// 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.

#pragma once

#include <memory>
#include <string>
#include <unordered_map>
#include <unordered_set>
#include <utility>

#include "arrow/io/caching.h"
#include "arrow/type_fwd.h"
#include "arrow/util/compression.h"
#include "arrow/util/type_fwd.h"
#include "parquet/encryption/encryption.h"
#include "parquet/exception.h"
#include "parquet/parquet_version.h"
#include "parquet/platform.h"
#include "parquet/schema.h"
#include "parquet/type_fwd.h"
#include "parquet/types.h"

namespace parquet {

/// Controls serialization format of data pages.  parquet-format v2.0.0
/// introduced a new data page metadata type DataPageV2 and serialized page
/// structure (for example, encoded levels are no longer compressed). Prior to
/// the completion of PARQUET-457 in 2020, this library did not implement
/// DataPageV2 correctly, so if you use the V2 data page format, you may have
/// forward compatibility issues (older versions of the library will be unable
/// to read the files). Note that some Parquet implementations do not implement
/// DataPageV2 at all.
enum class ParquetDataPageVersion { V1, V2 };

/// Controls the level of size statistics that are written to the file.
enum class SizeStatisticsLevel : uint8_t {
  // No size statistics are written.
  None = 0,
  // Only column chunk size statistics are written.
  ColumnChunk,
  // Both size statistics in the column chunk and page index are written.
  PageAndColumnChunk
};

/// Align the default buffer size to a small multiple of a page size.
constexpr int64_t kDefaultBufferSize = 4096 * 4;

constexpr int32_t kDefaultThriftStringSizeLimit = 100 * 1000 * 1000;
// Structs in the thrift definition are relatively large (at least 300 bytes).
// This limits total memory to the same order of magnitude as
// kDefaultStringSizeLimit.
constexpr int32_t kDefaultThriftContainerSizeLimit = 1000 * 1000;

// PARQUET-978: Minimize footer reads by reading 64 KB from the end of the file
constexpr int64_t kDefaultFooterReadSize = 64 * 1024;

class PARQUET_EXPORT ReaderProperties {
 public:
  explicit ReaderProperties(MemoryPool* pool = ::arrow::default_memory_pool())
      : pool_(pool) {}

  MemoryPool* memory_pool() const { return pool_; }

  std::shared_ptr<ArrowInputStream> GetStream(std::shared_ptr<ArrowInputFile> source,
                                              int64_t start, int64_t num_bytes);

  /// Buffered stream reading allows the user to control the memory usage of
  /// parquet readers. This ensure that all `RandomAccessFile::ReadAt` calls are
  /// wrapped in a buffered reader that uses a fix sized buffer (of size
  /// `buffer_size()`) instead of the full size of the ReadAt.
  ///
  /// The primary reason for this control knobs is for resource control and not
  /// performance.
  bool is_buffered_stream_enabled() const { return buffered_stream_enabled_; }
  /// Enable buffered stream reading.
  void enable_buffered_stream() { buffered_stream_enabled_ = true; }
  /// Disable buffered stream reading.
  void disable_buffered_stream() { buffered_stream_enabled_ = false; }

  bool read_dense_for_nullable() const { return read_dense_for_nullable_; }
  void enable_read_dense_for_nullable() { read_dense_for_nullable_ = true; }
  void disable_read_dense_for_nullable() { read_dense_for_nullable_ = false; }

  /// Return the size of the buffered stream buffer.
  int64_t buffer_size() const { return buffer_size_; }
  /// Set the size of the buffered stream buffer in bytes.
  void set_buffer_size(int64_t size) { buffer_size_ = size; }

  /// \brief Return the size limit on thrift strings.
  ///
  /// This limit helps prevent space and time bombs in files, but may need to
  /// be increased in order to read files with especially large headers.
  int32_t thrift_string_size_limit() const { return thrift_string_size_limit_; }
  /// Set the size limit on thrift strings.
  void set_thrift_string_size_limit(int32_t size) { thrift_string_size_limit_ = size; }

  /// \brief Return the size limit on thrift containers.
  ///
  /// This limit helps prevent space and time bombs in files, but may need to
  /// be increased in order to read files with especially large headers.
  int32_t thrift_container_size_limit() const { return thrift_container_size_limit_; }
  /// Set the size limit on thrift containers.
  void set_thrift_container_size_limit(int32_t size) {
    thrift_container_size_limit_ = size;
  }

  /// Set the decryption properties.
  void file_decryption_properties(std::shared_ptr<FileDecryptionProperties> decryption) {
    file_decryption_properties_ = std::move(decryption);
  }
  /// Return the decryption properties.
  const std::shared_ptr<FileDecryptionProperties>& file_decryption_properties() const {
    return file_decryption_properties_;
  }

  bool page_checksum_verification() const { return page_checksum_verification_; }
  void set_page_checksum_verification(bool check_crc) {
    page_checksum_verification_ = check_crc;
  }

  // Set the default read size to read the footer from a file. For high latency
  // file systems and files with large metadata (>64KB) this can increase performance
  // by reducing the number of round-trips to retrieve the entire file metadata.
  void set_footer_read_size(size_t size) { footer_read_size_ = size; }
  size_t footer_read_size() const { return footer_read_size_; }

 private:
  MemoryPool* pool_;
  int64_t buffer_size_ = kDefaultBufferSize;
  int32_t thrift_string_size_limit_ = kDefaultThriftStringSizeLimit;
  int32_t thrift_container_size_limit_ = kDefaultThriftContainerSizeLimit;
  bool buffered_stream_enabled_ = false;
  bool page_checksum_verification_ = false;
  // Used with a RecordReader.
  bool read_dense_for_nullable_ = false;
  size_t footer_read_size_ = kDefaultFooterReadSize;
  std::shared_ptr<FileDecryptionProperties> file_decryption_properties_;
};

ReaderProperties PARQUET_EXPORT default_reader_properties();

static constexpr int64_t kDefaultDataPageSize = 1024 * 1024;
static constexpr int64_t kDefaultMaxRowsPerPage = 20'000;
static constexpr bool DEFAULT_IS_DICTIONARY_ENABLED = true;
static constexpr int64_t DEFAULT_DICTIONARY_PAGE_SIZE_LIMIT = kDefaultDataPageSize;
static constexpr int64_t DEFAULT_WRITE_BATCH_SIZE = 1024;
static constexpr int64_t DEFAULT_MAX_ROW_GROUP_LENGTH = 1024 * 1024;
static constexpr bool DEFAULT_ARE_STATISTICS_ENABLED = true;
static constexpr int64_t DEFAULT_MAX_STATISTICS_SIZE = 4096;
static constexpr Encoding::type DEFAULT_ENCODING = Encoding::UNKNOWN;
static const char DEFAULT_CREATED_BY[] = CREATED_BY_VERSION;
static constexpr Compression::type DEFAULT_COMPRESSION_TYPE = Compression::UNCOMPRESSED;
static constexpr bool DEFAULT_IS_PAGE_INDEX_ENABLED = true;
static constexpr SizeStatisticsLevel DEFAULT_SIZE_STATISTICS_LEVEL =
    SizeStatisticsLevel::PageAndColumnChunk;

struct PARQUET_EXPORT BloomFilterOptions {
  /// Expected number of distinct values (NDV) in the bloom filter.
  ///
  /// Bloom filters are most effective for high-cardinality columns. A good default
  /// is to set ndv equal to the number of rows. Lower values reduce disk usage but
  /// may not be worthwhile for very small NDVs.
  ///
  /// Increasing ndv (without increasing fpp) increases disk and memory usage.
  int32_t ndv = 1 << 20;

