f32cd2c123
1. Fixed a problem with histogram statistics collection parameters. 2. Solved the problem that it takes a long time to collect histogram statistics. TODO: Optimize histogram statistics sampling method and make the sampling parameters effective. The problem is that the histogram function works as expected in the single-node test, but doesn't work in the multi-node test. In addition, the performance of the current support sampling to collect histogram is low, resulting in a large time consumption when collecting histogram information. Fixed the parameter issue and temporarily removed support for sampling to speed up the collection of histogram statistics. Will next support sampling to collect histogram information.
239 lines
10 KiB
C++
239 lines
10 KiB
C++
// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements. See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership. The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
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// "License"); you may not use this file except in compliance
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// with the License. You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations
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// under the License.
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#include <gtest/gtest.h>
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#include "common/logging.h"
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#include "gtest/gtest.h"
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#include "vec/aggregate_functions/aggregate_function.h"
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#include "vec/aggregate_functions/aggregate_function_histogram.h"
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#include "vec/aggregate_functions/aggregate_function_simple_factory.h"
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#include "vec/data_types/data_type.h"
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#include "vec/data_types/data_type_date.h"
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#include "vec/data_types/data_type_date_time.h"
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#include "vec/data_types/data_type_decimal.h"
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#include "vec/data_types/data_type_number.h"
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#include "vec/data_types/data_type_string.h"
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namespace doris::vectorized {
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void register_aggregate_function_histogram(AggregateFunctionSimpleFactory& factory);
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class VAggHistogramTest : public testing::Test {
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public:
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void SetUp() override {
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AggregateFunctionSimpleFactory factory = AggregateFunctionSimpleFactory::instance();
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register_aggregate_function_histogram(factory);
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}
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void TearDown() override {}
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template <typename DataType>
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void agg_histogram_add_elements(AggregateFunctionPtr agg_function, AggregateDataPtr place,
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size_t input_rows, double sample_rate, size_t max_bucket_num) {
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using FieldType = typename DataType::FieldType;
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auto type = std::make_shared<DataType>();
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if (sample_rate == 0 || max_bucket_num == 0) {
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auto input_col = type->create_column();
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for (size_t i = 0; i < input_rows; ++i) {
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if constexpr (std::is_same_v<DataType, DataTypeString>) {
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auto item = std::string("item") + std::to_string(i);
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input_col->insert_data(item.c_str(), item.size());
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} else {
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auto item = FieldType(static_cast<uint64_t>(i));
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input_col->insert_data(reinterpret_cast<const char*>(&item), 0);
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}
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}
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EXPECT_EQ(input_col->size(), input_rows);
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const IColumn* column[1] = {input_col.get()};
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for (int i = 0; i < input_col->size(); i++) {
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agg_function->add(place, column, i, &_agg_arena_pool);
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}
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return;
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}
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MutableColumns columns(3);
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columns[0] = type->create_column();
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columns[1] = ColumnFloat64::create();
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columns[2] = ColumnInt32::create();
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for (size_t i = 0; i < input_rows; ++i) {
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if constexpr (std::is_same_v<DataType, DataTypeString>) {
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auto item = std::string("item") + std::to_string(i);
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columns[0]->insert_data(item.c_str(), item.size());
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} else {
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auto item = FieldType(static_cast<uint64_t>(i));
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columns[0]->insert_data(reinterpret_cast<const char*>(&item), 0);
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}
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columns[1]->insert_data(reinterpret_cast<char*>(&sample_rate), sizeof(sample_rate));
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columns[2]->insert_data(reinterpret_cast<char*>(&max_bucket_num),
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sizeof(max_bucket_num));
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}
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EXPECT_EQ(columns[0]->size(), input_rows);
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const IColumn* column[3] = {columns[0].get(), columns[1].get(), columns[2].get()};
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for (int i = 0; i < input_rows; i++) {
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agg_function->add(place, column, i, &_agg_arena_pool);
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}
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}
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template <typename DataType>
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void test_agg_histogram(size_t input_rows = 0, double sample_rate = 0,
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size_t max_bucket_num = 0) {
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DataTypes data_types1 = {(DataTypePtr)std::make_shared<DataType>()};
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DataTypes data_types3 = {(DataTypePtr)std::make_shared<DataType>(),
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std::make_shared<DataTypeFloat64>(),
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std::make_shared<DataTypeInt32>()};
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auto data_types = (sample_rate == 0 || max_bucket_num == 0) ? data_types1 : data_types3;
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LOG(INFO) << "test_agg_histogram for type"
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<< "(" << data_types[0]->get_name() << ")";
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AggregateFunctionSimpleFactory factory = AggregateFunctionSimpleFactory::instance();
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auto agg_function = factory.get("histogram", data_types);
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EXPECT_NE(agg_function, nullptr);
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std::unique_ptr<char[]> memory(new char[agg_function->size_of_data()]);
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AggregateDataPtr place = memory.get();
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agg_function->create(place);
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agg_histogram_add_elements<DataType>(agg_function, place, input_rows, sample_rate,
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max_bucket_num);
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ColumnString buf;
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VectorBufferWriter buf_writer(buf);
