| // Licensed to the Apache Software Foundation (ASF) under one |
| // or more contributor license agreements. See the NOTICE file |
| // distributed with this work for additional information |
| // regarding copyright ownership. The ASF licenses this file |
| // to you 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 "olap/comparison_predicate.h" |
| |
| #include <google/protobuf/stubs/common.h> |
| #include <gtest/gtest.h> |
| #include <time.h> |
| |
| #include "olap/column_predicate.h" |
| #include "olap/field.h" |
| #include "olap/row_block2.h" |
| #include "olap/wrapper_field.h" |
| #include "runtime/mem_pool.h" |
| #include "runtime/string_value.hpp" |
| #include "runtime/vectorized_row_batch.h" |
| #include "util/logging.h" |
| |
| namespace doris { |
| |
| namespace datetime { |
| |
| static uint24_t to_date_timestamp(const char* date_string) { |
| tm time_tm; |
| strptime(date_string, "%Y-%m-%d", &time_tm); |
| |
| int value = (time_tm.tm_year + 1900) * 16 * 32 + (time_tm.tm_mon + 1) * 32 + time_tm.tm_mday; |
| return uint24_t(value); |
| } |
| |
| static uint64_t to_datetime_timestamp(const std::string& value_string) { |
| tm time_tm; |
| strptime(value_string.c_str(), "%Y-%m-%d %H:%M:%S", &time_tm); |
| |
| uint64_t value = |
| ((time_tm.tm_year + 1900) * 10000L + (time_tm.tm_mon + 1) * 100L + time_tm.tm_mday) * |
| 1000000L + |
| time_tm.tm_hour * 10000L + time_tm.tm_min * 100L + time_tm.tm_sec; |
| |
| return value; |
| } |
| |
| static std::string to_date_string(uint24_t& date_value) { |
| tm time_tm; |
| int value = date_value; |
| memset(&time_tm, 0, sizeof(time_tm)); |
| time_tm.tm_mday = static_cast<int>(value & 31); |
| time_tm.tm_mon = static_cast<int>(value >> 5 & 15) - 1; |
| time_tm.tm_year = static_cast<int>(value >> 9) - 1900; |
| char buf[20] = {'\0'}; |
| strftime(buf, sizeof(buf), "%Y-%m-%d", &time_tm); |
| return std::string(buf); |
| } |
| |
| static std::string to_datetime_string(uint64_t& datetime_value) { |
| tm time_tm; |
| int64_t part1 = (datetime_value / 1000000L); |
| int64_t part2 = (datetime_value - part1 * 1000000L); |
| |
| time_tm.tm_year = static_cast<int>((part1 / 10000L) % 10000) - 1900; |
| time_tm.tm_mon = static_cast<int>((part1 / 100) % 100) - 1; |
| time_tm.tm_mday = static_cast<int>(part1 % 100); |
| |
| time_tm.tm_hour = static_cast<int>((part2 / 10000L) % 10000); |
| time_tm.tm_min = static_cast<int>((part2 / 100) % 100); |
| time_tm.tm_sec = static_cast<int>(part2 % 100); |
| |
| char buf[20] = {'\0'}; |
| strftime(buf, 20, "%Y-%m-%d %H:%M:%S", &time_tm); |
| return std::string(buf); |
| } |
| |
| }; // namespace datetime |
| |
| #define TEST_PREDICATE_DEFINITION(CLASS_NAME) \ |
| class CLASS_NAME : public testing::Test { \ |
| public: \ |
| CLASS_NAME() : _vectorized_batch(NULL) { \ |
| _mem_tracker.reset(new MemTracker(-1)); \ |
| _mem_pool.reset(new MemPool(_mem_tracker.get())); \ |
| } \ |
| ~CLASS_NAME() { \ |
| if (_vectorized_batch != NULL) { \ |
| delete _vectorized_batch; \ |
| } \ |
| } \ |
| void SetTabletSchema(std::string name, const std::string& type, \ |
| const std::string& aggregation, uint32_t length, bool is_allow_null, \ |
| bool is_key, TabletSchema* tablet_schema) { \ |
| TabletSchemaPB tablet_schema_pb; \ |
| static int id = 0; \ |
| ColumnPB* column = tablet_schema_pb.add_column(); \ |
| column->set_unique_id(++id); \ |
| column->set_name(name); \ |
| column->set_type(type); \ |
| column->set_is_key(is_key); \ |
| column->set_is_nullable(is_allow_null); \ |
| column->set_length(length); \ |
| column->set_aggregation(aggregation); \ |
| column->set_precision(1000); \ |
| column->set_frac(1000); \ |
| column->set_is_bf_column(false); \ |
| tablet_schema->init_from_pb(tablet_schema_pb); \ |
| } \ |
| void InitVectorizedBatch(const TabletSchema* tablet_schema, \ |
| const std::vector<uint32_t>& ids, int size) { \ |
| _vectorized_batch = new VectorizedRowBatch(tablet_schema, ids, size); \ |
| _vectorized_batch->set_size(size); \ |
| } \ |
| \ |
| void init_row_block(const TabletSchema* tablet_schema, int size) { \ |
| Schema schema(*tablet_schema); \ |
| _row_block.reset(new RowBlockV2(schema, size)); \ |
| } \ |
| std::shared_ptr<MemTracker> _mem_tracker; \ |
| std::unique_ptr<MemPool> _mem_pool; \ |
| VectorizedRowBatch* _vectorized_batch; \ |
| std::unique_ptr<RowBlockV2> _row_block; \ |
| }; |
| |
| TEST_PREDICATE_DEFINITION(TestEqualPredicate) |
| TEST_PREDICATE_DEFINITION(TestLessPredicate) |
| |
| #define TEST_EQUAL_PREDICATE(TYPE, TYPE_NAME, FIELD_TYPE) \ |
| TEST_F(TestEqualPredicate, TYPE_NAME##_COLUMN) { \ |
| TabletSchema tablet_schema; \ |