  /// False-positive probability (FPP) of the bloom filter.
  ///
  /// Lower FPP values require more disk and memory space. For a fixed ndv, the
  /// space requirement grows roughly proportional to log(1/fpp). Recommended
  /// values are 0.1, 0.05, or 0.01. Very small values are counterproductive as
  /// the bitset may exceed the size of the actual data. Set ndv appropriately
  /// to minimize space usage.
  ///
  /// Below is a table to demonstrate estimated size using common values.
  ///
  /// | ndv        | fpp   | bits/key | size      |
  /// |:-----------|:------|:---------|:----------|
  /// | 100,000    | 0.10  | 10.5     | 128 KiB   |
  /// | 100,000    | 0.05  | 10.5     | 128 KiB   |
  /// | 100,000    | 0.01  | 10.5     | 128 KiB   |
  /// | 1,000,000  | 0.10  | 8.4      | 1024 KiB  |
  /// | 1,000,000  | 0.05  | 8.4      | 1024 KiB  |
  /// | 1,000,000  | 0.01  | 16.8     | 2048 KiB  |
  /// | 10,000,000 | 0.10  | 6.7      | 8192 KiB  |
  /// | 10,000,000 | 0.05  | 13.4     | 16384 KiB |
  /// | 10,000,000 | 0.01  | 13.4     | 16384 KiB |
  double fpp = 0.05;
};

class PARQUET_EXPORT ColumnProperties {
 public:
  ColumnProperties(Encoding::type encoding = DEFAULT_ENCODING,
                   Compression::type codec = DEFAULT_COMPRESSION_TYPE,
                   bool dictionary_enabled = DEFAULT_IS_DICTIONARY_ENABLED,
                   bool statistics_enabled = DEFAULT_ARE_STATISTICS_ENABLED,
                   size_t max_stats_size = DEFAULT_MAX_STATISTICS_SIZE,
                   bool page_index_enabled = DEFAULT_IS_PAGE_INDEX_ENABLED)
      : encoding_(encoding),
        codec_(codec),
        dictionary_enabled_(dictionary_enabled),
        statistics_enabled_(statistics_enabled),
        max_stats_size_(max_stats_size),
        page_index_enabled_(page_index_enabled) {}

  void set_encoding(Encoding::type encoding) { encoding_ = encoding; }

  void set_compression(Compression::type codec) { codec_ = codec; }

  void set_dictionary_enabled(bool dictionary_enabled) {
    dictionary_enabled_ = dictionary_enabled;
  }

  void set_statistics_enabled(bool statistics_enabled) {
    statistics_enabled_ = statistics_enabled;
  }

  void set_max_statistics_size(size_t max_stats_size) {
    max_stats_size_ = max_stats_size;
  }

  void set_compression_level(int compression_level) {
    if (!codec_options_) {
      codec_options_ = std::make_shared<CodecOptions>();
    }
    codec_options_->compression_level = compression_level;
  }

  void set_codec_options(const std::shared_ptr<CodecOptions>& codec_options) {
    codec_options_ = codec_options;
  }

  void set_page_index_enabled(bool page_index_enabled) {
    page_index_enabled_ = page_index_enabled;
  }

  void set_bloom_filter_options(const BloomFilterOptions& bloom_filter_options) {
    if (bloom_filter_options.fpp >= 1.0 || bloom_filter_options.fpp <= 0.0) {
      throw ParquetException(
          "Bloom filter false positive probability must be in (0.0, 1.0), got " +
          std::to_string(bloom_filter_options.fpp));
    }
    bloom_filter_options_ = bloom_filter_options;
  }

  Encoding::type encoding() const { return encoding_; }

  Compression::type compression() const { return codec_; }

  bool dictionary_enabled() const { return dictionary_enabled_; }

  bool statistics_enabled() const { return statistics_enabled_; }

  size_t max_statistics_size() const { return max_stats_size_; }

  int compression_level() const {
    if (!codec_options_) {
      return ::arrow::util::kUseDefaultCompressionLevel;
    }
    return codec_options_->compression_level;
  }

  const std::shared_ptr<CodecOptions>& codec_options() const { return codec_options_; }

  bool page_index_enabled() const { return page_index_enabled_; }

  std::optional<BloomFilterOptions> bloom_filter_options() const {
    return bloom_filter_options_;
  }

  bool bloom_filter_enabled() const { return bloom_filter_options_.has_value(); }

 private:
  Encoding::type encoding_;
  Compression::type codec_;
  bool dictionary_enabled_;
  bool statistics_enabled_;
  size_t max_stats_size_;
  std::shared_ptr<CodecOptions> codec_options_;
  bool page_index_enabled_;
  std::optional<BloomFilterOptions> bloom_filter_options_;
};

// EXPERIMENTAL: Options for content-defined chunking.
///
/// Content-defined chunking is an experimental feature that optimizes parquet
/// files for content addressable storage (CAS) systems by writing data pages
/// according to content-defined chunk boundaries. This allows for more
/// efficient deduplication of data across files, hence more efficient network
/// transfers and storage.
/// Each content-defined chunk is written as a separate parquet data page. The
/// following options control the chunks' size and the chunking process. Note
/// that the chunk size is calculated based on the logical value of the data,
/// before any encoding or compression is applied.
struct PARQUET_EXPORT CdcOptions {
  /// Minimum chunk size in bytes, default is 256 KiB
  /// The rolling hash will not be updated until this size is reached for each chunk.
  /// Note that all data sent through the hash function is counted towards the chunk
  /// size, including definition and repetition levels if present.
  int64_t min_chunk_size = 256 * 1024;
  /// Maximum chunk size in bytes, default is 1024 KiB
  /// The chunker will create a new chunk whenever the chunk size exceeds this value.
  /// Note that the parquet writer has a related `pagesize` property that controls
  /// the maximum size of a parquet data page after encoding. While setting
  /// `pagesize` to a smaller value than `max_chunk_size` doesn't affect the
  /// chunking effectiveness, it results in more small parquet data pages.
  int64_t max_chunk_size = 1024 * 1024;
  /// Number of bit adjustment to the gearhash mask in order to center the chunk size
  /// around the average size more aggressively, default is 0
  /// Increasing the normalization level increases the probability of finding a chunk,
  /// improving the deduplication ratio, but also increasing the number of small chunks
  /// resulting in many small parquet data pages. The default value provides a good
  /// balance between deduplication ratio and fragmentation.
  /// Use norm_level=1 or norm_level=2 to reach a higher deduplication ratio at the
  /// expense of fragmentation. Negative values can also be used to reduce the
  /// probability of finding a chunk, resulting in larger chunks and fewer data pages.
  /// Note that values outside [-3, 3] are not recommended, prefer using the default
  /// value of 0 for most use cases.
  int norm_level = 0;
};

