statistics_test.cc

// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements.  See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership.  The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License.  You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied.  See the License for the
// specific language governing permissions and limitations
// under the License.

#include <gtest/gtest.h>

#include <algorithm>
#include <array>
#include <cmath>
#include <cstdint>
#include <cstring>
#include <limits>
#include <memory>
#include <vector>

#include "arrow/array.h"
#include "arrow/buffer.h"
#include "arrow/memory_pool.h"
#include "arrow/testing/builder.h"
#include "arrow/testing/gtest_util.h"
#include "arrow/type_traits.h"
#include "arrow/util/bit_util.h"
#include "arrow/util/bitmap_ops.h"
#include "arrow/util/config.h"
#include "arrow/util/float16.h"
#include "arrow/util/logging_internal.h"
#include "arrow/util/ubsan.h"

#include "parquet/column_reader.h"
#include "parquet/column_writer.h"
#include "parquet/file_reader.h"
#include "parquet/file_writer.h"
#include "parquet/platform.h"
#include "parquet/schema.h"
#include "parquet/statistics.h"
#include "parquet/test_util.h"
#include "parquet/thrift_internal.h"
#include "parquet/types.h"

using arrow::default_memory_pool;
using arrow::MemoryPool;
using arrow::util::Float16;
using arrow::util::SafeCopy;

namespace bit_util = arrow::bit_util;

namespace parquet {

using schema::GroupNode;
using schema::NodePtr;
using schema::PrimitiveNode;

namespace test {

// ----------------------------------------------------------------------
// Test comparators

static ByteArray ByteArrayFromString(const std::string& s) {
  auto ptr = reinterpret_cast<const uint8_t*>(s.data());
  return ByteArray(static_cast<uint32_t>(s.size()), ptr);
}

static FLBA FLBAFromString(const std::string& s) {
  auto ptr = reinterpret_cast<const uint8_t*>(s.data());
  return FLBA(ptr);
}

TEST(Comparison, SignedByteArray) {
  // Signed byte array comparison is only used for Decimal comparison. When
  // decimals are encoded as byte arrays they use twos complement big-endian
  // encoded values. Comparisons of byte arrays of unequal types need to handle
  // sign extension.
  auto comparator = MakeComparator<ByteArrayType>(Type::BYTE_ARRAY, SortOrder::SIGNED);
  struct Case {
    std::vector<uint8_t> bytes;
    int order;
    ByteArray ToByteArray() const {
      return ByteArray(static_cast<int>(bytes.size()), bytes.data());
    }
  };

  // Test a mix of big-endian comparison values that are both equal and
  // unequal after sign extension.
  std::vector<Case> cases = {
      {{0x80, 0x80, 0, 0}, 0},           {{/*0xFF,*/ 0x80, 0, 0}, 1},
      {{0xFF, 0x80, 0, 0}, 1},           {{/*0xFF,*/ 0xFF, 0x01, 0}, 2},
      {{/*0xFF,  0xFF,*/ 0x80, 0}, 3},   {{/*0xFF,*/ 0xFF, 0x80, 0}, 3},
      {{0xFF, 0xFF, 0x80, 0}, 3},        {{/*0xFF,0xFF,0xFF,*/ 0x80}, 4},
      {{/*0xFF, 0xFF, 0xFF,*/ 0xFF}, 5}, {{/*0, 0,*/ 0x01, 0x01}, 6},
      {{/*0,*/ 0, 0x01, 0x01}, 6},       {{0, 0, 0x01, 0x01}, 6},
      {{/*0,*/ 0x01, 0x01, 0}, 7},       {{0x01, 0x01, 0, 0}, 8}};

  for (size_t x = 0; x < cases.size(); x++) {
    const auto& case1 = cases[x];
    // Empty array is always the smallest values
    EXPECT_TRUE(comparator->Compare(ByteArray(), case1.ToByteArray())) << x;
    EXPECT_FALSE(comparator->Compare(case1.ToByteArray(), ByteArray())) << x;
    // Equals is always false.
    EXPECT_FALSE(comparator->Compare(case1.ToByteArray(), case1.ToByteArray())) << x;

    for (size_t y = 0; y < cases.size(); y++) {
      const auto& case2 = cases[y];
      if (case1.order < case2.order) {
        EXPECT_TRUE(comparator->Compare(case1.ToByteArray(), case2.ToByteArray()))
            << x << " (order: " << case1.order << ") " << y << " (order: " << case2.order
            << ")";
      } else {
        EXPECT_FALSE(comparator->Compare(case1.ToByteArray(), case2.ToByteArray()))
            << x << " (order: " << case1.order << ") " << y << " (order: " << case2.order
            << ")";
      }
    }
  }
}

TEST(Comparison, UnsignedByteArray) {
  // Check if UTF-8 is compared using unsigned correctly
  auto comparator = MakeComparator<ByteArrayType>(Type::BYTE_ARRAY, SortOrder::UNSIGNED);

  std::string s1 = "arrange";
  std::string s2 = "arrangement";
  ByteArray s1ba = ByteArrayFromString(s1);
  ByteArray s2ba = ByteArrayFromString(s2);
  ASSERT_TRUE(comparator->Compare(s1ba, s2ba));

  // Multi-byte UTF-8 characters
  s1 = "braten";
  s2 = "bügeln";
  s1ba = ByteArrayFromString(s1);
  s2ba = ByteArrayFromString(s2);
  ASSERT_TRUE(comparator->Compare(s1ba, s2ba));

  s1 = "ünk123456";  // ü = 252
  s2 = "ănk123456";  // ă = 259
  s1ba = ByteArrayFromString(s1);
  s2ba = ByteArrayFromString(s2);
  ASSERT_TRUE(comparator->Compare(s1ba, s2ba));
}

TEST(Comparison, SignedFLBA) {
  int size = 4;
  auto comparator =
      MakeComparator<FLBAType>(Type::FIXED_LEN_BYTE_ARRAY, SortOrder::SIGNED, size);

  std::vector<uint8_t> byte_values[] = {
      {0x80, 0, 0, 0},          {0xFF, 0xFF, 0x01, 0},    {0xFF, 0xFF, 0x80, 0},
      {0xFF, 0xFF, 0xFF, 0x80}, {0xFF, 0xFF, 0xFF, 0xFF}, {0, 0, 0x01, 0x01},
      {0, 0x01, 0x01, 0},       {0x01, 0x01, 0, 0}};
  std::vector<FLBA> values_to_compare;
  for (auto& bytes : byte_values) {
    values_to_compare.emplace_back(FLBA(bytes.data()));
  }

  for (size_t x = 0; x < values_to_compare.size(); x++) {
    EXPECT_FALSE(comparator->Compare(values_to_compare[x], values_to_compare[x])) << x;
    for (size_t y = x + 1; y < values_to_compare.size(); y++) {
      EXPECT_TRUE(comparator->Compare(values_to_compare[x], values_to_compare[y]))
          << x << " " << y;
      EXPECT_FALSE(comparator->Compare(values_to_compare[y], values_to_compare[x]))
          << y << " " << x;
    }
  }
}

TEST(Comparison, UnsignedFLBA) {
  int size = 10;
  auto comparator =
      MakeComparator<FLBAType>(Type::FIXED_LEN_BYTE_ARRAY, SortOrder::UNSIGNED, size);

  std::string s1 = "Anti123456";
  std::string s2 = "Bunkd123456";
  FLBA s1flba = FLBAFromString(s1);
  FLBA s2flba = FLBAFromString(s2);
  ASSERT_TRUE(comparator->Compare(s1flba, s2flba));

  s1 = "Bunk123456";
  s2 = "Bünk123456";
  s1flba = FLBAFromString(s1);
  s2flba = FLBAFromString(s2);
  ASSERT_TRUE(comparator->Compare(s1flba, s2flba));
}

TEST(Comparison, SignedInt96) {
  parquet::Int96 a{{1, 41, 14}}, b{{1, 41, 42}};
  parquet::Int96 aa{{1, 41, 14}}, bb{{1, 41, 14}};
  parquet::Int96 aaa{{1, 41, static_cast<uint32_t>(-14)}}, bbb{{1, 41, 42}};

  auto comparator = MakeComparator<Int96Type>(Type::INT96, SortOrder::SIGNED);

  ASSERT_TRUE(comparator->Compare(a, b));
  ASSERT_TRUE(!comparator->Compare(aa, bb) && !comparator->Compare(bb, aa));
  ASSERT_TRUE(comparator->Compare(aaa, bbb));
}

TEST(Comparison, UnsignedInt96) {
  parquet::Int96 a{{1, 41, 14}}, b{{1, static_cast<uint32_t>(-41), 42}};
  parquet::Int96 aa{{1, 41, 14}}, bb{{1, 41, static_cast<uint32_t>(-14)}};
  parquet::Int96 aaa, bbb;

  auto comparator = MakeComparator<Int96Type>(Type::INT96, SortOrder::UNSIGNED);

  ASSERT_TRUE(comparator->Compare(a, b));
  ASSERT_TRUE(comparator->Compare(aa, bb));

