milvus-io
/
milvus
mirror of https://github.com/milvus-io/milvus.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'linxj' into 'develop' 

Linxj

See merge request jinhai/vecwise_engine!8
pull/3/head
xiaojun.lin 2019-03-25 19:21:44 +08:00
parent 9dac638104 06ca60aa8d
commit b1389854f0
16 changed files with 300 additions and 59 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

40
pyengine/engine/controller/scheduler.py
View File

@ -1,5 +1,7 @@
from engine.retrieval import search_index
from engine.ingestion import build_index
from engine.ingestion import serialize
class Singleton(type):
_instances = {}
@ -11,40 +13,40 @@ class Singleton(type):
class Scheduler(metaclass=Singleton):
def Search(self, index_file_key, vectors, k):
assert index_file_key
assert vectors
assert k
# assert index_file_key
# assert vectors
assert k != 0
return self.__scheduler(index_file_key, vectors, k)
query_vectors = serialize.to_array(vectors)
return self.__scheduler(index_file_key, query_vectors, k)
def __scheduler(self, index_data_key, vectors, k):
result_list = []
raw_data_list = index_data_key['raw']
index_data_list = index_data_key['index']
for key in raw_data_list:
raw_data, d = self.GetRawData(key)
if 'raw' in index_data_key:
raw_vectors = index_data_key['raw']
d = index_data_key['dimension']
index_builder = build_index.FactoryIndex()
index = index_builder().build(d, raw_data)
searcher = search_index.FaissSearch(index) # silly
index = index_builder().build(d, raw_vectors)
searcher = search_index.FaissSearch(index)
result_list.append(searcher.search_by_vectors(vectors, k))
if 'index' in index_data_key:
index_data_list = index_data_key['index']
for key in index_data_list:
index = self.GetIndexData(key)
index = GetIndexData(key)
searcher = search_index.FaissSearch(index)
result_list.append(searcher.search_by_vectors(vectors, k))
if len(result_list) == 1:
return result_list[0].vectors
result = search_index.top_k(sum(result_list), k)
return result
total_result = []
# result = search_index.top_k(result_list, k)
return result_list
def GetIndexData(self, key):
pass
def GetRawData(self, key):
pass
def GetIndexData(key):
return serialize.read_index(key)

60
pyengine/engine/controller/tests/test_scheduler.py Normal file
View File

@ -0,0 +1,60 @@
from ..scheduler import *
import unittest
import faiss
import numpy as np
class TestScheduler(unittest.TestCase):
def test_schedule(self):
d = 64
nb = 10000
nq = 100
nt = 5000
xt, xb, xq = get_dataset(d, nb, nt, nq)
file_name = "/tmp/faiss/tempfile_1"
index = faiss.IndexFlatL2(d)
print(index.is_trained)
index.add(xb)
faiss.write_index(index, file_name)
Dref, Iref = index.search(xq, 5)
index2 = faiss.read_index(file_name)
schuduler_instance = Scheduler()
# query args 1
query_index = dict()
query_index['index'] = [file_name]
vectors = schuduler_instance.Search(query_index, vectors=xq, k=5)
assert np.all(vectors == Iref)
# query args 2
query_index = dict()
query_index['raw'] = xt
query_index['dimension'] = d
query_index['index'] = [file_name]
vectors = schuduler_instance.Search(query_index, vectors=xq, k=5)
# print("success")
def get_dataset(d, nb, nt, nq):
"""A dataset that is not completely random but still challenging to
index
"""
d1 = 10 # intrinsic dimension (more or less)
n = nb + nt + nq
rs = np.random.RandomState(1338)
x = rs.normal(size=(n, d1))
x = np.dot(x, rs.rand(d1, d))
# now we have a d1-dim ellipsoid in d-dimensional space
# higher factor (>4) -> higher frequency -> less linear
x = x * (rs.rand(d) * 4 + 0.1)
x = np.sin(x)
x = x.astype('float32')
return x[:nt], x[nt:-nq], x[-nq:]
if __name__ == "__main__":
unittest.main()

