// 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 #include #include #include "olap/field.h" #include "olap/column_predicate.h" #include "olap/null_predicate.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; } }; class TestNullPredicate : public testing::Test { public: TestNullPredicate() : _vectorized_batch(NULL) { _mem_tracker.reset(new MemTracker(-1)); _mem_pool.reset(new MemPool(_mem_tracker.get())); } ~TestNullPredicate() { if (_vectorized_batch != NULL) { delete _vectorized_batch; } } void SetTabletSchema(std::string name, std::string type, 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&ids, int size) { _vectorized_batch = new VectorizedRowBatch(tablet_schema, ids, size); _vectorized_batch->set_size(size); } std::shared_ptr _mem_tracker; std::unique_ptr _mem_pool; VectorizedRowBatch* _vectorized_batch; }; #define TEST_IN_LIST_PREDICATE(TYPE, TYPE_NAME, FIELD_TYPE) \ TEST_F(TestNullPredicate, 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 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(_mem_pool->allocate(size * sizeof(TYPE))); \ col_vector->set_col_data(col_data); \ for (int i = 0; i < size; ++i) { \ *(col_data + i) = i; \ } \ \ ColumnPredicate* pred = new NullPredicate(0, true); \ pred->evaluate(_vectorized_batch); \ ASSERT_EQ(_vectorized_batch->size(), 0); \ \ /* for has nulls */ \ col_vector->set_no_nulls(false); \ bool* is_null = reinterpret_cast(_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(), 5); \ delete pred; \ } \ TEST_IN_LIST_PREDICATE(int8_t, TINYINT, "TINYINT") TEST_IN_LIST_PREDICATE(int16_t, SMALLINT, "SMALLINT") TEST_IN_LIST_PREDICATE(int32_t, INT, "INT") TEST_IN_LIST_PREDICATE(int64_t, BIGINT, "BIGINT") TEST_IN_LIST_PREDICATE(int128_t, LARGEINT, "LARGEINT") TEST_F(TestNullPredicate, FLOAT_COLUMN) { TabletSchema tablet_schema; SetTabletSchema(std::string("FLOAT_COLUMN"), "FLOAT", "REPLACE", 1, false, true, &tablet_schema); int size = 10; std::vector 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); float* col_data = reinterpret_cast(_mem_pool->allocate(size * sizeof(float))); col_vector->set_col_data(col_data); for (int i = 0; i < size; ++i) { *(col_data + i) = i + 0.1; } ColumnPredicate* pred = new NullPredicate(0, true); pred->evaluate(_vectorized_batch); ASSERT_EQ(_vectorized_batch->size(), 0); // for has nulls col_vector->set_no_nulls(false); bool* is_null = reinterpret_cast(_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 + 0.1; } } _vectorized_batch->set_size(size); _vectorized_batch->set_selected_in_use(false); pred->evaluate(_vectorized_batch); ASSERT_EQ(_vectorized_batch->size(), 5); delete pred; } TEST_F(TestNullPredicate, DOUBLE_COLUMN) { TabletSchema tablet_schema; SetTabletSchema(std::string("DOUBLE_COLUMN"), "DOUBLE", "REPLACE", 1, false, true, &tablet_schema); int size = 10; std::vector 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); double* col_data = reinterpret_cast(_mem_pool->allocate(size * sizeof(double))); col_vector->set_col_data(col_data); for (int i = 0; i < size; ++i) { *(col_data + i) = i + 0.1; } ColumnPredicate* pred = new NullPredicate(0, true); pred->evaluate(_vectorized_batch); ASSERT_EQ(_vectorized_batch->size(), 0); // for has nulls col_vector->set_no_nulls(false); bool* is_null = reinterpret_cast(_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 + 0.1; } } _vectorized_batch->set_size(size); _vectorized_batch->set_selected_in_use(false); pred->evaluate(_vectorized_batch); ASSERT_EQ(_vectorized_batch->size(), 5); delete pred; } TEST_F(TestNullPredicate, DECIMAL_COLUMN) { TabletSchema tablet_schema; SetTabletSchema(std::string("DECIMAL_COLUMN"), "DECIMAL", "REPLACE", 1, false, true, &tablet_schema); int size = 10; std::vector 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); decimal12_t* col_data = reinterpret_cast(_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; } ColumnPredicate* pred = new NullPredicate(0, true); pred->evaluate(_vectorized_batch); ASSERT_EQ(_vectorized_batch->size(), 0); // for has nulls col_vector->set_no_nulls(false); bool* is_null = reinterpret_cast(_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 % 3 == 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(), 4); delete pred; } TEST_F(TestNullPredicate, STRING_COLUMN) { TabletSchema tablet_schema; SetTabletSchema(std::string("STRING_COLUMN"), "VARCHAR", "REPLACE", 1, false, true, &tablet_schema); int size = 10; std::vector 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); StringValue* col_data = reinterpret_cast(_mem_pool->allocate(size * sizeof(StringValue))); col_vector->set_col_data(col_data); char* string_buffer = reinterpret_cast(_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; } ColumnPredicate* pred = new NullPredicate(0, true); ASSERT_EQ(_vectorized_batch->size(), 10); // for has nulls col_vector->set_no_nulls(false); bool* is_null = reinterpret_cast(_mem_pool->allocate(size)); memset(is_null, 0, size); col_vector->set_is_null(is_null); string_buffer = reinterpret_cast(_mem_pool->allocate(55)); for (int i = 0; i < size; ++i) { if (i % 3 == 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(), 4); delete pred; } TEST_F(TestNullPredicate, DATE_COLUMN) { TabletSchema tablet_schema; SetTabletSchema(std::string("DATE_COLUMN"), "DATE", "REPLACE", 1, false, true, &tablet_schema); int size = 6; std::vector 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); uint24_t* col_data = reinterpret_cast(_mem_pool->allocate(size * sizeof(uint24_t))); col_vector->set_col_data(col_data); std::vector 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; } ColumnPredicate* pred = new NullPredicate(0, true); pred->evaluate(_vectorized_batch); ASSERT_EQ(_vectorized_batch->size(), 0); // for has nulls col_vector->set_no_nulls(false); bool* is_null = reinterpret_cast(_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 % 3 == 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(), 2); delete pred; } TEST_F(TestNullPredicate, DATETIME_COLUMN) { TabletSchema tablet_schema; SetTabletSchema(std::string("DATETIME_COLUMN"), "DATETIME", "REPLACE", 1, false, true, &tablet_schema); int size = 6; std::vector 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); uint64_t* col_data = reinterpret_cast(_mem_pool->allocate(size * sizeof(uint64_t))); col_vector->set_col_data(col_data); std::vector 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; } ColumnPredicate* pred = new NullPredicate(0, true); pred->evaluate(_vectorized_batch); ASSERT_EQ(_vectorized_batch->size(), 0); // for has nulls col_vector->set_no_nulls(false); bool* is_null = reinterpret_cast(_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 % 3 == 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(), 2); delete pred; } } // namespace doris int main(int argc, char** argv) { std::string conffile = std::string(getenv("DORIS_HOME")) + "/conf/be.conf"; if (!doris::config::init(conffile.c_str(), false)) { fprintf(stderr, "error read config file. \n"); return -1; } doris::init_glog("be-test"); int ret = doris::OLAP_SUCCESS; testing::InitGoogleTest(&argc, argv); doris::CpuInfo::init(); ret = RUN_ALL_TESTS(); google::protobuf::ShutdownProtobufLibrary(); return ret; }