class PARQUET_EXPORT WriterProperties {
 public:
  class PARQUET_EXPORT Builder {
   public:
    Builder()
        : pool_(::arrow::default_memory_pool()),
          dictionary_pagesize_limit_(DEFAULT_DICTIONARY_PAGE_SIZE_LIMIT),
          write_batch_size_(DEFAULT_WRITE_BATCH_SIZE),
          max_row_group_length_(DEFAULT_MAX_ROW_GROUP_LENGTH),
          pagesize_(kDefaultDataPageSize),
          max_rows_per_page_(kDefaultMaxRowsPerPage),
          version_(ParquetVersion::PARQUET_2_6),
          data_page_version_(ParquetDataPageVersion::V1),
          created_by_(DEFAULT_CREATED_BY),
          store_decimal_as_integer_(false),
          page_checksum_enabled_(false),
          size_statistics_level_(DEFAULT_SIZE_STATISTICS_LEVEL),
          content_defined_chunking_enabled_(false),
          content_defined_chunking_options_({}) {}

    explicit Builder(const WriterProperties& properties)
        : pool_(properties.memory_pool()),
          dictionary_pagesize_limit_(properties.dictionary_pagesize_limit()),
          write_batch_size_(properties.write_batch_size()),
          max_row_group_length_(properties.max_row_group_length()),
          pagesize_(properties.data_pagesize()),
          max_rows_per_page_(properties.max_rows_per_page()),
          version_(properties.version()),
          data_page_version_(properties.data_page_version()),
          created_by_(properties.created_by()),
          store_decimal_as_integer_(properties.store_decimal_as_integer()),
          page_checksum_enabled_(properties.page_checksum_enabled()),
          size_statistics_level_(properties.size_statistics_level()),
          sorting_columns_(properties.sorting_columns()),
          default_column_properties_(properties.default_column_properties()),
          content_defined_chunking_enabled_(
              properties.content_defined_chunking_enabled()),
          content_defined_chunking_options_(
              properties.content_defined_chunking_options()) {
      CopyColumnSpecificProperties(properties);
    }

    /// \brief EXPERIMENTAL: Use content-defined page chunking for all columns.
    ///
    /// Optimize parquet files for content addressable storage (CAS) systems by writing
    /// data pages according to content-defined chunk boundaries. This allows for more
    /// efficient deduplication of data across files, hence more efficient network
    /// transfers and storage. The chunking is based on a rolling hash algorithm that
    /// identifies chunk boundaries based on the actual content of the data.
    ///
    /// Note that only the WriteArrow() interface is supported at the moment.
    Builder* enable_content_defined_chunking() {
      content_defined_chunking_enabled_ = true;
      return this;
    }

    /// \brief EXPERIMENTAL: Disable content-defined page chunking for all columns.
    Builder* disable_content_defined_chunking() {
      content_defined_chunking_enabled_ = false;
      return this;
    }

    /// \brief EXPERIMENTAL: Specify content-defined chunking options, see CdcOptions.
    Builder* content_defined_chunking_options(const CdcOptions& options) {
      content_defined_chunking_options_ = options;
      return this;
    }

    /// Specify the memory pool for the writer. Default default_memory_pool.
    Builder* memory_pool(MemoryPool* pool) {
      pool_ = pool;
      return this;
    }

    /// Enable dictionary encoding in general for all columns. Default
    /// enabled.
    Builder* enable_dictionary() {
      default_column_properties_.set_dictionary_enabled(true);
      return this;
    }

    /// Disable dictionary encoding in general for all columns. Default
    /// enabled.
    Builder* disable_dictionary() {
      default_column_properties_.set_dictionary_enabled(false);
      return this;
    }

    /// Enable dictionary encoding for column specified by `path`. Default
    /// enabled.
    Builder* enable_dictionary(const std::string& path) {
      dictionary_enabled_[path] = true;
      return this;
    }

    /// Enable dictionary encoding for column specified by `path`. Default
    /// enabled.
    Builder* enable_dictionary(const std::shared_ptr<schema::ColumnPath>& path) {
      return this->enable_dictionary(path->ToDotString());
    }

    /// Disable dictionary encoding for column specified by `path`. Default
    /// enabled.
    Builder* disable_dictionary(const std::string& path) {
      dictionary_enabled_[path] = false;
      return this;
    }

    /// Disable dictionary encoding for column specified by `path`. Default
    /// enabled.
    Builder* disable_dictionary(const std::shared_ptr<schema::ColumnPath>& path) {
      return this->disable_dictionary(path->ToDotString());
    }

    /// Specify the dictionary page size limit per row group. Default 1MB.
    Builder* dictionary_pagesize_limit(int64_t dictionary_psize_limit) {
      dictionary_pagesize_limit_ = dictionary_psize_limit;
      return this;
    }

    /// Specify the write batch size while writing batches of Arrow values
    /// into Parquet. Default 1024.
    Builder* write_batch_size(int64_t write_batch_size) {
      write_batch_size_ = write_batch_size;
      return this;
    }

    /// Specify the max number of rows to put in a single row group.
    /// Default 1Mi rows.
    Builder* max_row_group_length(int64_t max_row_group_length) {
      max_row_group_length_ = max_row_group_length;
      return this;
    }

    /// Specify the data page size.
    /// Default 1MB.
    Builder* data_pagesize(int64_t pg_size) {
      pagesize_ = pg_size;
      return this;
    }

    /// Specify the maximum number of rows per data page.
    /// Default 20K rows.
    Builder* max_rows_per_page(int64_t max_rows) {
      max_rows_per_page_ = max_rows;
      return this;
    }

    /// Specify the data page version.
    /// Default V1.
    Builder* data_page_version(ParquetDataPageVersion data_page_version) {
      data_page_version_ = data_page_version;
      return this;
    }

    /// Specify the Parquet file version.
    /// Default PARQUET_2_6.
    Builder* version(ParquetVersion::type version) {
      version_ = version;
      return this;
    }

    Builder* created_by(const std::string& created_by) {
      created_by_ = created_by;
      return this;
    }

    Builder* enable_page_checksum() {
      page_checksum_enabled_ = true;
      return this;
    }

    Builder* disable_page_checksum() {
      page_checksum_enabled_ = false;
      return this;
    }

    /// \brief Define the encoding that is used when we don't utilise dictionary encoding.
    //
    /// This is only applied if dictionary encoding is disabled. If the dictionary grows
    /// too large we always fall back to the PLAIN encoding.
    Builder* encoding(Encoding::type encoding_type) {
      if (encoding_type == Encoding::PLAIN_DICTIONARY ||
          encoding_type == Encoding::RLE_DICTIONARY) {
        throw ParquetException("Can't use dictionary encoding as fallback encoding");
      }

      default_column_properties_.set_encoding(encoding_type);
      return this;
    }

    /// \brief Define the encoding that is used when we don't utilise dictionary encoding.
    //
    /// This is only applied if dictionary encoding is disabled. If the dictionary grows
    /// too large we always fall back to the PLAIN encoding.
    Builder* encoding(const std::string& path, Encoding::type encoding_type) {
      if (encoding_type == Encoding::PLAIN_DICTIONARY ||
          encoding_type == Encoding::RLE_DICTIONARY) {
        throw ParquetException("Can't use dictionary encoding as fallback encoding");
      }

      encodings_[path] = encoding_type;
      return this;
    }

    /// \brief Define the encoding that is used when we don't utilise dictionary encoding.
    //
    /// This is only applied if dictionary encoding is disabled. If the dictionary grows
    /// too large we always fall back to the PLAIN encoding.
    Builder* encoding(const std::shared_ptr<schema::ColumnPath>& path,
                      Encoding::type encoding_type) {
      return this->encoding(path->ToDotString(), encoding_type);
    }

    /// Specify compression codec in general for all columns.
    /// Default UNCOMPRESSED.
    Builder* compression(Compression::type codec) {
      default_column_properties_.set_compression(codec);
      return this;
    }