| SetTabletSchema(std::string("TYPE_NAME##_COLUMN"), FIELD_TYPE, "REPLACE", 1, false, true, \ |
| &tablet_schema); \ |
| int size = 10; \ |
| std::vector<uint32_t> return_columns; \ |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { \ |
| return_columns.push_back(i); \ |
| } \ |
| InitVectorizedBatch(&tablet_schema, return_columns, size); \ |
| ColumnVector* col_vector = _vectorized_batch->column(0); \ |
| \ |
| /* for no nulls */ \ |
| col_vector->set_no_nulls(true); \ |
| TYPE* col_data = reinterpret_cast<TYPE*>(_mem_pool->allocate(size * sizeof(TYPE))); \ |
| col_vector->set_col_data(col_data); \ |
| for (int i = 0; i < size; ++i) { \ |
| *(col_data + i) = i; \ |
| } \ |
| TYPE value = 5; \ |
| ColumnPredicate* pred = new EqualPredicate<TYPE>(0, value); \ |
| pred->evaluate(_vectorized_batch); \ |
| ASSERT_EQ(_vectorized_batch->size(), 1); \ |
| uint16_t* sel = _vectorized_batch->selected(); \ |
| ASSERT_EQ(*(col_data + sel[0]), 5); \ |
| \ |
| /* for has nulls */ \ |
| col_vector->set_no_nulls(false); \ |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); \ |
| memset(is_null, 0, size); \ |
| col_vector->set_is_null(is_null); \ |
| for (int i = 0; i < size; ++i) { \ |
| if (i % 2 == 0) { \ |
| is_null[i] = true; \ |
| } else { \ |
| *(col_data + i) = i; \ |
| } \ |
| } \ |
| _vectorized_batch->set_size(size); \ |
| _vectorized_batch->set_selected_in_use(false); \ |
| pred->evaluate(_vectorized_batch); \ |
| ASSERT_EQ(_vectorized_batch->size(), 1); \ |
| sel = _vectorized_batch->selected(); \ |
| ASSERT_EQ(*(col_data + sel[0]), 5); \ |
| delete pred; \ |
| } |
| |
| TEST_EQUAL_PREDICATE(int8_t, TINYINT, "TINYINT") |
| TEST_EQUAL_PREDICATE(int16_t, SMALLINT, "SMALLINT") |
| TEST_EQUAL_PREDICATE(int32_t, INT, "INT") |
| TEST_EQUAL_PREDICATE(int64_t, BIGINT, "BIGINT") |
| TEST_EQUAL_PREDICATE(int128_t, LARGEINT, "LARGEINT") |
| |
| TEST_F(TestEqualPredicate, FLOAT_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("FLOAT_COLUMN"), "FLOAT", "REPLACE", 1, true, true, &tablet_schema); |
| int size = 10; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| float value = 5.0; |
| ColumnPredicate* pred = new EqualPredicate<float>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| float* col_data = reinterpret_cast<float*>(_mem_pool->allocate(size * sizeof(float))); |
| col_vector->set_col_data(col_data); |
| for (int i = 0; i < size; ++i) { |
| *(col_data + i) = i; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| uint16_t* sel = _vectorized_batch->selected(); |
| ASSERT_FLOAT_EQ(*(col_data + sel[0]), 5.0); |
| |
| // for ColumnBlock no null |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| *reinterpret_cast<float*>(col_block_view.data()) = i; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_FLOAT_EQ(*(float*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr(), 5.0); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| *(col_data + i) = i; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| sel = _vectorized_batch->selected(); |
| ASSERT_FLOAT_EQ(*(col_data + sel[0]), 5.0); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| *reinterpret_cast<float*>(col_block_view.data()) = i; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_FLOAT_EQ(*(float*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr(), 5.0); |
| |
| delete pred; |
| } |
| |
| TEST_F(TestEqualPredicate, DOUBLE_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("DOUBLE_COLUMN"), "DOUBLE", "REPLACE", 1, true, true, |
| &tablet_schema); |
| int size = 10; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| double value = 5.0; |
| ColumnPredicate* pred = new EqualPredicate<double>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| double* col_data = reinterpret_cast<double*>(_mem_pool->allocate(size * sizeof(double))); |
| col_vector->set_col_data(col_data); |
| for (int i = 0; i < size; ++i) { |
| *(col_data + i) = i; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| uint16_t* sel = _vectorized_batch->selected(); |
| ASSERT_DOUBLE_EQ(*(col_data + sel[0]), 5.0); |
| |
| // for ColumnBlock no null |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| *reinterpret_cast<double*>(col_block_view.data()) = i; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_DOUBLE_EQ(*(double*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr(), 5.0); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| *(col_data + i) = i; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| sel = _vectorized_batch->selected(); |
