mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-11-24 16:42:05 +00:00
Merge bc866e64ea into 7eee149487
This commit is contained in:
Arthur Passos
GitHub
commit
d51afdb65f
@ -48,6 +48,22 @@ public:
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consume(bytes);
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}
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template <typename TValue, typename ParquetType>
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void ALWAYS_INLINE readValuesOfDifferentSize(TValue * dst, size_t count)
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{
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auto necessary_bytes = count * sizeof(ParquetType);
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checkAvaible(necessary_bytes);
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const ParquetType* src = reinterpret_cast<const ParquetType*>(data);
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for (std::size_t i = 0; i < count; i++)
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{
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dst[i] = static_cast<TValue>(src[i]);
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}
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consume(necessary_bytes);
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}
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void ALWAYS_INLINE readDateTime64FromInt96(DateTime64 & dst)
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{
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static const int max_scale_num = 9;
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@ -240,8 +240,8 @@ TValue * getResizedPrimitiveData(TColumn & column, size_t size)
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} // anoynomous namespace
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template <>
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void ParquetPlainValuesReader<ColumnString>::readBatch(
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template <typename TColumn>
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void ParquetPlainByteArrayValuesReader<TColumn>::readBatch(
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MutableColumnPtr & col_ptr, LazyNullMap & null_map, UInt32 num_values)
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{
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auto & column = *assert_cast<ColumnString *>(col_ptr.get());
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@ -322,8 +322,8 @@ void ParquetBitPlainReader<TColumn>::readBatch(
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}
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template <>
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void ParquetPlainValuesReader<ColumnDecimal<DateTime64>, ParquetReaderTypes::TimestampInt96>::readBatch(
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template <typename TColumn>
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void ParquetPlainInt96ValuesReader<TColumn>::readBatch(
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MutableColumnPtr & col_ptr, LazyNullMap & null_map, UInt32 num_values)
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{
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auto cursor = col_ptr->size();
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@ -350,8 +350,8 @@ void ParquetPlainValuesReader<ColumnDecimal<DateTime64>, ParquetReaderTypes::Tim
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);
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}
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template <typename TColumn, ParquetReaderTypes reader_type>
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void ParquetPlainValuesReader<TColumn, reader_type>::readBatch(
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template <typename TColumn, typename ParquetType>
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void ParquetPlainValuesReader<TColumn, ParquetType>::readBatch(
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MutableColumnPtr & col_ptr, LazyNullMap & null_map, UInt32 num_values)
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{
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auto cursor = col_ptr->size();
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@ -365,11 +365,11 @@ void ParquetPlainValuesReader<TColumn, reader_type>::readBatch(
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null_map,
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/* individual_visitor */ [&](size_t nest_cursor)
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{
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plain_data_buffer.readValue(column_data[nest_cursor]);
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plain_data_buffer.readValuesOfDifferentSize<TValue, ParquetType>(column_data + nest_cursor, 1);
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},
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/* repeated_visitor */ [&](size_t nest_cursor, UInt32 count)
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{
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plain_data_buffer.readBytes(column_data + nest_cursor, count * sizeof(TValue));
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plain_data_buffer.readValuesOfDifferentSize<TValue, ParquetType>(column_data + nest_cursor, count);
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}
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);
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}
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@ -576,18 +576,19 @@ void ParquetRleDictReader<TColumnVector>::readBatch(
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}
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template class ParquetPlainValuesReader<ColumnInt32>;
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template class ParquetPlainValuesReader<ColumnUInt32>;
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template class ParquetPlainValuesReader<ColumnInt64>;
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template class ParquetPlainValuesReader<ColumnUInt64>;
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template class ParquetPlainValuesReader<ColumnBFloat16>;
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template class ParquetPlainValuesReader<ColumnFloat32>;
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template class ParquetPlainValuesReader<ColumnFloat64>;
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template class ParquetPlainValuesReader<ColumnDecimal<Decimal32>>;
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template class ParquetPlainValuesReader<ColumnDecimal<Decimal64>>;
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template class ParquetPlainValuesReader<ColumnDecimal<DateTime64>>;
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template class ParquetPlainValuesReader<ColumnString>;
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template class ParquetPlainValuesReader<ColumnUInt8>;
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template class ParquetPlainValuesReader<ColumnUInt8, int32_t>;
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template class ParquetPlainValuesReader<ColumnInt8, int32_t>;
