milvus-io
/
milvus
mirror of https://github.com/milvus-io/milvus.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
milvus/internal/core/unittest/test_group_by.cpp

819 lines
34 KiB
C++
Raw Permalink Blame History

// 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 "common/Schema.h"
#include "query/Plan.h"
#include "segcore/SegmentSealedImpl.h"
#include "segcore/reduce_c.h"
#include "segcore/plan_c.h"
#include "segcore/segment_c.h"
#include "test_utils/DataGen.h"
#include "test_utils/c_api_test_utils.h"
using namespace milvus;
using namespace milvus::query;
using namespace milvus::segcore;
using namespace milvus::storage;
using namespace milvus::tracer;
const char* METRICS_TYPE = "metric_type";
void
prepareSegmentSystemFieldData(const std::unique_ptr<SegmentSealed>& segment,
size_t row_count,
GeneratedData& data_set) {
auto field_data =
std::make_shared<milvus::FieldData<int64_t>>(DataType::INT64);
field_data->FillFieldData(data_set.row_ids_.data(), row_count);
auto field_data_info =
FieldDataInfo{RowFieldID.get(),
row_count,
std::vector<milvus::FieldDataPtr>{field_data}};
segment->LoadFieldData(RowFieldID, field_data_info);
field_data = std::make_shared<milvus::FieldData<int64_t>>(DataType::INT64);
field_data->FillFieldData(data_set.timestamps_.data(), row_count);
field_data_info =
FieldDataInfo{TimestampFieldID.get(),
row_count,
std::vector<milvus::FieldDataPtr>{field_data}};
segment->LoadFieldData(TimestampFieldID, field_data_info);
}
int
GetSearchResultBound(const SearchResult& search_result) {
int i = 0;
for (; i < search_result.seg_offsets_.size(); i++) {
if (search_result.seg_offsets_[i] == INVALID_SEG_OFFSET)
break;
}
return i - 1;
}
void
CheckGroupBySearchResult(const SearchResult& search_result,
int topK,
int nq,
bool strict) {
int total = topK * nq;
ASSERT_EQ(search_result.group_by_values_.value().size(), total);
ASSERT_EQ(search_result.seg_offsets_.size(), total);
ASSERT_EQ(search_result.distances_.size(), total);
ASSERT_TRUE(search_result.seg_offsets_[0] != INVALID_SEG_OFFSET);
int res_bound = GetSearchResultBound(search_result);
ASSERT_TRUE(res_bound > 0);
if (strict) {
ASSERT_TRUE(res_bound == total - 1);
} else {
ASSERT_TRUE(res_bound == total - 1 ||
search_result.seg_offsets_[res_bound + 1] ==
INVALID_SEG_OFFSET);
}
}
TEST(GroupBY, SealedIndex) {
using namespace milvus;
using namespace milvus::query;
using namespace milvus::segcore;
//0. prepare schema
int dim = 64;
auto schema = std::make_shared<Schema>();
auto vec_fid = schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, dim, knowhere::metric::L2);
auto int8_fid = schema->AddDebugField("int8", DataType::INT8);
auto int16_fid = schema->AddDebugField("int16", DataType::INT16);
auto int32_fid = schema->AddDebugField("int32", DataType::INT32);
auto int64_fid = schema->AddDebugField("int64", DataType::INT64);
auto str_fid = schema->AddDebugField("string1", DataType::VARCHAR);
auto bool_fid = schema->AddDebugField("bool", DataType::BOOL);
schema->set_primary_field_id(str_fid);
auto segment = CreateSealedSegment(schema);
size_t N = 100;
//2. load raw data
auto raw_data = DataGen(schema, N);
auto fields = schema->get_fields();
for (auto field_data : raw_data.raw_->fields_data()) {
int64_t field_id = field_data.field_id();
auto info = FieldDataInfo(field_data.field_id(), N);
auto field_meta = fields.at(FieldId(field_id));
info.channel->push(
CreateFieldDataFromDataArray(N, &field_data, field_meta));
info.channel->close();
segment->LoadFieldData(FieldId(field_id), info);
}
prepareSegmentSystemFieldData(segment, N, raw_data);
//3. load index
auto vector_data = raw_data.get_col<float>(vec_fid);
auto indexing = GenVecIndexing(
N, dim, vector_data.data(), knowhere::IndexEnum::INDEX_HNSW);
LoadIndexInfo load_index_info;
