Spaces:
Running
Running
File size: 7,880 Bytes
b110593 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 |
// _ _
// __ _____ __ ___ ___ __ _| |_ ___
// \ \ /\ / / _ \/ _` \ \ / / |/ _` | __/ _ \
// \ V V / __/ (_| |\ V /| | (_| | || __/
// \_/\_/ \___|\__,_| \_/ |_|\__,_|\__\___|
//
// Copyright © 2016 - 2024 Weaviate B.V. All rights reserved.
//
// CONTACT: [email protected]
//
package main
import (
"encoding/binary"
"encoding/json"
"fmt"
"io"
"math"
"net/http"
"os"
"sync"
"github.com/go-openapi/strfmt"
"github.com/google/uuid"
"github.com/pkg/errors"
"github.com/weaviate/weaviate/entities/models"
)
const (
class = "Benchmark"
nrSearchResults = 79
)
func createSchemaSIFTRequest(url string) *http.Request {
classObj := &models.Class{
Class: class,
Description: "Dummy class for benchmarking purposes",
Properties: []*models.Property{
{
DataType: []string{"int"},
Description: "The value of the counter in the dataset",
Name: "counter",
},
},
VectorIndexConfig: map[string]interface{}{ // values are from benchmark script
"distance": "l2-squared",
"ef": -1,
"efConstruction": 64,
"maxConnections": 64,
"vectorCacheMaxObjects": 1000000000,
},
Vectorizer: "none",
}
request := createRequest(url+"schema", "POST", classObj)
return request
}
func float32FromBytes(bytes []byte) float32 {
bits := binary.LittleEndian.Uint32(bytes)
float := math.Float32frombits(bits)
return float
}
func int32FromBytes(bytes []byte) int {
return int(binary.LittleEndian.Uint32(bytes))
}
func readSiftFloat(file string, maxObjects int) []*models.Object {
var objects []*models.Object
f, err := os.Open("sift/" + file)
if err != nil {
panic(errors.Wrap(err, "Could not open SIFT file"))
}
defer f.Close()
fi, err := f.Stat()
if err != nil {
panic(errors.Wrap(err, "Could not get SIFT file properties"))
}
fileSize := fi.Size()
if fileSize < 1000000 {
panic("The file is only " + fmt.Sprint(fileSize) + " bytes long. Did you forgot to install git lfs?")
}
// The sift data is a binary file containing floating point vectors
// For each entry, the first 4 bytes is the length of the vector (in number of floats, not in bytes)
// which is followed by the vector data with vector length * 4 bytes.
// |-length-vec1 (4bytes)-|-Vec1-data-(4*length-vector-1 bytes)-|-length-vec2 (4bytes)-|-Vec2-data-(4*length-vector-2 bytes)-|
// The vector length needs to be converted from bytes to int
// The vector data needs to be converted from bytes to float
// Note that the vector entries are of type float but are integer numbers eg 2.0
bytesPerF := 4
vectorLengthFloat := 128
vectorBytes := make([]byte, bytesPerF+vectorLengthFloat*bytesPerF)
for i := 0; i >= 0; i++ {
_, err = f.Read(vectorBytes)
if err == io.EOF {
break
} else if err != nil {
panic(err)
}
if int32FromBytes(vectorBytes[0:bytesPerF]) != vectorLengthFloat {
panic("Each vector must have 128 entries.")
}
var vectorFloat []float32
for j := 0; j < vectorLengthFloat; j++ {
start := (j + 1) * bytesPerF // first bytesPerF are length of vector
vectorFloat = append(vectorFloat, float32FromBytes(vectorBytes[start:start+bytesPerF]))
}
ObjectUuid := uuid.New()
object := &models.Object{
Class: class,
ID: strfmt.UUID(ObjectUuid.String()),
Vector: models.C11yVector(vectorFloat),
Properties: map[string]interface{}{
"counter": i,
},
}
objects = append(objects, object)
if i >= maxObjects {
break
}
}
if len(objects) < maxObjects {
panic("Could not load all elements.")