  // INT96 Timestamp
  aaa.value[2] = 2451545;  // 2000-01-01
  bbb.value[2] = 2451546;  // 2000-01-02
  // 12 hours + 34 minutes + 56 seconds.
  Int96SetNanoSeconds(aaa, 45296000000000);
  // 12 hours + 34 minutes + 50 seconds.
  Int96SetNanoSeconds(bbb, 45290000000000);
  ASSERT_TRUE(comparator->Compare(aaa, bbb));

  aaa.value[2] = 2451545;  // 2000-01-01
  bbb.value[2] = 2451545;  // 2000-01-01
  // 11 hours + 34 minutes + 56 seconds.
  Int96SetNanoSeconds(aaa, 41696000000000);
  // 12 hours + 34 minutes + 50 seconds.
  Int96SetNanoSeconds(bbb, 45290000000000);
  ASSERT_TRUE(comparator->Compare(aaa, bbb));

  aaa.value[2] = 2451545;  // 2000-01-01
  bbb.value[2] = 2451545;  // 2000-01-01
  // 12 hours + 34 minutes + 55 seconds.
  Int96SetNanoSeconds(aaa, 45295000000000);
  // 12 hours + 34 minutes + 56 seconds.
  Int96SetNanoSeconds(bbb, 45296000000000);
  ASSERT_TRUE(comparator->Compare(aaa, bbb));
}

TEST(Comparison, SignedInt64) {
  int64_t a = 1, b = 4;
  int64_t aa = 1, bb = 1;
  int64_t aaa = -1, bbb = 1;

  NodePtr node = PrimitiveNode::Make("SignedInt64", Repetition::REQUIRED, Type::INT64);
  ColumnDescriptor descr(node, 0, 0);

  auto comparator = MakeComparator<Int64Type>(&descr);

  ASSERT_TRUE(comparator->Compare(a, b));
  ASSERT_TRUE(!comparator->Compare(aa, bb) && !comparator->Compare(bb, aa));
  ASSERT_TRUE(comparator->Compare(aaa, bbb));
}

TEST(Comparison, UnsignedInt64) {
  uint64_t a = 1, b = 4;
  uint64_t aa = 1, bb = 1;
  uint64_t aaa = 1, bbb = -1;

  NodePtr node = PrimitiveNode::Make("UnsignedInt64", Repetition::REQUIRED, Type::INT64,
                                     ConvertedType::UINT_64);
  ColumnDescriptor descr(node, 0, 0);

  ASSERT_EQ(SortOrder::UNSIGNED, descr.sort_order());
  auto comparator = MakeComparator<Int64Type>(&descr);

  ASSERT_TRUE(comparator->Compare(a, b));
  ASSERT_TRUE(!comparator->Compare(aa, bb) && !comparator->Compare(bb, aa));
  ASSERT_TRUE(comparator->Compare(aaa, bbb));
}

TEST(Comparison, UnsignedInt32) {
  uint32_t a = 1, b = 4;
  uint32_t aa = 1, bb = 1;
  uint32_t aaa = 1, bbb = -1;

  NodePtr node = PrimitiveNode::Make("UnsignedInt32", Repetition::REQUIRED, Type::INT32,
                                     ConvertedType::UINT_32);
  ColumnDescriptor descr(node, 0, 0);

  ASSERT_EQ(SortOrder::UNSIGNED, descr.sort_order());
  auto comparator = MakeComparator<Int32Type>(&descr);

  ASSERT_TRUE(comparator->Compare(a, b));
  ASSERT_TRUE(!comparator->Compare(aa, bb) && !comparator->Compare(bb, aa));
  ASSERT_TRUE(comparator->Compare(aaa, bbb));
}

TEST(Comparison, UnknownSortOrder) {
  NodePtr node =
      PrimitiveNode::Make("Unknown", Repetition::REQUIRED, Type::FIXED_LEN_BYTE_ARRAY,
                          ConvertedType::INTERVAL, 12);
  ColumnDescriptor descr(node, 0, 0);

  ASSERT_THROW(Comparator::Make(&descr), ParquetException);
}

// ----------------------------------------------------------------------

template <typename TestType>
class TestStatistics : public PrimitiveTypedTest<TestType> {
 public:
  using c_type = typename TestType::c_type;

  std::vector<c_type> GetDeepCopy(
      const std::vector<c_type>&);  // allocates new memory for FLBA/ByteArray

  c_type* GetValuesPointer(std::vector<c_type>&);
  void DeepFree(std::vector<c_type>&);

  void TestMinMaxEncode() {
    this->GenerateData(1000);

    auto statistics1 = MakeStatistics<TestType>(this->schema_.Column(0));
    statistics1->Update(this->values_ptr_, this->values_.size(), 0);
    std::string encoded_min = statistics1->EncodeMin();
    std::string encoded_max = statistics1->EncodeMax();

    auto statistics2 = MakeStatistics<TestType>(
        this->schema_.Column(0), encoded_min, encoded_max, this->values_.size(),
        /*null_count=*/0, /*distinct_count=*/0,
        /*has_min_max=*/true, /*has_null_count=*/true, /*has_distinct_count=*/true,
        /*is_min_value_exact=*/true, /*is_max_value_exact=*/true);

    auto statistics3 = MakeStatistics<TestType>(this->schema_.Column(0));
    std::vector<uint8_t> valid_bits(
        bit_util::BytesForBits(static_cast<uint32_t>(this->values_.size())) + 1, 255);
    statistics3->UpdateSpaced(this->values_ptr_, valid_bits.data(), 0,
                              this->values_.size(), this->values_.size(), 0);
    std::string encoded_min_spaced = statistics3->EncodeMin();
    std::string encoded_max_spaced = statistics3->EncodeMax();

    // Use old API without is_{min/max}_value_exact
    auto statistics4 = MakeStatistics<TestType>(
        this->schema_.Column(0), encoded_min, encoded_max, this->values_.size(),
        /*null_count=*/0, /*distinct_count=*/0,
        /*has_min_max=*/true, /*has_null_count=*/true, /*has_distinct_count=*/true);
    ASSERT_EQ(encoded_min, statistics2->EncodeMin());
    ASSERT_EQ(encoded_max, statistics2->EncodeMax());
    ASSERT_EQ(statistics1->min(), statistics2->min());
    ASSERT_EQ(statistics1->max(), statistics2->max());
    ASSERT_EQ(statistics1->is_min_value_exact(), std::make_optional(true));
    ASSERT_EQ(statistics1->is_max_value_exact(), std::make_optional(true));
    ASSERT_EQ(statistics2->is_min_value_exact(), std::make_optional(true));
    ASSERT_EQ(statistics2->is_max_value_exact(), std::make_optional(true));
    ASSERT_EQ(encoded_min_spaced, statistics2->EncodeMin());
    ASSERT_EQ(encoded_max_spaced, statistics2->EncodeMax());
    ASSERT_EQ(statistics3->min(), statistics2->min());
    ASSERT_EQ(statistics3->max(), statistics2->max());
    ASSERT_EQ(statistics3->is_min_value_exact(), std::make_optional(true));
    ASSERT_EQ(statistics3->is_max_value_exact(), std::make_optional(true));
    ASSERT_EQ(statistics4->min(), statistics2->min());
    ASSERT_EQ(statistics4->max(), statistics2->max());
    ASSERT_EQ(statistics4->is_min_value_exact(), std::nullopt);
    ASSERT_EQ(statistics4->is_max_value_exact(), std::nullopt);
  }

  void TestReset() {
    this->GenerateData(1000);

    auto statistics = MakeStatistics<TestType>(this->schema_.Column(0));
    statistics->Update(this->values_ptr_, this->values_.size(), 0);
    ASSERT_EQ(this->values_.size(), statistics->num_values());

    statistics->Reset();
    ASSERT_TRUE(statistics->HasNullCount());
    ASSERT_FALSE(statistics->HasMinMax());
    ASSERT_FALSE(statistics->HasDistinctCount());
    ASSERT_EQ(0, statistics->null_count());
    ASSERT_EQ(0, statistics->num_values());
    ASSERT_EQ(0, statistics->distinct_count());
    ASSERT_EQ("", statistics->EncodeMin());
    ASSERT_EQ("", statistics->EncodeMax());
  }

  void TestMerge() {
    int num_null[2];
    random_numbers(2, 42, 0, 100, num_null);

    auto statistics1 = MakeStatistics<TestType>(this->schema_.Column(0));
    this->GenerateData(1000);
    statistics1->Update(this->values_ptr_, this->values_.size() - num_null[0],
                        num_null[0]);

    auto statistics2 = MakeStatistics<TestType>(this->schema_.Column(0));
    this->GenerateData(1000);
    statistics2->Update(this->values_ptr_, this->values_.size() - num_null[1],
                        num_null[1]);

    auto total = MakeStatistics<TestType>(this->schema_.Column(0));
    total->Merge(*statistics1);
    total->Merge(*statistics2);

