class MilvusClient(object):
def __init__(self, collection_name=None, host=None, port=None, timeout=60):
"""
Milvus client wrapper for python-sdk.
Default timeout set 60s
"""
self._collection_name = collection_name
try:
start_time = time.time()
if not host:
host = SERVER_HOST_DEFAULT
if not port:
port = SERVER_PORT_DEFAULT
logger.debug(host)
logger.debug(port)
# retry connect for remote server
i = 0
while time.time() < start_time + timeout:
try:
self._milvus = Milvus(host=host, port=port, try_connect=False, pre_ping=False)
if self._milvus.server_status():
logger.debug("Try connect times: %d, %s" % (i, round(time.time() - start_time, 2)))
break
except Exception as e:
logger.debug("Milvus connect failed: %d times" % i)
i = i + 1
if time.time() > start_time + timeout:
raise Exception("Server connect timeout")
except Exception as e:
raise e
self._metric_type = None
if self._collection_name and self.exists_collection():
self._metric_type = metric_type_to_str(self.describe()[1].metric_type)
self._dimension = self.describe()[1].dimension
def __str__(self):
return 'Milvus collection %s' % self._collection_name
def set_collection(self, name):
self._collection_name = name
def check_status(self, status):
if not status.OK():
logger.error(self._collection_name)
logger.error(status.message)
logger.error(self._milvus.server_status())
logger.error(self.count())
raise Exception("Status not ok")
def check_result_ids(self, result):
for index, item in enumerate(result):
if item[0].distance >= epsilon:
logger.error(index)
logger.error(item[0].distance)
raise Exception("Distance wrong")
def create_collection(self, collection_name, dimension, index_file_size, metric_type):
if not self._collection_name:
self._collection_name = collection_name
if metric_type not in METRIC_MAP.keys():
raise Exception("Not supported metric_type: %s" % metric_type)
metric_type = METRIC_MAP[metric_type]
create_param = {'collection_name': collection_name,
'dimension': dimension,
'index_file_size': index_file_size,
"metric_type": metric_type}
status = self._milvus.create_collection(create_param)
self.check_status(status)
def create_partition(self, tag_name):
status = self._milvus.create_partition(self._collection_name, tag_name)
self.check_status(status)
def drop_partition(self, tag_name):
status = self._milvus.drop_partition(self._collection_name, tag_name)
self.check_status(status)
def list_partitions(self):
status, tags = self._milvus.list_partitions(self._collection_name)
self.check_status(status)
return tags
@time_wrapper
def insert(self, X, ids=None, collection_name=None):
if collection_name is None:
collection_name = self._collection_name
status, result = self._milvus.insert(collection_name, X, ids)
self.check_status(status)
return status, result
def insert_rand(self):
insert_xb = random.randint(1, 100)
X = [[random.random() for _ in range(self._dimension)] for _ in range(insert_xb)]
X = utils.normalize(self._metric_type, X)
count_before = self.count()
status, _ = self.insert(X)
self.check_status(status)
self.flush()
if count_before + insert_xb != self.count():
raise Exception("Assert failed after inserting")
def get_rand_ids(self, length):
while True:
status, stats = self._milvus.get_collection_stats(self._collection_name)
self.check_status(status)
segments = stats["partitions"][0]["segments"]
# random choice one segment
segment = random.choice(segments)
status, segment_ids = self._milvus.list_id_in_segment(self._collection_name, segment["name"])
if not status.OK():
logger.error(status.message)
continue
if len(segment_ids):
break
if length >= len(segment_ids):
logger.debug("Reset length: %d" % len(segment_ids))
return segment_ids
return random.sample(segment_ids, length)
def get_rand_ids_each_segment(self, length):
res = []
status, stats = self._milvus.get_collection_stats(self._collection_name)
self.check_status(status)
segments = stats["partitions"][0]["segments"]
segments_num = len(segments)
# random choice from each segment
for segment in segments:
status, segment_ids = self._milvus.list_id_in_segment(self._collection_name, segment["name"])
