milvus/internal/core/unittest/test_query.cpp
zhagnlu 489087d18b
enhance: refactor executor framework V2 (#35251)
#32636

Signed-off-by: luzhang <luzhang@zilliz.com>
Co-authored-by: luzhang <luzhang@zilliz.com>
2024-09-13 20:57:09 +08:00

740 lines
30 KiB
C++

// 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
#include <gtest/gtest.h>
#include "pb/schema.pb.h"
#include "query/PlanImpl.h"
#include "query/PlanNode.h"
#include "query/ExecPlanNodeVisitor.h"
#include "segcore/SegmentSealed.h"
#include "test_utils/AssertUtils.h"
#include "test_utils/DataGen.h"
using json = nlohmann::json;
using namespace milvus;
using namespace milvus::query;
using namespace milvus::segcore;
namespace {
const int64_t ROW_COUNT = 100 * 1000;
}
TEST(Query, ParsePlaceholderGroup) {
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 10
round_decimal: 3
metric_type: "L2"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto schema = std::make_shared<Schema>();
schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, 16, knowhere::metric::L2);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
int64_t num_queries = 100000;
int dim = 16;
auto raw_group = CreatePlaceholderGroup(num_queries, dim);
auto blob = raw_group.SerializeAsString();
auto placeholder = ParsePlaceholderGroup(plan.get(), blob);
}
TEST(Query, ExecWithPredicateLoader) {
auto schema = std::make_shared<Schema>();
schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, 16, knowhere::metric::L2);
schema->AddDebugField("age", DataType::FLOAT);
auto counter_fid = schema->AddDebugField("counter", DataType::INT64);
schema->set_primary_field_id(counter_fid);
const char* raw_plan = R"(vector_anns: <
field_id: 100
predicates: <
binary_range_expr: <
column_info: <
field_id: 101
data_type: Float
>
lower_inclusive: true,
upper_inclusive: false,
lower_value: <
float_val: -1
>
upper_value: <
float_val: 1
>
>
>
query_info: <
topk: 5
round_decimal: 3
metric_type: "L2"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
int64_t N = ROW_COUNT;
auto dataset = DataGen(schema, N);
auto segment = CreateGrowingSegment(schema, empty_index_meta);
segment->PreInsert(N);
segment->Insert(0,
N,
dataset.row_ids_.data(),
dataset.timestamps_.data(),
dataset.raw_);
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
auto num_queries = 5;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, 16, 1024);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
Timestamp timestamp = 1000000;
auto sr = segment->Search(plan.get(), ph_group.get(), timestamp);
query::Json json = SearchResultToJson(*sr);
#ifdef __linux__
auto ref = json::parse(R"(
[
[
["982->0.000000", "25315->4.742000", "57893->4.758000", "1499->6.066000", "48201->6.075000"],
["41772->10.111000", "42126->11.532000", "80693->11.712000", "74859->11.790000", "79777->11.842000"],
["59251->2.543000", "65551->4.454000", "21617->5.144000", "50037->5.267000", "72204->5.332000"],
["59219->5.458000", "21995->6.078000", "97922->6.764000", "80887->6.898000", "61367->7.029000"],
["66353->5.696000", "30664->5.881000", "41087->5.917000", "34625->6.109000", "10393->6.633000"]
]
])");
#else // for mac
auto ref = json::parse(R"(
[
[
["982->0.000000", "31864->4.270000", "18916->4.651000", "71547->5.125000", "86706->5.991000"],
["96984->4.192000", "65514->6.011000", "89328->6.138000", "80284->6.526000", "68218->6.563000"],
["30119->2.464000", "52595->4.323000", "82365->4.725000", "32673->4.851000", "74834->5.009000"],
["99625->6.129000", "86582->6.900000", "10069->7.388000", "89982->7.672000", "85934->7.792000"],
["37759->3.581000", "97019->5.557000", "92444->5.681000", "31292->5.780000", "53543->5.844000"]
]
])");
#endif
std::cout << json.dump(2);
ASSERT_EQ(json.dump(2), ref.dump(2));
}
TEST(Query, ExecWithPredicateSmallN) {
auto schema = std::make_shared<Schema>();
schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, 7, knowhere::metric::L2);
schema->AddDebugField("age", DataType::FLOAT);