    /// Specify max statistics size to store min max value.
    /// Default 4KB.
    Builder* max_statistics_size(size_t max_stats_sz) {
      default_column_properties_.set_max_statistics_size(max_stats_sz);
      return this;
    }

    /// Specify compression codec for the column specified by `path`.
    /// Default UNCOMPRESSED.
    Builder* compression(const std::string& path, Compression::type codec) {
      codecs_[path] = codec;
      return this;
    }

    /// Specify compression codec for the column specified by `path`.
    /// Default UNCOMPRESSED.
    Builder* compression(const std::shared_ptr<schema::ColumnPath>& path,
                         Compression::type codec) {
      return this->compression(path->ToDotString(), codec);
    }

    /// \brief Specify the default compression level for the compressor in
    /// every column.  In case a column does not have an explicitly specified
    /// compression level, the default one would be used.
    ///
    /// The provided compression level is compressor specific. The user would
    /// have to familiarize oneself with the available levels for the selected
    /// compressor.  If the compressor does not allow for selecting different
    /// compression levels, calling this function would not have any effect.
    /// Parquet and Arrow do not validate the passed compression level.  If no
    /// level is selected by the user or if the special
    /// std::numeric_limits<int>::min() value is passed, then Arrow selects the
    /// compression level.
    ///
    /// If other compressor-specific options need to be set in addition to the compression
    /// level, use the codec_options method.
    Builder* compression_level(int compression_level) {
      default_column_properties_.set_compression_level(compression_level);
      return this;
    }

    /// \brief Specify a compression level for the compressor for the column
    /// described by path.
    ///
    /// The provided compression level is compressor specific. The user would
    /// have to familiarize oneself with the available levels for the selected
    /// compressor.  If the compressor does not allow for selecting different
    /// compression levels, calling this function would not have any effect.
    /// Parquet and Arrow do not validate the passed compression level.  If no
    /// level is selected by the user or if the special
    /// std::numeric_limits<int>::min() value is passed, then Arrow selects the
    /// compression level.
    Builder* compression_level(const std::string& path, int compression_level) {
      if (!codec_options_[path]) {
        codec_options_[path] = std::make_shared<CodecOptions>();
      }
      codec_options_[path]->compression_level = compression_level;
      return this;
    }

    /// \brief Specify a compression level for the compressor for the column
    /// described by path.
    ///
    /// The provided compression level is compressor specific. The user would
    /// have to familiarize oneself with the available levels for the selected
    /// compressor.  If the compressor does not allow for selecting different
    /// compression levels, calling this function would not have any effect.
    /// Parquet and Arrow do not validate the passed compression level.  If no
    /// level is selected by the user or if the special
    /// std::numeric_limits<int>::min() value is passed, then Arrow selects the
    /// compression level.
    Builder* compression_level(const std::shared_ptr<schema::ColumnPath>& path,
                               int compression_level) {
      return this->compression_level(path->ToDotString(), compression_level);
    }

    /// \brief Specify the default codec options for the compressor in
    /// every column.
    ///
    /// The codec options allow configuring the compression level as well
    /// as other codec-specific options.
    Builder* codec_options(
        const std::shared_ptr<::arrow::util::CodecOptions>& codec_options) {
      default_column_properties_.set_codec_options(codec_options);
      return this;
    }

    /// \brief Specify the codec options for the compressor for the column
    /// described by path.
    Builder* codec_options(
        const std::string& path,
        const std::shared_ptr<::arrow::util::CodecOptions>& codec_options) {
      codec_options_[path] = codec_options;
      return this;
    }

    /// \brief Specify the codec options for the compressor for the column
    /// described by path.
    Builder* codec_options(
        const std::shared_ptr<schema::ColumnPath>& path,
        const std::shared_ptr<::arrow::util::CodecOptions>& codec_options) {
      return this->codec_options(path->ToDotString(), codec_options);
    }

    /// Define the file encryption properties.
    /// Default NULL.
    Builder* encryption(
        std::shared_ptr<FileEncryptionProperties> file_encryption_properties) {
      file_encryption_properties_ = std::move(file_encryption_properties);
      return this;
    }

    /// Enable statistics in general.
    /// Default enabled.
    Builder* enable_statistics() {
      default_column_properties_.set_statistics_enabled(true);
      return this;
    }

    /// Disable statistics in general.
    /// Default enabled.
    Builder* disable_statistics() {
      default_column_properties_.set_statistics_enabled(false);
      return this;
    }

    /// Enable statistics for the column specified by `path`.
    /// Default enabled.
    Builder* enable_statistics(const std::string& path) {
      statistics_enabled_[path] = true;
      return this;
    }

    /// Enable statistics for the column specified by `path`.
    /// Default enabled.
    Builder* enable_statistics(const std::shared_ptr<schema::ColumnPath>& path) {
      return this->enable_statistics(path->ToDotString());
    }

    /// Define the sorting columns.
    /// Default empty.
    ///
    /// If sorting columns are set, user should ensure that records
    /// are sorted by sorting columns. Otherwise, the storing data
    /// will be inconsistent with sorting_columns metadata.
    Builder* set_sorting_columns(std::vector<SortingColumn> sorting_columns) {
      sorting_columns_ = std::move(sorting_columns);
      return this;
    }

    /// Disable statistics for the column specified by `path`.
    /// Default enabled.
    Builder* disable_statistics(const std::string& path) {
      statistics_enabled_[path] = false;
      return this;
    }

    /// Disable statistics for the column specified by `path`.
    /// Default enabled.
    Builder* disable_statistics(const std::shared_ptr<schema::ColumnPath>& path) {
      return this->disable_statistics(path->ToDotString());
    }

    /// Disable bloom filter for the column specified by `path`.
    /// Default disabled.
    Builder* disable_bloom_filter(const std::string& path) {
      bloom_filter_options_.erase(path);
      return this;
    }

    /// Disable bloom filter for the column specified by `path`.
    /// Default disabled.
    Builder* disable_bloom_filter(const std::shared_ptr<schema::ColumnPath>& path) {
      return this->disable_bloom_filter(path->ToDotString());
    }

    /// Enable bloom filter for the column specified by `path`.
    ///
    /// Default disabled.
    ///
    /// \note Bloom filter is not supported for boolean columns. ParquetException will
    /// be thrown during write if the column is of boolean type.
    Builder* enable_bloom_filter(const std::string& path,
                                 const BloomFilterOptions& bloom_filter_options) {
      bloom_filter_options_[path] = bloom_filter_options;
      return this;
    }

    /// Enable bloom filter for the column specified by `path`.
    ///
    /// Default disabled.
    ///
    /// \note Bloom filter is not supported for boolean columns. ParquetException will
    /// be thrown during write if the column is of boolean type.
    Builder* enable_bloom_filter(const std::shared_ptr<schema::ColumnPath>& path,
                                 const BloomFilterOptions& bloom_filter_options) {
      return this->enable_bloom_filter(path->ToDotString(), bloom_filter_options);
    }

