dimgigov
5dba7b5699
- Add Current Status / Limitations section to README - Fix benchmark compilation (Duration.ticks → inNanoseconds) - Implement real SSTable binary format with write/read/mmap support - Add BloomFilter serialize/deserialize for disk storage - Fix mmap.nim to use posix.open instead of system.open - New PLAN.md with improvement roadmap - All 214 tests pass
231 lines
7.3 KiB
Nim
231 lines
7.3 KiB
Nim
## BaraDB Benchmarks — performance tests for all engines
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import std/monotimes
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import std/times
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import std/tables
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import std/random
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import std/strutils
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import ../src/barabadb/storage/lsm
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import ../src/barabadb/storage/btree
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import ../src/barabadb/vector/engine as vengine
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import ../src/barabadb/vector/simd
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import ../src/barabadb/fts/engine as fts
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import ../src/barabadb/graph/engine as gengine
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proc elapsed(start: MonoTime): float64 =
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let ns = float64((getMonoTime() - start).inNanoseconds)
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return ns / 1_000_000_000.0
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proc formatOps(ops: int, secs: float64): string =
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let rate = float64(ops) / secs
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if rate > 1_000_000:
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return $(rate / 1_000_000).formatFloat(ffDecimal, 2) & "M ops/s"
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elif rate > 1_000:
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return $(rate / 1_000).formatFloat(ffDecimal, 2) & "K ops/s"
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else:
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return $rate.formatFloat(ffDecimal, 2) & " ops/s"
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proc benchLSMTree() =
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echo "=== LSM-Tree Storage ==="
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var db = newLSMTree("/tmp/baradb_bench_lsm")
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# Write benchmark
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let n = 100_000
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let start = getMonoTime()
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for i in 0..<n:
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db.put("key_" & $i, cast[seq[byte]]("value_" & $i))
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let writeTime = elapsed(start)
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echo " Write ", n, " keys: ", writeTime.formatFloat(ffDecimal, 3), "s (", formatOps(n, writeTime), ")"
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# Read benchmark
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let readStart = getMonoTime()
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var found = 0
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for i in 0..<n:
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let (ok, _) = db.get("key_" & $i)
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if ok: inc found
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let readTime = elapsed(readStart)
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echo " Read ", n, " keys: ", readTime.formatFloat(ffDecimal, 3), "s (", formatOps(n, readTime), ") (", found, " found)"
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db.close()
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proc benchBTree() =
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echo "=== B-Tree Index ==="
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var btree = newBTreeIndex[string, string]()
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let n = 100_000
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# Insert benchmark
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let start = getMonoTime()
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for i in 0..<n:
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btree.insert("key_" & $i, "value_" & $i)
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let insertTime = elapsed(start)
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echo " Insert ", n, " keys: ", insertTime.formatFloat(ffDecimal, 3), "s (", formatOps(n, insertTime), ")"
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# Get benchmark
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let getStart = getMonoTime()
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var found = 0
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for i in 0..<n:
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let vals = btree.get("key_" & $i)
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if vals.len > 0: inc found
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let getTime = elapsed(getStart)
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echo " Get ", n, " keys: ", getTime.formatFloat(ffDecimal, 3), "s (", formatOps(n, getTime), ") (", found, " found)"
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# Scan benchmark
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let scanStart = getMonoTime()
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let scanResults = btree.scan("key_1000", "key_2000")
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let scanTime = elapsed(scanStart)
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echo " Scan 1000 range: ", scanTime.formatFloat(ffDecimal, 6), "s (", scanResults.len, " results)"
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proc benchVectorSearch() =
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echo "=== Vector Engine (HNSW) ==="
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let dim = 128
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let n = 10_000
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var idx = vengine.newHNSWIndex(dim)
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# Insert benchmark
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randomize(42)
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let start = getMonoTime()
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for i in 0..<n:
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var vec = newSeq[float32](dim)
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for d in 0..<dim:
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vec[d] = rand(1.0)
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vengine.insert(idx, uint64(i), vec)
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let insertTime = elapsed(start)
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echo " Insert ", n, " vectors (dim=", dim, "): ", insertTime.formatFloat(ffDecimal, 3), "s (", formatOps(n, insertTime), ")"
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# Search benchmark
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var query = newSeq[float32](dim)
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for d in 0..<dim:
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query[d] = rand(1.0)
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let searchStart = getMonoTime()
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let results = vengine.search(idx, query, 10)
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let searchTime = elapsed(searchStart)
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echo " Search top-10: ", (searchTime * 1000).formatFloat(ffDecimal, 3), "ms"
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proc benchVectorSIMD() =
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echo "=== Vector SIMD Operations ==="
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let dim = 768
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let n = 10_000
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randomize(42)
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var corpus = newSeq[SimdVector](n)
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for i in 0..<n:
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corpus[i] = newSeq[float32](dim)
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for d in 0..<dim:
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corpus[i][d] = rand(1.0)
