", inMemory = true).expect(
"working database (out of memory?)")
else:
SqStoreRef.init(path, "fluffy").expectDb()
let getSizeStmt = db.prepareStmt(
"SELECT page_count * page_size as size FROM pragma_page_count(), pragma_page_size();",
NoParams, int64).get()
let unusedSize = db.prepareStmt(
"SELECT freelist_count * page_size as size FROM pragma_freelist_count(), pragma_page_size();",
NoParams, int64).get()
let vacStmt = db.prepareStmt(
"VACUUM;",
NoParams, void).get()
let kvStore = kvStore db.openKvStore().expectDb()
# This needs to go after `openKvStore`, as it checks whether the table name
# kvstore already exists.
let getKeysStmt = db.prepareStmt(
"SELECT key, length(value) FROM kvstore",
NoParams, RowInfo
).get()
ContentDB(
kv: kvStore,
maxSize: maxSize,
sizeStmt: getSizeStmt,
vacStmt: vacStmt,
getAll: getKeysStmt,
unusedSizeStmt: unusedSize
)
proc getNFurthestElements*(
db: ContentDB, target: UInt256, n: uint64): (seq[ObjInfo], int64) =
## Get at most n furthest elements from db in order from furthest to closest.
## Payload lengths are also returned so the caller can decide how many of
## those elements need to be deleted.
##
## Currently it uses xor metric
##
## Currently works by querying for all elements in database and doing all
## necessary work on program level. This is mainly due to two facts:
## - sqlite does not have build xor function, also it does not handle bitwise
## operations on blobs as expected
## - our nim wrapper for sqlite does not support create_function api of sqlite
## so we cannot create custom function comparing blobs at sql level. If that
## would be possible we may be able to all this work by one sql query
if n == 0:
return (newSeq[ObjInfo](), 0'i64)
var heap = initHeapQueue[ObjInfo]()
var totalContentSize: int64 = 0
var ri: RowInfo
for e in db.getAll.exec(ri):
let contentId = UInt256.fromBytesBE(ri.contentId)
# TODO: Currently it assumes xor distance, but when we start testing
# networks with other distance functions this needs to be adjusted to the
# custom distance function
let dist = contentId xor target
let obj = ObjInfo(
contentId: ri.contentId, payloadLength: ri.payloadLength, distFrom: dist)
if (uint64(len(heap)) < n):
heap.push(obj)
else:
if obj > heap[0]:
discard heap.replace(obj)
totalContentSize = totalContentSize + ri.payloadLength
var res: seq[ObjInfo] = newSeq[ObjInfo](heap.len())
var i = heap.len() - 1
while heap.len() > 0:
res[i] = heap.pop()
dec i
return (res, totalContentSize)
proc reclaimSpace*(db: ContentDB): void =
## Runs sqlite VACUUM commands which rebuilds the db, repacking it into a
## minimal amount of disk space.
## Ideal mode of operation, is to run it after several deletes.
## Another options would be to run 'PRAGMA auto_vacuum = FULL;' statement at
## the start of db to leave it up to sqlite to clean up
db.vacStmt.exec().expectDb()