    /// Allow decimals with 1 <= precision <= 18 to be stored as integers.
    ///
    /// In Parquet, DECIMAL can be stored in any of the following physical types:
    /// - int32: for 1 <= precision <= 9.
    /// - int64: for 10 <= precision <= 18.
    /// - fixed_len_byte_array: precision is limited by the array size.
    ///   Length n can store <= floor(log_10(2^(8*n - 1) - 1)) base-10 digits.
    /// - binary: precision is unlimited. The minimum number of bytes to store
    ///   the unscaled value is used.
    ///
    /// By default, this is DISABLED and all decimal types annotate fixed_len_byte_array.
    ///
    /// When enabled, the C++ writer will use following physical types to store decimals:
    /// - int32: for 1 <= precision <= 9.
    /// - int64: for 10 <= precision <= 18.
    /// - fixed_len_byte_array: for precision > 18.
    ///
    /// As a consequence, decimal columns stored in integer types are more compact.
    Builder* enable_store_decimal_as_integer() {
      store_decimal_as_integer_ = true;
      return this;
    }

    /// Disable decimal logical type with 1 <= precision <= 18 to be stored
    /// as integer physical type.
    ///
    /// Default disabled.
    Builder* disable_store_decimal_as_integer() {
      store_decimal_as_integer_ = false;
      return this;
    }

    /// Enable writing page index in general for all columns. Default enabled.
    ///
    /// Writing statistics to the page index disables the old method of writing
    /// statistics to each data page header.
    /// The page index makes filtering more efficient than the page header, as
    /// it gathers all the statistics for a Parquet file in a single place,
    /// avoiding scattered I/O.
    ///
    /// Please check the link below for more details:
    /// https://github.com/apache/parquet-format/blob/master/PageIndex.md
    Builder* enable_write_page_index() {
      default_column_properties_.set_page_index_enabled(true);
      return this;
    }

    /// Disable writing page index in general for all columns. Default enabled.
    Builder* disable_write_page_index() {
      default_column_properties_.set_page_index_enabled(false);
      return this;
    }

    /// Enable writing page index for column specified by `path`. Default enabled.
    Builder* enable_write_page_index(const std::string& path) {
      page_index_enabled_[path] = true;
      return this;
    }

    /// Enable writing page index for column specified by `path`. Default enabled.
    Builder* enable_write_page_index(const std::shared_ptr<schema::ColumnPath>& path) {
      return this->enable_write_page_index(path->ToDotString());
    }

    /// Disable writing page index for column specified by `path`. Default enabled.
    Builder* disable_write_page_index(const std::string& path) {
      page_index_enabled_[path] = false;
      return this;
    }

    /// Disable writing page index for column specified by `path`. Default enabled.
    Builder* disable_write_page_index(const std::shared_ptr<schema::ColumnPath>& path) {
      return this->disable_write_page_index(path->ToDotString());
    }

    /// \brief Set the level to write size statistics for all columns. Default is
    /// PageAndColumnChunk.
    ///
    /// \param level The level to write size statistics. Note that if page index is not
    /// enabled, page level size statistics will not be written even if the level
    /// is set to PageAndColumnChunk.
    Builder* set_size_statistics_level(SizeStatisticsLevel level) {
      size_statistics_level_ = level;
      return this;
    }

    /// \brief Build the WriterProperties with the builder parameters.
    /// \return The WriterProperties defined by the builder.
    std::shared_ptr<WriterProperties> build() {
      std::unordered_map<std::string, ColumnProperties> column_properties;
      auto get = [&](const std::string& key) -> ColumnProperties& {
        auto it = column_properties.find(key);
        if (it == column_properties.end())
          return column_properties[key] = default_column_properties_;
        else
          return it->second;
      };

      for (const auto& item : encodings_) get(item.first).set_encoding(item.second);
      for (const auto& item : codecs_) get(item.first).set_compression(item.second);
      for (const auto& item : codec_options_)
        get(item.first).set_codec_options(item.second);
      for (const auto& item : dictionary_enabled_)
        get(item.first).set_dictionary_enabled(item.second);
      for (const auto& item : statistics_enabled_)
        get(item.first).set_statistics_enabled(item.second);
      for (const auto& item : page_index_enabled_)
        get(item.first).set_page_index_enabled(item.second);
      for (const auto& item : bloom_filter_options_)
        get(item.first).set_bloom_filter_options(item.second);

      return std::shared_ptr<WriterProperties>(new WriterProperties(
          pool_, dictionary_pagesize_limit_, write_batch_size_, max_row_group_length_,
          pagesize_, max_rows_per_page_, version_, created_by_, page_checksum_enabled_,
          size_statistics_level_, std::move(file_encryption_properties_),
          default_column_properties_, column_properties, data_page_version_,
          store_decimal_as_integer_, std::move(sorting_columns_),
          content_defined_chunking_enabled_, content_defined_chunking_options_));
    }

   private:
    void CopyColumnSpecificProperties(const WriterProperties& properties);

    MemoryPool* pool_;
    int64_t dictionary_pagesize_limit_;
    int64_t write_batch_size_;
    int64_t max_row_group_length_;
    int64_t pagesize_;
    int64_t max_rows_per_page_;
    ParquetVersion::type version_;
    ParquetDataPageVersion data_page_version_;
    std::string created_by_;
    bool store_decimal_as_integer_;
    bool page_checksum_enabled_;
    SizeStatisticsLevel size_statistics_level_;

    std::shared_ptr<FileEncryptionProperties> file_encryption_properties_;

    // If empty, there is no sorting columns.
    std::vector<SortingColumn> sorting_columns_;

    // Settings used for each column unless overridden in any of the maps below
    ColumnProperties default_column_properties_;
    std::unordered_map<std::string, Encoding::type> encodings_;
    std::unordered_map<std::string, Compression::type> codecs_;
    std::unordered_map<std::string, std::shared_ptr<CodecOptions>> codec_options_;
    std::unordered_map<std::string, bool> dictionary_enabled_;
    std::unordered_map<std::string, bool> statistics_enabled_;
    std::unordered_map<std::string, bool> page_index_enabled_;
    std::unordered_map<std::string, BloomFilterOptions> bloom_filter_options_;

    bool content_defined_chunking_enabled_;
    CdcOptions content_defined_chunking_options_;
  };

  inline MemoryPool* memory_pool() const { return pool_; }

  inline int64_t dictionary_pagesize_limit() const { return dictionary_pagesize_limit_; }

  inline int64_t write_batch_size() const { return write_batch_size_; }

  inline int64_t max_row_group_length() const { return max_row_group_length_; }

  inline int64_t data_pagesize() const { return pagesize_; }

  inline int64_t max_rows_per_page() const { return max_rows_per_page_; }

  inline ParquetDataPageVersion data_page_version() const {
    return parquet_data_page_version_;
  }

  inline ParquetVersion::type version() const { return parquet_version_; }

  inline std::string created_by() const { return parquet_created_by_; }

  inline bool store_decimal_as_integer() const { return store_decimal_as_integer_; }

  inline bool page_checksum_enabled() const { return page_checksum_enabled_; }

  inline bool content_defined_chunking_enabled() const {
    return content_defined_chunking_enabled_;
  }
  inline CdcOptions content_defined_chunking_options() const {
    return content_defined_chunking_options_;
  }

  inline SizeStatisticsLevel size_statistics_level() const {
    return size_statistics_level_;
  }

  inline Encoding::type dictionary_index_encoding() const {
    if (parquet_version_ == ParquetVersion::PARQUET_1_0) {
      return Encoding::PLAIN_DICTIONARY;
    } else {
      return Encoding::RLE_DICTIONARY;
    }
  }

  inline Encoding::type dictionary_page_encoding() const {
    if (parquet_version_ == ParquetVersion::PARQUET_1_0) {
      return Encoding::PLAIN_DICTIONARY;
    } else {
      return Encoding::PLAIN;
    }
  }

  const ColumnProperties& column_properties(
      const std::shared_ptr<schema::ColumnPath>& path) const {
    auto it = column_properties_.find(path->ToDotString());
    if (it != column_properties_.end()) return it->second;
    return default_column_properties_;
  }