| ASSERT_DOUBLE_EQ(*(col_data + sel[0]), 5.0); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| *reinterpret_cast<double*>(col_block_view.data()) = i; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_DOUBLE_EQ(*(double*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr(), 5.0); |
| |
| delete pred; |
| } |
| |
| TEST_F(TestEqualPredicate, DECIMAL_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("DECIMAL_COLUMN"), "DECIMAL", "REPLACE", 1, true, true, |
| &tablet_schema); |
| int size = 10; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| decimal12_t value(5, 5); |
| ColumnPredicate* pred = new EqualPredicate<decimal12_t>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| decimal12_t* col_data = |
| reinterpret_cast<decimal12_t*>(_mem_pool->allocate(size * sizeof(decimal12_t))); |
| col_vector->set_col_data(col_data); |
| for (int i = 0; i < size; ++i) { |
| (*(col_data + i)).integer = i; |
| (*(col_data + i)).fraction = i; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| uint16_t* sel = _vectorized_batch->selected(); |
| ASSERT_EQ(*(col_data + sel[0]), value); |
| |
| // for ColumnBlock no null |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| reinterpret_cast<decimal12_t*>(col_block_view.data())->integer = i; |
| reinterpret_cast<decimal12_t*>(col_block_view.data())->fraction = i; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(*(decimal12_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr(), value); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| (*(col_data + i)).integer = i; |
| (*(col_data + i)).fraction = i; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| sel = _vectorized_batch->selected(); |
| ASSERT_EQ(*(col_data + sel[0]), value); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| reinterpret_cast<decimal12_t*>(col_block_view.data())->integer = i; |
| reinterpret_cast<decimal12_t*>(col_block_view.data())->fraction = i; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(*(decimal12_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr(), value); |
| |
| delete pred; |
| } |
| |
| TEST_F(TestEqualPredicate, STRING_COLUMN) { |
| TabletSchema char_tablet_schema; |
| SetTabletSchema(std::string("STRING_COLUMN"), "CHAR", "REPLACE", 5, true, true, |
| &char_tablet_schema); |
| // test WrapperField.from_string() for char type |
| WrapperField* field = WrapperField::create(char_tablet_schema.column(0)); |
| ASSERT_EQ(OLAP_SUCCESS, field->from_string("true")); |
| const std::string tmp = field->to_string(); |
| ASSERT_EQ(5, tmp.size()); |
| ASSERT_EQ('t', tmp[0]); |
| ASSERT_EQ('r', tmp[1]); |
| ASSERT_EQ('u', tmp[2]); |
| ASSERT_EQ('e', tmp[3]); |
| ASSERT_EQ(0, tmp[4]); |
| |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("STRING_COLUMN"), "VARCHAR", "REPLACE", 1, true, true, |
| &tablet_schema); |
| int size = 10; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| |
| StringValue value; |
| const char* value_buffer = "dddd"; |
| value.len = 4; |
| value.ptr = const_cast<char*>(value_buffer); |
| |
| ColumnPredicate* pred = new EqualPredicate<StringValue>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| StringValue* col_data = |
| reinterpret_cast<StringValue*>(_mem_pool->allocate(size * sizeof(StringValue))); |
| col_vector->set_col_data(col_data); |
| char* string_buffer = reinterpret_cast<char*>(_mem_pool->allocate(55)); |
| for (int i = 0; i < size; ++i) { |
| for (int j = 0; j <= i; ++j) { |
| string_buffer[j] = 'a' + i; |
| } |
| (*(col_data + i)).len = i + 1; |
| (*(col_data + i)).ptr = string_buffer; |
| string_buffer += i + 1; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| uint16_t* sel = _vectorized_batch->selected(); |
| ASSERT_EQ(sel[0], 3); |
| ASSERT_EQ(*(col_data + sel[0]), value); |
| |
| // for ColumnBlock no null |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| string_buffer = reinterpret_cast<char*>(_mem_pool->allocate(60)); |
| memset(string_buffer, 0, 60); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| for (int j = 0; j <= i; ++j) { |
| string_buffer[j] = 'a' + i; |
| } |
| reinterpret_cast<StringValue*>(col_block_view.data())->len = i + 1; |
| reinterpret_cast<StringValue*>(col_block_view.data())->ptr = string_buffer; |
| string_buffer += i + 1; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(*(StringValue*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr(), value); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| string_buffer = reinterpret_cast<char*>(_mem_pool->allocate(55)); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| for (int j = 0; j <= i; ++j) { |
| string_buffer[j] = 'a' + i; |
| } |
| (*(col_data + i)).len = i + 1; |
| (*(col_data + i)).ptr = string_buffer; |
| } |
| string_buffer += i + 1; |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| sel = _vectorized_batch->selected(); |
