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feat: Add compact, get_server_version and flush api
Signed-off-by: zhenshan.cao <[email protected]>
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import time | ||
import numpy as np | ||
from pymilvus import ( | ||
MilvusClient, | ||
) | ||
|
||
fmt = "\n=== {:30} ===\n" | ||
dim = 8 | ||
collection_name = "hello_milvus" | ||
milvus_client = MilvusClient("http://localhost:19530") | ||
|
||
has_collection = milvus_client.has_collection(collection_name, timeout=5) | ||
if has_collection: | ||
milvus_client.drop_collection(collection_name) | ||
milvus_client.create_collection(collection_name, dim, consistency_level="Strong", metric_type="L2") | ||
|
||
rng = np.random.default_rng(seed=19530) | ||
rows = [ | ||
{"id": 1, "vector": rng.random((1, dim))[0], "a": 100}, | ||
{"id": 2, "vector": rng.random((1, dim))[0], "b": 200}, | ||
{"id": 3, "vector": rng.random((1, dim))[0], "c": 300}, | ||
{"id": 4, "vector": rng.random((1, dim))[0], "d": 400}, | ||
{"id": 5, "vector": rng.random((1, dim))[0], "e": 500}, | ||
{"id": 6, "vector": rng.random((1, dim))[0], "f": 600}, | ||
] | ||
|
||
print(fmt.format("Start inserting entities")) | ||
insert_result = milvus_client.insert(collection_name, rows) | ||
print(fmt.format("Inserting entities done")) | ||
print(insert_result) | ||
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||
upsert_ret = milvus_client.upsert(collection_name, {"id": 2 , "vector": rng.random((1, dim))[0], "g": 100}) | ||
print(upsert_ret) | ||
|
||
print(fmt.format("Start flush")) | ||
milvus_client.flush(collection_name) | ||
print(fmt.format("flush done")) | ||
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||
result = milvus_client.query(collection_name, "", output_fields = ["count(*)"]) | ||
print(f"final entities in {collection_name} is {result[0]['count(*)']}") | ||
|
||
rows = [ | ||
{"id": 7, "vector": rng.random((1, dim))[0], "g": 700}, | ||
{"id": 8, "vector": rng.random((1, dim))[0], "h": 800}, | ||
{"id": 9, "vector": rng.random((1, dim))[0], "i": 900}, | ||
{"id": 10, "vector": rng.random((1, dim))[0], "j": 1000}, | ||
{"id": 11, "vector": rng.random((1, dim))[0], "k": 1100}, | ||
{"id": 12, "vector": rng.random((1, dim))[0], "l": 1200}, | ||
] | ||
|
||
print(fmt.format("Start inserting entities")) | ||
insert_result = milvus_client.insert(collection_name, rows) | ||
print(fmt.format("Inserting entities done")) | ||
print(insert_result) | ||
|
||
print(fmt.format("Start flush")) | ||
milvus_client.flush(collection_name) | ||
print(fmt.format("flush done")) | ||
|
||
result = milvus_client.query(collection_name, "", output_fields = ["count(*)"]) | ||
print(f"final entities in {collection_name} is {result[0]['count(*)']}") | ||
|
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print(fmt.format("Start compact")) | ||
job_id = milvus_client.compact(collection_name) | ||
print(f"job_id:{job_id}") | ||
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cnt = 0 | ||
state = milvus_client.get_compaction_state(job_id) | ||
while (state != "Completed" and cnt < 10): | ||
time.sleep(1.0) | ||
state = milvus_client.get_compaction_state(job_id) | ||
print(f"compaction state: {state}") | ||
cnt += 1 | ||
|
||
if state == "Completed": | ||
print(fmt.format("compact done")) | ||
else: | ||
print(fmt.format("compact timeout")) | ||
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result = milvus_client.query(collection_name, "", output_fields = ["count(*)"]) | ||
print(f"final entities in {collection_name} is {result[0]['count(*)']}") | ||
|
||
milvus_client.drop_collection(collection_name) |
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,57 @@ | ||
import time | ||
import numpy as np | ||
from pymilvus import ( | ||
MilvusClient, | ||
) | ||
|
||
fmt = "\n=== {:30} ===\n" | ||
dim = 8 | ||
collection_name = "hello_milvus" | ||
milvus_client = MilvusClient("http://localhost:19530") | ||
|
||
has_collection = milvus_client.has_collection(collection_name, timeout=5) | ||
if has_collection: | ||
milvus_client.drop_collection(collection_name) | ||
milvus_client.create_collection(collection_name, dim, consistency_level="Strong", metric_type="L2") | ||
|
||
rng = np.random.default_rng(seed=19530) | ||
rows = [ | ||
{"id": 1, "vector": rng.random((1, dim))[0], "a": 100}, | ||
{"id": 2, "vector": rng.random((1, dim))[0], "b": 200}, | ||
{"id": 3, "vector": rng.random((1, dim))[0], "c": 300}, | ||
{"id": 4, "vector": rng.random((1, dim))[0], "d": 400}, | ||
{"id": 5, "vector": rng.random((1, dim))[0], "e": 500}, | ||
{"id": 6, "vector": rng.random((1, dim))[0], "f": 600}, | ||
] | ||
|
||
print(fmt.format("Start inserting entities")) | ||
insert_result = milvus_client.insert(collection_name, rows) | ||
print(fmt.format("Inserting entities done")) | ||
print(insert_result) | ||
|
||
upsert_ret = milvus_client.upsert(collection_name, {"id": 2 , "vector": rng.random((1, dim))[0], "g": 100}) | ||
print(upsert_ret) | ||
|
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print(fmt.format("Start flush")) | ||
milvus_client.flush(collection_name) | ||
print(fmt.format("flush done")) | ||
|
||
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result = milvus_client.query(collection_name, "", output_fields = ["count(*)"]) | ||
print(f"final entities in {collection_name} is {result[0]['count(*)']}") | ||
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||
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print(f"start to delete by specifying filter in collection {collection_name}") | ||
delete_result = milvus_client.delete(collection_name, ids=[6]) | ||
print(delete_result) | ||
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||
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print(fmt.format("Start flush")) | ||
milvus_client.flush(collection_name) | ||
print(fmt.format("flush done")) | ||
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||
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result = milvus_client.query(collection_name, "", output_fields = ["count(*)"]) | ||
print(f"final entities in {collection_name} is {result[0]['count(*)']}") | ||
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milvus_client.drop_collection(collection_name) |
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,8 @@ | ||
from pymilvus import ( | ||
MilvusClient, | ||
) | ||
|
||
milvus_client = MilvusClient("http://localhost:19530") | ||
|
||
version = milvus_client.get_server_version() | ||
print(f"server version: {version}") |
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