self.check_status(status)
res.extend(segment_ids[:length])
return segments_num, res
def get_rand_entities(self, length):
ids = self.get_rand_ids(length)
status, get_res = self._milvus.get_entity_by_id(self._collection_name, ids)
self.check_status(status)
return ids, get_res
@time_wrapper
def get_entities(self, get_ids):
status, get_res = self._milvus.get_entity_by_id(self._collection_name, get_ids)
self.check_status(status)
return get_res
@time_wrapper
def delete(self, ids, collection_name=None):
if collection_name is None:
collection_name = self._collection_name
status = self._milvus.delete_entity_by_id(collection_name, ids)
self.check_status(status)
def delete_rand(self):
delete_id_length = random.randint(1, 100)
count_before = self.count()
logger.info("%s: length to delete: %d" % (self._collection_name, delete_id_length))
delete_ids = self.get_rand_ids(delete_id_length)
self.delete(delete_ids)
self.flush()
logger.info("%s: count after delete: %d" % (self._collection_name, self.count()))
status, get_res = self._milvus.get_entity_by_id(self._collection_name, delete_ids)
self.check_status(status)
for item in get_res:
if item:
raise Exception("Assert failed after delete")
if count_before - len(delete_ids) != self.count():
raise Exception("Assert failed after delete")
@time_wrapper
def flush(self, collection_name=None):
if collection_name is None:
collection_name = self._collection_name
status = self._milvus.flush([collection_name])
self.check_status(status)
@time_wrapper
def compact(self, collection_name=None):
if collection_name is None:
collection_name = self._collection_name
status = self._milvus.compact(collection_name)
self.check_status(status)
@time_wrapper
def create_index(self, index_type, index_param=None):
index_type = INDEX_MAP[index_type]
logger.info("Building index start, collection_name: %s, index_type: %s" % (self._collection_name, index_type))
if index_param:
logger.info(index_param)
status = self._milvus.create_index(self._collection_name, index_type, index_param)
self.check_status(status)
def describe_index(self):
status, result = self._milvus.get_index_info(self._collection_name)
self.check_status(status)
index_type = None
for k, v in INDEX_MAP.items():
if result._index_type == v:
index_type = k
break
return {"index_type": index_type, "index_param": result._params}
def drop_index(self):
logger.info("Drop index: %s" % self._collection_name)
return self._milvus.drop_index(self._collection_name)
def query(self, X, top_k, search_param=None, collection_name=None):
if collection_name is None:
collection_name = self._collection_name
status, result = self._milvus.search(collection_name, top_k, query_records=X, params=search_param)
self.check_status(status)
return result
def query_rand(self):
top_k = random.randint(1, 100)
nq = random.randint(1, 100)
nprobe = random.randint(1, 100)
search_param = {"nprobe": nprobe}
_, X = self.get_rand_entities(nq)
logger.info("%s, Search nq: %d, top_k: %d, nprobe: %d" % (self._collection_name, nq, top_k, nprobe))
status, _ = self._milvus.search(self._collection_name, top_k, query_records=X, params=search_param)
self.check_status(status)
# for i, item in enumerate(search_res):
# if item[0].id != ids[i]:
# logger.warning("The index of search result: %d" % i)
# raise Exception("Query failed")
# @time_wrapper
# def query_ids(self, top_k, ids, search_param=None):
# status, result = self._milvus.search_by_id(self._collection_name, ids, top_k, params=search_param)
# self.check_result_ids(result)
# return result
def count(self, name=None):
if name is None:
name = self._collection_name
logger.debug(self._milvus.count_entities(name))
row_count = self._milvus.count_entities(name)[1]
if not row_count:
row_count = 0
logger.debug("Row count: %d in collection: <%s>" % (row_count, name))
return row_count
def drop(self, timeout=120, name=None):
timeout = int(timeout)
if name is None:
name = self._collection_name
logger.info("Start delete collection: %s" % name)
status = self._milvus.drop_collection(name)