auto i64_fid = schema->AddDebugField("counter", DataType::INT64);
schema->set_primary_field_id(i64_fid);
const char* raw_plan = R"(vector_anns: <
field_id: 100
predicates: <
binary_range_expr: <
column_info: <
field_id: 101
data_type: Float
>
lower_inclusive: true,
upper_inclusive: false,
lower_value: <
float_val: -1
>
upper_value: <
float_val: 1
>
>
>
query_info: <
topk: 5
round_decimal: 3
metric_type: "L2"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
int64_t N = 177;
auto dataset = DataGen(schema, N);
auto segment = CreateGrowingSegment(schema, empty_index_meta);
segment->PreInsert(N);
segment->Insert(0,
N,
dataset.row_ids_.data(),
dataset.timestamps_.data(),
dataset.raw_);
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
auto num_queries = 5;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, 7, 1024);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
Timestamp timestamp = 1000000;
auto sr = segment->Search(plan.get(), ph_group.get(), timestamp);
query::Json json = SearchResultToJson(*sr);
std::cout << json.dump(2);
}
TEST(Query, ExecWithPredicate) {
auto schema = std::make_shared<Schema>();
schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, 16, knowhere::metric::L2);
schema->AddDebugField("age", DataType::FLOAT);
auto i64_fid = schema->AddDebugField("counter", DataType::INT64);
schema->set_primary_field_id(i64_fid);
const char* raw_plan = R"(vector_anns: <
field_id: 100
predicates: <
binary_range_expr: <
column_info: <
field_id: 101
data_type: Float
>
lower_inclusive: true,
upper_inclusive: false,
lower_value: <
float_val: -1
>
upper_value: <
float_val: 1
>
>
>
query_info: <
topk: 5
round_decimal: 3
metric_type: "L2"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
int64_t N = ROW_COUNT;
auto dataset = DataGen(schema, N);
auto segment = CreateGrowingSegment(schema, empty_index_meta);
segment->PreInsert(N);
segment->Insert(0,
N,
dataset.row_ids_.data(),
dataset.timestamps_.data(),
dataset.raw_);
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
auto num_queries = 5;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, 16, 1024);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
Timestamp timestamp = 1000000;
auto sr = segment->Search(plan.get(), ph_group.get(), timestamp);
query::Json json = SearchResultToJson(*sr);
#ifdef __linux__
auto ref = json::parse(R"(
[
[
["982->0.000000", "25315->4.742000", "57893->4.758000", "1499->6.066000", "48201->6.075000"],
["41772->10.111000", "42126->11.532000", "80693->11.712000", "74859->11.790000", "79777->11.842000"],
["59251->2.543000", "65551->4.454000", "21617->5.144000", "50037->5.267000", "72204->5.332000"],
["59219->5.458000", "21995->6.078000", "97922->6.764000", "80887->6.898000", "61367->7.029000"],
["66353->5.696000", "30664->5.881000", "41087->5.917000", "34625->6.109000", "10393->6.633000"]
]
])");
#else // for mac
auto ref = json::parse(R"(
[
[
["982->0.000000", "31864->4.270000", "18916->4.651000", "71547->5.125000", "86706->5.991000"],
["96984->4.192000", "65514->6.011000", "89328->6.138000", "80284->6.526000", "68218->6.563000"],
["30119->2.464000", "52595->4.323000", "82365->4.725000", "32673->4.851000", "74834->5.009000"],
["99625->6.129000", "86582->6.900000", "10069->7.388000", "89982->7.672000", "85934->7.792000"],
["37759->3.581000", "97019->5.557000", "92444->5.681000", "31292->5.780000", "53543->5.844000"]
]
])");
#endif
std::cout << json.dump(2);
ASSERT_EQ(json.dump(2), ref.dump(2));
}
TEST(Query, ExecTerm) {
auto schema = std::make_shared<Schema>();
schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, 16, knowhere::metric::L2);
schema->AddDebugField("age", DataType::FLOAT);
auto i64_fid = schema->AddDebugField("counter", DataType::INT64);
schema->set_primary_field_id(i64_fid);
const char* raw_plan = R"(vector_anns: <
field_id: 100
predicates: <
term_expr: <
column_info: <
field_id: 102
data_type: Int64
>
values: <
int64_val: 1
>
values: <
int64_val: 2
>
>
>
query_info: <
topk: 5
round_decimal: 3