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template class ParquetPlainValuesReader<ColumnUInt16, int32_t>;
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template class ParquetPlainValuesReader<ColumnInt16, int32_t>;
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template class ParquetPlainValuesReader<ColumnUInt32, int32_t>;
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template class ParquetPlainValuesReader<ColumnInt32, int32_t>;
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template class ParquetPlainValuesReader<ColumnUInt64, int64_t>;
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template class ParquetPlainValuesReader<ColumnInt64, int64_t>;
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template class ParquetPlainValuesReader<ColumnFloat32, float>;
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template class ParquetPlainValuesReader<ColumnFloat64, double>;
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template class ParquetPlainValuesReader<ColumnDecimal<Decimal32>, int32_t>;
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template class ParquetPlainValuesReader<ColumnDecimal<Decimal64>, int64_t>;
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template class ParquetPlainValuesReader<ColumnDecimal<DateTime64>, int64_t>;
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template class ParquetBitPlainReader<ColumnUInt8>;
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@ -598,12 +599,10 @@ template class ParquetRleLCReader<ColumnUInt8>;
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template class ParquetRleLCReader<ColumnUInt16>;
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template class ParquetRleLCReader<ColumnUInt32>;
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template class ParquetRleDictReader<ColumnUInt8>;
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template class ParquetRleDictReader<ColumnInt32>;
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template class ParquetRleDictReader<ColumnUInt32>;
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template class ParquetRleDictReader<ColumnInt64>;
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template class ParquetRleDictReader<ColumnUInt64>;
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template class ParquetRleDictReader<ColumnBFloat16>;
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template class ParquetRleDictReader<ColumnFloat32>;
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template class ParquetRleDictReader<ColumnFloat64>;
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template class ParquetRleDictReader<ColumnDecimal<Decimal32>>;
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@ -613,4 +612,8 @@ template class ParquetRleDictReader<ColumnDecimal<Decimal256>>;
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template class ParquetRleDictReader<ColumnDecimal<DateTime64>>;
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template class ParquetRleDictReader<ColumnString>;
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template class ParquetPlainByteArrayValuesReader<ColumnString>;
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template class ParquetPlainInt96ValuesReader<ColumnDecimal<DateTime64>>;
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}
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@ -150,7 +150,7 @@ enum class ParquetReaderTypes
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/**
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* The definition level is RLE or BitPacked encoding, while data is read directly
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*/
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template <typename TColumn, ParquetReaderTypes reader_type = ParquetReaderTypes::Normal>
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template <typename TColumn, typename ParquetType>
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class ParquetPlainValuesReader : public ParquetDataValuesReader
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{
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public:
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@ -172,6 +172,50 @@ private:
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ParquetDataBuffer plain_data_buffer;
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};
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template <typename TColumn>
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class ParquetPlainInt96ValuesReader : public ParquetDataValuesReader
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{
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public:
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ParquetPlainInt96ValuesReader(
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Int32 max_def_level_,
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std::unique_ptr<RleValuesReader> def_level_reader_,
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ParquetDataBuffer data_buffer_)
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: max_def_level(max_def_level_)
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, def_level_reader(std::move(def_level_reader_))
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, plain_data_buffer(std::move(data_buffer_))
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{}
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void readBatch(MutableColumnPtr & col_ptr, LazyNullMap & null_map, UInt32 num_values) override;
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private:
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Int32 max_def_level;
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std::unique_ptr<RleValuesReader> def_level_reader;
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ParquetDataBuffer plain_data_buffer;
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};
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template <typename TColumn>
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class ParquetPlainByteArrayValuesReader : public ParquetDataValuesReader
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{
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public:
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ParquetPlainByteArrayValuesReader(
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Int32 max_def_level_,
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std::unique_ptr<RleValuesReader> def_level_reader_,
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ParquetDataBuffer data_buffer_)
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: max_def_level(max_def_level_)
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, def_level_reader(std::move(def_level_reader_))
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, plain_data_buffer(std::move(data_buffer_))
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{}
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void readBatch(MutableColumnPtr & col_ptr, LazyNullMap & null_map, UInt32 num_values) override;
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private:
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Int32 max_def_level;
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std::unique_ptr<RleValuesReader> def_level_reader;