  Encoding::type encoding(const std::shared_ptr<schema::ColumnPath>& path) const {
    return column_properties(path).encoding();
  }

  Compression::type compression(const std::shared_ptr<schema::ColumnPath>& path) const {
    return column_properties(path).compression();
  }

  int compression_level(const std::shared_ptr<schema::ColumnPath>& path) const {
    return column_properties(path).compression_level();
  }

  const std::shared_ptr<CodecOptions> codec_options(
      const std::shared_ptr<schema::ColumnPath>& path) const {
    return column_properties(path).codec_options();
  }

  bool dictionary_enabled(const std::shared_ptr<schema::ColumnPath>& path) const {
    return column_properties(path).dictionary_enabled();
  }

  const std::vector<SortingColumn>& sorting_columns() const { return sorting_columns_; }

  bool statistics_enabled(const std::shared_ptr<schema::ColumnPath>& path) const {
    return column_properties(path).statistics_enabled();
  }

  size_t max_statistics_size(const std::shared_ptr<schema::ColumnPath>& path) const {
    return column_properties(path).max_statistics_size();
  }

  bool page_index_enabled(const std::shared_ptr<schema::ColumnPath>& path) const {
    return column_properties(path).page_index_enabled();
  }

  bool page_index_enabled() const {
    if (default_column_properties_.page_index_enabled()) {
      return true;
    }
    for (const auto& item : column_properties_) {
      if (item.second.page_index_enabled()) {
        return true;
      }
    }
    return false;
  }

  // Return whether bloom filter is enabled for any column.
  bool bloom_filter_enabled() const {
    return std::any_of(column_properties_.cbegin(), column_properties_.cend(),
                       [](const auto& p) { return p.second.bloom_filter_enabled(); });
  }

  std::optional<BloomFilterOptions> bloom_filter_options(
      const std::shared_ptr<schema::ColumnPath>& path) const {
    return column_properties(path).bloom_filter_options();
  }

  inline FileEncryptionProperties* file_encryption_properties() const {
    return file_encryption_properties_.get();
  }

  std::shared_ptr<ColumnEncryptionProperties> column_encryption_properties(
      const std::string& path) const {
    if (file_encryption_properties_) {
      return file_encryption_properties_->column_encryption_properties(path);
    } else {
      return NULLPTR;
    }
  }

  // \brief Return the default column properties
  const ColumnProperties& default_column_properties() const {
    return default_column_properties_;
  }

 private:
  explicit WriterProperties(
      MemoryPool* pool, int64_t dictionary_pagesize_limit, int64_t write_batch_size,
      int64_t max_row_group_length, int64_t pagesize, int64_t max_rows_per_page,
      ParquetVersion::type version, const std::string& created_by,
      bool page_write_checksum_enabled, SizeStatisticsLevel size_statistics_level,
      std::shared_ptr<FileEncryptionProperties> file_encryption_properties,
      const ColumnProperties& default_column_properties,
      const std::unordered_map<std::string, ColumnProperties>& column_properties,
      ParquetDataPageVersion data_page_version, bool store_short_decimal_as_integer,
      std::vector<SortingColumn> sorting_columns, bool content_defined_chunking_enabled,
      CdcOptions content_defined_chunking_options)
      : pool_(pool),
        dictionary_pagesize_limit_(dictionary_pagesize_limit),
        write_batch_size_(write_batch_size),
        max_row_group_length_(max_row_group_length),
        pagesize_(pagesize),
        max_rows_per_page_(max_rows_per_page),
        parquet_data_page_version_(data_page_version),
        parquet_version_(version),
        parquet_created_by_(created_by),
        store_decimal_as_integer_(store_short_decimal_as_integer),
        page_checksum_enabled_(page_write_checksum_enabled),
        size_statistics_level_(size_statistics_level),
        file_encryption_properties_(file_encryption_properties),
        sorting_columns_(std::move(sorting_columns)),
        default_column_properties_(default_column_properties),
        column_properties_(column_properties),
        content_defined_chunking_enabled_(content_defined_chunking_enabled),
        content_defined_chunking_options_(content_defined_chunking_options) {}

  MemoryPool* pool_;
  int64_t dictionary_pagesize_limit_;
  int64_t write_batch_size_;
  int64_t max_row_group_length_;
  int64_t pagesize_;
  int64_t max_rows_per_page_;
  ParquetDataPageVersion parquet_data_page_version_;
  ParquetVersion::type parquet_version_;
  std::string parquet_created_by_;
  bool store_decimal_as_integer_;
  bool page_checksum_enabled_;
  SizeStatisticsLevel size_statistics_level_;

  std::shared_ptr<FileEncryptionProperties> file_encryption_properties_;

  std::vector<SortingColumn> sorting_columns_;

  ColumnProperties default_column_properties_;
  std::unordered_map<std::string, ColumnProperties> column_properties_;

  bool content_defined_chunking_enabled_;
  CdcOptions content_defined_chunking_options_;
};

PARQUET_EXPORT const std::shared_ptr<WriterProperties>& default_writer_properties();

// ----------------------------------------------------------------------
// Properties specific to Apache Arrow columnar read and write

static constexpr bool kArrowDefaultUseThreads = false;

// Default number of rows to read when using ::arrow::RecordBatchReader
static constexpr int64_t kArrowDefaultBatchSize = 64 * 1024;

constexpr inline ::arrow::Type::type kArrowDefaultBinaryType = ::arrow::Type::BINARY;
constexpr inline ::arrow::Type::type kArrowDefaultListType = ::arrow::Type::LIST;

/// EXPERIMENTAL: Properties for configuring FileReader behavior.
class PARQUET_EXPORT ArrowReaderProperties {
 public:
  explicit ArrowReaderProperties(bool use_threads = kArrowDefaultUseThreads)
      : use_threads_(use_threads),
        read_dict_indices_(),
        batch_size_(kArrowDefaultBatchSize),
        pre_buffer_(true),
        cache_options_(::arrow::io::CacheOptions::LazyDefaults()),
        coerce_int96_timestamp_unit_(::arrow::TimeUnit::NANO),
        binary_type_(kArrowDefaultBinaryType),
        list_type_(kArrowDefaultListType),
        arrow_extensions_enabled_(false),
        should_load_statistics_(false),
        smallest_decimal_enabled_(false) {}

  /// \brief Set whether to use the IO thread pool to parse columns in parallel.
  ///
  /// Default is false.
  void set_use_threads(bool use_threads) { use_threads_ = use_threads; }
  /// Return whether will use multiple threads.
  bool use_threads() const { return use_threads_; }

  /// \brief Set whether to read a particular column as dictionary encoded.
  ///
  /// If the file metadata contains a serialized Arrow schema, then ...
  ////
  /// This is only supported for columns with a Parquet physical type of
  /// BYTE_ARRAY, such as string or binary types.
  void set_read_dictionary(int column_index, bool read_dict) {
    if (read_dict) {
      read_dict_indices_.insert(column_index);
    } else {
      read_dict_indices_.erase(column_index);
    }
  }
  /// Return whether the column at the index will be read as dictionary.
  bool read_dictionary(int column_index) const {
    if (read_dict_indices_.find(column_index) != read_dict_indices_.end()) {
      return true;
    } else {
      return false;
    }
  }