    ASSERT_EQ(num_null[0] + num_null[1], total->null_count());
    ASSERT_EQ(this->values_.size() * 2 - num_null[0] - num_null[1], total->num_values());
    ASSERT_EQ(total->min(), std::min(statistics1->min(), statistics2->min()));
    ASSERT_EQ(total->max(), std::max(statistics1->max(), statistics2->max()));
  }

  void TestEquals() {
    const auto n_values = 1;
    auto statistics_have_minmax1 = MakeStatistics<TestType>(this->schema_.Column(0));
    const auto seed1 = 1;
    this->GenerateData(n_values, seed1);
    statistics_have_minmax1->Update(this->values_ptr_, this->values_.size(), 0);
    auto statistics_have_minmax2 = MakeStatistics<TestType>(this->schema_.Column(0));
    const auto seed2 = 9999;
    this->GenerateData(n_values, seed2);
    statistics_have_minmax2->Update(this->values_ptr_, this->values_.size(), 0);
    auto statistics_no_minmax = MakeStatistics<TestType>(this->schema_.Column(0));

    ASSERT_EQ(true, statistics_have_minmax1->Equals(*statistics_have_minmax1));
    ASSERT_EQ(true, statistics_no_minmax->Equals(*statistics_no_minmax));
    ASSERT_EQ(false, statistics_have_minmax1->Equals(*statistics_have_minmax2));
    ASSERT_EQ(false, statistics_have_minmax1->Equals(*statistics_no_minmax));
  }

  void TestFullRoundtrip(int64_t num_values, int64_t null_count) {
    this->GenerateData(num_values);

    // compute statistics for the whole batch
    auto expected_stats = MakeStatistics<TestType>(this->schema_.Column(0));
    expected_stats->Update(this->values_ptr_, num_values - null_count, null_count);

    auto sink = CreateOutputStream();
    auto gnode = std::static_pointer_cast<GroupNode>(this->node_);
    std::shared_ptr<WriterProperties> writer_properties =
        WriterProperties::Builder().enable_statistics("column")->build();
    auto file_writer = ParquetFileWriter::Open(sink, gnode, writer_properties);
    auto row_group_writer = file_writer->AppendRowGroup();
    auto column_writer =
        static_cast<TypedColumnWriter<TestType>*>(row_group_writer->NextColumn());

    // simulate the case when data comes from multiple buffers,
    // in which case special care is necessary for FLBA/ByteArray types
    for (int i = 0; i < 2; i++) {
      int64_t batch_num_values = i ? num_values - num_values / 2 : num_values / 2;
      int64_t batch_null_count = i ? null_count : 0;
      DCHECK(null_count <= num_values);  // avoid too much headache
      std::vector<int16_t> definition_levels(batch_null_count, 0);
      definition_levels.insert(definition_levels.end(),
                               batch_num_values - batch_null_count, 1);
      auto beg = this->values_.begin() + i * num_values / 2;
      auto end = beg + batch_num_values;
      std::vector<c_type> batch = GetDeepCopy(std::vector<c_type>(beg, end));
      c_type* batch_values_ptr = GetValuesPointer(batch);
      column_writer->WriteBatch(batch_num_values, definition_levels.data(), nullptr,
                                batch_values_ptr);
      DeepFree(batch);
    }
    column_writer->Close();
    row_group_writer->Close();
    file_writer->Close();

    ASSERT_OK_AND_ASSIGN(auto buffer, sink->Finish());
    auto source = std::make_shared<::arrow::io::BufferReader>(buffer);
    auto file_reader = ParquetFileReader::Open(source);
    auto rg_reader = file_reader->RowGroup(0);
    auto column_chunk = rg_reader->metadata()->ColumnChunk(0);
    if (!column_chunk->is_stats_set()) return;
    std::shared_ptr<Statistics> stats = column_chunk->statistics();
    // check values after serialization + deserialization
    EXPECT_EQ(null_count, stats->null_count());
    EXPECT_EQ(num_values - null_count, stats->num_values());
    EXPECT_TRUE(expected_stats->HasMinMax());
    EXPECT_EQ(expected_stats->EncodeMin(), stats->EncodeMin());
    EXPECT_EQ(expected_stats->EncodeMax(), stats->EncodeMax());

    std::shared_ptr<EncodedStatistics> enc_stats = column_chunk->encoded_statistics();
    EXPECT_EQ(null_count, enc_stats->null_count);
    EXPECT_TRUE(enc_stats->has_min);
    EXPECT_TRUE(enc_stats->has_max);
    EXPECT_EQ(expected_stats->EncodeMin(), enc_stats->min());
    EXPECT_EQ(expected_stats->EncodeMax(), enc_stats->max());
    EXPECT_EQ(enc_stats->is_min_value_exact, std::make_optional(true));
    EXPECT_EQ(enc_stats->is_max_value_exact, std::make_optional(true));
  }
};

template <typename TestType>
typename TestType::c_type* TestStatistics<TestType>::GetValuesPointer(
    std::vector<typename TestType::c_type>& values) {
  return values.data();
}

template <>
bool* TestStatistics<BooleanType>::GetValuesPointer(std::vector<bool>& values) {
  static std::vector<uint8_t> bool_buffer;
  bool_buffer.clear();
  bool_buffer.resize(values.size());
  std::copy(values.begin(), values.end(), bool_buffer.begin());
  return reinterpret_cast<bool*>(bool_buffer.data());
}

template <typename TestType>
typename std::vector<typename TestType::c_type> TestStatistics<TestType>::GetDeepCopy(
    const std::vector<typename TestType::c_type>& values) {
  return values;
}

template <>
std::vector<FLBA> TestStatistics<FLBAType>::GetDeepCopy(const std::vector<FLBA>& values) {
  std::vector<FLBA> copy;
  MemoryPool* pool = ::arrow::default_memory_pool();
  for (const FLBA& flba : values) {
    uint8_t* ptr;
    PARQUET_THROW_NOT_OK(pool->Allocate(FLBA_LENGTH, &ptr));
    memcpy(ptr, flba.ptr, FLBA_LENGTH);
    copy.emplace_back(ptr);
  }
  return copy;
}

template <>
std::vector<ByteArray> TestStatistics<ByteArrayType>::GetDeepCopy(
    const std::vector<ByteArray>& values) {
  std::vector<ByteArray> copy;
  MemoryPool* pool = default_memory_pool();
  for (const ByteArray& ba : values) {
    uint8_t* ptr;
    PARQUET_THROW_NOT_OK(pool->Allocate(ba.len, &ptr));
    SafeMemcpy(ptr, ba.ptr, ba.len);
    copy.emplace_back(ba.len, ptr);
  }
  return copy;
}

template <typename TestType>
void TestStatistics<TestType>::DeepFree(std::vector<typename TestType::c_type>& values) {}

template <>
void TestStatistics<FLBAType>::DeepFree(std::vector<FLBA>& values) {
  MemoryPool* pool = default_memory_pool();
  for (FLBA& flba : values) {
    auto ptr = const_cast<uint8_t*>(flba.ptr);
    memset(ptr, 0, FLBA_LENGTH);
    pool->Free(ptr, FLBA_LENGTH);
  }
}

template <>
void TestStatistics<ByteArrayType>::DeepFree(std::vector<ByteArray>& values) {
  MemoryPool* pool = default_memory_pool();
  for (ByteArray& ba : values) {
    auto ptr = const_cast<uint8_t*>(ba.ptr);
    memset(ptr, 0, ba.len);
    pool->Free(ptr, ba.len);
  }
}

template <>
void TestStatistics<ByteArrayType>::TestMinMaxEncode() {
  this->GenerateData(1000);
  // Test that we encode min max strings correctly
  auto statistics1 = MakeStatistics<ByteArrayType>(this->schema_.Column(0));
  statistics1->Update(this->values_ptr_, this->values_.size(), 0);
  std::string encoded_min = statistics1->EncodeMin();
  std::string encoded_max = statistics1->EncodeMax();

  // encoded is same as unencoded
  ASSERT_EQ(encoded_min,
            std::string(reinterpret_cast<const char*>(statistics1->min().ptr),
                        statistics1->min().len));
  ASSERT_EQ(encoded_max,
            std::string(reinterpret_cast<const char*>(statistics1->max().ptr),
                        statistics1->max().len));

  auto statistics2 = MakeStatistics<ByteArrayType>(
      this->schema_.Column(0), encoded_min, encoded_max, this->values_.size(),
      /*null_count=*/0,
      /*distinct_count=*/0, /*has_min_max=*/true, /*has_null_count=*/true,
      /*has_distinct_count=*/true, /*is_min_value_exact=*/true,
      /*is_max_value_exact=*/true);

  ASSERT_EQ(encoded_min, statistics2->EncodeMin());
  ASSERT_EQ(encoded_max, statistics2->EncodeMax());
  ASSERT_EQ(statistics1->min(), statistics2->min());
  ASSERT_EQ(statistics1->max(), statistics2->max());
}

using Types = ::testing::Types<Int32Type, Int64Type, FloatType, DoubleType, ByteArrayType,
                               FLBAType, BooleanType>;

TYPED_TEST_SUITE(TestStatistics, Types);

TYPED_TEST(TestStatistics, MinMaxEncode) {
  this->SetUpSchema(Repetition::REQUIRED);
  ASSERT_NO_FATAL_FAILURE(this->TestMinMaxEncode());
}

TYPED_TEST(TestStatistics, Reset) {
  this->SetUpSchema(Repetition::OPTIONAL);
  ASSERT_NO_FATAL_FAILURE(this->TestReset());
}