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ParquetDataBuffer plain_data_buffer;
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};
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template <typename TColumn>
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class ParquetBitPlainReader : public ParquetDataValuesReader
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{
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@ -173,13 +173,7 @@ ColumnPtr readDictPage(
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}
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template <typename TColumn>
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std::unique_ptr<ParquetDataValuesReader> createPlainReader(
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const parquet::ColumnDescriptor & col_des,
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RleValuesReaderPtr def_level_reader,
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ParquetDataBuffer buffer);
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template <is_col_over_big_decimal TColumnDecimal>
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template <is_col_over_big_decimal TColumnDecimal, typename ParquetType>
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std::unique_ptr<ParquetDataValuesReader> createPlainReader(
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const parquet::ColumnDescriptor & col_des,
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RleValuesReaderPtr def_level_reader,
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@ -192,25 +186,62 @@ std::unique_ptr<ParquetDataValuesReader> createPlainReader(
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std::move(buffer));
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}
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template <typename TColumn>
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template <typename TColumn, typename ParquetType>
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std::unique_ptr<ParquetDataValuesReader> createPlainReader(
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const parquet::ColumnDescriptor & col_des,
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RleValuesReaderPtr def_level_reader,
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ParquetDataBuffer buffer)
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{
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if (std::is_same_v<TColumn, ColumnDecimal<DateTime64>> && col_des.physical_type() == parquet::Type::INT96)
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return std::make_unique<ParquetPlainValuesReader<TColumn, ParquetReaderTypes::TimestampInt96>>(
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if constexpr (std::is_same_v<TColumn, ColumnDecimal<DateTime64>> && std::is_same_v<ParquetType, ParquetInt96TypeStub>)
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return std::make_unique<ParquetPlainInt96ValuesReader<TColumn>>(
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col_des.max_definition_level(), std::move(def_level_reader), std::move(buffer));
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return std::make_unique<ParquetPlainValuesReader<TColumn>>(
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if constexpr (std::is_same_v<ParquetType, ParquetByteArrayTypeStub>)
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{
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return std::make_unique<ParquetPlainByteArrayValuesReader<TColumn>>(
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col_des.max_definition_level(), std::move(def_level_reader), std::move(buffer));
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}
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return std::make_unique<ParquetPlainValuesReader<TColumn, ParquetType>>(
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col_des.max_definition_level(), std::move(def_level_reader), std::move(buffer));
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}
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template <typename TColumn, typename ParquetType>
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std::unique_ptr<ParquetDataValuesReader> createReader(
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const parquet::ColumnDescriptor & col_descriptor,
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RleValuesReaderPtr def_level_reader,
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const uint8_t * buffer,
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std::size_t buffer_max_size,
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const DataTypePtr & base_data_type)
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{
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if constexpr (std::is_same_v<ParquetType, bool>)
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{
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auto bit_reader = std::make_unique<arrow::bit_util::BitReader>(buffer, buffer_max_size);
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return std::make_unique<ParquetBitPlainReader<TColumn>>(
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col_descriptor.max_definition_level(), std::move(def_level_reader), std::move(bit_reader));
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}
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else
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{
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ParquetDataBuffer parquet_buffer = [&]()
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{
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if constexpr (!std::is_same_v<ColumnDecimal<DateTime64>, TColumn>)
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return ParquetDataBuffer(buffer, buffer_max_size);
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auto scale = assert_cast<const DataTypeDateTime64 &>(*base_data_type).getScale();
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return ParquetDataBuffer(buffer, buffer_max_size, scale);
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}();
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return createPlainReader<TColumn, ParquetType>(col_descriptor, std::move(def_level_reader), parquet_buffer);
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}
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}
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} // anonymous namespace
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template <typename TColumn>
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ParquetLeafColReader<TColumn>::ParquetLeafColReader(
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template <typename TColumn, typename ParquetType>
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ParquetLeafColReader<TColumn, ParquetType>::ParquetLeafColReader(
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const parquet::ColumnDescriptor & col_descriptor_,
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DataTypePtr base_type_,
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std::unique_ptr<parquet::ColumnChunkMetaData> meta_,
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@ -223,8 +254,8 @@ ParquetLeafColReader<TColumn>::ParquetLeafColReader(