proc size*(db: ContentDB): int64 =
## Retrun current size of DB as product of sqlite page_count and page_size
## https://www.sqlite.org/pragma.html#pragma_page_count
## https://www.sqlite.org/pragma.html#pragma_page_size
## It returns total size of db i.e both data and metadata used to store content
## also it is worth noting that when deleting content, size may lags behind due
## to the way how deleting works in sqlite.
## Good description can be found in: https://www.sqlite.org/lang_vacuum.html
var size: int64 = 0
discard (db.sizeStmt.exec do(res: int64):
size = res).expectDb()
return size
proc unusedSize(db: ContentDB): int64 =
## Returns the total size of the pages which are unused by the database,
## i.e they can be re-used for new content.
var size: int64 = 0
discard (db.unusedSizeStmt.exec do(res: int64):
size = res).expectDb()
return size
proc realSize*(db: ContentDB): int64 =
db.size() - db.unusedSize()
proc get*(db: ContentDB, key: openArray[byte]): Option[seq[byte]] =
var res: Option[seq[byte]]
proc onData(data: openArray[byte]) = res = some(@data)
discard db.kv.get(key, onData).expectDb()
return res
proc put(db: ContentDB, key, value: openArray[byte]) =
db.kv.put(key, value).expectDb()
proc contains*(db: ContentDB, key: openArray[byte]): bool =
db.kv.contains(key).expectDb()
proc del*(db: ContentDB, key: openArray[byte]) =
db.kv.del(key).expectDb()
# TODO: Could also decide to use the ContentKey SSZ bytestring, as this is what
# gets send over the network in requests, but that would be a bigger key. Or the
# same hashing could be done on it here.
# However ContentId itself is already derived through different digests
# depending on the content type, and this ContentId typically needs to be
# checked with the Radius/distance of the node anyhow. So lets see how we end up
# using this mostly in the code.
proc get*(db: ContentDB, key: ContentId): Option[seq[byte]] =
# TODO: Here it is unfortunate that ContentId is a uint256 instead of Digest256.
db.get(key.toByteArrayBE())
proc put*(db: ContentDB, key: ContentId, value: openArray[byte]) =
db.put(key.toByteArrayBE(), value)
proc contains*(db: ContentDB, key: ContentId): bool =
db.contains(key.toByteArrayBE())
proc del*(db: ContentDB, key: ContentId) =
db.del(key.toByteArrayBE())
proc deleteFractionOfContent*(
db: ContentDB,
target: Uint256,
targetFraction: float64): (UInt256, int64, int64, int64) =
## Procedure which tries to delete fraction of database by scanning maxObjPerScan
## furthest elements.
## If the maxObjPerScan furthest elements, is not enough to attain required fraction
## procedure deletes all but one element and report how many bytes have been
## deleted
## Procedure do not call reclaim space, it is left to the caller.
let (furthestElements, totalContentSize) = db.getNFurthestElements(target, maxObjPerScan)
var bytesDeleted: int64 = 0
let bytesToDelete = int64(targetFraction * float64(totalContentSize))
let numOfElements = len(furthestElements)
var numOfDeletedElements: int64 = 0
if numOfElements == 0:
# no elements in database, return some zero value
return (UInt256.zero, 0'i64, 0'i64, 0'i64)
let lastIdx = len(furthestElements) - 1
for i, elem in furthestElements:
if i == lastIdx:
# this is our last element, do not delete it and report it as last non deleted
# element
return (elem.distFrom, bytesDeleted, totalContentSize, numOfDeletedElements)
if bytesDeleted + elem.payloadLength < bytesToDelete:
db.del(elem.contentId)
bytesDeleted = bytesDeleted + elem.payloadLength
inc numOfDeletedElements
else:
return (elem.distFrom, bytesDeleted, totalContentSize, numOfDeletedElements)
proc put*(
db: ContentDB,
key: ContentId,
value: openArray[byte],
target: UInt256): PutResult =
db.put(key, value)
# We use real size for our pruning threshold, which means that database file
# will reach size specified in db.maxSize, and will stay that size thorough
# node life time, as after content deletion free pages will be re used.
# TODO:
# 1. Devise vacuum strategy - after few pruning cycles database can become
# fragmented which may impact performance, so at some point in time `VACUUM`
# will need to be run to defragment the db.
# 2. Deal with the edge case where a user configures max db size lower than
# current db.size(). With such config the database would try to prune itself with
# each addition.
let dbSize = db.realSize()
if dbSize < int64(db.maxSize):
return PutResult(kind: ContentStored)
else:
# TODO Add some configuration for this magic number
let (
furthestNonDeletedElement,
deletedBytes,
totalContentSize,
deletedElements
) =
db.deleteFractionOfContent(target, 0.25)
let deletedFraction = float64(deletedBytes) / float64(totalContentSize)
return PutResult(
kind: DbPruned,
furthestStoredElementDistance: furthestNonDeletedElement,
fractionOfDeletedContent: deletedFraction,
numOfDeletedElements: deletedElements)