TYPED_TEST(TestStatistics, Equals) {
  this->SetUpSchema(Repetition::OPTIONAL);
  ASSERT_NO_FATAL_FAILURE(this->TestEquals());
}

TYPED_TEST(TestStatistics, FullRoundtrip) {
  this->SetUpSchema(Repetition::OPTIONAL);
  ASSERT_NO_FATAL_FAILURE(this->TestFullRoundtrip(100, 31));
  ASSERT_NO_FATAL_FAILURE(this->TestFullRoundtrip(1000, 415));
  ASSERT_NO_FATAL_FAILURE(this->TestFullRoundtrip(10000, 926));
}

template <typename TestType>
class TestNumericStatistics : public TestStatistics<TestType> {};

using NumericTypes = ::testing::Types<Int32Type, Int64Type, FloatType, DoubleType>;

TYPED_TEST_SUITE(TestNumericStatistics, NumericTypes);

TYPED_TEST(TestNumericStatistics, Merge) {
  this->SetUpSchema(Repetition::OPTIONAL);
  ASSERT_NO_FATAL_FAILURE(this->TestMerge());
}

TYPED_TEST(TestNumericStatistics, Equals) {
  this->SetUpSchema(Repetition::OPTIONAL);
  ASSERT_NO_FATAL_FAILURE(this->TestEquals());
}

template <typename TestType>
class TestStatisticsHasFlag : public TestStatistics<TestType> {
 public:
  void SetUp() override {
    TestStatistics<TestType>::SetUp();
    this->SetUpSchema(Repetition::OPTIONAL);
  }

  std::optional<int64_t> MergeDistinctCount(
      std::optional<int64_t> initial,
      const std::vector<std::optional<int64_t>>& subsequent) {
    EncodedStatistics encoded_statistics;
    if (initial) {
      encoded_statistics.has_distinct_count = true;
      encoded_statistics.distinct_count = *initial;
    }
    std::shared_ptr<TypedStatistics<TestType>> statistics =
        std::dynamic_pointer_cast<TypedStatistics<TestType>>(
            Statistics::Make(this->schema_.Column(0), &encoded_statistics,
                             /*num_values=*/1000));
    for (const auto& distinct_count : subsequent) {
      EncodedStatistics next_encoded_statistics;
      if (distinct_count) {
        next_encoded_statistics.has_distinct_count = true;
        next_encoded_statistics.distinct_count = *distinct_count;
      }
      std::shared_ptr<TypedStatistics<TestType>> next_statistics =
          std::dynamic_pointer_cast<TypedStatistics<TestType>>(
              Statistics::Make(this->schema_.Column(0), &next_encoded_statistics,
                               /*num_values=*/1000));
      statistics->Merge(*next_statistics);
    }
    EncodedStatistics final_statistics = statistics->Encode();
    EXPECT_EQ(statistics->HasDistinctCount(), final_statistics.has_distinct_count);
    if (statistics->HasDistinctCount()) {
      EXPECT_EQ(statistics->distinct_count(), final_statistics.distinct_count);
      return statistics->distinct_count();
    }
    return std::nullopt;
  }

  std::shared_ptr<TypedStatistics<TestType>> MergedStatistics(
      const TypedStatistics<TestType>& stats1, const TypedStatistics<TestType>& stats2) {
    auto chunk_statistics = MakeStatistics<TestType>(this->schema_.Column(0));
    chunk_statistics->Merge(stats1);
    chunk_statistics->Merge(stats2);
    return chunk_statistics;
  }

  void VerifyMergedStatistics(
      const TypedStatistics<TestType>& stats1, const TypedStatistics<TestType>& stats2,
      const std::function<void(TypedStatistics<TestType>*)>& test_fn) {
    ASSERT_NO_FATAL_FAILURE(test_fn(MergedStatistics(stats1, stats2).get()));
    ASSERT_NO_FATAL_FAILURE(test_fn(MergedStatistics(stats2, stats1).get()));
  }

  // Distinct count should set to false when Merge is called, unless one of the statistics
  // has a zero count.
  void TestMergeDistinctCount() {
    // Sanity tests.
    ASSERT_EQ(std::nullopt, MergeDistinctCount(std::nullopt, {}));
    ASSERT_EQ(10, MergeDistinctCount(10, {}));

    ASSERT_EQ(std::nullopt, MergeDistinctCount(std::nullopt, {0}));
    ASSERT_EQ(std::nullopt, MergeDistinctCount(std::nullopt, {10, 0}));
    ASSERT_EQ(10, MergeDistinctCount(10, {0, 0}));
    ASSERT_EQ(10, MergeDistinctCount(0, {10, 0}));
    ASSERT_EQ(10, MergeDistinctCount(0, {0, 10}));
    ASSERT_EQ(10, MergeDistinctCount(0, {0, 10, 0}));
    ASSERT_EQ(std::nullopt, MergeDistinctCount(10, {0, 10}));
    ASSERT_EQ(std::nullopt, MergeDistinctCount(10, {0, std::nullopt}));
    ASSERT_EQ(std::nullopt, MergeDistinctCount(0, {std::nullopt, 0}));
  }

  // If all values in a page are null or nan, its stats should not set min-max.
  // Merging its stats with another page having good min-max stats should not
  // drop the valid min-max from the latter page.
  void TestMergeMinMax() {
    this->GenerateData(1000);
    // Create a statistics object without min-max.
    std::shared_ptr<TypedStatistics<TestType>> statistics1;
    {
      statistics1 = MakeStatistics<TestType>(this->schema_.Column(0));
      statistics1->Update(this->values_ptr_, /*num_values=*/0,
                          /*null_count=*/this->values_.size());
      auto encoded_stats1 = statistics1->Encode();
      EXPECT_FALSE(statistics1->HasMinMax());
      EXPECT_FALSE(encoded_stats1.has_min);
      EXPECT_FALSE(encoded_stats1.has_max);
      EXPECT_EQ(encoded_stats1.is_max_value_exact, std::nullopt);
      EXPECT_EQ(encoded_stats1.is_min_value_exact, std::nullopt);
    }
    // Create a statistics object with min-max.
    std::shared_ptr<TypedStatistics<TestType>> statistics2;
    {
      statistics2 = MakeStatistics<TestType>(this->schema_.Column(0));
      statistics2->Update(this->values_ptr_, this->values_.size(), 0);
      auto encoded_stats2 = statistics2->Encode();
      EXPECT_TRUE(statistics2->HasMinMax());
      EXPECT_TRUE(encoded_stats2.has_min);
      EXPECT_TRUE(encoded_stats2.has_max);
      EXPECT_EQ(encoded_stats2.is_min_value_exact, std::make_optional(true));
      EXPECT_EQ(encoded_stats2.is_max_value_exact, std::make_optional(true));
    }
    VerifyMergedStatistics(*statistics1, *statistics2,
                           [](TypedStatistics<TestType>* merged_statistics) {
                             EXPECT_TRUE(merged_statistics->HasMinMax());
                             EXPECT_TRUE(merged_statistics->Encode().has_min);
                             EXPECT_TRUE(merged_statistics->Encode().has_max);
                             EXPECT_EQ(merged_statistics->Encode().is_min_value_exact,
                                       std::make_optional(true));
                             EXPECT_EQ(merged_statistics->Encode().is_max_value_exact,
                                       std::make_optional(true));
                           });
  }

  // Default statistics should have null_count even if no nulls is written.
  // However, if statistics is created from thrift message, it might not
  // have null_count. Merging statistics from such page will result in an
  // invalid null_count as well.
  void TestMergeNullCount() {
    this->GenerateData(/*num_values=*/1000);

    // Page should have null-count even if no nulls
    std::shared_ptr<TypedStatistics<TestType>> statistics1;
    {
      statistics1 = MakeStatistics<TestType>(this->schema_.Column(0));
      statistics1->Update(this->values_ptr_, /*num_values=*/this->values_.size(),
                          /*null_count=*/0);
      auto encoded_stats1 = statistics1->Encode();
      EXPECT_TRUE(statistics1->HasNullCount());
      EXPECT_EQ(0, statistics1->null_count());
      EXPECT_TRUE(statistics1->Encode().has_null_count);
    }
    // Merge with null-count should also have null count
    VerifyMergedStatistics(*statistics1, *statistics1,
                           [](TypedStatistics<TestType>* merged_statistics) {
                             EXPECT_TRUE(merged_statistics->HasNullCount());
                             EXPECT_EQ(0, merged_statistics->null_count());
                             auto encoded = merged_statistics->Encode();
                             EXPECT_TRUE(encoded.has_null_count);
                             EXPECT_EQ(0, encoded.null_count);
                           });

    // When loaded from thrift, might not have null count.
    std::shared_ptr<TypedStatistics<TestType>> statistics2;
    {
      EncodedStatistics encoded_statistics2;
      encoded_statistics2.has_null_count = false;
      statistics2 = std::dynamic_pointer_cast<TypedStatistics<TestType>>(
          Statistics::Make(this->schema_.Column(0), &encoded_statistics2,
                           /*num_values=*/1000));
      EXPECT_FALSE(statistics2->Encode().has_null_count);
      EXPECT_FALSE(statistics2->HasNullCount());
    }