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{
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}
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template <typename TColumn>
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ColumnWithTypeAndName ParquetLeafColReader<TColumn>::readBatch(UInt64 rows_num, const String & name)
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template <typename TColumn, typename ParquetType>
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ColumnWithTypeAndName ParquetLeafColReader<TColumn, ParquetType>::readBatch(UInt64 rows_num, const String & name)
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{
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reading_rows_num = rows_num;
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auto readPageIfEmpty = [&]()
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@ -251,8 +282,10 @@ ColumnWithTypeAndName ParquetLeafColReader<TColumn>::readBatch(UInt64 rows_num,
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return releaseColumn(name);
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}
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template <>
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void ParquetLeafColReader<ColumnString>::resetColumn(UInt64 rows_num)
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template <typename TColumn, typename ParquetType>
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void ParquetLeafColReader<TColumn, ParquetType>::resetColumn(UInt64 rows_num)
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{
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if constexpr (std::is_same_v<TColumn, ColumnString>)
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{
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if (reading_low_cardinality)
|
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{
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@ -273,9 +306,7 @@ void ParquetLeafColReader<ColumnString>::resetColumn(UInt64 rows_num)
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reserveColumnStrRows(column, rows_num);
|
||||
}
|
||||
}
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|
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template <typename TColumn>
|
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void ParquetLeafColReader<TColumn>::resetColumn(UInt64 rows_num)
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||||
else
|
||||
{
|
||||
assert(!reading_low_cardinality);
|
||||
|
||||
@ -283,9 +314,10 @@ void ParquetLeafColReader<TColumn>::resetColumn(UInt64 rows_num)
|
||||
column->reserve(rows_num);
|
||||
null_map = std::make_unique<LazyNullMap>(rows_num);
|
||||
}
|
||||
}
|
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|
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template <typename TColumn>
|
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void ParquetLeafColReader<TColumn>::degradeDictionary()
|
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template <typename TColumn, typename ParquetType>
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void ParquetLeafColReader<TColumn, ParquetType>::degradeDictionary()
|
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{
|
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// if last batch read all dictionary indices, then degrade is not needed this time
|
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if (!column)
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@ -331,8 +363,8 @@ void ParquetLeafColReader<TColumn>::degradeDictionary()
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LOG_DEBUG(log, "degraded dictionary to normal column");
|
||||
}
|
||||
|
||||
template <typename TColumn>
|
||||
ColumnWithTypeAndName ParquetLeafColReader<TColumn>::releaseColumn(const String & name)
|
||||
template <typename TColumn, typename ParquetType>
|
||||
ColumnWithTypeAndName ParquetLeafColReader<TColumn, ParquetType>::releaseColumn(const String & name)
|
||||
{
|
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DataTypePtr data_type = base_data_type;
|
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if (reading_low_cardinality)
|
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@ -365,8 +397,8 @@ ColumnWithTypeAndName ParquetLeafColReader<TColumn>::releaseColumn(const String
|
||||
return res;
|
||||
}
|
||||
|
||||
template <typename TColumn>
|
||||
void ParquetLeafColReader<TColumn>::readPage()
|
||||
template <typename TColumn, typename ParquetType>
|
||||
void ParquetLeafColReader<TColumn, ParquetType>::readPage()
|
||||
{
|
||||
// refer to: ColumnReaderImplBase::ReadNewPage in column_reader.cc
|
||||
// this is where decompression happens
|
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@ -408,8 +440,8 @@ void ParquetLeafColReader<TColumn>::readPage()
|
||||
}
|
||||
}
|
||||
|
||||
template <typename TColumn>
|
||||
void ParquetLeafColReader<TColumn>::initDataReader(
|
||||
template <typename TColumn, typename ParquetType>
|
||||
void ParquetLeafColReader<TColumn, ParquetType>::initDataReader(
|
||||
parquet::Encoding::type enconding_type,
|
||||
const uint8_t * buffer,
|
||||
std::size_t max_size,
|
||||
@ -425,29 +457,8 @@ void ParquetLeafColReader<TColumn>::initDataReader(
|
||||
degradeDictionary();
|
||||
}
|
||||
|
||||
if (col_descriptor.physical_type() == parquet::Type::BOOLEAN)
|
||||
{
|
||||
if constexpr (std::is_same_v<TColumn, ColumnUInt8>)
|
||||
{
|
||||
auto bit_reader = std::make_unique<arrow::bit_util::BitReader>(buffer, max_size);
|
||||
data_values_reader = std::make_unique<ParquetBitPlainReader<ColumnUInt8>>(col_descriptor.max_definition_level(),
|
||||
std::move(def_level_reader),
|
||||
std::move(bit_reader));
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
ParquetDataBuffer parquet_buffer = [&]()
|
||||
{
|
||||
if constexpr (!std::is_same_v<ColumnDecimal<DateTime64>, TColumn>)
|
||||
return ParquetDataBuffer(buffer, max_size);
|
||||
|
||||
auto scale = assert_cast<const DataTypeDateTime64 &>(*base_data_type).getScale();
|
||||
return ParquetDataBuffer(buffer, max_size, scale);
|
||||
}();
|
||||
data_values_reader = createPlainReader<TColumn>(
|
||||
col_descriptor, std::move(def_level_reader), std::move(parquet_buffer));
|
||||
}
|
||||
data_values_reader = createReader<TColumn, ParquetType>(
|
||||
col_descriptor, std::move(def_level_reader), buffer, max_size, base_data_type);
|
||||
break;
|
||||
}
|
||||
case parquet::Encoding::RLE_DICTIONARY:
|
||||
@ -476,8 +487,8 @@ void ParquetLeafColReader<TColumn>::initDataReader(
|
||||
}
|
||||
}
|
||||
|
||||
template <typename TColumn>
|
||||
void ParquetLeafColReader<TColumn>::readPageV1(const parquet::DataPageV1 & page)
|
||||
template <typename TColumn, typename ParquetType>
|
||||
void ParquetLeafColReader<TColumn, ParquetType>::readPageV1(const parquet::DataPageV1 & page)
|
||||
{
|
||||
cur_page_values = page.num_values();
|
||||
|
||||
@ -562,8 +573,8 @@ void ParquetLeafColReader<TColumn>::readPageV1(const parquet::DataPageV1 & page)
|
||||
* The data buffer is "offset-ed" by rl bytes length and then dl decoder is built using RLE decoder. Since dl bytes length was present in the header,
|
||||
* there is no need to read it and apply an offset like in page v1.