| ASSERT_EQ(*(col_data + sel[0]), value); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| string_buffer = reinterpret_cast<char*>(_mem_pool->allocate(55)); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| for (int j = 0; j <= i; ++j) { |
| string_buffer[j] = 'a' + i; |
| } |
| reinterpret_cast<StringValue*>(col_block_view.data())->len = i + 1; |
| reinterpret_cast<StringValue*>(col_block_view.data())->ptr = string_buffer; |
| string_buffer += i + 1; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(*(StringValue*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr(), value); |
| |
| delete field; |
| delete pred; |
| } |
| |
| TEST_F(TestEqualPredicate, DATE_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("DATE_COLUMN"), "DATE", "REPLACE", 1, true, true, &tablet_schema); |
| int size = 6; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| uint24_t value = datetime::to_date_timestamp("2017-09-10"); |
| ColumnPredicate* pred = new EqualPredicate<uint24_t>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| uint24_t* col_data = reinterpret_cast<uint24_t*>(_mem_pool->allocate(size * sizeof(uint24_t))); |
| col_vector->set_col_data(col_data); |
| |
| std::vector<std::string> date_array; |
| date_array.push_back("2017-09-07"); |
| date_array.push_back("2017-09-08"); |
| date_array.push_back("2017-09-09"); |
| date_array.push_back("2017-09-10"); |
| date_array.push_back("2017-09-11"); |
| date_array.push_back("2017-09-12"); |
| for (int i = 0; i < size; ++i) { |
| uint24_t timestamp = datetime::to_date_timestamp(date_array[i].c_str()); |
| *(col_data + i) = timestamp; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| uint16_t* sel = _vectorized_batch->selected(); |
| ASSERT_EQ(sel[0], 3); |
| ASSERT_EQ(*(col_data + sel[0]), value); |
| ASSERT_EQ(datetime::to_date_string(*(col_data + sel[0])), "2017-09-10"); |
| |
| // for ColumnBlock no nulls |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| uint24_t timestamp = datetime::to_date_timestamp(date_array[i].c_str()); |
| *reinterpret_cast<uint24_t*>(col_block_view.data()) = timestamp; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(datetime::to_date_string( |
| *(uint24_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()), |
| "2017-09-10"); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| uint24_t timestamp = datetime::to_date_timestamp(date_array[i].c_str()); |
| *(col_data + i) = timestamp; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| sel = _vectorized_batch->selected(); |
| ASSERT_EQ(*(col_data + sel[0]), value); |
| ASSERT_EQ(datetime::to_date_string(*(col_data + sel[0])), "2017-09-10"); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| uint24_t timestamp = datetime::to_date_timestamp(date_array[i].c_str()); |
| *reinterpret_cast<uint24_t*>(col_block_view.data()) = timestamp; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(datetime::to_date_string( |
| *(uint24_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()), |
| "2017-09-10"); |
| |
| delete pred; |
| } |
| |
| TEST_F(TestEqualPredicate, DATETIME_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("DATETIME_COLUMN"), "DATETIME", "REPLACE", 1, true, true, |
| &tablet_schema); |
| int size = 6; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| uint64_t value = datetime::to_datetime_timestamp("2017-09-10 01:00:00"); |
| ColumnPredicate* pred = new EqualPredicate<uint64_t>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| uint64_t* col_data = reinterpret_cast<uint64_t*>(_mem_pool->allocate(size * sizeof(uint64_t))); |
| col_vector->set_col_data(col_data); |
| |
| std::vector<std::string> date_array; |
| date_array.push_back("2017-09-07 00:00:00"); |
| date_array.push_back("2017-09-08 00:01:00"); |
| date_array.push_back("2017-09-09 00:00:01"); |
| date_array.push_back("2017-09-10 01:00:00"); |
| date_array.push_back("2017-09-11 01:01:00"); |
| date_array.push_back("2017-09-12 01:01:01"); |
| for (int i = 0; i < size; ++i) { |
| uint64_t timestamp = datetime::to_datetime_timestamp(date_array[i].c_str()); |
| *(col_data + i) = timestamp; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| uint16_t* sel = _vectorized_batch->selected(); |
| ASSERT_EQ(sel[0], 3); |
| ASSERT_EQ(*(col_data + sel[0]), value); |
| ASSERT_EQ(datetime::to_datetime_string(*(col_data + sel[0])), "2017-09-10 01:00:00"); |
| |
| // for ColumnBlock no nulls |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| uint64_t timestamp = datetime::to_datetime_timestamp(date_array[i].c_str()); |