    // Merge without null-count should not have null count
    VerifyMergedStatistics(*statistics1, *statistics2,
                           [](TypedStatistics<TestType>* merged_statistics) {
                             EXPECT_FALSE(merged_statistics->HasNullCount());
                             EXPECT_FALSE(merged_statistics->Encode().has_null_count);
                           });
  }

  // statistics.all_null_value is used to build the page index.
  // If statistics doesn't have null count, all_null_value should be false.
  void TestMissingNullCount() {
    EncodedStatistics encoded_statistics;
    encoded_statistics.has_null_count = false;
    auto statistics = Statistics::Make(this->schema_.Column(0), &encoded_statistics,
                                       /*num_values=*/1000);
    auto typed_stats = std::dynamic_pointer_cast<TypedStatistics<TestType>>(statistics);
    EXPECT_FALSE(typed_stats->HasNullCount());
    auto encoded = typed_stats->Encode();
    EXPECT_FALSE(encoded.all_null_value);
    EXPECT_FALSE(encoded.has_null_count);
    EXPECT_FALSE(encoded.has_distinct_count);
    EXPECT_FALSE(encoded.has_min);
    EXPECT_FALSE(encoded.has_max);
    EXPECT_FALSE(encoded.is_min_value_exact.has_value());
    EXPECT_FALSE(encoded.is_max_value_exact.has_value());
  }
};

TYPED_TEST_SUITE(TestStatisticsHasFlag, Types);

TYPED_TEST(TestStatisticsHasFlag, MergeDistinctCount) {
  ASSERT_NO_FATAL_FAILURE(this->TestMergeDistinctCount());
}

TYPED_TEST(TestStatisticsHasFlag, MergeNullCount) {
  ASSERT_NO_FATAL_FAILURE(this->TestMergeNullCount());
}

TYPED_TEST(TestStatisticsHasFlag, MergeMinMax) {
  ASSERT_NO_FATAL_FAILURE(this->TestMergeMinMax());
}

TYPED_TEST(TestStatisticsHasFlag, MissingNullCount) {
  ASSERT_NO_FATAL_FAILURE(this->TestMissingNullCount());
}

// Helper for basic statistics tests below
void AssertStatsSet(const ApplicationVersion& version,
                    std::shared_ptr<parquet::WriterProperties> props,
                    const ColumnDescriptor* column, bool expected_is_set) {
  auto metadata_builder = ColumnChunkMetaDataBuilder::Make(props, column);
  auto column_chunk = ColumnChunkMetaData::Make(metadata_builder->contents(), column,
                                                default_reader_properties(), &version);
  EncodedStatistics stats;
  stats.set_is_signed(false);
  metadata_builder->SetStatistics(stats);
  ASSERT_EQ(column_chunk->is_stats_set(), expected_is_set);
  if (expected_is_set) {
    ASSERT_TRUE(column_chunk->encoded_statistics() != nullptr);
  } else {
    ASSERT_TRUE(column_chunk->encoded_statistics() == nullptr);
  }
}

// Statistics are restricted for few types in older parquet version
TEST(CorruptStatistics, Basics) {
  std::string created_by = "parquet-mr version 1.8.0";
  ApplicationVersion version(created_by);
  SchemaDescriptor schema;
  schema::NodePtr node;
  std::vector<schema::NodePtr> fields;
  // Test Physical Types
  fields.push_back(schema::PrimitiveNode::Make("col1", Repetition::OPTIONAL, Type::INT32,
                                               ConvertedType::NONE));
  fields.push_back(schema::PrimitiveNode::Make("col2", Repetition::OPTIONAL,
                                               Type::BYTE_ARRAY, ConvertedType::NONE));
  // Test Logical Types
  fields.push_back(schema::PrimitiveNode::Make("col3", Repetition::OPTIONAL, Type::INT32,
                                               ConvertedType::DATE));
  fields.push_back(schema::PrimitiveNode::Make("col4", Repetition::OPTIONAL, Type::INT32,
                                               ConvertedType::UINT_32));
  fields.push_back(schema::PrimitiveNode::Make("col5", Repetition::OPTIONAL,
                                               Type::FIXED_LEN_BYTE_ARRAY,
                                               ConvertedType::INTERVAL, 12));
  fields.push_back(schema::PrimitiveNode::Make("col6", Repetition::OPTIONAL,
                                               Type::BYTE_ARRAY, ConvertedType::UTF8));
  node = schema::GroupNode::Make("schema", Repetition::REQUIRED, fields);
  schema.Init(node);

  parquet::WriterProperties::Builder builder;
  builder.created_by(created_by);
  std::shared_ptr<parquet::WriterProperties> props = builder.build();

  AssertStatsSet(version, props, schema.Column(0), true);
  AssertStatsSet(version, props, schema.Column(1), false);
  AssertStatsSet(version, props, schema.Column(2), true);
  AssertStatsSet(version, props, schema.Column(3), false);
  AssertStatsSet(version, props, schema.Column(4), false);
  AssertStatsSet(version, props, schema.Column(5), false);
}

// Statistics for all types have no restrictions in newer parquet version
TEST(CorrectStatistics, Basics) {
  std::string created_by = "parquet-cpp version 1.3.0";
  ApplicationVersion version(created_by);
  SchemaDescriptor schema;
  schema::NodePtr node;
  std::vector<schema::NodePtr> fields;
  // Test Physical Types
  fields.push_back(schema::PrimitiveNode::Make("col1", Repetition::OPTIONAL, Type::INT32,
                                               ConvertedType::NONE));
  fields.push_back(schema::PrimitiveNode::Make("col2", Repetition::OPTIONAL,
                                               Type::BYTE_ARRAY, ConvertedType::NONE));
  // Test Logical Types
  fields.push_back(schema::PrimitiveNode::Make("col3", Repetition::OPTIONAL, Type::INT32,
                                               ConvertedType::DATE));
  fields.push_back(schema::PrimitiveNode::Make("col4", Repetition::OPTIONAL, Type::INT32,
                                               ConvertedType::UINT_32));
  fields.push_back(schema::PrimitiveNode::Make("col5", Repetition::OPTIONAL,
                                               Type::FIXED_LEN_BYTE_ARRAY,
                                               ConvertedType::INTERVAL, 12));
  fields.push_back(schema::PrimitiveNode::Make("col6", Repetition::OPTIONAL,
                                               Type::BYTE_ARRAY, ConvertedType::UTF8));
  node = schema::GroupNode::Make("schema", Repetition::REQUIRED, fields);
  schema.Init(node);

  parquet::WriterProperties::Builder builder;
  builder.created_by(created_by);
  std::shared_ptr<parquet::WriterProperties> props = builder.build();

  AssertStatsSet(version, props, schema.Column(0), true);
  AssertStatsSet(version, props, schema.Column(1), true);
  AssertStatsSet(version, props, schema.Column(2), true);
  AssertStatsSet(version, props, schema.Column(3), true);
  AssertStatsSet(version, props, schema.Column(4), true);
  AssertStatsSet(version, props, schema.Column(5), true);
}

// Test SortOrder class
static const int NUM_VALUES = 10;

template <typename T>
struct RebindLogical {
  using ParquetType = T;
  using CType = typename T::c_type;
};

template <>
struct RebindLogical<Float16LogicalType> {
  using ParquetType = FLBAType;
  using CType = ParquetType::c_type;
};

template <typename T>
class TestStatisticsSortOrder : public ::testing::Test {
 public:
  using TestType = typename RebindLogical<T>::ParquetType;
  using c_type = typename TestType::c_type;

  void SetUp() override {
#ifndef ARROW_WITH_SNAPPY
    GTEST_SKIP() << "Test requires Snappy compression";
#endif
  }

  void AddNodes(std::string name) {
    fields_.push_back(schema::PrimitiveNode::Make(
        name, Repetition::REQUIRED, TestType::type_num, ConvertedType::NONE));
  }

  void SetUpSchema() {
    stats_.resize(fields_.size());
    values_.resize(NUM_VALUES);
    schema_ = std::static_pointer_cast<GroupNode>(
        GroupNode::Make("Schema", Repetition::REQUIRED, fields_));

    parquet_sink_ = CreateOutputStream();
  }

  void SetValues();

  void WriteParquet() {
    // Add writer properties
    parquet::WriterProperties::Builder builder;
    builder.compression(parquet::Compression::SNAPPY);
    builder.created_by("parquet-cpp version 1.3.0");
    std::shared_ptr<parquet::WriterProperties> props = builder.build();

    // Create a ParquetFileWriter instance
    auto file_writer = parquet::ParquetFileWriter::Open(parquet_sink_, schema_, props);

    // Append a RowGroup with a specific number of rows.
    auto rg_writer = file_writer->AppendRowGroup();

    this->SetValues();

    // Insert Values
    for (int i = 0; i < static_cast<int>(fields_.size()); i++) {
      auto column_writer =
          static_cast<parquet::TypedColumnWriter<TestType>*>(rg_writer->NextColumn());
      column_writer->WriteBatch(NUM_VALUES, nullptr, nullptr, values_.data());
    }
  }

  void VerifyParquetStats() {
    ASSERT_OK_AND_ASSIGN(auto pbuffer, parquet_sink_->Finish());