|
||||
* */
|
||||
template <typename TColumn>
|
||||
void ParquetLeafColReader<TColumn>::readPageV2(const parquet::DataPageV2 & page)
|
||||
template <typename TColumn, typename ParquetType>
|
||||
void ParquetLeafColReader<TColumn, ParquetType>::readPageV2(const parquet::DataPageV2 & page)
|
||||
{
|
||||
cur_page_values = page.num_values();
|
||||
|
||||
@ -609,11 +620,19 @@ void ParquetLeafColReader<TColumn>::readPageV2(const parquet::DataPageV2 & page)
|
||||
initDataReader(page.encoding(), buffer, page.size() - total_levels_length, std::move(def_level_reader));
|
||||
}
|
||||
|
||||
template <typename TColumn>
|
||||
std::unique_ptr<ParquetDataValuesReader> ParquetLeafColReader<TColumn>::createDictReader(
|
||||
template <typename TColumn, typename ParquetType>
|
||||
std::unique_ptr<ParquetDataValuesReader> ParquetLeafColReader<TColumn, ParquetType>::createDictReader(
|
||||
std::unique_ptr<RleValuesReader> def_level_reader, std::unique_ptr<RleValuesReader> rle_data_reader)
|
||||
{
|
||||
if (reading_low_cardinality && std::same_as<TColumn, ColumnString>)
|
||||
if constexpr (std::is_same_v<TColumn, ColumnUInt8> || std::is_same_v<TColumn, ColumnInt8>
|
||||
|| std::is_same_v<TColumn, ColumnUInt16> || std::is_same_v<TColumn, ColumnInt16>)
|
||||
{
|
||||
throw Exception(ErrorCodes::NOT_IMPLEMENTED, "Dictionary encoding for booleans is not supported");
|
||||
}
|
||||
|
||||
if (reading_low_cardinality)
|
||||
{
|
||||
if constexpr (std::same_as<TColumn, ColumnString>)
|
||||
{
|
||||
std::unique_ptr<ParquetDataValuesReader> res;
|
||||
visitColStrIndexType(dictionary->size(), [&]<typename TCol>(TCol *)
|
||||
@ -625,10 +644,6 @@ std::unique_ptr<ParquetDataValuesReader> ParquetLeafColReader<TColumn>::createDi
|
||||
});
|
||||
return res;
|
||||
}
|
||||
|
||||
if (col_descriptor.physical_type() == parquet::Type::type::BOOLEAN)
|
||||
{
|
||||
throw Exception(ErrorCodes::NOT_IMPLEMENTED, "Dictionary encoding for booleans is not supported");
|
||||
}
|
||||
|
||||
return std::make_unique<ParquetRleDictReader<TColumn>>(
|
||||
@ -639,19 +654,23 @@ std::unique_ptr<ParquetDataValuesReader> ParquetLeafColReader<TColumn>::createDi
|
||||
}
|
||||
|
||||
|
||||
template class ParquetLeafColReader<ColumnUInt8>;
|
||||
template class ParquetLeafColReader<ColumnInt32>;
|
||||
template class ParquetLeafColReader<ColumnUInt32>;
|
||||
template class ParquetLeafColReader<ColumnInt64>;
|
||||
template class ParquetLeafColReader<ColumnUInt64>;
|
||||
template class ParquetLeafColReader<ColumnBFloat16>;
|
||||
template class ParquetLeafColReader<ColumnFloat32>;
|
||||
template class ParquetLeafColReader<ColumnFloat64>;
|
||||
template class ParquetLeafColReader<ColumnString>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<Decimal32>>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<Decimal64>>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<Decimal128>>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<Decimal256>>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<DateTime64>>;
|
||||
template class ParquetLeafColReader<ColumnUInt8, bool>;
|
||||
template class ParquetLeafColReader<ColumnUInt8, int32_t>;
|
||||
template class ParquetLeafColReader<ColumnInt8, int32_t>;
|
||||
template class ParquetLeafColReader<ColumnUInt16, int32_t>;
|
||||
template class ParquetLeafColReader<ColumnInt16, int32_t>;
|
||||
template class ParquetLeafColReader<ColumnUInt32, int32_t>;
|
||||
template class ParquetLeafColReader<ColumnInt32, int32_t>;
|
||||
template class ParquetLeafColReader<ColumnUInt64, int64_t>;
|
||||
template class ParquetLeafColReader<ColumnInt64, int64_t>;
