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milvus/internal/core/unittest/test_group_by.cpp
MrPresent-Han 9e2e7157e9
feat: support search_group_by for milvus(#25324) (#28983) 
related: #25324

Search GroupBy function, used to aggregate result entities based on a
specific scalar column.
several points to mention:

1. Temporarliy, the whole groupby is implemented separated from
iterative expr framework **for the first period**
2. In the long term, the groupBy operation will be incorporated into the
iterative expr framework:https://github.com/milvus-io/milvus/pull/28166
3. This pr includes some unrelated mocked interface regarding alterIndex
due to some unworth-to-mention reasons. All these un-associated content
will be removed before the final pr is merged. This version of pr is
only for review
4. All other related details were commented in the files comparison

Signed-off-by: MrPresent-Han <chun.han@zilliz.com>
2024-01-05 15:50:47 +08:00

480 lines
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//
// Created by zilliz on 2023/12/1.
//
#include <gtest/gtest.h>
#include "common/Schema.h"
#include "segcore/SegmentSealedImpl.h"
#include "test_utils/DataGen.h"
#include "query/Plan.h"
#include "segcore/segment_c.h"
#include "segcore/reduce_c.h"
#include "test_utils/c_api_test_utils.h"
#include "segcore/plan_c.h"
using namespace milvus;
using namespace milvus::segcore;
using namespace milvus::query;
using namespace milvus::storage;
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);
}
TEST(GroupBY, Normal2){
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);
//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());
auto& group_by_values = search_result->group_by_values_;
ASSERT_EQ(search_result->group_by_values_.size(), search_result->seg_offsets_.size());
ASSERT_EQ(search_result->distances_.size(), search_result->seg_offsets_.size());
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());
auto& group_by_values = search_result->group_by_values_;
ASSERT_EQ(search_result->group_by_values_.size(), search_result->seg_offsets_.size());
ASSERT_EQ(search_result->distances_.size(), search_result->seg_offsets_.size());
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());
auto& group_by_values = search_result->group_by_values_;
ASSERT_EQ(search_result->group_by_values_.size(), search_result->seg_offsets_.size());
ASSERT_EQ(search_result->distances_.size(), search_result->seg_offsets_.size());
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());
auto& group_by_values = search_result->group_by_values_;
ASSERT_EQ(search_result->group_by_values_.size(), search_result->seg_offsets_.size());
ASSERT_EQ(search_result->distances_.size(), search_result->seg_offsets_.size());
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());
auto& group_by_values = search_result->group_by_values_;
ASSERT_EQ(search_result->group_by_values_.size(), search_result->seg_offsets_.size());
ASSERT_EQ(search_result->distances_.size(), search_result->seg_offsets_.size());
int size = group_by_values.size();
std::unordered_set<std::string_view> strs_set;
float lastDistance = 0.0;
for(size_t i = 0; i < size; i++){
if(std::holds_alternative<std::string_view>(group_by_values[i])){
std::string_view g_val = std::get<std::string_view>(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());
auto& group_by_values = search_result->group_by_values_;
ASSERT_EQ(search_result->group_by_values_.size(), search_result->seg_offsets_.size());
ASSERT_EQ(search_result->distances_.size(), search_result->seg_offsets_.size());
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, 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);
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, {}, &c_search_res_1);
ASSERT_EQ(status.error_code, Success);
status = Search(c_segment_2, c_plan, c_ph_group, {}, &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);
}
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