self.check_status(status)
i = 0
while i < timeout:
if self.count(name=name):
time.sleep(1)
i = i + 1
continue
else:
break
if i >= timeout:
logger.error("Delete collection timeout")
def describe(self):
# logger.info(self._milvus.get_collection_info(self._collection_name))
return self._milvus.get_collection_info(self._collection_name)
def show_collections(self):
return self._milvus.list_collections()
def exists_collection(self, collection_name=None):
if collection_name is None:
collection_name = self._collection_name
_, res = self._milvus.has_collection(collection_name)
# self.check_status(status)
return res
def clean_db(self):
collection_names = self.show_collections()[1]
for name in collection_names:
logger.debug(name)
self.drop(name=name)
@time_wrapper
def preload_collection(self):
status = self._milvus.load_collection(self._collection_name, timeout=3000)
self.check_status(status)
return status
def get_server_version(self):
_, res = self._milvus.server_version()
return res
def get_server_mode(self):
return self.cmd("mode")
def get_server_commit(self):
return self.cmd("build_commit_id")
def get_server_config(self):
return json.loads(self.cmd("get_config *"))
def get_mem_info(self):
result = json.loads(self.cmd("get_system_info"))
result_human = {
# unit: Gb
"memory_used": round(int(result["memory_used"]) / (1024*1024*1024), 2)
}
return result_human
def cmd(self, command):
status, res = self._milvus._cmd(command)
logger.info("Server command: %s, result: %s" % (command, res))
self.check_status(status)
return res
class MilvusClient(object):
def __init__(self, collection_name=None, ip=None, port=None, timeout=60):
self._collection_name = collection_name
try:
i = 1
start_time = time.time()
if not ip:
self._milvus = Milvus(host=SERVER_HOST_DEFAULT,
port=SERVER_PORT_DEFAULT)
else:
# retry connect for remote server
while time.time() < start_time + timeout:
try:
self._milvus = Milvus(host=ip, port=port)
if self._milvus.server_status():
logger.debug(
"Try connect times: %d, %s" %
(i, round(time.time() - start_time, 2)))
break
except Exception as e:
logger.debug("Milvus connect failed")
i = i + 1
except Exception as e:
raise e
def __str__(self):
return 'Milvus collection %s' % self._collection_name
def check_status(self, status):
if not status.OK():
logger.error(status.message)
raise Exception("Status not ok")
def check_result_ids(self, result):
for index, item in enumerate(result):
if item[0].distance >= epsilon:
logger.error(index)
logger.error(item[0].distance)
raise Exception("Distance wrong")
def create_collection(self, collection_name, dimension, index_file_size,
metric_type):
if not self._collection_name:
self._collection_name = collection_name
if metric_type == "l2":
metric_type = MetricType.L2
elif metric_type == "ip":
metric_type = MetricType.IP
elif metric_type == "jaccard":
metric_type = MetricType.JACCARD
elif metric_type == "hamming":
metric_type = MetricType.HAMMING
elif metric_type == "sub":
metric_type = MetricType.SUBSTRUCTURE
elif metric_type == "super":
metric_type = MetricType.SUPERSTRUCTURE
else:
logger.error("Not supported metric_type: %s" % metric_type)
create_param = {
'collection_name': collection_name,
'dimension': dimension,
'index_file_size': index_file_size,
"metric_type": metric_type
}
status = self._milvus.create_collection(create_param)
self.check_status(status)
@time_wrapper
def insert(self, X, ids=None):
status, result = self._milvus.add_vectors(self._collection_name, X,
ids)
self.check_status(status)
return status, result
@time_wrapper
def delete_vectors(self, ids):
status = self._milvus.delete_by_id(self._collection_name, ids)
self.check_status(status)
@time_wrapper
def flush(self):
status = self._milvus.flush([self._collection_name])
self.check_status(status)
@time_wrapper
def compact(self):
status = self._milvus.compact(self._collection_name)
self.check_status(status)
@time_wrapper
def create_index(self, index_type, index_param=None):
index_type = INDEX_MAP[index_type]
logger.info(
"Building index start, collection_name: %s, index_type: %s" %
