#!/usr/bin/env bash

CURDIR=$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)
# shellcheck source=../shell_config.sh
. "$CURDIR"/../shell_config.sh

PAR_PATH="$CURDIR"/02998_native_parquet_reader.parquet
# the content of parquet file can be generated by following codes
# <<EndOfCodes
# 
# #include <Columns/ColumnNullable.h>
# #include <Columns/ColumnString.h>
# #include <Common/tests/gtest_global_register.h>
# #include <Core/Block.h>
# #include <DataTypes/DataTypeDateTime64.h>
# #include <DataTypes/DataTypeLowCardinality.h>
# #include <DataTypes/DataTypeNullable.h>
# #include <DataTypes/DataTypeString.h>
# #include <DataTypes/DataTypesDecimal.h>
# #include <IO/WriteBufferFromFile.h>
# #include <Processors/Formats/IOutputFormat.h>
# #include <Processors/Formats/Impl/Parquet/ParquetRecordReader.h>
# 
# namespace
# {
# 
# using namespace DB;
# 
# const UInt32 ROW_NUM = 2000;
# const UInt32 MIN_STRING_LEN = 3;
# const UInt32 MAX_STRING_LEN = 5;
# 
# const UInt32 PLAIN_ENCODING_CARDINALITY = ROW_NUM * 2;
# const UInt32 MIX_ENCODING_CARDINALITY = 800;
# const UInt32 DICT_ENCODING_CARDINALITY = 20;
# 
# UInt16 nextNum()
# {
#     static UInt16 idx = 0;
#     static UInt16 nums[] = {0, 21845, 43690};
#     static size_t nums_len = sizeof(nums) / sizeof(nums[0]);
#     return nums[(idx++) % nums_len]++;
# }
# 
# template <typename NumericDataType>
# void generateValues(MutableColumnPtr & col, size_t num)
# {
#     using FieldType = typename NumericDataType::FieldType;
# 
#     const size_t next_num_bytes = sizeof(nextNum());
#     char bytewise_val[sizeof(FieldType)];
# 
#     while (col->size() < num)
#     {
#         for (auto bytes = 0; bytes < sizeof(FieldType); bytes += next_num_bytes)
#         {
#             auto tmp = nextNum();
#             memcpy(bytewise_val + bytes, &tmp, std::min(next_num_bytes, sizeof(FieldType) - bytes));
#         }
#         if (is_decimal<FieldType>)
#         {
#             // clean highest 3 bits, make sure the result doest not exceed the limits of the decimal type
#             if (bytewise_val[sizeof(FieldType) - 1] > 0)
#                 bytewise_val[sizeof(FieldType) - 1] &= 0x0f;
#             else
#                 bytewise_val[sizeof(FieldType) - 1] |= 0xf0;
#         }
#         FieldType val;
#         memcpy(&val, &bytewise_val, sizeof(FieldType));
#         col->insert(val);
#     }
# }
# 
# template <>
# void generateValues<DataTypeString>(MutableColumnPtr & col, size_t num)
# {
#     std::string str;
#     while (col->size() < num)
#     {
#         auto len = MIN_STRING_LEN + nextNum() % (MAX_STRING_LEN - MIN_STRING_LEN);
#         str.clear();
#         for (size_t i = 0; i < len; i++)
#         {
#             str.push_back('a' + nextNum() % ('z' - 'a'));
#         }
#         col->insert(str);
#     }
# }
# 
# template <typename DataType>
# ColumnWithTypeAndName generateColumn(
#     std::shared_ptr<DataType> ch_type,
#     size_t cardinality,
#     const std::string & col_name,
#     const std::set<size_t> & null_indice)
# {
#     DataTypePtr col_type = ch_type;
#     if (!null_indice.empty())
#     {
#         col_type = std::make_shared<DataTypeNullable>(ch_type);
#     }
# 
#     auto values = ch_type->createColumn();
#     values->reserve(cardinality);
#     generateValues<DataType>(values, cardinality);
# 
#     auto col = col_type->createColumn();
#     col->reserve(ROW_NUM);
#     for (size_t i = 0; i < ROW_NUM; i++)
#     {
#         if (!null_indice.empty() && null_indice.contains(i))
#         {
#             col->insert(Null());
#         }
#         else
#         {
#             col->insert(values->operator[](nextNum() % cardinality));
#         }
#     }
#     return {std::move(col), col_type, col_name};
# }
# 
# Block generateBlock()
# {
#     ColumnsWithTypeAndName cols;
# 
#     // test Int32 type
#     std::set<size_t> null_indice{512, 1001, 211, 392, 553, 1725};
#     // Nullability is expressed by definition level, and encoded by bit packed with smallest group size of 8
#     // when null value appeared. Here we make a big bit packed group with more than 1000 values.