load_index_info.field_id = vec_fid.get();
load_index_info.index = std::move(indexing);
load_index_info.index_params[METRICS_TYPE] = knowhere::metric::L2;
segment->LoadIndex(load_index_info);
int topK = 100;
//4. search group by int8
{
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 101
>
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 num_queries = 1;
auto seed = 1024;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
auto search_result =
segment->Search(plan.get(), ph_group.get(), 1L << 63);
CheckGroupBySearchResult(*search_result, topK, num_queries, false);
auto& group_by_values = search_result->group_by_values_.value();
int size = group_by_values.size();
std::unordered_set<int8_t> i8_set;
float lastDistance = 0.0;
for (size_t i = 0; i < size; i++) {
if (std::holds_alternative<int8_t>(group_by_values[i])) {
int8_t g_val = std::get<int8_t>(group_by_values[i]);
ASSERT_FALSE(i8_set.count(g_val) >
0); //no repetition on groupBy field
i8_set.insert(g_val);
auto distance = search_result->distances_.at(i);
ASSERT_TRUE(
lastDistance <=
distance); //distance should be decreased as metrics_type is L2
lastDistance = distance;
} else {
//check padding
ASSERT_EQ(search_result->seg_offsets_[i], INVALID_SEG_OFFSET);
ASSERT_EQ(search_result->distances_[i], 0.0);
}
}
}
//4. search group by int16
{
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 102
>
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 num_queries = 1;
auto seed = 1024;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
auto search_result =
segment->Search(plan.get(), ph_group.get(), 1L << 63);
CheckGroupBySearchResult(*search_result, topK, num_queries, false);
auto& group_by_values = search_result->group_by_values_.value();
int size = group_by_values.size();
std::unordered_set<int16_t> i16_set;
float lastDistance = 0.0;
for (size_t i = 0; i < size; i++) {
if (std::holds_alternative<int16_t>(group_by_values[i])) {
int16_t g_val = std::get<int16_t>(group_by_values[i]);
ASSERT_FALSE(i16_set.count(g_val) >
0); //no repetition on groupBy field
i16_set.insert(g_val);
auto distance = search_result->distances_.at(i);
ASSERT_TRUE(
lastDistance <=
distance); //distance should be decreased as metrics_type is L2
lastDistance = distance;
} else {
//check padding
ASSERT_EQ(search_result->seg_offsets_[i], INVALID_SEG_OFFSET);
ASSERT_EQ(search_result->distances_[i], 0.0);
}
}
}
//4. search group by int32
{
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 103
>
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 num_queries = 1;
auto seed = 1024;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
auto search_result =
segment->Search(plan.get(), ph_group.get(), 1L << 63);
CheckGroupBySearchResult(*search_result, topK, num_queries, false);
auto& group_by_values = search_result->group_by_values_.value();
int size = group_by_values.size();
std::unordered_set<int32_t> i32_set;
float lastDistance = 0.0;
for (size_t i = 0; i < size; i++) {
if (std::holds_alternative<int32_t>(group_by_values[i])) {
int16_t g_val = std::get<int32_t>(group_by_values[i]);
ASSERT_FALSE(i32_set.count(g_val) >
0); //no repetition on groupBy field
i32_set.insert(g_val);
auto distance = search_result->distances_.at(i);
ASSERT_TRUE(
lastDistance <=
distance); //distance should be decreased as metrics_type is L2
lastDistance = distance;
} else {
//check padding
ASSERT_EQ(search_result->seg_offsets_[i], INVALID_SEG_OFFSET);
ASSERT_EQ(search_result->distances_[i], 0.0);
}
}
}
//4. search group by int64
{
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 104
>
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 num_queries = 1;
auto seed = 1024;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
auto search_result =
segment->Search(plan.get(), ph_group.get(), 1L << 63);