(self._collection_name, index_type))
if index_param:
logger.info(index_param)
status = self._milvus.create_index(self._collection_name, index_type,
index_param)
self.check_status(status)
def describe_index(self):
status, result = self._milvus.describe_index(self._collection_name)
self.check_status(status)
index_type = None
for k, v in INDEX_MAP.items():
if result._index_type == v:
index_type = k
break
return {"index_type": index_type, "index_param": result._params}
def drop_index(self):
logger.info("Drop index: %s" % self._collection_name)
return self._milvus.drop_index(self._collection_name)
@time_wrapper
def query(self, X, top_k, search_param=None):
status, result = self._milvus.search_vectors(self._collection_name,
top_k,
query_records=X,
params=search_param)
self.check_status(status)
return result
@time_wrapper
def query_ids(self, top_k, ids, search_param=None):
status, result = self._milvus.search_by_ids(self._collection_name,
ids,
top_k,
params=search_param)
self.check_result_ids(result)
return result
def count(self):
return self._milvus.count_collection(self._collection_name)[1]
def delete(self, timeout=120):
timeout = int(timeout)
logger.info("Start delete collection: %s" % self._collection_name)
self._milvus.drop_collection(self._collection_name)
i = 0
while i < timeout:
if self.count():
time.sleep(1)
i = i + 1
continue
else:
break
if i >= timeout:
logger.error("Delete collection timeout")
def describe(self):
return self._milvus.describe_collection(self._collection_name)
def show_collections(self):
return self._milvus.show_collections()
def exists_collection(self, collection_name=None):
if collection_name is None:
collection_name = self._collection_name
status, res = self._milvus.has_collection(collection_name)
# self.check_status(status)
return res
@time_wrapper
def preload_collection(self):
status = self._milvus.preload_collection(self._collection_name,
timeout=3000)
self.check_status(status)
return status
def get_server_version(self):
status, res = self._milvus.server_version()
return res
def get_server_mode(self):
return self.cmd("mode")
def get_server_commit(self):
return self.cmd("build_commit_id")
def get_server_config(self):
return json.loads(self.cmd("get_config *"))
def get_mem_info(self):
result = json.loads(self.cmd("get_system_info"))
result_human = {
# unit: Gb
"memory_used":
round(int(result["memory_used"]) / (1024 * 1024 * 1024), 2)
}
return result_human
def cmd(self, command):
status, res = self._milvus._cmd(command)
logger.info("Server command: %s, result: %s" % (command, res))
self.check_status(status)
return res
def main():
milvus = Milvus()
# Print client version
print('# Client version: {}'.format(milvus.client_version()))
# Connect milvus server
# Please change HOST and PORT to the correct one
param = {'host': _HOST, 'port': _PORT}
cnn_status = milvus.connect(**param)
print('# Connect Status: {}'.format(cnn_status))
# Check if connected
# is_connected = milvus.connected
print('# Is connected: {}'.format(milvus.connected))
# Print milvus server version
print('# Server version: {}'.format(milvus.server_version()))
# Describe table
table_name = 'table01'
res_status, table = milvus.describe_table(table_name)
print('# Describe table status: {}'.format(res_status))
print('# Describe table:{}'.format(table))
# Create table
# Check if `table01` exists, if not, create a table `table01`
dimension = 256
if not table:
param = {
'table_name': table_name,
'dimension': dimension,
'index_type': IndexType.IDMAP,
'store_raw_vector': False
}
res_status = milvus.create_table(Prepare.table_schema(**param))
print('# Create table status: {}'.format(res_status))
# Show tables and their description
status, tables = milvus.show_tables()
pprint(tables)
# Add vectors
# Prepare vector with 256 dimension
vectors = Prepare.records([[random.random() for _ in range(dimension)]
for _ in range(20)])
# Insert vectors into table 'table01'
status, ids = milvus.add_vectors(table_name=table_name, records=vectors)
print('# Add vector status: {}'.format(status))
pprint(ids)