20
pyengine/engine/controller/tests/test_vector_engine.py
View File

@ -3,6 +3,7 @@ from engine.settings import DATABASE_DIRECTORY
from flask import jsonify
import pytest
import os
import numpy as np
import logging
logging.basicConfig(level = logging.INFO,format = '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
@ -11,7 +12,7 @@ logger = logging.getLogger(__name__)
class TestVectorEngine:
def setup_class(self):
self.__vector = [1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8]
self.__limit = 3
self.__limit = 1
def teardown_class(self):
@ -39,6 +40,7 @@ class TestVectorEngine:
# Check the group list
code, group_list = VectorEngine.GetGroupList()
assert code == VectorEngine.SUCCESS_CODE
print("group_list: ", group_list)
assert group_list == [{'group_name': 'test_group', 'file_number': 0}]
# Add Vector for not exist group
@ -49,6 +51,18 @@ class TestVectorEngine:
code = VectorEngine.AddVector('test_group', self.__vector)
assert code == VectorEngine.SUCCESS_CODE
# Add vector for exist group
code = VectorEngine.AddVector('test_group', self.__vector)
assert code == VectorEngine.SUCCESS_CODE
# Add vector for exist group
code = VectorEngine.AddVector('test_group', self.__vector)
assert code == VectorEngine.SUCCESS_CODE
# Add vector for exist group
code = VectorEngine.AddVector('test_group', self.__vector)
assert code == VectorEngine.SUCCESS_CODE
# Check search vector interface
code, vector_id = VectorEngine.SearchVector('test_group', self.__vector, self.__limit)
assert code == VectorEngine.SUCCESS_CODE
@ -89,10 +103,12 @@ class TestVectorEngine:
expected_list = [self.__vector]
vector_list = VectorEngine.GetVectorListFromRawFile('test_group', filename)
print('expected_list: ', expected_list)
print('vector_list: ', vector_list)
expected_list = np.asarray(expected_list).astype('float32')
assert vector_list == expected_list
assert np.all(vector_list == expected_list)
code = VectorEngine.ClearRawFile('test_group')
assert code == VectorEngine.SUCCESS_CODE

35
pyengine/engine/controller/tests/test_views.py
View File

@ -11,6 +11,7 @@ logging.basicConfig(level = logging.INFO,format = '%(asctime)s - %(name)s - %(le
logger = logging.getLogger(__name__)
class TestViews:
HEADERS = {'Content-Type': 'application/json'}
def loads(self, resp):
return json.loads(resp.data.decode())
@ -18,51 +19,61 @@ class TestViews:
def test_group(self, test_client):
data = {"dimension": 10}
resp = test_client.get('/vector/group/6')
resp = test_client.get('/vector/group/6', headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 1
resp = test_client.post('/vector/group/6', data=json.dumps(data))
resp = test_client.post('/vector/group/6', data=json.dumps(data), headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
resp = test_client.get('/vector/group/6')
resp = test_client.get('/vector/group/6', headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
# GroupList
resp = test_client.get('/vector/group')
resp = test_client.get('/vector/group', headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
assert self.loads(resp)['group_list'] == [{'file_number': 0, 'group_name': '6'}]
resp = test_client.delete('/vector/group/6')
resp = test_client.delete('/vector/group/6', headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
def test_vector(self, test_client):
dimension = {"dimension": 10}
resp = test_client.post('/vector/group/6', data=json.dumps(dimension))
dimension = {"dimension": 8}
resp = test_client.post('/vector/group/6', data=json.dumps(dimension), headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
vector = {"vector": [1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8]}
resp = test_client.post('/vector/add/6', data=json.dumps(vector))
resp = test_client.post('/vector/add/6', data=json.dumps(vector), headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
resp = test_client.post('/vector/index/6')
vector = {"vector": [1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8]}
resp = test_client.post('/vector/add/6', data=json.dumps(vector), headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
limit = {"vector": [1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8], "limit": 3}
resp = test_client.get('/vector/search/6', data=json.dumps(limit))
vector = {"vector": [1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8]}
resp = test_client.post('/vector/add/6', data=json.dumps(vector), headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
resp = test_client.post('/vector/index/6', headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
limit = {"vector": [1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8], "limit": 1}
resp = test_client.get('/vector/search/6', data=json.dumps(limit), headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0
assert self.loads(resp)['vector_id'] == 0
resp = test_client.delete('/vector/group/6')
resp = test_client.delete('/vector/group/6', headers = TestViews.HEADERS)
assert resp.status_code == 200
assert self.loads(resp)['code'] == 0