CheckGroupBySearchResult(*search_result, topK, num_queries, false);
auto& group_by_values = search_result->group_by_values_.value();
int size = group_by_values.size();
std::unordered_set<int64_t> i64_set;
float lastDistance = 0.0;
for (size_t i = 0; i < size; i++) {
if (std::holds_alternative<int64_t>(group_by_values[i])) {
int16_t g_val = std::get<int64_t>(group_by_values[i]);
ASSERT_FALSE(i64_set.count(g_val) >
0); //no repetition on groupBy field
i64_set.insert(g_val);
auto distance = search_result->distances_.at(i);
ASSERT_TRUE(
lastDistance <=
distance); //distance should be decreased as metrics_type is L2
lastDistance = distance;
} else {
//check padding
ASSERT_EQ(search_result->seg_offsets_[i], INVALID_SEG_OFFSET);
ASSERT_EQ(search_result->distances_[i], 0.0);
}
}
}
//4. search group by string
{
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 105
>
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 num_queries = 1;
auto seed = 1024;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
auto search_result =
segment->Search(plan.get(), ph_group.get(), 1L << 63);
CheckGroupBySearchResult(*search_result, topK, num_queries, false);
auto& group_by_values = search_result->group_by_values_.value();
int size = group_by_values.size();
std::unordered_set<std::string> strs_set;
float lastDistance = 0.0;
for (size_t i = 0; i < size; i++) {
if (std::holds_alternative<std::string>(group_by_values[i])) {
std::string g_val =
std::move(std::get<std::string>(group_by_values[i]));
ASSERT_FALSE(strs_set.count(g_val) >
0); //no repetition on groupBy field
strs_set.insert(g_val);
auto distance = search_result->distances_.at(i);
ASSERT_TRUE(
lastDistance <=
distance); //distance should be decreased as metrics_type is L2
lastDistance = distance;
} else {
//check padding
ASSERT_EQ(search_result->seg_offsets_[i], INVALID_SEG_OFFSET);
ASSERT_EQ(search_result->distances_[i], 0.0);
}
}
}
//4. search group by bool
{
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 106
>
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 num_queries = 1;
auto seed = 1024;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
auto search_result =
segment->Search(plan.get(), ph_group.get(), 1L << 63);
CheckGroupBySearchResult(*search_result, topK, num_queries, false);
auto& group_by_values = search_result->group_by_values_.value();
int size = group_by_values.size();
std::unordered_set<bool> bools_set;
int boolValCount = 0;
float lastDistance = 0.0;
for (size_t i = 0; i < size; i++) {
if (std::holds_alternative<bool>(group_by_values[i])) {
bool g_val = std::get<bool>(group_by_values[i]);
ASSERT_FALSE(bools_set.count(g_val) >
0); //no repetition on groupBy field
bools_set.insert(g_val);
boolValCount += 1;
auto distance = search_result->distances_.at(i);
ASSERT_TRUE(
lastDistance <=
distance); //distance should be decreased as metrics_type is L2
lastDistance = distance;
} else {
//check padding
ASSERT_EQ(search_result->seg_offsets_[i], INVALID_SEG_OFFSET);
ASSERT_EQ(search_result->distances_[i], 0.0);
}
ASSERT_TRUE(boolValCount <= 2); //bool values cannot exceed two
}
}
}
TEST(GroupBY, SealedData) {
using namespace milvus;
using namespace milvus::query;
using namespace milvus::segcore;
//0. prepare schema
int dim = 64;
auto schema = std::make_shared<Schema>();
auto vec_fid = schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, dim, knowhere::metric::L2);
auto int8_fid = schema->AddDebugField("int8", DataType::INT8);
auto int16_fid = schema->AddDebugField("int16", DataType::INT16);
auto int32_fid = schema->AddDebugField("int32", DataType::INT32);
auto int64_fid = schema->AddDebugField("int64", DataType::INT64);
auto str_fid = schema->AddDebugField("string1", DataType::VARCHAR);