# Search vectors
# When adding vectors for the first time, server will take at least 5s to
# persist vector data, so you have to wait for 6s after adding vectors for
# the first time.
print('# Waiting for 6s...')
time.sleep(6)
q_records = Prepare.records([[random.random() for _ in range(dimension)]
for _ in range(2)])
param = {
'table_name': table_name,
'query_records': q_records,
'top_k': 10,
}
status, results = milvus.search_vectors(**param)
print('# Search vectors status: {}'.format(status))
pprint(results)
# Get table row count
status, result = milvus.get_table_row_count(table_name)
print('# Status: {}'.format(status))
print('# Count: {}'.format(result))
# Disconnect
status = milvus.disconnect()
print('# Disconnect Status: {}'.format(status))
class MilvusClient(object):
def __init__(self, table_name=None, ip=None, port=None, timeout=60):
self._milvus = Milvus()
self._table_name = table_name
try:
i = 1
start_time = time.time()
if not ip:
self._milvus.connect(host=SERVER_HOST_DEFAULT,
port=SERVER_PORT_DEFAULT)
else:
# retry connect for remote server
while time.time() < start_time + timeout:
try:
self._milvus.connect(host=ip, port=port)
if self._milvus.connected() is True:
logger.debug(
"Try connect times: %d, %s" %
(i, round(time.time() - start_time, 2)))
break
except Exception as e:
logger.debug("Milvus connect failed")
i = i + 1
except Exception as e:
raise e
def __str__(self):
return 'Milvus table %s' % self._table_name
def check_status(self, status):
if not status.OK():
logger.error(status.message)
# raise Exception("Status not ok")
def create_table(self, table_name, dimension, index_file_size,
metric_type):
if not self._table_name:
self._table_name = table_name
if metric_type == "l2":
metric_type = MetricType.L2
elif metric_type == "ip":
metric_type = MetricType.IP
elif metric_type == "jaccard":
metric_type = MetricType.JACCARD
elif metric_type == "hamming":
metric_type = MetricType.HAMMING
else:
logger.error("Not supported metric_type: %s" % metric_type)
create_param = {
'table_name': table_name,
'dimension': dimension,
'index_file_size': index_file_size,
"metric_type": metric_type
}
status = self._milvus.create_table(create_param)
self.check_status(status)
@time_wrapper
def insert(self, X, ids=None):
status, result = self._milvus.add_vectors(self._table_name, X, ids)
self.check_status(status)
return status, result
@time_wrapper
def create_index(self, index_type, nlist):
index_params = {
"index_type": INDEX_MAP[index_type],
"nlist": nlist,
}
logger.info("Building index start, table_name: %s, index_params: %s" %
(self._table_name, json.dumps(index_params)))
status = self._milvus.create_index(self._table_name,
index=index_params)
self.check_status(status)
def describe_index(self):
status, result = self._milvus.describe_index(self._table_name)
index_type = None
for k, v in INDEX_MAP.items():
if result._index_type == v:
index_type = k
break
nlist = result._nlist
res = {"index_type": index_type, "nlist": nlist}
return res
def drop_index(self):
logger.info("Drop index: %s" % self._table_name)
return self._milvus.drop_index(self._table_name)