metric_type: "L2"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
int64_t N = ROW_COUNT;
auto dataset = DataGen(schema, N);
auto segment = CreateGrowingSegment(schema, empty_index_meta);
segment->PreInsert(N);
segment->Insert(0,
N,
dataset.row_ids_.data(),
dataset.timestamps_.data(),
dataset.raw_);
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
auto num_queries = 3;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, 16, 1024);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
Timestamp timestamp = 1000000;
auto sr = segment->Search(plan.get(), ph_group.get(), timestamp);
int topk = 5;
auto json = SearchResultToJson(*sr);
ASSERT_EQ(sr->total_nq_, num_queries);
ASSERT_EQ(sr->unity_topK_, topk);
}
TEST(Query, ExecEmpty) {
auto schema = std::make_shared<Schema>();
schema->AddDebugField("age", DataType::FLOAT);
schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, 16, knowhere::metric::L2);
const char* raw_plan = R"(vector_anns: <
field_id: 101
query_info: <
topk: 5
round_decimal: 3
metric_type: "L2"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
int64_t N = ROW_COUNT;
auto segment = CreateGrowingSegment(schema, empty_index_meta);
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
auto num_queries = 5;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, 16, 1024);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
Timestamp timestamp = 1000000;
auto sr = segment->Search(plan.get(), ph_group.get(), timestamp);
std::cout << SearchResultToJson(*sr);
ASSERT_EQ(sr->unity_topK_, 0);
for (auto i : sr->seg_offsets_) {
ASSERT_EQ(i, -1);
}
for (auto v : sr->distances_) {
ASSERT_EQ(v, std::numeric_limits<float>::max());
}
}
TEST(Query, ExecWithoutPredicateFlat) {
auto schema = std::make_shared<Schema>();
schema->AddDebugField("fakevec", DataType::VECTOR_FLOAT, 16, std::nullopt);
schema->AddDebugField("age", DataType::FLOAT);
auto i64_fid = schema->AddDebugField("counter", DataType::INT64);
schema->set_primary_field_id(i64_fid);
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 5
round_decimal: 3
metric_type: "L2"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
int64_t N = ROW_COUNT;
auto dataset = DataGen(schema, N);
auto segment = CreateGrowingSegment(schema, empty_index_meta);
segment->PreInsert(N);
segment->Insert(0,
N,
dataset.row_ids_.data(),
dataset.timestamps_.data(),
dataset.raw_);
auto num_queries = 5;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, 16, 1024);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
Timestamp timestamp = 1000000;
auto sr = segment->Search(plan.get(), ph_group.get(), timestamp);
std::vector<std::vector<std::string>> results;
auto json = SearchResultToJson(*sr);
std::cout << json.dump(2);
}
TEST(Query, ExecWithoutPredicate) {
auto schema = std::make_shared<Schema>();
schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, 16, knowhere::metric::L2);
schema->AddDebugField("age", DataType::FLOAT);
auto i64_fid = schema->AddDebugField("counter", DataType::INT64);
schema->set_primary_field_id(i64_fid);
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 5
round_decimal: 3
metric_type: "L2"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
int64_t N = ROW_COUNT;
auto dataset = DataGen(schema, N);
auto segment = CreateGrowingSegment(schema, empty_index_meta);
segment->PreInsert(N);
segment->Insert(0,
N,
dataset.row_ids_.data(),
dataset.timestamps_.data(),
dataset.raw_);
auto num_queries = 5;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, 16, 1024);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
Timestamp timestamp = 1000000;
auto sr = segment->Search(plan.get(), ph_group.get(), timestamp);
assert_order(*sr, "l2");
std::vector<std::vector<std::string>> results;
auto json = SearchResultToJson(*sr);
#ifdef __linux__
auto ref = json::parse(R"(
[
[
["982->0.000000", "25315->4.742000", "57893->4.758000", "1499->6.066000", "48201->6.075000"],
["41772->10.111000", "42126->11.532000", "80693->11.712000", "74859->11.790000", "79777->11.842000"],
