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milvus/internal/core/unittest/test_sealed.cpp
xige-16 2ca53fa668 Fix msgstream deadlock when loadCollection 
Signed-off-by: xige-16 <xi.ge@zilliz.com>
2021-02-07 15:47:10 +08:00

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// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software distributed under the License
// is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
// or implied. See the License for the specific language governing permissions and limitations under the License
//
// Created by mike on 12/28/20.
//
#include "test_utils/DataGen.h"
#include <gtest/gtest.h>
#include <knowhere/index/vector_index/VecIndex.h>
#include <knowhere/index/vector_index/adapter/VectorAdapter.h>
#include <knowhere/index/vector_index/VecIndexFactory.h>
#include <knowhere/index/vector_index/IndexIVF.h>
#include "segcore/SegmentSealedImpl.h"
using namespace milvus;
using namespace milvus::segcore;
using namespace milvus::query;
TEST(Sealed, without_predicate) {
using namespace milvus::query;
using namespace milvus::segcore;
auto schema = std::make_shared<Schema>();
auto dim = 16;
auto topK = 5;
auto metric_type = MetricType::METRIC_L2;
auto fake_id = schema->AddDebugField("fakevec", DataType::VECTOR_FLOAT, dim, metric_type);
schema->AddDebugField("age", DataType::FLOAT);
std::string dsl = R"({
"bool": {
"must": [
{
"vector": {
"fakevec": {
"metric_type": "L2",
"params": {
"nprobe": 10
},
"query": "$0",
"topk": 5
}
}
}
]
}
})";
int64_t N = 1000 * 1000;
auto dataset = DataGen(schema, N);
auto vec_col = dataset.get_col<float>(0);
for (int64_t i = 0; i < 1000 * dim; ++i) {
vec_col.push_back(0);
}
auto query_ptr = vec_col.data() + 4200 * dim;
auto segment = CreateGrowingSegment(schema);
segment->PreInsert(N);
segment->Insert(0, N, dataset.row_ids_.data(), dataset.timestamps_.data(), dataset.raw_);
auto plan = CreatePlan(*schema, dsl);
auto num_queries = 5;
auto ph_group_raw = CreatePlaceholderGroupFromBlob(num_queries, 16, query_ptr);
auto ph_group = ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
QueryResult qr;
Timestamp time = 1000000;
std::vector<const PlaceholderGroup*> ph_group_arr = {ph_group.get()};
qr = segment->Search(plan.get(), ph_group_arr.data(), &time, 1);
auto pre_result = QueryResultToJson(qr);
auto indexing = std::make_shared<knowhere::IVF>();
auto conf = knowhere::Config{{knowhere::meta::DIM, dim},
{knowhere::meta::TOPK, topK},
{knowhere::IndexParams::nlist, 100},
{knowhere::IndexParams::nprobe, 10},
{knowhere::Metric::TYPE, milvus::knowhere::Metric::L2},
{knowhere::meta::DEVICEID, 0}};
auto database = knowhere::GenDataset(N, dim, vec_col.data() + 1000 * dim);
indexing->Train(database, conf);
indexing->AddWithoutIds(database, conf);
EXPECT_EQ(indexing->Count(), N);
EXPECT_EQ(indexing->Dim(), dim);
auto query_dataset = knowhere::GenDataset(num_queries, dim, query_ptr);
auto result = indexing->Query(query_dataset, conf, nullptr);
auto ids = result->Get<int64_t*>(milvus::knowhere::meta::IDS); // for comparison
auto dis = result->Get<float*>(milvus::knowhere::meta::DISTANCE); // for comparison
std::vector<int64_t> vec_ids(ids, ids + topK * num_queries);
std::vector<float> vec_dis(dis, dis + topK * num_queries);
qr.internal_seg_offsets_ = vec_ids;
qr.result_distances_ = vec_dis;
auto ref_result = QueryResultToJson(qr);
LoadIndexInfo load_info;
load_info.field_id = fake_id.get();
load_info.index = indexing;
load_info.index_params["metric_type"] = "L2";
segment->LoadIndexing(load_info);
qr = QueryResult();
qr = segment->Search(plan.get(), ph_group_arr.data(), &time, 1);
auto post_result = QueryResultToJson(qr);
std::cout << ref_result.dump(1);
std::cout << post_result.dump(1);
ASSERT_EQ(ref_result.dump(2), post_result.dump(2));
}
TEST(Sealed, with_predicate) {
using namespace milvus::query;
using namespace milvus::segcore;
auto schema = std::make_shared<Schema>();
auto dim = 16;
auto topK = 5;
auto metric_type = MetricType::METRIC_L2;
auto fake_id = schema->AddDebugField("fakevec", DataType::VECTOR_FLOAT, dim, metric_type);
schema->AddDebugField("counter", DataType::INT64);
std::string dsl = R"({
"bool": {
"must": [
{
"range": {
"counter": {
"GE": 420000,
"LT": 420005
}
}
},
{
"vector": {
"fakevec": {
"metric_type": "L2",
"params": {
"nprobe": 10
},
"query": "$0",
"topk": 5
}
}
}
]
}
})";
int64_t N = 1000 * 1000;
auto dataset = DataGen(schema, N);
auto vec_col = dataset.get_col<float>(0);
auto query_ptr = vec_col.data() + 420000 * dim;
auto segment = CreateGrowingSegment(schema);
segment->PreInsert(N);
segment->Insert(0, N, dataset.row_ids_.data(), dataset.timestamps_.data(), dataset.raw_);
auto plan = CreatePlan(*schema, dsl);