23
pyengine/engine/controller/vector_engine.py
View File

@ -8,6 +8,7 @@ from flask import jsonify
from engine import db
from engine.ingestion import build_index
from engine.controller.scheduler import Scheduler
from engine.ingestion import serialize
import sys, os
class VectorEngine(object):
@ -93,7 +94,7 @@ class VectorEngine(object):
# check if the file can be indexed
if file.row_number + 1 >= ROW_LIMIT:
raw_data = GetVectorListFromRawFile(group_id)
raw_data = VectorEngine.GetVectorListFromRawFile(group_id)
d = group.dimension
# create index
@ -102,9 +103,11 @@ class VectorEngine(object):
# TODO(jinhai): store index into Cache
index_filename = file.filename + '_index'
serialize.write_index(file_name=index_filename, index=index)
# TODO(jinhai): Update raw_file_name => index_file_name
FileTable.query.filter(FileTable.group_name == group_id).filter(FileTable.type == 'raw').update({'row_number':file.row_number + 1, 'type': 'index'})
FileTable.query.filter(FileTable.group_name == group_id).filter(FileTable.type == 'raw').update({'row_number':file.row_number + 1,
'type': 'index',
'filename': index_filename})
pass
else:
@ -134,16 +137,20 @@ class VectorEngine(object):
if code == VectorEngine.FAULT_CODE:
return VectorEngine.GROUP_NOT_EXIST
group = GroupTable.query.filter(GroupTable.group_name == group_id).first()
# find all files
files = FileTable.query.filter(FileTable.group_name == group_id).all()
raw_keys = [ i.filename for i in files if i.type == 'raw' ]
index_keys = [ i.filename for i in files if i.type == 'index' ]
index_map = {}
index_map['raw'] = raw_keys
index_map['index'] = index_keys # {raw:[key1, key2], index:[key3, key4]}
index_map['index'] = index_keys
index_map['raw'] = VectorEngine.GetVectorListFromRawFile(group_id, "fakename") #TODO: pass by key, get from storage
index_map['dimension'] = group.dimension
scheduler_instance = Scheduler()
result = scheduler_instance.Search(index_map, vector, limit)
vectors = []
vectors.append(vector)
result = scheduler_instance.Search(index_map, vectors, limit)
vector_id = 0
@ -183,7 +190,7 @@ class VectorEngine(object):
@staticmethod
def GetVectorListFromRawFile(group_id, filename="todo"):
return VectorEngine.group_dict[group_id]
return serialize.to_array(VectorEngine.group_dict[group_id])
@staticmethod
def ClearRawFile(group_id):

7
pyengine/engine/controller/views.py
View File

@ -26,11 +26,12 @@ class VectorSearch(Resource):
def __init__(self):
self.__parser = reqparse.RequestParser()
self.__parser.add_argument('vector', type=float, action='append', location=['json'])
self.__parser.add_argument('limit', type=int, action='append', location=['json'])
self.__parser.add_argument('limit', type=int, location=['json'])
def get(self, group_id):
args = self.__parser.parse_args()
print('vector: ', args['vector'])
print('VectorSearch vector: ', args['vector'])
print('limit: ', args['limit'])
# go to search every thing
code, vector_id = VectorEngine.SearchVector(group_id, args['vector'], args['limit'])
return jsonify({'code': code, 'vector_id': vector_id})
@ -50,7 +51,7 @@ class Group(Resource):
def __init__(self):
self.__parser = reqparse.RequestParser()
self.__parser.add_argument('group_id', type=str)
self.__parser.add_argument('dimension', type=int, action='append', location=['json'])
self.__parser.add_argument('dimension', type=int, location=['json'])
def post(self, group_id):
args = self.__parser.parse_args()

4
pyengine/engine/ingestion/build_index.py
View File

@ -15,7 +15,7 @@ def FactoryIndex(index_name="DefaultIndex"):
class Index():
def build(d, vectors, DEVICE=INDEX_DEVICES.CPU):
def build(self, d, vectors, DEVICE=INDEX_DEVICES.CPU):
pass
@staticmethod
@ -35,7 +35,7 @@ class DefaultIndex(Index):
# maybe need to specif parameters
pass
def build(d, vectors, DEVICE=INDEX_DEVICES.CPU):
def build(self, d, vectors, DEVICE=INDEX_DEVICES.CPU):
index = faiss.IndexFlatL2(d) # trained
index.add(vectors)
return index

11
pyengine/engine/ingestion/serialize.py Normal file
View File

@ -0,0 +1,11 @@
import faiss
import numpy as np
def write_index(index, file_name):
faiss.write_index(index, file_name)
def read_index(file_name):
return faiss.read_index(file_name)
def to_array(vec):
return np.asarray(vec).astype('float32')