|
||||
template class ParquetLeafColReader<ColumnFloat32, float>;
|
||||
template class ParquetLeafColReader<ColumnFloat64, double>;
|
||||
template class ParquetLeafColReader<ColumnString, ParquetByteArrayTypeStub>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<Decimal32>, int32_t>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<Decimal64>, int64_t>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<Decimal128>, ParquetByteArrayTypeStub>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<Decimal256>, ParquetByteArrayTypeStub>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<DateTime64>, ParquetInt96TypeStub>;
|
||||
template class ParquetLeafColReader<ColumnDecimal<DateTime64>, int64_t>;
|
||||
|
||||
}
|
||||
|
||||
@ -17,7 +17,10 @@ class ColumnDescriptor;
|
||||
namespace DB
|
||||
{
|
||||
|
||||
template <typename TColumn>
|
||||
struct ParquetByteArrayTypeStub {};
|
||||
struct ParquetInt96TypeStub {};
|
||||
|
||||
template <typename TColumn, typename ParquetType>
|
||||
class ParquetLeafColReader : public ParquetColumnReader
|
||||
{
|
||||
public:
|
||||
|
||||
@ -93,19 +93,20 @@ private:
|
||||
std::unique_ptr<ParquetColumnReader> fromInt32INT(const parquet::IntLogicalType & int_type);
|
||||
std::unique_ptr<ParquetColumnReader> fromInt64INT(const parquet::IntLogicalType & int_type);
|
||||
|
||||
template<class DataType>
|
||||
template<class ClickHouseType, typename ParquetType>
|
||||
auto makeLeafReader()
|
||||
{
|
||||
return std::make_unique<ParquetLeafColReader<typename DataType::ColumnType>>(
|
||||
col_descriptor, std::make_shared<DataType>(), std::move(meta), std::move(page_reader));
|
||||
return std::make_unique<ParquetLeafColReader<typename ClickHouseType::ColumnType, ParquetType>>(
|
||||
col_descriptor, std::make_shared<ClickHouseType>(), std::move(meta), std::move(page_reader));
|
||||
}
|
||||
|
||||
template<class DecimalType>
|
||||
template<class DecimalType, typename ParquetType>
|
||||
auto makeDecimalLeafReader()
|
||||
{
|
||||
auto data_type = std::make_shared<DataTypeDecimal<DecimalType>>(
|
||||
col_descriptor.type_precision(), col_descriptor.type_scale());
|
||||
return std::make_unique<ParquetLeafColReader<ColumnDecimal<DecimalType>>>(
|
||||
|
||||
return std::make_unique<ParquetLeafColReader<ColumnDecimal<DecimalType>, ParquetType>>(
|
||||
col_descriptor, std::move(data_type), std::move(meta), std::move(page_reader));
|
||||
}
|
||||
|
||||
@ -157,11 +158,11 @@ std::unique_ptr<ParquetColumnReader> ColReaderFactory::fromInt32()
|
||||
case parquet::LogicalType::Type::INT:
|
||||
return fromInt32INT(dynamic_cast<const parquet::IntLogicalType &>(*col_descriptor.logical_type()));
|
||||
case parquet::LogicalType::Type::NONE:
|
||||
return makeLeafReader<DataTypeInt32>();
|
||||
return makeLeafReader<DataTypeInt32, int32_t>();
|
||||
case parquet::LogicalType::Type::DATE:
|
||||
return makeLeafReader<DataTypeDate32>();
|
||||
return makeLeafReader<DataTypeDate32, int32_t>();
|
||||
case parquet::LogicalType::Type::DECIMAL:
|
||||
return makeDecimalLeafReader<Decimal32>();
|
||||
return makeDecimalLeafReader<Decimal32, int32_t>();
|
||||
default:
|
||||
return throwUnsupported();
|
||||
}
|
||||
@ -174,16 +175,16 @@ std::unique_ptr<ParquetColumnReader> ColReaderFactory::fromInt64()
|
||||
case parquet::LogicalType::Type::INT:
|
||||
return fromInt64INT(dynamic_cast<const parquet::IntLogicalType &>(*col_descriptor.logical_type()));
|
||||
case parquet::LogicalType::Type::NONE:
|
||||
return makeLeafReader<DataTypeInt64>();
|
||||
return makeLeafReader<DataTypeInt64, int64_t>();
|
||||