auto bool_fid = schema->AddDebugField("bool", DataType::BOOL);
schema->set_primary_field_id(str_fid);
auto segment = CreateSealedSegment(schema);
size_t N = 100;
//2. load raw data
auto raw_data = DataGen(schema, N);
auto fields = schema->get_fields();
for (auto field_data : raw_data.raw_->fields_data()) {
int64_t field_id = field_data.field_id();
auto info = FieldDataInfo(field_data.field_id(), N);
auto field_meta = fields.at(FieldId(field_id));
info.channel->push(
CreateFieldDataFromDataArray(N, &field_data, field_meta));
info.channel->close();
segment->LoadFieldData(FieldId(field_id), info);
}
prepareSegmentSystemFieldData(segment, N, raw_data);
int topK = 100;
//3. search group by int8
{
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 101
>
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 num_queries = 1;
auto seed = 1024;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
auto search_result =
segment->Search(plan.get(), ph_group.get(), 1L << 63);
CheckGroupBySearchResult(*search_result, topK, num_queries, false);
auto& group_by_values = search_result->group_by_values_.value();
int size = group_by_values.size();
std::unordered_set<int8_t> i8_set;
float lastDistance = 0.0;
for (size_t i = 0; i < size; i++) {
if (std::holds_alternative<int8_t>(group_by_values[i])) {
int8_t g_val = std::get<int8_t>(group_by_values[i]);
ASSERT_FALSE(i8_set.count(g_val) >
0); //no repetition on groupBy field
i8_set.insert(g_val);
auto distance = search_result->distances_.at(i);
ASSERT_TRUE(
lastDistance <=
distance); //distance should be decreased as metrics_type is L2
lastDistance = distance;
} else {
//check padding
ASSERT_EQ(search_result->seg_offsets_[i], INVALID_SEG_OFFSET);
ASSERT_EQ(search_result->distances_[i], 0.0);
}
}
}
}
TEST(GroupBY, Reduce) {
using namespace milvus;
using namespace milvus::query;
using namespace milvus::segcore;
//0. prepare schema
int dim = 64;
auto schema = std::make_shared<Schema>();
auto vec_fid = schema->AddDebugField(
"fakevec", DataType::VECTOR_FLOAT, dim, knowhere::metric::L2);
auto int64_fid = schema->AddDebugField("int64", DataType::INT64);
auto fp16_fid = schema->AddDebugField(
"fakevec_fp16", DataType::VECTOR_FLOAT16, dim, knowhere::metric::L2);
auto bf16_fid = schema->AddDebugField(
"fakevec_bf16", DataType::VECTOR_BFLOAT16, dim, knowhere::metric::L2);
schema->set_primary_field_id(int64_fid);
auto segment1 = CreateSealedSegment(schema);
auto segment2 = CreateSealedSegment(schema);
//1. load raw data
size_t N = 100;
uint64_t seed = 512;
uint64_t ts_offset = 0;
int repeat_count_1 = 2;
int repeat_count_2 = 5;
auto raw_data1 = DataGen(schema, N, seed, ts_offset, repeat_count_1);
auto raw_data2 = DataGen(schema, N, seed, ts_offset, repeat_count_2);
auto fields = schema->get_fields();
//load segment1 raw data
for (auto field_data : raw_data1.raw_->fields_data()) {
int64_t field_id = field_data.field_id();
auto info = FieldDataInfo(field_data.field_id(), N);
auto field_meta = fields.at(FieldId(field_id));
info.channel->push(
CreateFieldDataFromDataArray(N, &field_data, field_meta));
info.channel->close();
segment1->LoadFieldData(FieldId(field_id), info);
}
prepareSegmentSystemFieldData(segment1, N, raw_data1);
//load segment2 raw data
for (auto field_data : raw_data2.raw_->fields_data()) {
int64_t field_id = field_data.field_id();
auto info = FieldDataInfo(field_data.field_id(), N);
auto field_meta = fields.at(FieldId(field_id));
info.channel->push(
CreateFieldDataFromDataArray(N, &field_data, field_meta));
info.channel->close();
segment2->LoadFieldData(FieldId(field_id), info);
}
prepareSegmentSystemFieldData(segment2, N, raw_data2);
//3. load index
auto vector_data_1 = raw_data1.get_col<float>(vec_fid);
auto indexing_1 = GenVecIndexing(
