// 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/null_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 "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;
}

}; // namespace datetime

class TestNullPredicate : public testing::Test {
public:
    TestNullPredicate() : _vectorized_batch(nullptr), _row_block(nullptr) {
        _mem_tracker.reset(new MemTracker(-1));
        _mem_pool.reset(new MemPool(_mem_tracker.get()));
    }

    ~TestNullPredicate() {
        if (_vectorized_batch != nullptr) {
            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<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;
};

#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, 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);                                                         \
        }                                                                                        \
        std::unique_ptr<ColumnPredicate> pred(new NullPredicate(0, true));                       \
                                                                                                 \
        /* for VectorizedBatch nulls */                                                          \
        InitVectorizedBatch(&tablet_schema, return_columns, size);                               \
        init_row_block(&tablet_schema, size);                                                    \
        ColumnVector* col_vector = _vectorized_batch->column(0);                                 \
        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;                                                                 \
        }                                                                                        \
        pred->evaluate(_vectorized_batch);                                                       \
        ASSERT_EQ(_vectorized_batch->size(), 0);                                                 \
                                                                                                 \
        /* for ColumnBlock 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);                                              \
            *reinterpret_cast<TYPE*>(col_block_view.data()) = i;                                 \
        }                                                                                        \
        pred->evaluate(&col_block, _row_block->selection_vector(), &select_size);                \
        ASSERT_EQ(select_size, 0);                                                               \
                                                                                                 \
        /* 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(), 5);                                                 \
                                                                                                 \
        /* 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<TYPE*>(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, 5);                                                               \
        pred.reset();                                                                            \
    }

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, 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);
    }
    std::unique_ptr<ColumnPredicate> pred(new NullPredicate(0, true));

    // 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 + 0.1;
    }
    pred->evaluate(_vectorized_batch);
    ASSERT_EQ(_vectorized_batch->size(), 0);

    // 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);
        *reinterpret_cast<float*>(col_block_view.data()) = i + 0.1;
    }
    pred->evaluate(&col_block, _row_block->selection_vector(), &select_size);
    ASSERT_EQ(select_size, 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 + 0.1;
        }
    }
    _vectorized_batch->set_size(size);
    _vectorized_batch->set_selected_in_use(false);
    pred->evaluate(_vectorized_batch);
    ASSERT_EQ(_vectorized_batch->size(), 5);

    // 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 + 0.1;
        }
    }
    _row_block->clear();
    select_size = _row_block->selected_size();
    pred->evaluate(&col_block, _row_block->selection_vector(), &select_size);
    ASSERT_EQ(select_size, 5);
}

TEST_F(TestNullPredicate, 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);
    }
    std::unique_ptr<ColumnPredicate> pred(new NullPredicate(0, true));

    // 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 + 0.1;
    }
    pred->evaluate(_vectorized_batch);
    ASSERT_EQ(_vectorized_batch->size(), 0);

    // 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);
        *reinterpret_cast<double*>(col_block_view.data()) = i + 0.1;
    }
    pred->evaluate(&col_block, _row_block->selection_vector(), &select_size);
    ASSERT_EQ(select_size, 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 + 0.1;
        }
    }
    _vectorized_batch->set_size(size);
    _vectorized_batch->set_selected_in_use(false);
    pred->evaluate(_vectorized_batch);
    ASSERT_EQ(_vectorized_batch->size(), 5);

    // 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 + 0.1;
        }
    }
    _row_block->clear();
    select_size = _row_block->selected_size();
    pred->evaluate(&col_block, _row_block->selection_vector(), &select_size);
    ASSERT_EQ(select_size, 5);
}

TEST_F(TestNullPredicate, 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);
    }
    std::unique_ptr<ColumnPredicate> pred(new NullPredicate(0, true));

    // 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(), 0);

    // 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);
        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, 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 % 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);

    // for ColumnBlock has nulls
    col_block_view = ColumnBlockView(&col_block);
    for (int i = 0; i < size; ++i, col_block_view.advance(1)) {
        if (i % 3 == 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, 4);
}

TEST_F(TestNullPredicate, 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);
    }
    std::unique_ptr<ColumnPredicate> pred(new NullPredicate(0, true));

    // 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;
    }
    ASSERT_EQ(_vectorized_batch->size(), 10);
    pred->evaluate(_vectorized_batch);
    ASSERT_EQ(_vectorized_batch->size(), 0);

    // 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);

    string_buffer = reinterpret_cast<char*>(_mem_pool->allocate(55));
    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, 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 % 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);

    // 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 % 3 == 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, 4);
}

TEST_F(TestNullPredicate, 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);
    }
    std::unique_ptr<ColumnPredicate> pred(new NullPredicate(0, true));

    // 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(), 0);

    // 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, 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 % 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);

    // for ColumnBlock has nulls
    col_block_view = ColumnBlockView(&col_block);
    for (int i = 0; i < size; ++i, col_block_view.advance(1)) {
        if (i % 3 == 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, 2);
}

TEST_F(TestNullPredicate, 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);
    }
    std::unique_ptr<ColumnPredicate> pred(new NullPredicate(0, true));

    // 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(), 0);

    // 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_date_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, 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 % 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);

    // for ColumnBlock has nulls
    col_block_view = ColumnBlockView(&col_block);
    for (int i = 0; i < size; ++i, col_block_view.advance(1)) {
        if (i % 3 == 0) {
            col_block_view.set_null_bits(1, true);
        } else {
            col_block_view.set_null_bits(1, false);
            uint64_t timestamp = datetime::to_date_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, 2);
}

} // 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;
}