["59251->2.543000", "68714->4.356000", "65551->4.454000", "21617->5.144000", "50037->5.267000"],
["33572->5.432000", "59219->5.458000", "21995->6.078000", "97922->6.764000", "17913->6.831000"],
["66353->5.696000", "30664->5.881000", "41087->5.917000", "34625->6.109000", "24554->6.195000"]
]
])");
#else // for mac
auto ref = json::parse(R"(
[
[
["982->0.000000", "31864->4.270000", "18916->4.651000", "78227->4.808000", "71547->5.125000"],
["96984->4.192000", "45733->4.912000", "32891->5.016000", "65514->6.011000", "89328->6.138000"],
["30119->2.464000", "23782->3.724000", "52595->4.323000", "82365->4.725000", "32673->4.851000"],
["99625->6.129000", "86582->6.900000", "60608->7.285000", "10069->7.388000", "89982->7.672000"],
["37759->3.581000", "50907->4.776000", "45814->4.872000", "97019->5.557000", "92444->5.681000"]
]
])");
#endif
std::cout << json.dump(2);
ASSERT_EQ(json.dump(2), ref.dump(2));
}
TEST(Query, InnerProduct) {
int64_t N = 100000;
constexpr auto dim = 16;
constexpr auto topk = 10;
auto num_queries = 5;
auto schema = std::make_shared<Schema>();
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 5
round_decimal: 3
metric_type: "IP"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
auto vec_fid = schema->AddDebugField(
"normalized", DataType::VECTOR_FLOAT, dim, knowhere::metric::IP);
auto i64_fid = schema->AddDebugField("age", DataType::INT64);
schema->set_primary_field_id(i64_fid);
auto dataset = DataGen(schema, N);
auto segment = CreateGrowingSegment(schema, empty_index_meta);
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
segment->PreInsert(N);
segment->Insert(0,
N,
dataset.row_ids_.data(),
dataset.timestamps_.data(),
dataset.raw_);
auto col = dataset.get_col<float>(vec_fid);
auto ph_group_raw =
CreatePlaceholderGroupFromBlob(num_queries, 16, col.data());
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
Timestamp ts = N * 2;
auto sr = segment->Search(plan.get(), ph_group.get(), ts);
assert_order(*sr, "ip");
}
TEST(Query, FillSegment) {
namespace pb = milvus::proto;
pb::schema::CollectionSchema proto;
proto.set_name("col");
proto.set_description("asdfhsalkgfhsadg");
auto dim = 16;
{
auto field = proto.add_fields();
field->set_name("fakevec");
field->set_nullable(false);
field->set_is_primary_key(false);
field->set_description("asdgfsagf");
field->set_fieldid(100);
field->set_data_type(pb::schema::DataType::FloatVector);
auto param = field->add_type_params();
param->set_key("dim");
param->set_value("16");
auto iparam = field->add_index_params();
iparam->set_key("metric_type");
iparam->set_value("L2");
}
{
auto field = proto.add_fields();
field->set_name("the_key");
field->set_nullable(false);
field->set_fieldid(101);
field->set_is_primary_key(true);
field->set_description("asdgfsagf");
field->set_data_type(pb::schema::DataType::Int64);
}
{
auto field = proto.add_fields();
field->set_name("the_value");
field->set_nullable(true);
field->set_fieldid(102);
field->set_is_primary_key(false);
field->set_description("asdgfsagf");
field->set_data_type(pb::schema::DataType::Int32);
}
auto schema = Schema::ParseFrom(proto);
// dispatch here
int N = 100000;
auto dataset = DataGen(schema, N);
const auto std_vec = dataset.get_col<int64_t>(FieldId(101)); // ids field
const auto std_vfloat_vec =
dataset.get_col<float>(FieldId(100)); // vector field
const auto std_i32_vec =
dataset.get_col<int32_t>(FieldId(102)); // scalar field
const auto i32_vec_valid_data = dataset.get_col_valid(FieldId(102));
std::vector<std::unique_ptr<SegmentInternalInterface>> segments;
segments.emplace_back([&] {
auto segment = CreateGrowingSegment(schema, empty_index_meta);
segment->PreInsert(N);
segment->Insert(0,
N,
dataset.row_ids_.data(),
dataset.timestamps_.data(),
dataset.raw_);
return segment;
}());
segments.emplace_back([&] {
auto segment = CreateSealedSegment(schema);
SealedLoadFieldData(dataset, *segment);
return segment;
}());