N, dim, vector_data_1.data(), knowhere::IndexEnum::INDEX_HNSW);
LoadIndexInfo load_index_info_1;
load_index_info_1.field_id = vec_fid.get();
load_index_info_1.index = std::move(indexing_1);
load_index_info_1.index_params[METRICS_TYPE] = knowhere::metric::L2;
segment1->LoadIndex(load_index_info_1);
auto vector_data_2 = raw_data2.get_col<float>(vec_fid);
auto indexing_2 = GenVecIndexing(
N, dim, vector_data_2.data(), knowhere::IndexEnum::INDEX_HNSW);
LoadIndexInfo load_index_info_2;
load_index_info_2.field_id = vec_fid.get();
load_index_info_2.index = std::move(indexing_2);
load_index_info_2.index_params[METRICS_TYPE] = knowhere::metric::L2;
segment2->LoadIndex(load_index_info_2);
//4. search group by respectively
const char* raw_plan = R"(vector_anns: <
field_id: 100
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 101
>
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 num_queries = 10;
auto topK = 100;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
CPlaceholderGroup c_ph_group = ph_group.release();
CSearchPlan c_plan = plan.release();
CSegmentInterface c_segment_1 = segment1.release();
CSegmentInterface c_segment_2 = segment2.release();
CSearchResult c_search_res_1;
CSearchResult c_search_res_2;
auto status =
Search({}, c_segment_1, c_plan, c_ph_group, 1L << 63, &c_search_res_1);
ASSERT_EQ(status.error_code, Success);
status =
Search({}, c_segment_2, c_plan, c_ph_group, 1L << 63, &c_search_res_2);
ASSERT_EQ(status.error_code, Success);
std::vector<CSearchResult> results;
results.push_back(c_search_res_1);
results.push_back(c_search_res_2);
auto slice_nqs = std::vector<int64_t>{num_queries / 2, num_queries / 2};
auto slice_topKs = std::vector<int64_t>{topK / 2, topK};
CSearchResultDataBlobs cSearchResultData;
status = ReduceSearchResultsAndFillData(&cSearchResultData,
c_plan,
results.data(),
results.size(),
slice_nqs.data(),
slice_topKs.data(),
slice_nqs.size());
CheckSearchResultDuplicate(results);
DeleteSearchResult(c_search_res_1);
DeleteSearchResult(c_search_res_2);
DeleteSearchResultDataBlobs(cSearchResultData);
DeleteSearchPlan(c_plan);
DeletePlaceholderGroup(c_ph_group);
DeleteSegment(c_segment_1);
DeleteSegment(c_segment_2);
}
TEST(GroupBY, GrowingRawData) {
//0. set up growing segment
int dim = 128;
uint64_t seed = 512;
auto schema = std::make_shared<Schema>();
auto metric_type = knowhere::metric::L2;
auto int64_field_id = schema->AddDebugField("int64", DataType::INT64);
auto int32_field_id = schema->AddDebugField("int32", DataType::INT32);
auto vec_field_id = schema->AddDebugField(
"embeddings", DataType::VECTOR_FLOAT, 128, metric_type);
schema->set_primary_field_id(int64_field_id);
auto config = SegcoreConfig::default_config();
config.set_chunk_rows(128);
config.set_enable_interim_segment_index(
false); //no growing index, test brute force
auto segment_growing = CreateGrowingSegment(schema, nullptr, 1, config);
auto segment_growing_impl =
dynamic_cast<SegmentGrowingImpl*>(segment_growing.get());
//1. prepare raw data in growing segment
int64_t rows_per_batch = 512;
int n_batch = 3;
for (int i = 0; i < n_batch; i++) {
auto data_set = DataGen(schema, rows_per_batch);
auto offset = segment_growing_impl->PreInsert(rows_per_batch);
segment_growing_impl->Insert(offset,
rows_per_batch,
data_set.row_ids_.data(),
data_set.timestamps_.data(),
data_set.raw_);
}
//2. Search group by
const char* raw_plan = R"(vector_anns: <
field_id: 102
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 101
>
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 num_queries = 10;
auto topK = 100;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
auto search_result =
segment_growing_impl->Search(plan.get(), ph_group.get(), 1L << 63);
CheckGroupBySearchResult(*search_result, topK, num_queries, true);