    // Create a ParquetReader instance
    std::unique_ptr<parquet::ParquetFileReader> parquet_reader =
        parquet::ParquetFileReader::Open(
            std::make_shared<::arrow::io::BufferReader>(pbuffer));

    // Get the File MetaData
    std::shared_ptr<parquet::FileMetaData> file_metadata = parquet_reader->metadata();
    std::shared_ptr<parquet::RowGroupMetaData> rg_metadata = file_metadata->RowGroup(0);
    for (int i = 0; i < static_cast<int>(fields_.size()); i++) {
      ARROW_SCOPED_TRACE("Statistics for field #", i);
      std::shared_ptr<parquet::ColumnChunkMetaData> cc_metadata =
          rg_metadata->ColumnChunk(i);
      EXPECT_EQ(stats_[i].min(), cc_metadata->statistics()->EncodeMin());
      EXPECT_EQ(stats_[i].max(), cc_metadata->statistics()->EncodeMax());
      EXPECT_EQ(stats_[i].is_max_value_exact, std::make_optional(true));
      EXPECT_EQ(stats_[i].is_min_value_exact, std::make_optional(true));
    }
  }

 protected:
  std::vector<c_type> values_;
  std::vector<uint8_t> values_buf_;
  std::vector<schema::NodePtr> fields_;
  std::shared_ptr<schema::GroupNode> schema_;
  std::shared_ptr<::arrow::io::BufferOutputStream> parquet_sink_;
  std::vector<EncodedStatistics> stats_;
};

using CompareTestTypes = ::testing::Types<Int32Type, Int64Type, FloatType, DoubleType,
                                          ByteArrayType, FLBAType, Float16LogicalType>;

// TYPE::INT32
template <>
void TestStatisticsSortOrder<Int32Type>::AddNodes(std::string name) {
  // UINT_32 logical type to set Unsigned Statistics
  fields_.push_back(schema::PrimitiveNode::Make(name, Repetition::REQUIRED, Type::INT32,
                                                ConvertedType::UINT_32));
  // INT_32 logical type to set Signed Statistics
  fields_.push_back(schema::PrimitiveNode::Make(name, Repetition::REQUIRED, Type::INT32,
                                                ConvertedType::INT_32));
}

template <>
void TestStatisticsSortOrder<Int32Type>::SetValues() {
  for (int i = 0; i < NUM_VALUES; i++) {
    values_[i] = i - 5;  // {-5, -4, -3, -2, -1, 0, 1, 2, 3, 4};
  }

  // Write UINT32 min/max values
  stats_[0]
      .set_min(std::string(reinterpret_cast<const char*>(&values_[5]), sizeof(c_type)))
      .set_max(std::string(reinterpret_cast<const char*>(&values_[4]), sizeof(c_type)));
  stats_[0].is_max_value_exact = true;
  stats_[0].is_min_value_exact = true;

  // Write INT32 min/max values
  stats_[1]
      .set_min(std::string(reinterpret_cast<const char*>(&values_[0]), sizeof(c_type)))
      .set_max(std::string(reinterpret_cast<const char*>(&values_[9]), sizeof(c_type)));
  stats_[1].is_max_value_exact = true;
  stats_[1].is_min_value_exact = true;
}

// TYPE::INT64
template <>
void TestStatisticsSortOrder<Int64Type>::AddNodes(std::string name) {
  // UINT_64 logical type to set Unsigned Statistics
  fields_.push_back(schema::PrimitiveNode::Make(name, Repetition::REQUIRED, Type::INT64,
                                                ConvertedType::UINT_64));
  // INT_64 logical type to set Signed Statistics
  fields_.push_back(schema::PrimitiveNode::Make(name, Repetition::REQUIRED, Type::INT64,
                                                ConvertedType::INT_64));
}

template <>
void TestStatisticsSortOrder<Int64Type>::SetValues() {
  for (int i = 0; i < NUM_VALUES; i++) {
    values_[i] = i - 5;  // {-5, -4, -3, -2, -1, 0, 1, 2, 3, 4};
  }

  // Write UINT64 min/max values
  stats_[0]
      .set_min(std::string(reinterpret_cast<const char*>(&values_[5]), sizeof(c_type)))
      .set_max(std::string(reinterpret_cast<const char*>(&values_[4]), sizeof(c_type)));
  stats_[0].is_max_value_exact = true;
  stats_[0].is_min_value_exact = true;

  // Write INT64 min/max values
  stats_[1]
      .set_min(std::string(reinterpret_cast<const char*>(&values_[0]), sizeof(c_type)))
      .set_max(std::string(reinterpret_cast<const char*>(&values_[9]), sizeof(c_type)));
  stats_[1].is_max_value_exact = true;
  stats_[1].is_min_value_exact = true;
}

// TYPE::FLOAT
template <>
void TestStatisticsSortOrder<FloatType>::SetValues() {
  for (int i = 0; i < NUM_VALUES; i++) {
    values_[i] = static_cast<float>(i) -
                 5;  // {-5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0};
  }

  // Write Float min/max values
  stats_[0]
      .set_min(std::string(reinterpret_cast<const char*>(&values_[0]), sizeof(c_type)))
      .set_max(std::string(reinterpret_cast<const char*>(&values_[9]), sizeof(c_type)));
  stats_[0].is_max_value_exact = true;
  stats_[0].is_min_value_exact = true;
}

// TYPE::DOUBLE
template <>
void TestStatisticsSortOrder<DoubleType>::SetValues() {
  for (int i = 0; i < NUM_VALUES; i++) {
    values_[i] = static_cast<float>(i) -
                 5;  // {-5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0};
  }

  // Write Double min/max values
  stats_[0]
      .set_min(std::string(reinterpret_cast<const char*>(&values_[0]), sizeof(c_type)))
      .set_max(std::string(reinterpret_cast<const char*>(&values_[9]), sizeof(c_type)));
  stats_[0].is_max_value_exact = true;
  stats_[0].is_min_value_exact = true;
}

// TYPE::ByteArray
template <>
void TestStatisticsSortOrder<ByteArrayType>::AddNodes(std::string name) {
  // UTF8 logical type to set Unsigned Statistics
  fields_.push_back(schema::PrimitiveNode::Make(name, Repetition::REQUIRED,
                                                Type::BYTE_ARRAY, ConvertedType::UTF8));
}

template <>
void TestStatisticsSortOrder<ByteArrayType>::SetValues() {
  int max_byte_array_len = 10;
  size_t nbytes = NUM_VALUES * max_byte_array_len;
  values_buf_.resize(nbytes);
  std::vector<std::string> vals = {"c123", "b123", "a123", "d123", "e123",
                                   "f123", "g123", "h123", "i123", "ü123"};

  uint8_t* base = &values_buf_.data()[0];
  for (int i = 0; i < NUM_VALUES; i++) {
    memcpy(base, vals[i].c_str(), vals[i].length());
    values_[i].ptr = base;
    values_[i].len = static_cast<uint32_t>(vals[i].length());
    base += vals[i].length();
  }

  // Write String min/max values
  stats_[0]
      .set_min(
          std::string(reinterpret_cast<const char*>(vals[2].c_str()), vals[2].length()))
      .set_max(
          std::string(reinterpret_cast<const char*>(vals[9].c_str()), vals[9].length()));
  stats_[0].is_max_value_exact = true;
  stats_[0].is_min_value_exact = true;
}

// TYPE::FLBAArray
template <>
void TestStatisticsSortOrder<FLBAType>::AddNodes(std::string name) {
  // FLBA has only Unsigned Statistics
  fields_.push_back(schema::PrimitiveNode::Make(name, Repetition::REQUIRED,
                                                Type::FIXED_LEN_BYTE_ARRAY,
                                                ConvertedType::NONE, FLBA_LENGTH));
}

template <>
void TestStatisticsSortOrder<FLBAType>::SetValues() {
  size_t nbytes = NUM_VALUES * FLBA_LENGTH;
  values_buf_.resize(nbytes);
  char vals[NUM_VALUES][FLBA_LENGTH] = {"b12345", "a12345", "c12345", "d12345", "e12345",
                                        "f12345", "g12345", "h12345", "z12345", "a12345"};

  uint8_t* base = &values_buf_.data()[0];
  for (int i = 0; i < NUM_VALUES; i++) {
    memcpy(base, &vals[i][0], FLBA_LENGTH);
    values_[i].ptr = base;
    base += FLBA_LENGTH;
  }