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 5
round_decimal: 3
metric_type: "L2"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
auto ph_proto = CreatePlaceholderGroup(10, 16, 443);
auto ph = ParsePlaceholderGroup(plan.get(), ph_proto.SerializeAsString());
Timestamp ts = N * 2UL;
auto topk = 5;
auto num_queries = 10;
for (auto& segment : segments) {
plan->target_entries_.clear();
plan->target_entries_.push_back(
schema->get_field_id(FieldName("fakevec")));
plan->target_entries_.push_back(
schema->get_field_id(FieldName("the_value")));
auto result = segment->Search(plan.get(), ph.get(), ts);
result->result_offsets_.resize(topk * num_queries);
segment->FillTargetEntry(plan.get(), *result);
segment->FillPrimaryKeys(plan.get(), *result);
auto& fields_data = result->output_fields_data_;
ASSERT_EQ(fields_data.size(), 2);
for (auto field_id : plan->target_entries_) {
ASSERT_EQ(fields_data.count(field_id), true);
}
auto vec_field_id = schema->get_field_id(FieldName("fakevec"));
auto output_vec_field_data =
fields_data.at(vec_field_id)->vectors().float_vector().data();
ASSERT_EQ(output_vec_field_data.size(), topk * num_queries * dim);
auto i32_field_id = schema->get_field_id(FieldName("the_value"));
auto output_i32_field_data =
fields_data.at(i32_field_id)->scalars().int_data().data();
ASSERT_EQ(output_i32_field_data.size(), topk * num_queries);
auto output_i32_valid_data = fields_data.at(i32_field_id)->valid_data();
ASSERT_EQ(output_i32_valid_data.size(), topk * num_queries);
for (int i = 0; i < topk * num_queries; i++) {
int64_t val = std::get<int64_t>(result->primary_keys_[i]);
auto internal_offset = result->seg_offsets_[i];
auto std_val = std_vec[internal_offset];
auto std_i32 = std_i32_vec[internal_offset];
auto std_i32_valid = i32_vec_valid_data[internal_offset];
std::vector<float> std_vfloat(dim);
std::copy_n(std_vfloat_vec.begin() + dim * internal_offset,
dim,
std_vfloat.begin());
ASSERT_EQ(val, std_val) << "io:" << internal_offset;
if (val != -1) {
// check vector field
std::vector<float> vfloat(dim);
memcpy(vfloat.data(),
&output_vec_field_data[i * dim],
dim * sizeof(float));
ASSERT_EQ(vfloat, std_vfloat);
// check int32 field
int i32;
memcpy(&i32, &output_i32_field_data[i], sizeof(int32_t));
ASSERT_EQ(i32, std_i32);
// check int32 valid field
bool i32_valid;
memcpy(&i32_valid, &output_i32_valid_data[i], sizeof(bool));
ASSERT_EQ(i32_valid, std_i32_valid);
}
}
}
}
TEST(Query, ExecWithPredicateBinary) {
auto schema = std::make_shared<Schema>();
auto vec_fid = schema->AddDebugField(
"fakevec", DataType::VECTOR_BINARY, 512, knowhere::metric::JACCARD);
auto float_fid = schema->AddDebugField("age", DataType::FLOAT);
auto i64_fid = schema->AddDebugField("counter", DataType::INT64);
schema->set_primary_field_id(i64_fid);
const char* raw_plan = R"(vector_anns: <
field_id: 100
predicates: <
binary_range_expr: <
column_info: <
field_id: 101
data_type: Float
>
lower_inclusive: true,
upper_inclusive: false,
lower_value: <
float_val: -1
>
upper_value: <
float_val: 1
>
>
>
query_info: <
topk: 5
round_decimal: 3
metric_type: "JACCARD"
search_params: "{\"nprobe\": 10}"
>
placeholder_tag: "$0"
>)";
int64_t N = ROW_COUNT;
auto dataset = DataGen(schema, N);
auto segment = CreateGrowingSegment(schema, empty_index_meta);
segment->PreInsert(N);
segment->Insert(0,
N,
dataset.row_ids_.data(),
dataset.timestamps_.data(),
dataset.raw_);
auto vec_ptr = dataset.get_col<uint8_t>(vec_fid);
auto plan_str = translate_text_plan_to_binary_plan(raw_plan);
auto plan =
CreateSearchPlanByExpr(*schema, plan_str.data(), plan_str.size());
auto num_queries = 5;
auto ph_group_raw = CreateBinaryPlaceholderGroupFromBlob(
num_queries, 512, vec_ptr.data() + 1024 * 512 / 8);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
Timestamp timestamp = 1000000;
auto sr = segment->Search(plan.get(), ph_group.get(), timestamp);
query::Json json = SearchResultToJson(*sr);
std::cout << json.dump(2);
// ASSERT_EQ(json.dump(2), ref.dump(2));
}