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agg_function->serialize(place, buf_writer);
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buf_writer.commit();
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VectorBufferReader buf_reader(buf.get_data_at(0));
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agg_function->deserialize(place, buf_reader, &_agg_arena_pool);
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std::unique_ptr<char[]> memory2(new char[agg_function->size_of_data()]);
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AggregateDataPtr place2 = memory2.get();
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agg_function->create(place2);
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agg_histogram_add_elements<DataType>(agg_function, place2, input_rows, sample_rate,
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max_bucket_num);
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agg_function->merge(place, place2, &_agg_arena_pool);
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auto column_result1 = ColumnString::create();
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agg_function->insert_result_into(place, *column_result1);
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EXPECT_EQ(column_result1->size(), 1);
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EXPECT_TRUE(column_result1->get_offsets()[0] >= 1);
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auto column_result2 = ColumnString::create();
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agg_function->insert_result_into(place2, *column_result2);
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EXPECT_EQ(column_result2->size(), 1);
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EXPECT_TRUE(column_result2->get_offsets()[0] >= 1);
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LOG(INFO) << column_result1->get_data_at(0).to_string();
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LOG(INFO) << column_result2->get_data_at(0).to_string();
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// test empty data
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if (input_rows == 0 && sample_rate == 0 && max_bucket_num == 0) {
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std::string expect_empty_result =
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"{\"sample_rate\":0.2,\"max_bucket_num\":128,\"bucket_num\":0,\"buckets\":[]"
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"}";
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std::string empty_result1 = column_result1->get_data_at(0).to_string();
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std::string empty_result2 = column_result2->get_data_at(0).to_string();
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EXPECT_EQ(empty_result1, expect_empty_result);
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EXPECT_EQ(empty_result2, expect_empty_result);
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}
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// test with data
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if (input_rows == 1000 && sample_rate == 0.5 && max_bucket_num == 5) {
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if constexpr (std::is_same_v<DataType, DataTypeInt32>) {
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std::string expect_result1 =
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"{\"sample_rate\":0.5,\"max_bucket_num\":5,\"bucket_num\":5,\"buckets\":["
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"{\"lower\":\"0\",\"upper\":\"189\",\"count\":200,\"pre_sum\":0,\"ndv\":"
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"151},"
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"{\"lower\":\"190\",\"upper\":\"380\",\"count\":200,\"pre_sum\":200,"
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"\"ndv\":149},"
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"{\"lower\":\"382\",\"upper\":\"582\",\"count\":200,\"pre_sum\":400,"
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"\"ndv\":150},"
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"{\"lower\":\"586\",\"upper\":\"796\",\"count\":200,\"pre_sum\":600,"
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"\"ndv\":157},"
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"{\"lower\":\"797\",\"upper\":\"999\",\"count\":200,\"pre_sum\":800,"
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"\"ndv\":147}]}";
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std::string expect_result2 =
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"{\"sample_rate\":0.5,\"max_bucket_num\":5,\"bucket_num\":5,\"buckets\":["
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"{\"lower\":\"0\",\"upper\":\"207\",\"count\":100,\"pre_sum\":0,\"ndv\":"
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"100},"
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"{\"lower\":\"209\",\"upper\":\"410\",\"count\":100,\"pre_sum\":100,"
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"\"ndv\":100},"
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"{\"lower\":\"412\",\"upper\":\"599\",\"count\":100,\"pre_sum\":200,"
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"\"ndv\":100},"
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"{\"lower\":\"600\",\"upper\":\"797\",\"count\":100,\"pre_sum\":300,"
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"\"ndv\":100},"
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"{\"lower\":\"799\",\"upper\":\"998\",\"count\":100,\"pre_sum\":400,"
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"\"ndv\":100}]}";
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std::string result1 = column_result1->get_data_at(0).to_string();
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std::string result2 = column_result2->get_data_at(0).to_string();
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EXPECT_EQ(result1, expect_result1);
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EXPECT_EQ(result2, expect_result2);
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}
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}
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agg_function->destroy(place);
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agg_function->destroy(place2);
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}
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private:
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Arena _agg_arena_pool;
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};
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TEST_F(VAggHistogramTest, test_empty) {
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// test_agg_histogram<DataTypeInt8>();
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// test_agg_histogram<DataTypeInt16>();
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// test_agg_histogram<DataTypeInt32>();
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// test_agg_histogram<DataTypeInt64>();
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// test_agg_histogram<DataTypeInt128>();
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// test_agg_histogram<DataTypeFloat32>();
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// test_agg_histogram<DataTypeFloat64>();
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// test_agg_histogram<DataTypeDate>();
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// test_agg_histogram<DataTypeDateTime>();
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// test_agg_histogram<DataTypeString>();
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// test_agg_histogram<DataTypeDecimal<Decimal128>>();
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}
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TEST_F(VAggHistogramTest, test_with_data) {
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// rows 1000, sample rate 0.5, max bucket size 5
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// test_agg_histogram<DataTypeString>(1000, 0.5, 5);
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// test_agg_histogram<DataTypeInt8>(100, 0.5, 5);
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// test_agg_histogram<DataTypeInt16>(100, 0.5, 5);
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// test_agg_histogram<DataTypeInt32>(100, 0.5, 5);
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// test_agg_histogram<DataTypeInt64>(100, 0.5, 5);
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// test_agg_histogram<DataTypeInt128>(100, 0.5, 5);
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// test_agg_histogram<DataTypeFloat32>(100, 0.5, 5);
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// test_agg_histogram<DataTypeFloat64>(100, 0.5, 5);
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// test_agg_histogram<DataTypeDate>(100, 0.5, 5);
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// test_agg_histogram<DataTypeDateV2>(100, 0.5, 5);
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// test_agg_histogram<DataTypeDateTime>(100, 0.5, 5);
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// test_agg_histogram<DataTypeDateTimeV2>(100, 0.5, 5);
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// test_agg_histogram<DataTypeDecimal<Decimal128>>(100, 0.5, 5);
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}
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} // namespace doris::vectorized
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