@time_wrapper
def query(self, X, top_k, nprobe):
status, result = self._milvus.search_vectors(self._table_name, top_k,
nprobe, X)
self.check_status(status)
return result
def count(self):
return self._milvus.get_table_row_count(self._table_name)[1]
def delete(self, timeout=60):
logger.info("Start delete table: %s" % self._table_name)
self._milvus.delete_table(self._table_name)
i = 0
while i < timeout:
if self.count():
time.sleep(1)
i = i + 1
continue
else:
break
if i >= timeout:
logger.error("Delete table timeout")
def describe(self):
return self._milvus.describe_table(self._table_name)
def show_tables(self):
return self._milvus.show_tables()
def exists_table(self, table_name=None):
if table_name is None:
table_name = self._table_name
status, res = self._milvus.has_table(table_name)
self.check_status(status)
return res
@time_wrapper
def preload_table(self):
return self._milvus.preload_table(self._table_name, timeout=3000)
def get_server_version(self):
status, res = self._milvus.server_version()
return res
def get_server_mode(self):
return self.cmd("mode")
def get_server_commit(self):
return self.cmd("build_commit_id")
def get_server_config(self):
return json.loads(self.cmd("get_config *"))
def get_mem_info(self):
result = json.loads(self.cmd("get_system_info"))
result_human = {
# unit: Gb
"memory_used":
round(int(result["memory_used"]) / (1024 * 1024 * 1024), 2)
}
return result_human
def cmd(self, command):
status, res = self._milvus._cmd(command)
logger.info("Server command: %s, result: %s" % (command, res))
self.check_status(status)
return res
class MilvusANN(object):
def __init__(self, host='10.46.5.98', port='19530'):
self.milvus = Milvus()
print("Client Version:", self.milvus.client_version())
status = self.milvus.connect(host, port)
if status.OK():
print("Server connected.")
else:
print("Server connect fail.")
sys.exit(1)
print("Server Version:", self.milvus.server_version()[-1])
def desc(self, tabel_name=None):
milvus = self.milvus
milvus.show_collections()
# milvus.drop_collection()
if tabel_name:
print(f"Describe: {milvus.describe_collection(tabel_name)[-1]}")
print(
f"Vector number in {tabel_name}: {milvus.count_collection(tabel_name)}"
)
def create_tabel_demo(self):
# Create table demo_table if it dosen't exist.
milvus = self.milvus
table_name = 'demo_table'
status, ok = milvus.has_collection(table_name)
if not ok:
param = {
'collection_name': table_name,
'dimension': 16,
'index_file_size':
1024, # optional index_file_size：文件到达这个大小的时候，milvus开始为这个文件创建索引。
'metric_type': MetricType.L2 # optional
}
milvus.create_collection(param)
# Show tables in Milvus server
_, collections = milvus.show_collections()
# Describe demo_table
_, table = milvus.describe_collection(table_name)
print(table)
def insert_vectors_demo(self, collection_name):
milvus = self.milvus
# 10000 vectors with 16 dimension
# element per dimension is float32 type
# vectors should be a 2-D array
# vectors = [[random.random() for _ in range(16)] for _ in range(10000)]
vectors = np.random.rand(10000, 16).astype(np.float32).tolist()