  /// \brief Set the Arrow binary type to read BYTE_ARRAY columns as.
  ///
  /// Allowed values are Type::BINARY, Type::LARGE_BINARY and Type::BINARY_VIEW.
  /// Default is Type::BINARY.
  ///
  /// If a BYTE_ARRAY column has the STRING logical type, it is read as the
  /// Arrow string type corresponding to the configured binary type (for example
  /// Type::LARGE_STRING if the configured binary type is Type::LARGE_BINARY).
  ///
  /// However, if a serialized Arrow schema is found in the Parquet metadata,
  /// this setting is ignored and the Arrow schema takes precedence
  /// (see ArrowWriterProperties::store_schema).
  void set_binary_type(::arrow::Type::type value) { binary_type_ = value; }
  /// Return the Arrow binary type to read BYTE_ARRAY columns as.
  ::arrow::Type::type binary_type() const { return binary_type_; }

  /// \brief Set the Arrow list type to read Parquet list columns as.
  ///
  /// Allowed values are Type::LIST and Type::LARGE_LIST.
  /// Default is Type::LIST.
  ///
  /// However, if a serialized Arrow schema is found in the Parquet metadata,
  /// this setting is ignored and the Arrow schema takes precedence
  /// (see ArrowWriterProperties::store_schema).
  void set_list_type(::arrow::Type::type value) { list_type_ = value; }
  /// Return the Arrow list type to read Parquet list columns as.
  ::arrow::Type::type list_type() const { return list_type_; }

  /// \brief Set the maximum number of rows to read into a record batch.
  ///
  /// Will only be fewer rows when there are no more rows in the file.
  /// Note that some APIs such as ReadTable may ignore this setting.
  void set_batch_size(int64_t batch_size) { batch_size_ = batch_size; }
  /// Return the batch size in rows.
  ///
  /// Note that some APIs such as ReadTable may ignore this setting.
  int64_t batch_size() const { return batch_size_; }

  /// Enable read coalescing (default false).
  ///
  /// When enabled, the Arrow reader will pre-buffer necessary regions
  /// of the file in-memory. This is intended to improve performance on
  /// high-latency filesystems (e.g. Amazon S3).
  void set_pre_buffer(bool pre_buffer) { pre_buffer_ = pre_buffer; }
  /// Return whether read coalescing is enabled.
  bool pre_buffer() const { return pre_buffer_; }

  /// Set options for read coalescing. This can be used to tune the
  /// implementation for characteristics of different filesystems.
  void set_cache_options(::arrow::io::CacheOptions options) { cache_options_ = options; }
  /// Return the options for read coalescing.
  const ::arrow::io::CacheOptions& cache_options() const { return cache_options_; }

  /// Set execution context for read coalescing.
  void set_io_context(const ::arrow::io::IOContext& ctx) { io_context_ = ctx; }
  /// Return the execution context used for read coalescing.
  const ::arrow::io::IOContext& io_context() const { return io_context_; }

  /// Set timestamp unit to use for deprecated INT96-encoded timestamps
  /// (default is NANO).
  void set_coerce_int96_timestamp_unit(::arrow::TimeUnit::type unit) {
    coerce_int96_timestamp_unit_ = unit;
  }

  ::arrow::TimeUnit::type coerce_int96_timestamp_unit() const {
    return coerce_int96_timestamp_unit_;
  }

  /// Enable Parquet-supported Arrow extension types.
  ///
  /// When enabled, Parquet logical types will be mapped to their corresponding Arrow
  /// extension types at read time, if such exist. Currently only arrow::extension::json()
  /// extension type is supported. Columns whose LogicalType is JSON will be interpreted
  /// as arrow::extension::json(), with storage type inferred from the serialized Arrow
  /// schema if present, or `utf8` by default.
  void set_arrow_extensions_enabled(bool extensions_enabled) {
    arrow_extensions_enabled_ = extensions_enabled;
  }
  bool get_arrow_extensions_enabled() const { return arrow_extensions_enabled_; }

  /// \brief Set whether to load statistics as much as possible.
  ///
  /// Default is false.
  void set_should_load_statistics(bool should_load_statistics) {
    should_load_statistics_ = should_load_statistics;
  }
  /// Return whether loading statistics as much as possible.
  bool should_load_statistics() const { return should_load_statistics_; }

  /// \brief Set whether to infer Decimal32/64 from Parquet decimal logical types.
  ///
  /// Default is false for compatibility, meaning that only Decimal128 and Decimal256
  /// can be inferred.
  void set_smallest_decimal_enabled(bool smallest_decimal_enable) {
    smallest_decimal_enabled_ = smallest_decimal_enable;
  }
  /// \brief Whether to infer Decimal32/64 from Parquet decimal logical types.
  ///
  /// When enabled, Parquet decimal columns will be inferred as the smallest possible
  /// Arrow Decimal type.
  /// When disabled, Parquet decimal columns will be inferred as either Decimal128 or
  /// Decimal256, but not Decimal32/64.
  ///
  /// Note: if an Arrow schema is found in the Parquet metadata, it will take priority and
  /// this setting will be ignored.
  bool smallest_decimal_enabled() const { return smallest_decimal_enabled_; }

 private:
  bool use_threads_;
  std::unordered_set<int> read_dict_indices_;
  int64_t batch_size_;
  bool pre_buffer_;
  ::arrow::io::IOContext io_context_;
  ::arrow::io::CacheOptions cache_options_;
  ::arrow::TimeUnit::type coerce_int96_timestamp_unit_;
  ::arrow::Type::type binary_type_;
  ::arrow::Type::type list_type_;
  bool arrow_extensions_enabled_;
  bool should_load_statistics_;
  bool smallest_decimal_enabled_;
};

/// EXPERIMENTAL: Constructs the default ArrowReaderProperties
PARQUET_EXPORT
ArrowReaderProperties default_arrow_reader_properties();

class PARQUET_EXPORT ArrowWriterProperties {
 public:
  enum EngineVersion {
    V1,  // Supports only nested lists.
    V2   // Full support for all nesting combinations
  };
  class Builder {
   public:
    Builder()
        : write_timestamps_as_int96_(false),
          coerce_timestamps_enabled_(false),
          coerce_timestamps_unit_(::arrow::TimeUnit::SECOND),
          truncated_timestamps_allowed_(false),
          store_schema_(false),
          compliant_nested_types_(true),
          engine_version_(V2),
          use_threads_(kArrowDefaultUseThreads),
          executor_(NULLPTR),
          write_time_adjusted_to_utc_(false) {}

    /// \brief Disable writing legacy int96 timestamps (default disabled).
    Builder* disable_deprecated_int96_timestamps() {
      write_timestamps_as_int96_ = false;
      return this;
    }

    /// \brief Enable writing legacy int96 timestamps (default disabled).
    ///
    /// May be turned on to write timestamps compatible with older Parquet writers.
    /// This takes precedent over coerce_timestamps.
    Builder* enable_deprecated_int96_timestamps() {
      write_timestamps_as_int96_ = true;
      return this;
    }

    /// \brief Coerce all timestamps to the specified time unit.
    /// \param unit time unit to truncate to.
    /// For Parquet versions 1.0 and 2.4, nanoseconds are casted to microseconds.
    Builder* coerce_timestamps(::arrow::TimeUnit::type unit) {
      coerce_timestamps_enabled_ = true;
      coerce_timestamps_unit_ = unit;
      return this;
    }