auto& group_by_values = search_result->group_by_values_.value();
int idx = 0;
for (int i = 0; i < num_queries; i++) {
std::unordered_set<int32_t> i32_set;
float lastDistance = 0.0;
for (int j = 0; j < topK; j++) {
if (std::holds_alternative<int32_t>(group_by_values[idx])) {
int32_t g_val = std::get<int32_t>(group_by_values[idx]);
ASSERT_FALSE(i32_set.count(g_val) >
0); //no repetition on groupBy field
i32_set.insert(g_val);
auto distance = search_result->distances_.at(idx);
ASSERT_TRUE(
lastDistance <=
distance); //distance should be decreased as metrics_type is L2
lastDistance = distance;
} else {
//check padding
ASSERT_EQ(search_result->seg_offsets_[idx], INVALID_SEG_OFFSET);
ASSERT_EQ(search_result->distances_[idx], 0.0);
}
idx++;
}
}
}
TEST(GroupBY, GrowingIndex) {
//0. set up growing segment
int dim = 128;
uint64_t seed = 512;
auto schema = std::make_shared<Schema>();
auto metric_type = knowhere::metric::L2;
auto int64_field_id = schema->AddDebugField("int64", DataType::INT64);
auto int32_field_id = schema->AddDebugField("int32", DataType::INT32);
auto vec_field_id = schema->AddDebugField(
"embeddings", DataType::VECTOR_FLOAT, 128, metric_type);
schema->set_primary_field_id(int64_field_id);
std::map<std::string, std::string> index_params = {
{"index_type", "IVF_FLAT"},
{"metric_type", metric_type},
{"nlist", "128"}};
std::map<std::string, std::string> type_params = {{"dim", "128"}};
FieldIndexMeta fieldIndexMeta(
vec_field_id, std::move(index_params), std::move(type_params));
std::map<FieldId, FieldIndexMeta> fieldMap = {
{vec_field_id, fieldIndexMeta}};
IndexMetaPtr metaPtr =
std::make_shared<CollectionIndexMeta>(10000, std::move(fieldMap));
auto config = SegcoreConfig::default_config();
config.set_chunk_rows(128);
config.set_enable_interim_segment_index(
true); //no growing index, test growing inter index
config.set_nlist(128);
auto segment_growing = CreateGrowingSegment(schema, metaPtr, 1, config);
auto segment_growing_impl =
dynamic_cast<SegmentGrowingImpl*>(segment_growing.get());
//1. prepare raw data in growing segment
int64_t rows_per_batch = 1024;
int n_batch = 10;
for (int i = 0; i < n_batch; i++) {
auto data_set = DataGen(schema, rows_per_batch);
auto offset = segment_growing_impl->PreInsert(rows_per_batch);
segment_growing_impl->Insert(offset,
rows_per_batch,
data_set.row_ids_.data(),
data_set.timestamps_.data(),
data_set.raw_);
}
//2. Search group by int32
const char* raw_plan = R"(vector_anns: <
field_id: 102
query_info: <
topk: 100
metric_type: "L2"
search_params: "{\"ef\": 10}"
group_by_field_id: 101
>
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 num_queries = 10;
auto topK = 100;
auto ph_group_raw = CreatePlaceholderGroup(num_queries, dim, seed);
auto ph_group =
ParsePlaceholderGroup(plan.get(), ph_group_raw.SerializeAsString());
auto search_result =
segment_growing_impl->Search(plan.get(), ph_group.get(), 1L << 63);
CheckGroupBySearchResult(*search_result, topK, num_queries, true);
auto& group_by_values = search_result->group_by_values_.value();
int idx = 0;
for (int i = 0; i < num_queries; i++) {
std::unordered_set<int32_t> i32_set;
float lastDistance = 0.0;
for (int j = 0; j < topK; j++) {
if (std::holds_alternative<int32_t>(group_by_values[idx])) {
int32_t g_val = std::get<int32_t>(group_by_values[idx]);
ASSERT_FALSE(i32_set.count(g_val) >
0); //no repetition on groupBy field
i32_set.insert(g_val);
auto distance = search_result->distances_.at(idx);
ASSERT_TRUE(
lastDistance <=
distance); //distance should be decreased as metrics_type is L2
lastDistance = distance;
} else {
//check padding
ASSERT_EQ(search_result->seg_offsets_[idx], INVALID_SEG_OFFSET);
ASSERT_EQ(search_result->distances_[idx], 0.0);
}
idx++;
}
}
}
Reference in New Issue View Git Blame Copy Permalink