case parquet::LogicalType::Type::TIMESTAMP:
|
||||
{
|
||||
const auto & tm_type = dynamic_cast<const parquet::TimestampLogicalType &>(*col_descriptor.logical_type());
|
||||
auto read_type = std::make_shared<DataTypeDateTime64>(getScaleFromLogicalTimestamp(tm_type.time_unit()));
|
||||
return std::make_unique<ParquetLeafColReader<ColumnDecimal<DateTime64>>>(
|
||||
return std::make_unique<ParquetLeafColReader<ColumnDecimal<DateTime64>, int64_t>>(
|
||||
col_descriptor, std::move(read_type), std::move(meta), std::move(page_reader));
|
||||
}
|
||||
case parquet::LogicalType::Type::DECIMAL:
|
||||
return makeDecimalLeafReader<Decimal64>();
|
||||
return makeDecimalLeafReader<Decimal64, int64_t>();
|
||||
default:
|
||||
return throwUnsupported();
|
||||
}
|
||||
@ -195,7 +196,7 @@ std::unique_ptr<ParquetColumnReader> ColReaderFactory::fromByteArray()
|
||||
{
|
||||
case parquet::LogicalType::Type::STRING:
|
||||
case parquet::LogicalType::Type::NONE:
|
||||
return makeLeafReader<DataTypeString>();
|
||||
return makeLeafReader<DataTypeString, ParquetByteArrayTypeStub>();
|
||||
default:
|
||||
return throwUnsupported();
|
||||
}
|
||||
@ -210,9 +211,9 @@ std::unique_ptr<ParquetColumnReader> ColReaderFactory::fromFLBA()
|
||||
if (col_descriptor.type_length() > 0)
|
||||
{
|
||||
if (col_descriptor.type_length() <= static_cast<int>(sizeof(Decimal128)))
|
||||
return makeDecimalLeafReader<Decimal128>();
|
||||
return makeDecimalLeafReader<Decimal128, ParquetByteArrayTypeStub>();
|
||||
if (col_descriptor.type_length() <= static_cast<int>(sizeof(Decimal256)))
|
||||
return makeDecimalLeafReader<Decimal256>();
|
||||
return makeDecimalLeafReader<Decimal256, ParquetByteArrayTypeStub>();
|
||||
}
|
||||
|
||||
return throwUnsupported(PreformattedMessage::create(
|
||||
@ -227,11 +228,23 @@ std::unique_ptr<ParquetColumnReader> ColReaderFactory::fromInt32INT(const parque
|
||||
{
|
||||
switch (int_type.bit_width())
|
||||
{
|
||||
case 8:
|
||||
{
|
||||
if (int_type.is_signed())
|
||||
return makeLeafReader<DataTypeInt8, int32_t>();
|
||||
return makeLeafReader<DataTypeUInt8, int32_t>();
|
||||
}
|
||||
case 16:
|
||||
{
|
||||
if (int_type.is_signed())
|
||||
return makeLeafReader<DataTypeInt16, int32_t>();
|
||||
return makeLeafReader<DataTypeUInt16, int32_t>();
|
||||
}
|
||||
case 32:
|
||||
{
|
||||
if (int_type.is_signed())
|
||||
return makeLeafReader<DataTypeInt32>();
|
||||
return makeLeafReader<DataTypeUInt32>();
|
||||
return makeLeafReader<DataTypeInt32, int32_t>();
|
||||
return makeLeafReader<DataTypeUInt32, int32_t>();
|
||||
}
|
||||
default:
|
||||
return throwUnsupported(PreformattedMessage::create(", bit width: {}", int_type.bit_width()));
|
||||
@ -245,8 +258,8 @@ std::unique_ptr<ParquetColumnReader> ColReaderFactory::fromInt64INT(const parque
|
||||
case 64:
|
||||
{
|
||||
if (int_type.is_signed())
|
||||
return makeLeafReader<DataTypeInt64>();
|
||||
return makeLeafReader<DataTypeUInt64>();
|
||||
return makeLeafReader<DataTypeInt64, int64_t>();
|
||||
return makeLeafReader<DataTypeUInt64, int64_t>();
|
||||
}
|
||||
default:
|
||||
return throwUnsupported(PreformattedMessage::create(", bit width: {}", int_type.bit_width()));
|
||||
@ -263,7 +276,7 @@ std::unique_ptr<ParquetColumnReader> ColReaderFactory::makeReader()
|
||||
switch (col_descriptor.physical_type())
|
||||
{
|
||||
case parquet::Type::BOOLEAN:
|
||||
return makeLeafReader<DataTypeUInt8>();
|
||||
return makeLeafReader<DataTypeUInt8, bool>();
|
||||
case parquet::Type::INT32:
|
||||
return fromInt32();
|
||||
case parquet::Type::INT64:
|
||||