| *reinterpret_cast<uint64_t*>(col_block_view.data()) = timestamp; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(datetime::to_datetime_string( |
| *(uint64_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()), |
| "2017-09-10 01:00:00"); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| uint64_t timestamp = datetime::to_datetime_timestamp(date_array[i].c_str()); |
| *(col_data + i) = timestamp; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| sel = _vectorized_batch->selected(); |
| ASSERT_EQ(*(col_data + sel[0]), value); |
| ASSERT_EQ(datetime::to_datetime_string(*(col_data + sel[0])), "2017-09-10 01:00:00"); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| uint64_t timestamp = datetime::to_datetime_timestamp(date_array[i].c_str()); |
| *reinterpret_cast<uint64_t*>(col_block_view.data()) = timestamp; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(datetime::to_datetime_string( |
| *(uint64_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()), |
| "2017-09-10 01:00:00"); |
| |
| delete pred; |
| } |
| |
| #define TEST_LESS_PREDICATE(TYPE, TYPE_NAME, FIELD_TYPE) \ |
| TEST_F(TestLessPredicate, TYPE_NAME##_COLUMN) { \ |
| TabletSchema tablet_schema; \ |
| SetTabletSchema(std::string("TYPE_NAME_COLUMN"), FIELD_TYPE, "REPLACE", 1, false, true, \ |
| &tablet_schema); \ |
| int size = 10; \ |
| std::vector<uint32_t> return_columns; \ |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { \ |
| return_columns.push_back(i); \ |
| } \ |
| InitVectorizedBatch(&tablet_schema, return_columns, size); \ |
| ColumnVector* col_vector = _vectorized_batch->column(0); \ |
| \ |
| /* for no nulls */ \ |
| col_vector->set_no_nulls(true); \ |
| TYPE* col_data = reinterpret_cast<TYPE*>(_mem_pool->allocate(size * sizeof(TYPE))); \ |
| col_vector->set_col_data(col_data); \ |
| for (int i = 0; i < size; ++i) { \ |
| *(col_data + i) = i; \ |
| } \ |
| TYPE value = 5; \ |
| ColumnPredicate* pred = new LessPredicate<TYPE>(0, value); \ |
| pred->evaluate(_vectorized_batch); \ |
| ASSERT_EQ(_vectorized_batch->size(), 5); \ |
| uint16_t* sel = _vectorized_batch->selected(); \ |
| TYPE sum = 0; \ |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { \ |
| sum += *(col_data + sel[i]); \ |
| } \ |
| ASSERT_EQ(sum, 10); \ |
| \ |
| /* for has nulls */ \ |
| col_vector->set_no_nulls(false); \ |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); \ |
| memset(is_null, 0, size); \ |
| col_vector->set_is_null(is_null); \ |
| for (int i = 0; i < size; ++i) { \ |
| if (i % 2 == 0) { \ |
| is_null[i] = true; \ |
| } else { \ |
| *(col_data + i) = i; \ |
| } \ |
| } \ |
| _vectorized_batch->set_size(size); \ |
| _vectorized_batch->set_selected_in_use(false); \ |
| pred->evaluate(_vectorized_batch); \ |
| ASSERT_EQ(_vectorized_batch->size(), 2); \ |
| sel = _vectorized_batch->selected(); \ |
| sum = 0; \ |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { \ |
| sum += *(col_data + sel[i]); \ |
| } \ |
| ASSERT_EQ(sum, 4); \ |
| delete pred; \ |
| } |
| |
| TEST_LESS_PREDICATE(int8_t, TINYINT, "TINYINT") |
| TEST_LESS_PREDICATE(int16_t, SMALLINT, "SMALLINT") |
| TEST_LESS_PREDICATE(int32_t, INT, "INT") |
| TEST_LESS_PREDICATE(int64_t, BIGINT, "BIGINT") |
| TEST_LESS_PREDICATE(int128_t, LARGEINT, "LARGEINT") |
| |
| TEST_F(TestLessPredicate, FLOAT_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("FLOAT_COLUMN"), "FLOAT", "REPLACE", 1, true, true, |
| &tablet_schema); |
| int size = 10; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| float value = 5.0; |
| ColumnPredicate* pred = new LessPredicate<float>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| float* col_data = reinterpret_cast<float*>(_mem_pool->allocate(size * sizeof(float))); |
| col_vector->set_col_data(col_data); |
| for (int i = 0; i < size; ++i) { |
| *(col_data + i) = i; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 5); |
| uint16_t* sel = _vectorized_batch->selected(); |
| float sum = 0; |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { |
| sum += *(col_data + sel[i]); |
| } |
| ASSERT_FLOAT_EQ(sum, 10.0); |
| |
| // for ColumnBlock no null |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| *reinterpret_cast<float*>(col_block_view.data()) = i; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 5); |
| sum = 0; |
| for (int i = 0; i < 5; ++i) { |
| sum += *(float*)col_block.cell(_row_block->selection_vector()[i]).cell_ptr(); |
| } |
| ASSERT_FLOAT_EQ(sum, 10.0); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| *(col_data + i) = i; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 2); |
| sel = _vectorized_batch->selected(); |
| sum = 0; |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { |
| sum += *(col_data + sel[i]); |
| } |
| ASSERT_FLOAT_EQ(sum, 4.0); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| *reinterpret_cast<float*>(col_block_view.data()) = i; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 2); |
| sum = 0; |
| for (int i = 0; i < 2; ++i) { |
| sum += *(float*)col_block.cell(_row_block->selection_vector()[i]).cell_ptr(); |
| } |
| ASSERT_FLOAT_EQ(sum, 4.0); |
| |
| delete pred; |
| } |
| |
| TEST_F(TestLessPredicate, DOUBLE_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("DOUBLE_COLUMN"), "DOUBLE", "REPLACE", 1, true, true, |
| &tablet_schema); |
| int size = 10; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| double value = 5.0; |
| ColumnPredicate* pred = new LessPredicate<double>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| double* col_data = reinterpret_cast<double*>(_mem_pool->allocate(size * sizeof(double))); |
| col_vector->set_col_data(col_data); |
| for (int i = 0; i < size; ++i) { |
| *(col_data + i) = i; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 5); |
| uint16_t* sel = _vectorized_batch->selected(); |
| double sum = 0; |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { |
| sum += *(col_data + sel[i]); |
| } |
| ASSERT_DOUBLE_EQ(sum, 10.0); |
| |
| // for ColumnBlock no null |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| *reinterpret_cast<double*>(col_block_view.data()) = i; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 5); |
| sum = 0; |
| for (int i = 0; i < 5; ++i) { |
| sum += *(double*)col_block.cell(_row_block->selection_vector()[i]).cell_ptr(); |
| } |
| ASSERT_DOUBLE_EQ(sum, 10.0); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| *(col_data + i) = i; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 2); |
| sel = _vectorized_batch->selected(); |
| sum = 0; |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { |
| sum += *(col_data + sel[i]); |
| } |
| ASSERT_DOUBLE_EQ(sum, 4.0); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| *reinterpret_cast<double*>(col_block_view.data()) = i; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 2); |
| sum = 0; |
| for (int i = 0; i < 2; ++i) { |
| sum += *(double*)col_block.cell(_row_block->selection_vector()[i]).cell_ptr(); |
| } |
| ASSERT_DOUBLE_EQ(sum, 4.0); |
| |
| delete pred; |
| } |
| |
| TEST_F(TestLessPredicate, DECIMAL_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("DECIMAL_COLUMN"), "DECIMAL", "REPLACE", 1, true, true, |
| &tablet_schema); |
| int size = 10; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| decimal12_t value(5, 5); |
| ColumnPredicate* pred = new LessPredicate<decimal12_t>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| decimal12_t* col_data = |
| reinterpret_cast<decimal12_t*>(_mem_pool->allocate(size * sizeof(decimal12_t))); |
| col_vector->set_col_data(col_data); |
| for (int i = 0; i < size; ++i) { |
| (*(col_data + i)).integer = i; |
| (*(col_data + i)).fraction = i; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 5); |
| uint16_t* sel = _vectorized_batch->selected(); |
| decimal12_t sum(0, 0); |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { |
| sum += *(col_data + sel[i]); |
| } |
| ASSERT_EQ(sum.integer, 10); |
| ASSERT_EQ(sum.fraction, 10); |
| |
| // for ColumnBlock no null |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| reinterpret_cast<decimal12_t*>(col_block_view.data())->integer = i; |
| reinterpret_cast<decimal12_t*>(col_block_view.data())->fraction = i; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 5); |
| sum.integer = 0; |
| sum.fraction = 0; |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { |
| sum += *(col_data + sel[i]); |
| } |
| ASSERT_EQ(sum.integer, 10); |
| ASSERT_EQ(sum.fraction, 10); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| (*(col_data + i)).integer = i; |
| (*(col_data + i)).fraction = i; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 2); |
| sum.integer = 0; |
| sum.fraction = 0; |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { |
| sum += *(col_data + sel[i]); |
| } |
| ASSERT_EQ(sum.integer, 4); |
| ASSERT_EQ(sum.fraction, 4); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| reinterpret_cast<decimal12_t*>(col_block_view.data())->integer = i; |
| reinterpret_cast<decimal12_t*>(col_block_view.data())->fraction = i; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 2); |
| sum.integer = 0; |
| sum.fraction = 0; |
| for (int i = 0; i < _vectorized_batch->size(); ++i) { |
| sum += *(col_data + sel[i]); |
| } |
| ASSERT_EQ(sum.integer, 4); |
| ASSERT_EQ(sum.fraction, 4); |
| |
| delete pred; |
| } |
| |