auto num_queries = 5;
auto ph_group_raw = CreatePlaceholderGroupFromBlob(num_queries, 16, query_ptr);
auto ph_group = ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
QueryResult qr;
Timestamp time = 10000000;
std::vector<const PlaceholderGroup*> ph_group_arr = {ph_group.get()};
qr = segment->Search(plan.get(), ph_group_arr.data(), &time, 1);
auto pre_qr = qr;
auto indexing = std::make_shared<knowhere::IVF>();
auto conf = knowhere::Config{{knowhere::meta::DIM, dim},
{knowhere::meta::TOPK, topK},
{knowhere::IndexParams::nlist, 100},
{knowhere::IndexParams::nprobe, 10},
{knowhere::Metric::TYPE, milvus::knowhere::Metric::L2},
{knowhere::meta::DEVICEID, 0}};
auto database = knowhere::GenDataset(N, dim, vec_col.data());
indexing->Train(database, conf);
indexing->AddWithoutIds(database, conf);
EXPECT_EQ(indexing->Count(), N);
EXPECT_EQ(indexing->Dim(), dim);
auto query_dataset = knowhere::GenDataset(num_queries, dim, query_ptr);
auto result = indexing->Query(query_dataset, conf, nullptr);
LoadIndexInfo load_info;
load_info.field_id = fake_id.get();
load_info.index = indexing;
load_info.index_params["metric_type"] = "L2";
segment->LoadIndexing(load_info);
qr = QueryResult();
qr = segment->Search(plan.get(), ph_group_arr.data(), &time, 1);
auto post_qr = qr;
for (int i = 0; i < num_queries; ++i) {
auto offset = i * topK;
ASSERT_EQ(post_qr.internal_seg_offsets_[offset], 420000 + i);
ASSERT_EQ(post_qr.result_distances_[offset], 0.0);
}
}
TEST(Sealed, LoadFieldData) {
auto dim = 16;
auto topK = 5;
int64_t N = 1000 * 1000;
auto metric_type = MetricType::METRIC_L2;
auto schema = std::make_shared<Schema>();
auto fakevec_id = schema->AddDebugField("fakevec", DataType::VECTOR_FLOAT, dim, metric_type);
auto counter_id = schema->AddDebugField("counter", DataType::INT64);
auto double_id = schema->AddDebugField("double", DataType::DOUBLE);
auto nothing_id = schema->AddDebugField("nothing", DataType::INT32);
auto dataset = DataGen(schema, N);
auto fakevec = dataset.get_col<float>(0);
auto indexing = GenIndexing(N, dim, fakevec.data());
auto segment = CreateSealedSegment(schema);
std::string dsl = R"({
"bool": {
"must": [
{
"range": {
"double": {
"GE": -1,
"LT": 1
}
}
},
{
"vector": {
"fakevec": {
"metric_type": "L2",
"params": {
"nprobe": 10
},
"query": "$0",
"topk": 5
}
}
}
]
}
})";
Timestamp time = 1000000;
auto plan = CreatePlan(*schema, dsl);
auto num_queries = 5;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, 16, 1024);
auto ph_group = ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
std::vector<const PlaceholderGroup*> ph_group_arr = {ph_group.get()};
ASSERT_ANY_THROW(segment->Search(plan.get(), ph_group_arr.data(), &time, 1));
SealedLoader(dataset, *segment);
segment->DropFieldData(nothing_id);
segment->Search(plan.get(), ph_group_arr.data(), &time, 1);
segment->DropFieldData(fakevec_id);
ASSERT_ANY_THROW(segment->Search(plan.get(), ph_group_arr.data(), &time, 1));
LoadIndexInfo vec_info;
vec_info.field_id = fakevec_id.get();
vec_info.index = indexing;
vec_info.index_params["metric_type"] = milvus::knowhere::Metric::L2;
segment->LoadIndex(vec_info);
ASSERT_EQ(segment->num_chunk(), 1);
auto chunk_span1 = segment->chunk_data<int64_t>(FieldOffset(1), 0);
auto chunk_span2 = segment->chunk_data<double>(FieldOffset(2), 0);
auto ref1 = dataset.get_col<int64_t>(1);
auto ref2 = dataset.get_col<double>(2);
for (int i = 0; i < N; ++i) {
ASSERT_EQ(chunk_span1[i], ref1[i]);
ASSERT_EQ(chunk_span2[i], ref2[i]);
}
auto qr = segment->Search(plan.get(), ph_group_arr.data(), &time, 1);
auto json = QueryResultToJson(qr);
std::cout << json.dump(1);
segment->DropIndex(fakevec_id);
ASSERT_ANY_THROW(segment->Search(plan.get(), ph_group_arr.data(), &time, 1));
segment->LoadIndex(vec_info);
auto qr2 = segment->Search(plan.get(), ph_group_arr.data(), &time, 1);
auto json2 = QueryResultToJson(qr);
ASSERT_EQ(json.dump(-2), json2.dump(-2));
segment->DropFieldData(double_id);
ASSERT_ANY_THROW(segment->Search(plan.get(), ph_group_arr.data(), &time, 1));
auto std_json = Json::parse(R"(
[
[
[
"980486->3.149221",
"579754->3.634295",
"318367->3.661235",
"265835->4.333358",
"302798->4.553688"
],
[
"233390->7.931535",
"238958->8.109344",
"230645->8.439169",
"901939->8.658772",
"380328->8.731251"
],
[
"897246->3.749835",
"750683->3.897577",
"857598->4.230977",
"299009->4.379639",
"440010->4.454046"
],
[
"37641->3.783446",
"22628->4.719435",
"840855->4.782170",
"709627->5.063170",
"635836->5.156095"
],
[
"810401->3.926393",
"46575->4.054171",
"201740->4.274491",
"669040->4.399628",
"231500->4.831223"
]
]
]
)");
ASSERT_EQ(std_json.dump(-2), json.dump(-2));
}
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