@ -276,13 +289,13 @@ std::unique_ptr<ParquetColumnReader> ColReaderFactory::makeReader()
|
||||
auto scale = getScaleFromArrowTimeUnit(arrow_properties.coerce_int96_timestamp_unit());
|
||||
read_type = std::make_shared<DataTypeDateTime64>(scale);
|
||||
}
|
||||
return std::make_unique<ParquetLeafColReader<ColumnDecimal<DateTime64>>>(
|
||||
return std::make_unique<ParquetLeafColReader<ColumnDecimal<DateTime64>, ParquetInt96TypeStub>>(
|
||||
col_descriptor, read_type, std::move(meta), std::move(page_reader));
|
||||
}
|
||||
case parquet::Type::FLOAT:
|
||||
return makeLeafReader<DataTypeFloat32>();
|
||||
return makeLeafReader<DataTypeFloat32, float>();
|
||||
case parquet::Type::DOUBLE:
|
||||
return makeLeafReader<DataTypeFloat64>();
|
||||
return makeLeafReader<DataTypeFloat64, double>();
|
||||
case parquet::Type::BYTE_ARRAY:
|
||||
return fromByteArray();
|
||||
case parquet::Type::FIXED_LEN_BYTE_ARRAY:
|
||||
|
||||
@ -0,0 +1,40 @@
|
||||
-94 53304 17815465730223871
|
||||
57 15888 33652524900575246
|
||||
-4 14877 53832092832965652
|
||||
33 3387 86326601511136103
|
||||
104 3383 115438187156564782
|
||||
-11 37403 145056169255259589
|
||||
-72 46473 159324626361233509
|
||||
103 35510 173644182696185097
|
||||
-26 60902 185175917734318892
|
||||
70 48767 193167023342307884
|
||||
2 21648 247953090704786001
|
||||
20 2986 268127160817221407
|
||||
76 20277 290178827409195337
|
||||
61 28692 305149163504092270
|
||||
-74 65427 326871531363668398
|
||||
-15 20256 351812901947846888
|
||||
-39 65472 357371822264135234
|
||||
79 38671 371605113770958364
|
||||
-29 41706 394460710549666968
|
||||
92 25026 412913269933311543
|
||||
-94 53304 17815465730223871
|
||||
57 15888 33652524900575246
|
||||
-4 14877 53832092832965652
|
||||
33 3387 86326601511136103
|
||||
104 3383 115438187156564782
|
||||
-11 37403 145056169255259589
|
||||
-72 46473 159324626361233509
|
||||
103 35510 173644182696185097
|
||||
-26 60902 185175917734318892
|
||||
70 48767 193167023342307884
|
||||
2 21648 247953090704786001
|
||||
20 2986 268127160817221407
|
||||
76 20277 290178827409195337
|
||||
61 28692 305149163504092270
|
||||
-74 65427 326871531363668398
|
||||
-15 20256 351812901947846888
|
||||
-39 65472 357371822264135234
|
||||
79 38671 371605113770958364
|
||||
-29 41706 394460710549666968
|
||||
92 25026 412913269933311543
|
||||
@ -0,0 +1,22 @@
|
||||
#!/usr/bin/env bash
|
||||
# Tags: no-ubsan, no-fasttest
|
||||
|
||||
CUR_DIR=$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)
|
||||
# shellcheck source=../shell_config.sh
|
||||
. "$CUR_DIR"/../shell_config.sh
|
||||
|
||||
|
||||
USER_FILES_PATH=$($CLICKHOUSE_CLIENT_BINARY --query "select _path,_file from file('nonexist.txt', 'CSV', 'val1 char')" 2>&1 | grep Exception | awk '{gsub("/nonexist.txt","",$9); print $9}')
|
||||
|
||||
WORKING_DIR="${USER_FILES_PATH}/${CLICKHOUSE_TEST_UNIQUE_NAME}"
|
||||
|
||||
mkdir -p "${WORKING_DIR}"
|
||||
|
||||
DATA_FILE="${CUR_DIR}/data_parquet/multi_column_bf.gz.parquet"
|
||||
|
||||
DATA_FILE_USER_PATH="${WORKING_DIR}/multi_column_bf.gz.parquet"
|
||||
|
||||
cp ${DATA_FILE} ${DATA_FILE_USER_PATH}
|
||||
|
||||
${CLICKHOUSE_CLIENT} --query="select int8_logical, uint16_logical, uint64_logical from file('${DATA_FILE_USER_PATH}', Parquet) order by uint64_logical limit 20 SETTINGS input_format_parquet_use_native_reader=false;";
|
||||
${CLICKHOUSE_CLIENT} --query="select int8_logical, uint16_logical, uint64_logical from file('${DATA_FILE_USER_PATH}', Parquet) order by uint64_logical limit 20 SETTINGS input_format_parquet_use_native_reader=true;";
|
||||
Loading…
Reference in New Issue
Block a user