  // Write FLBA min,max values
  stats_[0]
      .set_min(std::string(reinterpret_cast<const char*>(&vals[1][0]), FLBA_LENGTH))
      .set_max(std::string(reinterpret_cast<const char*>(&vals[8][0]), FLBA_LENGTH));
  stats_[0].is_max_value_exact = true;
  stats_[0].is_min_value_exact = true;
}

template <>
void TestStatisticsSortOrder<Float16LogicalType>::AddNodes(std::string name) {
  auto node =
      schema::PrimitiveNode::Make(name, Repetition::REQUIRED, LogicalType::Float16(),
                                  Type::FIXED_LEN_BYTE_ARRAY, sizeof(uint16_t));
  fields_.push_back(std::move(node));
}

template <>
void TestStatisticsSortOrder<Float16LogicalType>::SetValues() {
  constexpr int kValueLen = 2;
  constexpr int kNumBytes = NUM_VALUES * kValueLen;

  const Float16 f16_vals[NUM_VALUES] = {
      Float16::FromFloat(+2.0f), Float16::FromFloat(-4.0f), Float16::FromFloat(+4.0f),
      Float16::FromFloat(-2.0f), Float16::FromFloat(-1.0f), Float16::FromFloat(+3.0f),
      Float16::FromFloat(+1.0f), Float16::FromFloat(-5.0f), Float16::FromFloat(+0.0f),
      Float16::FromFloat(-3.0f),
  };

  values_buf_.resize(kNumBytes);
  uint8_t* ptr = values_buf_.data();
  for (int i = 0; i < NUM_VALUES; ++i) {
    f16_vals[i].ToLittleEndian(ptr);
    values_[i].ptr = ptr;
    ptr += kValueLen;
  }

  stats_[0]
      .set_min(std::string(reinterpret_cast<const char*>(values_[7].ptr), kValueLen))
      .set_max(std::string(reinterpret_cast<const char*>(values_[2].ptr), kValueLen));
  stats_[0].is_max_value_exact = true;
  stats_[0].is_min_value_exact = true;
}

TYPED_TEST_SUITE(TestStatisticsSortOrder, CompareTestTypes);

TYPED_TEST(TestStatisticsSortOrder, MinMax) {
  this->AddNodes("Column ");
  this->SetUpSchema();
  this->WriteParquet();
  ASSERT_NO_FATAL_FAILURE(this->VerifyParquetStats());
}

template <typename ArrowType>
void TestByteArrayStatisticsFromArrow() {
  using TypeTraits = ::arrow::TypeTraits<ArrowType>;
  using ArrayType = typename TypeTraits::ArrayType;

  auto values = ArrayFromJSON(TypeTraits::type_singleton(),
                              "[\"c123\", \"b123\", \"a123\", null, "
                              "null, \"f123\", \"g123\", \"h123\", \"i123\", \"ü123\"]");

  const auto& typed_values = static_cast<const ArrayType&>(*values);

  NodePtr node = PrimitiveNode::Make("field", Repetition::REQUIRED, Type::BYTE_ARRAY,
                                     ConvertedType::UTF8);
  ColumnDescriptor descr(node, 0, 0);
  auto stats = MakeStatistics<ByteArrayType>(&descr);
  ASSERT_NO_FATAL_FAILURE(stats->Update(*values));

  ASSERT_EQ(ByteArray(typed_values.GetView(2)), stats->min());
  ASSERT_EQ(ByteArray(typed_values.GetView(9)), stats->max());
  ASSERT_EQ(2, stats->null_count());
}

TEST(TestByteArrayStatisticsFromArrow, StringType) {
  // Part of ARROW-3246. Replicating TestStatisticsSortOrder test but via Arrow
  TestByteArrayStatisticsFromArrow<::arrow::StringType>();
}

TEST(TestByteArrayStatisticsFromArrow, LargeStringType) {
  TestByteArrayStatisticsFromArrow<::arrow::LargeStringType>();
}

// Ensure UNKNOWN sort order is handled properly
using TestStatisticsSortOrderFLBA = TestStatisticsSortOrder<FLBAType>;

TEST_F(TestStatisticsSortOrderFLBA, UnknownSortOrder) {
  this->fields_.push_back(schema::PrimitiveNode::Make(
      "Column 0", Repetition::REQUIRED, Type::FIXED_LEN_BYTE_ARRAY,
      ConvertedType::INTERVAL, FLBA_LENGTH));
  this->SetUpSchema();
  this->WriteParquet();

  ASSERT_OK_AND_ASSIGN(auto pbuffer, parquet_sink_->Finish());

  // Create a ParquetReader instance
  std::unique_ptr<parquet::ParquetFileReader> parquet_reader =
      parquet::ParquetFileReader::Open(
          std::make_shared<::arrow::io::BufferReader>(pbuffer));
  // Get the File MetaData
  std::shared_ptr<parquet::FileMetaData> file_metadata = parquet_reader->metadata();
  std::shared_ptr<parquet::RowGroupMetaData> rg_metadata = file_metadata->RowGroup(0);
  std::shared_ptr<parquet::ColumnChunkMetaData> cc_metadata = rg_metadata->ColumnChunk(0);

  // stats should not be set for UNKNOWN sort order
  ASSERT_FALSE(cc_metadata->is_stats_set());
}

template <typename T>
static std::string EncodeValue(const T& val) {
  return std::string(reinterpret_cast<const char*>(&val), sizeof(val));
}
static std::string EncodeValue(const FLBA& val, int length = sizeof(uint16_t)) {
  return std::string(reinterpret_cast<const char*>(val.ptr), length);
}

template <typename Stats, typename Array, typename T = typename Array::value_type>
void AssertMinMaxAre(Stats stats, const Array& values, T expected_min, T expected_max) {
  stats->Update(values.data(), values.size(), 0);
  ASSERT_TRUE(stats->HasMinMax());
  EXPECT_EQ(stats->EncodeMin(), EncodeValue(expected_min));
  EXPECT_EQ(stats->EncodeMax(), EncodeValue(expected_max));
  EXPECT_EQ(stats->is_min_value_exact(), std::make_optional(true));
  EXPECT_EQ(stats->is_max_value_exact(), std::make_optional(true));
}

template <typename Stats, typename Array, typename T = typename Stats::T>
void AssertMinMaxAre(Stats stats, const Array& values, const uint8_t* valid_bitmap,
                     T expected_min, T expected_max) {
  auto n_values = values.size();
  auto null_count = ::arrow::internal::CountSetBits(valid_bitmap, n_values, 0);
  auto non_null_count = n_values - null_count;
  stats->UpdateSpaced(values.data(), valid_bitmap, 0, non_null_count + null_count,
                      non_null_count, null_count);
  ASSERT_TRUE(stats->HasMinMax());
  EXPECT_EQ(stats->EncodeMin(), EncodeValue(expected_min));
  EXPECT_EQ(stats->EncodeMax(), EncodeValue(expected_max));
  EXPECT_EQ(stats->is_min_value_exact(), std::make_optional(true));
  EXPECT_EQ(stats->is_max_value_exact(), std::make_optional(true));
}

template <typename Stats, typename Array>
void AssertUnsetMinMax(Stats stats, const Array& values) {
  stats->Update(values.data(), values.size(), 0);
  ASSERT_FALSE(stats->HasMinMax());
  ASSERT_FALSE(stats->is_min_value_exact().has_value());
  ASSERT_FALSE(stats->is_max_value_exact().has_value());
}

template <typename Stats, typename Array>
void AssertUnsetMinMax(Stats stats, const Array& values, const uint8_t* valid_bitmap) {
  auto n_values = values.size();
  auto null_count = ::arrow::internal::CountSetBits(valid_bitmap, n_values, 0);
  auto non_null_count = n_values - null_count;
  stats->UpdateSpaced(values.data(), valid_bitmap, 0, non_null_count + null_count,
                      non_null_count, null_count);
  ASSERT_FALSE(stats->HasMinMax());
  ASSERT_FALSE(stats->is_min_value_exact().has_value());
  ASSERT_FALSE(stats->is_max_value_exact().has_value());
}

template <typename ParquetType, typename T = typename ParquetType::c_type>
void CheckExtrema() {
  using UT = typename std::make_unsigned<T>::type;

  const T smin = std::numeric_limits<T>::min();
  const T smax = std::numeric_limits<T>::max();
  const T umin = SafeCopy<T>(std::numeric_limits<UT>::min());
  const T umax = SafeCopy<T>(std::numeric_limits<UT>::max());

  constexpr int kNumValues = 8;
  std::array<T, kNumValues> values{0,    smin,     smax,     umin,
                                   umax, smin + 1, smax - 1, umax - 1};

  NodePtr unsigned_node = PrimitiveNode::Make(
      "uint", Repetition::OPTIONAL,
      LogicalType::Int(sizeof(T) * CHAR_BIT, false /*signed*/), ParquetType::type_num);
  ColumnDescriptor unsigned_descr(unsigned_node, 1, 1);
  NodePtr signed_node = PrimitiveNode::Make(
      "int", Repetition::OPTIONAL,
      LogicalType::Int(sizeof(T) * CHAR_BIT, true /*signed*/), ParquetType::type_num);
  ColumnDescriptor signed_descr(signed_node, 1, 1);

  {
    ARROW_SCOPED_TRACE("unsigned statistics: umin = ", umin, ", umax = ", umax,
                       ", node type = ", unsigned_node->logical_type()->ToString(),
                       ", physical type = ", unsigned_descr.physical_type(),
                       ", sort order = ", unsigned_descr.sort_order());
    auto unsigned_stats = MakeStatistics<ParquetType>(&unsigned_descr);
    AssertMinMaxAre(unsigned_stats, values, umin, umax);
  }
  {
    ARROW_SCOPED_TRACE("signed statistics: smin = ", smin, ", smax = ", smax,
                       ", node type = ", signed_node->logical_type()->ToString(),
                       ", physical type = ", signed_descr.physical_type(),
                       ", sort order = ", signed_descr.sort_order());
    auto signed_stats = MakeStatistics<ParquetType>(&signed_descr);
    AssertMinMaxAre(signed_stats, values, smin, smax);
  }