}
return objects
}
func benchmarkSift(c *http.Client, url string, maxObjects, numBatches int) (map[string]int64, error) {
clearExistingObjects(c, url)
objects := readSiftFloat("sift_base.fvecs", maxObjects)
queries := readSiftFloat("sift_query.fvecs", maxObjects/100)
requestSchema := createSchemaSIFTRequest(url)
passedTime := make(map[string]int64)
// Add schema
responseSchemaCode, _, timeSchema, err := performRequest(c, requestSchema)
passedTime["AddSchema"] = timeSchema
if err != nil {
return nil, errors.Wrap(err, "Could not add schema, error: ")
} else if responseSchemaCode != 200 {
return nil, errors.Errorf("Could not add schma, http error code: %v", responseSchemaCode)
}
// Batch-add
passedTime["BatchAdd"] = 0
wg := sync.WaitGroup{}
batchSize := len(objects) / numBatches
errorChan := make(chan error, numBatches)
timeChan := make(chan int64, numBatches)
for i := 0; i < numBatches; i++ {
wg.Add(1)
go func(batchId int, errChan chan<- error) {
batchObjects := objects[batchId*batchSize : (batchId+1)*batchSize]
requestAdd := createRequest(url+"batch/objects", "POST", batch{batchObjects})
responseAddCode, _, timeBatchAdd, err := performRequest(c, requestAdd)
timeChan <- timeBatchAdd
if err != nil {
errChan <- errors.Wrap(err, "Could not add batch, error: ")
} else if responseAddCode != 200 {
errChan <- errors.Errorf("Could not add batch, http error code: %v", responseAddCode)
}
wg.Done()
}(i, errorChan)
}
wg.Wait()
close(errorChan)
close(timeChan)
for err := range errorChan {
return nil, err
}
for timing := range timeChan {
passedTime["BatchAdd"] += timing
}
// Read entries
nrSearchResultsUse := nrSearchResults
if maxObjects < nrSearchResultsUse {
nrSearchResultsUse = maxObjects
}
requestRead := createRequest(url+"objects?limit="+fmt.Sprint(nrSearchResultsUse)+"&class="+class, "GET", nil)
responseReadCode, body, timeGetObjects, err := performRequest(c, requestRead)
passedTime["GetObjects"] = timeGetObjects
if err != nil {
return nil, errors.Wrap(err, "Could not read objects")
} else if responseReadCode != 200 {
return nil, errors.New("Could not read objects, http error code: " + fmt.Sprint(responseReadCode))
}
var result map[string]interface{}
if err := json.Unmarshal(body, &result); err != nil {
return nil, errors.Wrap(err, "Could not unmarshal read response")
}
if int(result["totalResults"].(float64)) != nrSearchResultsUse {
errString := "Found " + fmt.Sprint(int(result["totalResults"].(float64))) +
" results. Expected " + fmt.Sprint(nrSearchResultsUse) + "."
return nil, errors.New(errString)
}
// Use sample queries
for _, query := range queries {
queryString := "{Get{" + class + "(nearVector: {vector:" + fmt.Sprint(query.Vector) + " }){counter}}}"
requestQuery := createRequest(url+"graphql", "POST", models.GraphQLQuery{
Query: queryString,
})
responseQueryCode, body, timeQuery, err := performRequest(c, requestQuery)
passedTime["Query"] += timeQuery
if err != nil {
return nil, errors.Wrap(err, "Could not query objects")
} else if responseQueryCode != 200 {
return nil, errors.Errorf("Could not query objects, http error code: %v", responseQueryCode)
}
var result map[string]interface{}
if err := json.Unmarshal(body, &result); err != nil {
return nil, errors.Wrap(err, "Could not unmarshal query response")
}
if result["data"] == nil || result["errors"] != nil {
return nil, errors.New("GraphQL Error")
}
}
// Delete class (with schema and all entries) to clear all entries so next round can start fresh
requestDelete := createRequest(url+"schema/"+class, "DELETE", nil)
responseDeleteCode, _, timeDelete, err := performRequest(c, requestDelete)
passedTime["Delete"] += timeDelete
if err != nil {
return nil, errors.Wrap(err, "Could not delete class")
} else if responseDeleteCode != 200 {
return nil, errors.Errorf("Could not delete class, http error code: %v", responseDeleteCode)
}
return passedTime, nil
}
|