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var query = newSeq[float32](dim)
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for d in 0..<dim:
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query[d] = rand(1.0)
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# Cosine distance benchmark
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let start = getMonoTime()
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for i in 0..<n:
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discard cosineSimd(query, corpus[i])
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let cosineTime = elapsed(start)
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echo " Cosine distance (dim=768, n=10K): ", cosineTime.formatFloat(ffDecimal, 3), "s (", formatOps(n, cosineTime), ")"
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# L2 distance benchmark
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let l2Start = getMonoTime()
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for i in 0..<n:
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discard l2NormSimd(query, corpus[i])
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let l2Time = elapsed(l2Start)
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echo " L2 distance (dim=768, n=10K): ", l2Time.formatFloat(ffDecimal, 3), "s (", formatOps(n, l2Time), ")"
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# Dot product benchmark
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let dotStart = getMonoTime()
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for i in 0..<n:
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discard dotProductSimd(query, corpus[i])
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let dotTime = elapsed(dotStart)
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echo " Dot product (dim=768, n=10K): ", dotTime.formatFloat(ffDecimal, 3), "s (", formatOps(n, dotTime), ")"
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proc benchFTS() =
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echo "=== Full-Text Search ==="
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var idx = fts.newInvertedIndex()
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let n = 10_000
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# Index benchmark
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let docs = @[
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"Nim is a statically typed compiled systems programming language",
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"It combines the speed of C with an expressive syntax like Python",
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"Memory management is deterministic with reference counting",
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"The compiler produces optimized native code for all platforms",
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"Metaprogramming and generics enable powerful abstractions",
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]
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let start = getMonoTime()
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for i in 0..<n:
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idx.addDocument(uint64(i), docs[i mod docs.len])
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let indexTime = elapsed(start)
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echo " Index ", n, " docs: ", indexTime.formatFloat(ffDecimal, 3), "s (", formatOps(n, indexTime), ")"
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# Search benchmark
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let searchStart = getMonoTime()
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for i in 0..<1000:
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discard idx.search("Nim programming language")
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let searchTime = elapsed(searchStart)
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echo " Search 1000 queries: ", searchTime.formatFloat(ffDecimal, 3), "s (", formatOps(1000, searchTime), ")"
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# Fuzzy search benchmark
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let fuzzyStart = getMonoTime()
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for i in 0..<100:
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discard idx.fuzzySearch("programing", maxDistance = 2)
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let fuzzyTime = elapsed(fuzzyStart)
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echo " Fuzzy search 100 queries: ", fuzzyTime.formatFloat(ffDecimal, 3), "s (", formatOps(100, fuzzyTime), ")"
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proc benchGraph() =
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echo "=== Graph Engine ==="
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var g = gengine.newGraph()
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let nodeCount = 1000
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let edgeCount = 5000
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# Add nodes
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let nodeStart = getMonoTime()
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for i in 0..<nodeCount:
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discard gengine.addNode(g, "Node_" & $i)
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let nodeTime = elapsed(nodeStart)
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echo " Add ", nodeCount, " nodes: ", nodeTime.formatFloat(ffDecimal, 6), "s"
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# Add edges
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randomize(42)
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let edgeStart = getMonoTime()
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for i in 0..<edgeCount:
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let src = NodeId(uint64(rand(nodeCount - 1)) + 1)
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let dst = NodeId(uint64(rand(nodeCount - 1)) + 1)
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discard gengine.addEdge(g, src, dst)
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let edgeTime = elapsed(edgeStart)
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echo " Add ", edgeCount, " edges: ", edgeTime.formatFloat(ffDecimal, 6), "s"
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# BFS benchmark
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let bfsStart = getMonoTime()
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for i in 0..<100:
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discard gengine.bfs(g, NodeId(1))
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let bfsTime = elapsed(bfsStart)
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echo " BFS 100 traversals: ", bfsTime.formatFloat(ffDecimal, 3), "s (", formatOps(100, bfsTime), ")"
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# PageRank benchmark
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let prStart = getMonoTime()
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discard gengine.pageRank(g, 10)
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let prTime = elapsed(prStart)
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echo " PageRank (10 iterations): ", prTime.formatFloat(ffDecimal, 3), "s"
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proc main() =
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echo ""
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echo "╔══════════════════════════════════════════════════╗"
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echo "║ BaraDB Performance Benchmarks ║"
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echo "╚══════════════════════════════════════════════════╝"
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echo ""
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benchLSMTree()
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echo ""
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benchBTree()
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echo ""
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benchVectorSearch()
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echo ""
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benchVectorSIMD()
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echo ""
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benchFTS()
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echo ""
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benchGraph()
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echo ""
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when isMainModule:
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main()
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