# You can also use numpy to generate random vectors:
# `vectors = np.random.rand(10000, 16).astype(np.float32).tolist()`
# Insert vectors into demo_table, return status and vectors id list
status, self.ids = milvus.insert(collection_name,
vectors) # 时间戳 1581655102 786 118
# Wait for 6 seconds, until Milvus server persist vector data.
time.sleep(6)
# Get demo_table row count
status, result = milvus.count_collection(collection_name)
# create index of vectors, search more rapidly
index_param = {'nlist': 2048}
# Create ivflat index in demo_table
# You can search vectors without creating index. however, Creating index help to
# search faster
status = milvus.create_index(collection_name,
index_type=IndexType.IVFLAT,
params=index_param)
# describe index, get information of index
status, index = milvus.describe_index(collection_name)
print(index)
# Use the top 10 vectors for similarity search
self._query_vectors = vectors[0:10]
def search_vectors_demo(self, query_vectors, collection_name):
milvus = self.milvus
# execute vector similarity search
status, results = milvus.search_vectors(collection_name,
top_k=1,
query_records=query_vectors,
params={'nprobe': 16})
if status.OK():
# indicate search result
# also use by:
# `results.distance_array[0][0] == 0.0 or results.id_array[0][0] == ids[0]`
if results[0][0].distance == 0.0 or results[0][0].id == self.ids[0]:
print('Query result is correct')
else:
print('Query result isn\'t correct')
# print results
print(results)
def drop_table(self, collection_name):
milvus = self.milvus
# Delete demo_table
status = milvus.drop_collection(collection_name)
# Disconnect from Milvus
status = milvus.disconnect()
class MilvusClient(object):
def __init__(self, table_name=None, host=None, port=None):
self._milvus = Milvus()
self._table_name = table_name
try:
if not host:
self._milvus.connect(host=SERVER_HOST_DEFAULT,
port=SERVER_PORT_DEFAULT)
else:
self._milvus.connect(host=host, port=port)
except Exception as e:
raise e
def __str__(self):
return 'Milvus table %s' % self._table_name
def check_status(self, status):
if not status.OK():
logger.error(status.message)
raise Exception("Status not ok")
def create_table(self, table_name, dimension, index_file_size,
metric_type):
if not self._table_name:
self._table_name = table_name
if metric_type == "l2":
metric_type = MetricType.L2
elif metric_type == "ip":
metric_type = MetricType.IP
else:
logger.error("Not supported metric_type: %s" % metric_type)
self._metric_type = metric_type
create_param = {
'table_name': table_name,
'dimension': dimension,
'index_file_size': index_file_size,
"metric_type": metric_type
}
status = self._milvus.create_table(create_param)
self.check_status(status)
@time_wrapper
def insert(self, X, ids):
if self._metric_type == MetricType.IP:
logger.info("Set normalize for metric_type: Inner Product")
X = sklearn.preprocessing.normalize(X, axis=1, norm='l2')
X = X.astype(numpy.float32)
status, result = self._milvus.add_vectors(self._table_name,
X.tolist(),
ids=ids)
self.check_status(status)
return status, result
@time_wrapper
def create_index(self, index_type, nlist):
if index_type == "flat":
index_type = IndexType.FLAT
elif index_type == "ivf_flat":
index_type = IndexType.IVFLAT
elif index_type == "ivf_sq8":
index_type = IndexType.IVF_SQ8
elif index_type == "ivf_sq8h":
index_type = IndexType.IVF_SQ8H
elif index_type == "nsg":
index_type = IndexType.NSG
elif index_type == "ivf_pq":
index_type = IndexType.IVF_PQ
index_params = {
"index_type": index_type,
"nlist": nlist,
}
logger.info("Building index start, table_name: %s, index_params: %s" %
(self._table_name, json.dumps(index_params)))
status = self._milvus.create_index(self._table_name,
index=index_params,
timeout=6 * 3600)
self.check_status(status)
def describe_index(self):
return self._milvus.describe_index(self._table_name)
def drop_index(self):
logger.info("Drop index: %s" % self._table_name)
return self._milvus.drop_index(self._table_name)
@time_wrapper
def query(self, X, top_k, nprobe):
if self._metric_type == MetricType.IP:
logger.info("Set normalize for metric_type: Inner Product")
X = sklearn.preprocessing.normalize(X, axis=1, norm='l2')
X = X.astype(numpy.float32)
status, results = self._milvus.search_vectors(self._table_name, top_k,
nprobe, X.tolist())
self.check_status(status)
ids = []
for result in results:
tmp_ids = []
for item in result:
tmp_ids.append(item.id)
ids.append(tmp_ids)
return ids
def count(self):
return self._milvus.get_table_row_count(self._table_name)[1]
def delete(self, table_name):
logger.info("Start delete table: %s" % table_name)
return self._milvus.delete_table(table_name)
def describe(self):
return self._milvus.describe_table(self._table_name)
def exists_table(self, table_name):
return self._milvus.has_table(table_name)
def get_server_version(self):
status, res = self._milvus.server_version()
self.check_status(status)
return res
@time_wrapper
def preload_table(self):
return self._milvus.preload_table(self._table_name)
class ANN(object):
def __init__(self, host='10.119.33.90', port='19530', show_info=False):
self.client = Milvus(host, port)
if show_info:
logger.info({
"ClientVersion": self.client.client_version(),
"ServerVersion": self.client.server_version()
})
def create_collection(self,
collection_name,
collection_param,
partition_tag=None,
overwrite=True):
"""
:param collection_name:
:param collection_param:
collection_param = {
"fields": [
# Milvus doesn't support string type now, but we are considering supporting it soon.
# {"name": "title", "type": DataType.STRING},
{"name": "category_", "type": DataType.INT32},
{"name": "vector", "type": DataType.FLOAT_VECTOR, "params": {"dim": 768}},
],
"segment_row_limit": 4096,
"auto_id": False
}
:param overwrite:
:return:
"""
if self.client.has_collection(collection_name) and overwrite:
self.client.drop_collection(collection_name)
self.client.flush()
time.sleep(5)
self.client.create_collection(collection_name, collection_param)
elif self.client.has_collection(collection_name):
print(f"{collection_name} already exist !!!")
else:
self.client.create_collection(collection_name, collection_param)
if partition_tag is not None:
self.client.create_partition(collection_name,
partition_tag=partition_tag)
def create_index(self,
collection_name,
field_name,
index_type='IVF_FLAT',
metric_type='IP',
index_params=None):
"""
MetricType:
INVALID = 0
L2 = 1
IP = 2
# Only supported for byte vectors
HAMMING = 3
JACCARD = 4
TANIMOTO = 5
#
SUBSTRUCTURE = 6
SUPERSTRUCTURE = 7
IndexType:
INVALID = 0
FLAT = 1
IVFLAT = 2
IVF_SQ8 = 3
RNSG = 4
IVF_SQ8H = 5
IVF_PQ = 6
HNSW = 11
ANNOY = 12
# alternative name
IVF_FLAT = IVFLAT
IVF_SQ8_H = IVF_SQ8H
class DataType(IntEnum):
NULL = 0
INT8 = 1
INT16 = 2
INT32 = 3
INT64 = 4
STRING = 20
BOOL = 30
FLOAT = 40
DOUBLE = 41
VECTOR = 100
UNKNOWN = 9999
class RangeType(IntEnum):
LT = 0 # less than
LTE = 1 # less than or equal
EQ = 2 # equal
GT = 3 # greater than
GTE = 4 # greater than or equal
NE = 5 # not equal
:return:
"""
if index_params is None:
index_params = {'nlist': 1024}
params = {
'index_type': index_type,
# 'index_file_size': 1024,
'params': index_params,
'metric_type': metric_type,
}
self.client.create_index(collection_name, field_name,
params) # field_name='embedding'
def batch_insert(self, collection_name, entities, batch_size=100000):
# 分区
n = len(entities[0]['values'])
num_part = n // batch_size + 1
ids = []
values_list = [_['values'] for _ in entities]
for i in range(num_part):
for e, values in zip(entities, values_list):
e['values'] = values[i * batch_size:(i + 1) * batch_size]
ids += self.client.insert(collection_name, entities)
self.client.flush()
return ids
def search(self): # todo: 获取相同的信息
pass
def drop_collection(self, collection_name):
if self.client.has_collection(collection_name):
self.client.drop_collection(collection_name)
def drop_partition(self, collection_name, partition_tag):
if self.client.has_partition(collection_name, partition_tag):
self.client.drop_partition(collection_name,
partition_tag,
timeout=30)
