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enhance: add example for null and default_value (#2479)
Signed-off-by: lixinguo <[email protected]> Co-authored-by: lixinguo <[email protected]>
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# 1. connect to Milvus | ||
# 2. create collection | ||
# 3. insert data | ||
# 4. create index | ||
# 5. query on entities | ||
# 6. drop collection | ||
import time | ||
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import numpy as np | ||
from pymilvus import ( | ||
connections, | ||
utility, | ||
FieldSchema, CollectionSchema, DataType, | ||
Collection, | ||
) | ||
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fmt = "\n=== {:30} ===\n" | ||
search_latency_fmt = "search latency = {:.4f}s" | ||
dim = 8 | ||
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################################################################################# | ||
# 1. connect to Milvus | ||
print(fmt.format("start connecting to Milvus")) | ||
connections.connect("default", host="localhost", port="19530") | ||
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has = utility.has_collection("hello_milvus") | ||
print(f"Does collection hello_milvus exist in Milvus: {has}") | ||
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################################################################################# | ||
# 2. create collection | ||
# We're going to create a collection with 4 fields. | ||
# +-+---------------------+------------+---------------------+--------------------------------------------------+ | ||
# | | field name | field type | other attributes | field description | | ||
# +-+---------------------+------------+---------------------+--------------------------------------------------+ | ||
# |1| "pk" | VarChar | is_primary=True | "primary field" | | ||
# | | | | auto_id=False | | | ||
# +-+---------------------+------------+---------------------+--------------------------------------------------+ | ||
# |2| "nullable_fid" | Double | nullable=True | "a double field can insert null" | | ||
# +-+---------------------+------------+---------------------+--------------------------------------------------+ | ||
# |3| "default_value_fid" | Int64 | default_value=1 | "a int64 field can insert with default value" | | ||
# +-+---------------------+------------+---------------------+--------------------------------------------------+ | ||
# |4| "embeddings" | FloatVector| dim=8 | "float vector with dim 8" | | ||
# +-+---------------------+------------+---------------------+--------------------------------------------------+ | ||
fields = [ | ||
FieldSchema(name="pk", dtype=DataType.VARCHAR, is_primary=True, auto_id=False, max_length=100), | ||
FieldSchema(name="nullable_fid", dtype=DataType.DOUBLE,nullable=True), | ||
FieldSchema(name="default_value_fid", dtype=DataType.INT64,default_value=1), | ||
FieldSchema(name="embeddings", dtype=DataType.FLOAT_VECTOR, dim=dim) | ||
] | ||
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schema = CollectionSchema(fields, "hello_milvus is the demo to introduce the nullable and default value functions") | ||
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print(fmt.format("Create collection `hello_milvus`")) | ||
hello_milvus = Collection("hello_milvus", schema, consistency_level="Strong") | ||
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################################################################################ | ||
# 3. insert data | ||
# For fields marked as nullable=True: | ||
# you can skip the field when inserting data, or set it directly to a null value, and the system will treat it as null | ||
# For fields marked default_value: | ||
# the system will automatically apply this value if no data is specified for the field during insertion | ||
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print(fmt.format("Start inserting entities")) | ||
rng = np.random.default_rng(seed=19530) | ||
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data_rows = [ | ||
{ | ||
# skip the field when inserting data | ||
"pk": "19530", | ||
"embeddings": rng.random((1, dim), np.float32)[0] | ||
}, | ||
{ | ||
# set it directly to a null value | ||
"pk": "19531", | ||
"nullable_fid": None, | ||
"default_value_fid": None, | ||
"embeddings": rng.random((1, dim), np.float32)[0] | ||
}, | ||
] | ||
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hello_milvus.insert(data_rows) | ||
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hello_milvus.flush() | ||
print(f"Number of entities in Milvus: {hello_milvus.num_entities}") # check the num_entities | ||
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################################################################################ | ||
# 4. create index | ||
print(fmt.format("Start Creating index IVF_FLAT")) | ||
index = { | ||
"index_type": "IVF_FLAT", | ||
"metric_type": "L2", | ||
"params": {"nlist": 128}, | ||
} | ||
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hello_milvus.create_index("embeddings", index) | ||
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################################################################################ | ||
# 5. query on entities | ||
print(fmt.format("Start loading")) | ||
hello_milvus.load() | ||
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print(fmt.format("Start querying")) | ||
start_time = time.time() | ||
result = hello_milvus.query(expr='pk in ["19530","19531"]', output_fields=["nullable_fid", "default_value_fid","embeddings"]) | ||
end_time = time.time() | ||
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print(f"query result:\n-{result[0]}") | ||
print(search_latency_fmt.format(end_time - start_time)) | ||
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############################################################################### | ||
# 6. drop collection | ||
# Finally, drop the hello_milvus collection | ||
print(fmt.format("Drop collection `hello_milvus`")) | ||
utility.drop_collection("hello_milvus") |