0
pyengine/engine/ingestion/tests/__init__.py Normal file
View File

88
pyengine/engine/ingestion/tests/test_build.py Normal file
View File

@ -0,0 +1,88 @@
from ..build_index import *
import faiss
import numpy as np
import unittest
class TestBuildIndex(unittest.TestCase):
def test_factory_method(self):
index_builder = FactoryIndex()
index = index_builder()
self.assertIsInstance(index, DefaultIndex)
def test_default_index(self):
d = 64
nb = 10000
nq = 100
_, xb, xq = get_dataset(d, nb, 500, nq)
# Expected result
index = faiss.IndexFlatL2(d)
index.add(xb)
Dref, Iref = index.search(xq, 5)
builder = DefaultIndex()
index2 = builder.build(d, xb)
Dnew, Inew = index2.search(xq, 5)
assert np.all(Dnew == Dref) and np.all(Inew == Iref)
def test_increase(self):
d = 64
nb = 10000
nq = 100
nt = 500
xt, xb, xq = get_dataset(d, nb, nt, nq)
index = faiss.IndexFlatL2(d)
index.add(xb)
assert index.ntotal == nb
Index.increase(index, xt)
assert index.ntotal == nb + nt
def test_serialize(self):
d = 64
nb = 10000
nq = 100
nt = 500
xt, xb, xq = get_dataset(d, nb, nt, nq)
index = faiss.IndexFlatL2(d)
index.add(xb)
Dref, Iref = index.search(xq, 5)
ar_data = Index.serialize(index)
reader = faiss.VectorIOReader()
faiss.copy_array_to_vector(ar_data, reader.data)
index2 = faiss.read_index(reader)
Dnew, Inew = index2.search(xq, 5)
assert np.all(Dnew == Dref) and np.all(Inew == Iref)
def get_dataset(d, nb, nt, nq):
"""A dataset that is not completely random but still challenging to
index
"""
d1 = 10 # intrinsic dimension (more or less)
n = nb + nt + nq
rs = np.random.RandomState(1338)
x = rs.normal(size=(n, d1))
x = np.dot(x, rs.rand(d1, d))
# now we have a d1-dim ellipsoid in d-dimensional space
# higher factor (>4) -> higher frequency -> less linear
x = x * (rs.rand(d) * 4 + 0.1)
x = np.sin(x)
x = x.astype('float32')
return x[:nt], x[nt:-nq], x[-nq:]
if __name__ == "__main__":
unittest.main()

1
pyengine/engine/model/group_table.py
View File

@ -12,7 +12,6 @@ class GroupTable(db.Model):
self.group_name = group_name
self.dimension = dimension
self.file_number = 0
self.dimension = 0
def __repr__(self):

8
pyengine/engine/retrieval/search_index.py
View File

@ -7,8 +7,9 @@ class SearchResult():
self.vectors = I
def __add__(self, other):
self.distance += other.distance
self.vectors += other.vectors
distance = self.distance + other.distance
vectors = self.vectors + other.vectors
return SearchResult(distance, vectors)
class FaissSearch():
@ -31,6 +32,7 @@ class FaissSearch():
D, I = self.__index.search(vector_list, k)
return SearchResult(D, I)
import heapq
def top_k(input, k):
#sorted = heapq.nsmallest(k, input, key=input.key)
pass

1
pyengine/engine/retrieval/tests/basic_test.py
View File

@ -74,7 +74,6 @@ def basic_test():
index.add(xb) # add vectors to the index
print(index.ntotal)
#faiss.write_index(index, "/tmp/faiss/tempfile_1")
writer = faiss.VectorIOWriter()
faiss.write_index(index, writer)
ar_data = faiss.vector_to_array(writer.data)

3
pyengine/engine/retrieval/tests/scheduler_test.py
View File

@ -1,3 +0,0 @@
from engine.controller import scheduler
# scheduler.Scheduler.Search()

48
pyengine/engine/retrieval/tests/test_search.py Normal file
View File

@ -0,0 +1,48 @@
from ..search_index import *
import unittest
import numpy as np
class TestSearchSingleThread(unittest.TestCase):
def test_search_by_vectors(self):
d = 64
nb = 10000
nq = 100
_, xb, xq = get_dataset(d, nb, 500, nq)
index = faiss.IndexFlatL2(d)
index.add(xb)
# expect result
Dref, Iref = index.search(xq, 5)
searcher = FaissSearch(index)
result = searcher.search_by_vectors(xq, 5)
assert np.all(result.distance == Dref) \
and np.all(result.vectors == Iref)
pass
def test_top_k(selfs):
pass
def get_dataset(d, nb, nt, nq):
"""A dataset that is not completely random but still challenging to
index
"""
d1 = 10 # intrinsic dimension (more or less)
n = nb + nt + nq
rs = np.random.RandomState(1338)
x = rs.normal(size=(n, d1))
x = np.dot(x, rs.rand(d1, d))
# now we have a d1-dim ellipsoid in d-dimensional space
# higher factor (>4) -> higher frequency -> less linear
x = x * (rs.rand(d) * 4 + 0.1)
x = np.sin(x)
x = x.astype('float32')
return x[:nt], x[nt:-nq], x[-nq:]
if __name__ == "__main__":
unittest.main()

2
pyengine/engine/settings.py
View File

@ -6,4 +6,4 @@ SQLALCHEMY_TRACK_MODIFICATIONS = False
SQLALCHEMY_DATABASE_URI = "mysql+pymysql://vecwise@127.0.0.1:3306/vecdata"
ROW_LIMIT = 10000000
DATABASE_DIRECTORY = '/home/jinhai/disk0/vecwise/db'
DATABASE_DIRECTORY = '/tmp'