    /// \brief Allow loss of data when truncating timestamps.
    ///
    /// This is disallowed by default and an error will be returned.
    Builder* allow_truncated_timestamps() {
      truncated_timestamps_allowed_ = true;
      return this;
    }

    /// \brief Disallow loss of data when truncating timestamps (default).
    Builder* disallow_truncated_timestamps() {
      truncated_timestamps_allowed_ = false;
      return this;
    }

    /// \brief EXPERIMENTAL: Write binary serialized Arrow schema to the file,
    /// to enable certain read options (like "read_dictionary") to be set
    /// automatically
    Builder* store_schema() {
      store_schema_ = true;
      return this;
    }

    /// \brief When enabled, will not preserve Arrow field names for list types.
    ///
    /// Instead of using the field names Arrow uses for the values array of
    /// list types (default "item"), will use "element", as is specified in
    /// the Parquet spec.
    ///
    /// This is enabled by default.
    Builder* enable_compliant_nested_types() {
      compliant_nested_types_ = true;
      return this;
    }

    /// Preserve Arrow list field name.
    Builder* disable_compliant_nested_types() {
      compliant_nested_types_ = false;
      return this;
    }

    /// Set the version of the Parquet writer engine.
    Builder* set_engine_version(EngineVersion version) {
      engine_version_ = version;
      return this;
    }

    /// \brief Set whether to use multiple threads to write columns
    /// in parallel in the buffered row group mode.
    ///
    /// WARNING: If writing multiple files in parallel in the same
    /// executor, deadlock may occur if use_threads is true. Please
    /// disable it in this case.
    ///
    /// Default is false.
    Builder* set_use_threads(bool use_threads) {
      use_threads_ = use_threads;
      return this;
    }

    /// \brief Set the executor to write columns in parallel in the
    /// buffered row group mode.
    ///
    /// Default is nullptr and the default cpu executor will be used.
    Builder* set_executor(::arrow::internal::Executor* executor) {
      executor_ = executor;
      return this;
    }

    /// \brief Set the value of isAdjustedTOUTC when writing a TIME column
    ///
    /// Default is false because Arrow TIME data is expressed in an unspecified timezone.
    /// Note this setting doesn't affect TIMESTAMP data.
    Builder* set_time_adjusted_to_utc(bool adjusted) {
      write_time_adjusted_to_utc_ = adjusted;
      return this;
    }

    /// Create the final properties.
    std::shared_ptr<ArrowWriterProperties> build() {
      return std::shared_ptr<ArrowWriterProperties>(new ArrowWriterProperties(
          write_timestamps_as_int96_, coerce_timestamps_enabled_, coerce_timestamps_unit_,
          truncated_timestamps_allowed_, store_schema_, compliant_nested_types_,
          engine_version_, use_threads_, executor_, write_time_adjusted_to_utc_));
    }

   private:
    bool write_timestamps_as_int96_;

    bool coerce_timestamps_enabled_;
    ::arrow::TimeUnit::type coerce_timestamps_unit_;
    bool truncated_timestamps_allowed_;

    bool store_schema_;
    bool compliant_nested_types_;
    EngineVersion engine_version_;

    bool use_threads_;
    ::arrow::internal::Executor* executor_;

    bool write_time_adjusted_to_utc_;
  };

  bool support_deprecated_int96_timestamps() const { return write_timestamps_as_int96_; }

  bool coerce_timestamps_enabled() const { return coerce_timestamps_enabled_; }
  ::arrow::TimeUnit::type coerce_timestamps_unit() const {
    return coerce_timestamps_unit_;
  }

  bool truncated_timestamps_allowed() const { return truncated_timestamps_allowed_; }

  bool store_schema() const { return store_schema_; }

  /// \brief Enable nested type naming according to the parquet specification.
  ///
  /// Older versions of arrow wrote out field names for nested lists based on the name
  /// of the field.  According to the parquet specification they should always be
  /// "element".
  bool compliant_nested_types() const { return compliant_nested_types_; }

  /// \brief The underlying engine version to use when writing Arrow data.
  ///
  /// V2 is currently the latest V1 is considered deprecated but left in
  /// place in case there are bugs detected in V2.
  EngineVersion engine_version() const { return engine_version_; }

  /// \brief Returns whether the writer will use multiple threads
  /// to write columns in parallel in the buffered row group mode.
  bool use_threads() const { return use_threads_; }

  /// \brief Returns the executor used to write columns in parallel.
  ::arrow::internal::Executor* executor() const;

  /// \brief The value of isAdjustedTOUTC when writing a TIME column
  ///
  /// Note this setting doesn't affect TIMESTAMP data.
  bool write_time_adjusted_to_utc() const { return write_time_adjusted_to_utc_; }

 private:
  explicit ArrowWriterProperties(bool write_nanos_as_int96,
                                 bool coerce_timestamps_enabled,
                                 ::arrow::TimeUnit::type coerce_timestamps_unit,
                                 bool truncated_timestamps_allowed, bool store_schema,
                                 bool compliant_nested_types,
                                 EngineVersion engine_version, bool use_threads,
                                 ::arrow::internal::Executor* executor,
                                 bool write_time_adjusted_to_utc)
      : write_timestamps_as_int96_(write_nanos_as_int96),
        coerce_timestamps_enabled_(coerce_timestamps_enabled),
        coerce_timestamps_unit_(coerce_timestamps_unit),
        truncated_timestamps_allowed_(truncated_timestamps_allowed),
        store_schema_(store_schema),
        compliant_nested_types_(compliant_nested_types),
        engine_version_(engine_version),
        use_threads_(use_threads),
        executor_(executor),
        write_time_adjusted_to_utc_(write_time_adjusted_to_utc) {}

  const bool write_timestamps_as_int96_;
  const bool coerce_timestamps_enabled_;
  const ::arrow::TimeUnit::type coerce_timestamps_unit_;
  const bool truncated_timestamps_allowed_;
  const bool store_schema_;
  const bool compliant_nested_types_;
  const EngineVersion engine_version_;
  const bool use_threads_;
  ::arrow::internal::Executor* executor_;
  const bool write_time_adjusted_to_utc_;
};

/// \brief State object used for writing Arrow data directly to a Parquet
/// column chunk. API possibly not stable
struct ArrowWriteContext {
  ArrowWriteContext(MemoryPool* memory_pool, ArrowWriterProperties* properties)
      : memory_pool(memory_pool),
        properties(properties),
        data_buffer(AllocateBuffer(memory_pool)),
        def_levels_buffer(AllocateBuffer(memory_pool)) {}

  template <typename T>
  ::arrow::Status GetScratchData(const int64_t num_values, T** out) {
    ARROW_RETURN_NOT_OK(this->data_buffer->Resize(num_values * sizeof(T), false));
    *out = reinterpret_cast<T*>(this->data_buffer->mutable_data());
    return ::arrow::Status::OK();
  }

  MemoryPool* memory_pool;
  const ArrowWriterProperties* properties;

  // Buffer used for storing the data of an array converted to the physical type
  // as expected by parquet-cpp.
  std::shared_ptr<ResizableBuffer> data_buffer;

  // We use the shared ownership of this buffer
  std::shared_ptr<ResizableBuffer> def_levels_buffer;
};

PARQUET_EXPORT
std::shared_ptr<ArrowWriterProperties> default_arrow_writer_properties();

}  // namespace parquet