| TEST_F(TestLessPredicate, STRING_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("STRING_COLUMN"), "VARCHAR", "REPLACE", 1, true, true, |
| &tablet_schema); |
| int size = 10; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| |
| StringValue value; |
| const char* value_buffer = "dddd"; |
| value.len = 4; |
| value.ptr = const_cast<char*>(value_buffer); |
| ColumnPredicate* pred = new LessPredicate<StringValue>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| StringValue* col_data = |
| reinterpret_cast<StringValue*>(_mem_pool->allocate(size * sizeof(StringValue))); |
| col_vector->set_col_data(col_data); |
| char* string_buffer = reinterpret_cast<char*>(_mem_pool->allocate(55)); |
| for (int i = 0; i < size; ++i) { |
| for (int j = 0; j <= i; ++j) { |
| string_buffer[j] = 'a' + i; |
| } |
| (*(col_data + i)).len = i + 1; |
| (*(col_data + i)).ptr = string_buffer; |
| string_buffer += i + 1; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 3); |
| uint16_t* sel = _vectorized_batch->selected(); |
| ASSERT_TRUE(strncmp((*(col_data + sel[0])).ptr, "a", 1) == 0); |
| |
| // for ColumnBlock no null |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| string_buffer = reinterpret_cast<char*>(_mem_pool->allocate(60)); |
| memset(string_buffer, 0, 60); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| for (int j = 0; j <= i; ++j) { |
| string_buffer[j] = 'a' + i; |
| } |
| reinterpret_cast<StringValue*>(col_block_view.data())->len = i + 1; |
| reinterpret_cast<StringValue*>(col_block_view.data())->ptr = string_buffer; |
| string_buffer += i + 1; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 3); |
| ASSERT_TRUE( |
| strncmp((*(StringValue*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()) |
| .ptr, |
| "a", 1) == 0); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| string_buffer = reinterpret_cast<char*>(_mem_pool->allocate(55)); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| for (int j = 0; j <= i; ++j) { |
| string_buffer[j] = 'a' + i; |
| } |
| (*(col_data + i)).len = i + 1; |
| (*(col_data + i)).ptr = string_buffer; |
| } |
| string_buffer += i + 1; |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| sel = _vectorized_batch->selected(); |
| ASSERT_TRUE(strncmp((*(col_data + sel[0])).ptr, "bb", 2) == 0); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| string_buffer = reinterpret_cast<char*>(_mem_pool->allocate(55)); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| for (int j = 0; j <= i; ++j) { |
| string_buffer[j] = 'a' + i; |
| } |
| reinterpret_cast<StringValue*>(col_block_view.data())->len = i + 1; |
| reinterpret_cast<StringValue*>(col_block_view.data())->ptr = string_buffer; |
| string_buffer += i + 1; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_TRUE( |
| strncmp((*(StringValue*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()) |
| .ptr, |
| "bb", 2) == 0); |
| |
| delete pred; |
| } |
| |
| TEST_F(TestLessPredicate, DATE_COLUMN) { |
| TabletSchema tablet_schema; |
| SetTabletSchema(std::string("DATE_COLUMN"), "DATE", "REPLACE", 1, true, true, &tablet_schema); |
| int size = 6; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| uint24_t value = datetime::to_date_timestamp("2017-09-10"); |
| ColumnPredicate* pred = new LessPredicate<uint24_t>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| uint24_t* col_data = reinterpret_cast<uint24_t*>(_mem_pool->allocate(size * sizeof(uint24_t))); |
| col_vector->set_col_data(col_data); |
| |
| std::vector<std::string> date_array; |
| date_array.push_back("2017-09-07"); |
| date_array.push_back("2017-09-08"); |
| date_array.push_back("2017-09-09"); |
| date_array.push_back("2017-09-10"); |
| date_array.push_back("2017-09-11"); |
| date_array.push_back("2017-09-12"); |
| for (int i = 0; i < size; ++i) { |
| uint24_t timestamp = datetime::to_date_timestamp(date_array[i].c_str()); |
| *(col_data + i) = timestamp; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 3); |
| uint16_t* sel = _vectorized_batch->selected(); |
| ASSERT_EQ(datetime::to_date_string(*(col_data + sel[0])), "2017-09-07"); |
| |
| // for ColumnBlock no nulls |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| uint24_t timestamp = datetime::to_date_timestamp(date_array[i].c_str()); |
| *reinterpret_cast<uint24_t*>(col_block_view.data()) = timestamp; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 3); |
| ASSERT_EQ(datetime::to_date_string( |
| *(uint24_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()), |
| "2017-09-07"); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| uint24_t timestamp = datetime::to_date_timestamp(date_array[i].c_str()); |