#     for (size_t i = 0; i < 170; i++)
#     {
#         null_indice.emplace(622 + i * 6);
#     }
#     cols.emplace_back(generateColumn(
#         std::make_shared<DataTypeInt32>(), PLAIN_ENCODING_CARDINALITY, "plain_encoding_i32", null_indice));
#     null_indice = {917, 482, 283, 580, 1926, 1667, 1971};
#     cols.emplace_back(generateColumn(
#         std::make_shared<DataTypeInt32>(), DICT_ENCODING_CARDINALITY, "dict_encoding_i32", null_indice));
# 
#     // test string type
#     null_indice = {818, 928, 1958, 1141, 1553, 1407, 690, 1769};
#     cols.emplace_back(generateColumn(
#         std::make_shared<DataTypeString>(), PLAIN_ENCODING_CARDINALITY, "plain_encoding_str", null_indice));
#     null_indice = {1441, 1747, 216, 1209, 89, 52, 536, 625};
#     cols.emplace_back(generateColumn(
#         std::make_shared<DataTypeString>(), MIX_ENCODING_CARDINALITY, "mix_encoding_str", null_indice));
#     null_indice = {1478, 1862, 894, 1314, 1844, 243, 869, 551};
#     cols.emplace_back(generateColumn(
#         std::make_shared<DataTypeString>(), DICT_ENCODING_CARDINALITY, "dict_encoding_str", null_indice));
# 
#     // test DateTime64 type
#     auto dt_type = std::make_shared<DataTypeDateTime64>(ParquetRecordReader::default_datetime64_scale);
#     null_indice = {1078, 112, 1981, 795, 371, 1176, 1526, 11};
#     cols.emplace_back(generateColumn(dt_type, PLAIN_ENCODING_CARDINALITY, "plain_encoding_dt64", null_indice));
#     null_indice = {1734, 1153, 1893, 1205, 644, 1670, 1482, 1479};
#     cols.emplace_back(generateColumn(dt_type, DICT_ENCODING_CARDINALITY, "dict_encoding_dt64", null_indice));
# 
#     // test Decimal128 type
#     auto d128_type = std::make_shared<DataTypeDecimal128>(DecimalUtils::max_precision<Decimal128>, 3);
#     null_indice = {852, 1448, 1569, 896, 1866, 1655, 100, 418};
#     cols.emplace_back(generateColumn(d128_type, PLAIN_ENCODING_CARDINALITY, "plain_encoding_decimal128", null_indice));
# 
#     return {cols};
# }
# 
# void dumpBlock(const Block & block)
# {
#     WriteBufferFromFile output_buf("/tmp/ut-out.csv");
#     auto out = getContext().context->getOutputFormat("CSVWithNames", output_buf, block);
#     out->write(block);
#     out->finalize();
#     std::cerr << block.dumpStructure() << std::endl << std::endl;
# }
# 
# }
#
# EndOfCodes 
#
# How to generate the parquet file:
# 1. Use above C++ codes.
#    Put above codes in src/Common/tests/gtest_main.cpp, add following two inlines in main function:
#     tryRegisterFormats();
#     dumpBlock(generateBlock());
# 2. Genetate /tmp/ut-out.csv.
#    After compiled, run any test, such as "./src/unit_tests_dbms --gtest_filter=IColumn.dumpStructure", 
# 3. Generate the parquet file by following spark sql
#    create temporary view tv using csv options('path' '/tmp/ut-out.csv', 'header' 'true', 'nullValue' '\\N');
#    insert overwrite directory "/tmp/test-parquet" using Parquet
#      options('parquet.dictionary.page.size' '500')
#      select /*+ COALESCE(1) */ cast(plain_encoding_i32 as int), cast(dict_encoding_i32 as int),
#             plain_encoding_str, mix_encoding_str, dict_encoding_str,
#             cast(plain_encoding_dt64 as timestamp), cast(dict_encoding_dt64 as timestamp),
#             cast(plain_encoding_decimal128 as decimal(38, 3))
#      from tv;
#   

CH_SCHEMA="\
    plain_encoding_i32 Nullable(Int32), \
    dict_encoding_i32 Nullable(Int32), \
    plain_encoding_str Nullable(String), \
    mix_encoding_str Nullable(String), \
    dict_encoding_str LowCardinality(Nullable(String)), \
    plain_encoding_dt64 Nullable(DateTime64(9)), \
    dict_encoding_dt64 Nullable(DateTime64(9)), \
    plain_encoding_decimal128 Nullable(Decimal(38, 3))"
QUERY="SELECT * from file('$PAR_PATH', 'Parquet', '$CH_SCHEMA')"

# there may be more than on group in parquet files, unstable results may generated by multithreads
$CLICKHOUSE_LOCAL --multiquery --max_threads 1 --input_format_parquet_use_native_reader true --query "$QUERY"