| *(col_data + i) = timestamp; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| sel = _vectorized_batch->selected(); |
| ASSERT_EQ(datetime::to_date_string(*(col_data + sel[0])), "2017-09-08"); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| uint24_t timestamp = datetime::to_date_timestamp(date_array[i].c_str()); |
| *reinterpret_cast<uint24_t*>(col_block_view.data()) = timestamp; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(datetime::to_date_string( |
| *(uint24_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()), |
| "2017-09-08"); |
| |
| delete pred; |
| } |
| |
| TEST_F(TestLessPredicate, DATETIME_COLUMN) { |
| TabletSchema tablet_schema; |
| TabletColumn tablet_column; |
| SetTabletSchema(std::string("DATETIME_COLUMN"), "DATETIME", "REPLACE", 1, true, true, |
| &tablet_schema); |
| int size = 6; |
| std::vector<uint32_t> return_columns; |
| for (int i = 0; i < tablet_schema.num_columns(); ++i) { |
| return_columns.push_back(i); |
| } |
| |
| uint64_t value = datetime::to_datetime_timestamp("2017-09-10 01:00:00"); |
| ColumnPredicate* pred = new LessPredicate<uint64_t>(0, value); |
| |
| // for VectorizedBatch no nulls |
| InitVectorizedBatch(&tablet_schema, return_columns, size); |
| ColumnVector* col_vector = _vectorized_batch->column(0); |
| col_vector->set_no_nulls(true); |
| uint64_t* col_data = reinterpret_cast<uint64_t*>(_mem_pool->allocate(size * sizeof(uint64_t))); |
| col_vector->set_col_data(col_data); |
| |
| std::vector<std::string> date_array; |
| date_array.push_back("2017-09-07 00:00:00"); |
| date_array.push_back("2017-09-08 00:01:00"); |
| date_array.push_back("2017-09-09 00:00:01"); |
| date_array.push_back("2017-09-10 01:00:00"); |
| date_array.push_back("2017-09-11 01:01:00"); |
| date_array.push_back("2017-09-12 01:01:01"); |
| for (int i = 0; i < size; ++i) { |
| uint64_t timestamp = datetime::to_datetime_timestamp(date_array[i].c_str()); |
| *(col_data + i) = timestamp; |
| } |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 3); |
| uint16_t* sel = _vectorized_batch->selected(); |
| ASSERT_EQ(datetime::to_datetime_string(*(col_data + sel[0])), "2017-09-07 00:00:00"); |
| |
| // for ColumnBlock no nulls |
| init_row_block(&tablet_schema, size); |
| ColumnBlock col_block = _row_block->column_block(0); |
| auto select_size = _row_block->selected_size(); |
| ColumnBlockView col_block_view(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| col_block_view.set_null_bits(1, false); |
| uint64_t timestamp = datetime::to_datetime_timestamp(date_array[i].c_str()); |
| *reinterpret_cast<uint64_t*>(col_block_view.data()) = timestamp; |
| } |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 3); |
| ASSERT_EQ(datetime::to_datetime_string( |
| *(uint64_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()), |
| "2017-09-07 00:00:00"); |
| |
| // for VectorizedBatch has nulls |
| col_vector->set_no_nulls(false); |
| bool* is_null = reinterpret_cast<bool*>(_mem_pool->allocate(size)); |
| memset(is_null, 0, size); |
| col_vector->set_is_null(is_null); |
| for (int i = 0; i < size; ++i) { |
| if (i % 2 == 0) { |
| is_null[i] = true; |
| } else { |
| uint64_t timestamp = datetime::to_datetime_timestamp(date_array[i].c_str()); |
| *(col_data + i) = timestamp; |
| } |
| } |
| _vectorized_batch->set_size(size); |
| _vectorized_batch->set_selected_in_use(false); |
| pred->evaluate(_vectorized_batch); |
| ASSERT_EQ(_vectorized_batch->size(), 1); |
| sel = _vectorized_batch->selected(); |
| ASSERT_EQ(datetime::to_datetime_string(*(col_data + sel[0])), "2017-09-08 00:01:00"); |
| |
| // for ColumnBlock has nulls |
| col_block_view = ColumnBlockView(&col_block); |
| for (int i = 0; i < size; ++i, col_block_view.advance(1)) { |
| if (i % 2 == 0) { |
| col_block_view.set_null_bits(1, true); |
| } else { |
| col_block_view.set_null_bits(1, false); |
| uint64_t timestamp = datetime::to_datetime_timestamp(date_array[i].c_str()); |
| *reinterpret_cast<uint64_t*>(col_block_view.data()) = timestamp; |
| } |
| } |
| _row_block->clear(); |
| select_size = _row_block->selected_size(); |
| pred->evaluate(&col_block, _row_block->selection_vector(), &select_size); |
| ASSERT_EQ(select_size, 1); |
| ASSERT_EQ(datetime::to_datetime_string( |
| *(uint64_t*)col_block.cell(_row_block->selection_vector()[0]).cell_ptr()), |
| "2017-09-08 00:01:00"); |
| |
| delete pred; |
| } |
| |
| } // namespace doris |
| |
| int main(int argc, char** argv) { |
| int ret = doris::OLAP_SUCCESS; |
| testing::InitGoogleTest(&argc, argv); |
| doris::CpuInfo::init(); |
| ret = RUN_ALL_TESTS(); |
| google::protobuf::ShutdownProtobufLibrary(); |
| return ret; |
| } |