  // With validity bitmap
  std::vector<bool> is_valid = {true, false, false, false, false, true, true, true};
  std::shared_ptr<Buffer> valid_bitmap;
  ::arrow::BitmapFromVector(is_valid, &valid_bitmap);
  {
    ARROW_SCOPED_TRACE("spaced unsigned statistics: umin = ", umin, ", umax = ", umax,
                       ", node type = ", unsigned_node->logical_type()->ToString(),
                       ", physical type = ", unsigned_descr.physical_type(),
                       ", sort order = ", unsigned_descr.sort_order());
    auto unsigned_stats = MakeStatistics<ParquetType>(&unsigned_descr);
    AssertMinMaxAre(unsigned_stats, values, valid_bitmap->data(), T{0}, umax - 1);
  }
  {
    ARROW_SCOPED_TRACE("spaced signed statistics: smin = ", smin, ", smax = ", smax,
                       ", node type = ", signed_node->logical_type()->ToString(),
                       ", physical type = ", signed_descr.physical_type(),
                       ", sort order = ", signed_descr.sort_order());
    auto signed_stats = MakeStatistics<ParquetType>(&signed_descr);
    AssertMinMaxAre(signed_stats, values, valid_bitmap->data(), smin + 1, smax - 1);
  }
}

TEST(TestStatistic, Int32Extrema) { CheckExtrema<Int32Type>(); }
TEST(TestStatistic, Int64Extrema) { CheckExtrema<Int64Type>(); }

template <typename T>
class TestFloatStatistics : public ::testing::Test {
 public:
  using ParquetType = typename RebindLogical<T>::ParquetType;
  using c_type = typename ParquetType::c_type;

  void Init();
  void SetUp() override {
    this->Init();
    ASSERT_NE(EncodeValue(negative_zero_), EncodeValue(positive_zero_));
  }

  bool signbit(c_type val);
  void CheckEq(const c_type& l, const c_type& r);
  NodePtr MakeNode(const std::string& name, Repetition::type rep);

  template <typename Stats, typename Values>
  void CheckMinMaxZeroesSign(Stats stats, const Values& values) {
    stats->Update(values.data(), values.size(), /*null_count=*/0);
    ASSERT_TRUE(stats->HasMinMax());

    this->CheckEq(stats->min(), positive_zero_);
    ASSERT_TRUE(this->signbit(stats->min()));
    ASSERT_EQ(stats->EncodeMin(), EncodeValue(negative_zero_));

    this->CheckEq(stats->max(), positive_zero_);
    ASSERT_FALSE(this->signbit(stats->max()));
    ASSERT_EQ(stats->EncodeMax(), EncodeValue(positive_zero_));
  }

  // ARROW-5562: Ensure that -0.0f and 0.0f values are properly handled like in
  // parquet-mr
  void TestNegativeZeroes() {
    NodePtr node = this->MakeNode("f", Repetition::OPTIONAL);
    ColumnDescriptor descr(node, 1, 1);

    {
      std::array<c_type, 2> values{negative_zero_, positive_zero_};
      auto stats = MakeStatistics<ParquetType>(&descr);
      CheckMinMaxZeroesSign(stats, values);
    }

    {
      std::array<c_type, 2> values{positive_zero_, negative_zero_};
      auto stats = MakeStatistics<ParquetType>(&descr);
      CheckMinMaxZeroesSign(stats, values);
    }

    {
      std::array<c_type, 2> values{negative_zero_, negative_zero_};
      auto stats = MakeStatistics<ParquetType>(&descr);
      CheckMinMaxZeroesSign(stats, values);
    }

    {
      std::array<c_type, 2> values{positive_zero_, positive_zero_};
      auto stats = MakeStatistics<ParquetType>(&descr);
      CheckMinMaxZeroesSign(stats, values);
    }
  }

  // PARQUET-1225: Float NaN values may lead to incorrect min-max
  template <typename Values>
  void CheckNaNs(ColumnDescriptor* descr, const Values& all_nans, const Values& some_nans,
                 const Values& other_nans, c_type min, c_type max, uint8_t valid_bitmap,
                 uint8_t valid_bitmap_no_nans) {
    auto some_nan_stats = MakeStatistics<ParquetType>(descr);
    // Ingesting only nans should not yield valid min max
    AssertUnsetMinMax(some_nan_stats, all_nans);
    // Ingesting a mix of NaNs and non-NaNs should yield a valid min max.
    AssertMinMaxAre(some_nan_stats, some_nans, min, max);
    // Ingesting only nans after a valid min/max, should have no effect
    AssertMinMaxAre(some_nan_stats, all_nans, min, max);

    some_nan_stats = MakeStatistics<ParquetType>(descr);
    AssertUnsetMinMax(some_nan_stats, all_nans, &valid_bitmap);
    // NaNs should not pollute min max when excluded via null bitmap.
    AssertMinMaxAre(some_nan_stats, some_nans, &valid_bitmap_no_nans, min, max);
    // Ingesting NaNs with a null bitmap should not change the result.
    AssertMinMaxAre(some_nan_stats, some_nans, &valid_bitmap, min, max);

    // An array that doesn't start with NaN
    auto other_stats = MakeStatistics<ParquetType>(descr);
    AssertMinMaxAre(other_stats, other_nans, min, max);
  }

  void TestNaNs();

 protected:
  std::vector<uint8_t> data_buf_;
  c_type positive_zero_;
  c_type negative_zero_;
};

template <typename T>
void TestFloatStatistics<T>::Init() {
  positive_zero_ = c_type{};
  negative_zero_ = -positive_zero_;
}
template <>
void TestFloatStatistics<Float16LogicalType>::Init() {
  data_buf_.resize(4);
  (+Float16(0)).ToLittleEndian(&data_buf_[0]);
  positive_zero_ = FLBA{&data_buf_[0]};
  (-Float16(0)).ToLittleEndian(&data_buf_[2]);
  negative_zero_ = FLBA{&data_buf_[2]};
}

template <typename T>
NodePtr TestFloatStatistics<T>::MakeNode(const std::string& name, Repetition::type rep) {
  return PrimitiveNode::Make(name, rep, ParquetType::type_num);
}
template <>
NodePtr TestFloatStatistics<Float16LogicalType>::MakeNode(const std::string& name,
                                                          Repetition::type rep) {
  return PrimitiveNode::Make(name, rep, LogicalType::Float16(),
                             Type::FIXED_LEN_BYTE_ARRAY, 2);
}

template <typename T>
void TestFloatStatistics<T>::CheckEq(const c_type& l, const c_type& r) {
  ASSERT_EQ(l, r);
}
template <>
void TestFloatStatistics<Float16LogicalType>::CheckEq(const c_type& a, const c_type& b) {
  auto l = Float16::FromLittleEndian(a.ptr);
  auto r = Float16::FromLittleEndian(b.ptr);
  ASSERT_EQ(l, r);
}

template <typename T>
bool TestFloatStatistics<T>::signbit(c_type val) {
  return std::signbit(val);
}
template <>
bool TestFloatStatistics<Float16LogicalType>::signbit(c_type val) {
  return Float16::FromLittleEndian(val.ptr).signbit();
}

template <typename T>
void TestFloatStatistics<T>::TestNaNs() {
  constexpr int kNumValues = 8;
  NodePtr node = this->MakeNode("f", Repetition::OPTIONAL);
  ColumnDescriptor descr(node, 1, 1);

  constexpr c_type nan = std::numeric_limits<c_type>::quiet_NaN();
  constexpr c_type min = -4.0f;
  constexpr c_type max = 3.0f;

  std::array<c_type, kNumValues> all_nans{nan, nan, nan, nan, nan, nan, nan, nan};
  std::array<c_type, kNumValues> some_nans{nan, max, -3.0f, -1.0f, nan, 2.0f, min, nan};
  std::array<c_type, kNumValues> other_nans{1.5f, max, -3.0f, -1.0f, nan, 2.0f, min, nan};

  uint8_t valid_bitmap = 0x7F;  // 0b01111111
  // NaNs excluded
  uint8_t valid_bitmap_no_nans = 0x6E;  // 0b01101110

  this->CheckNaNs(&descr, all_nans, some_nans, other_nans, min, max, valid_bitmap,
                  valid_bitmap_no_nans);
}

struct BufferedFloat16 {
  explicit BufferedFloat16(Float16 f16) : f16(f16) {
    this->f16.ToLittleEndian(bytes_.data());
  }
  explicit BufferedFloat16(float f) : BufferedFloat16(Float16::FromFloat(f)) {}
  const uint8_t* bytes() const { return bytes_.data(); }

  Float16 f16;
  std::array<uint8_t, 2> bytes_;
};

template <>
void TestFloatStatistics<Float16LogicalType>::TestNaNs() {
  constexpr int kNumValues = 8;

  NodePtr node = this->MakeNode("f", Repetition::OPTIONAL);
  ColumnDescriptor descr(node, 1, 1);

  using F16 = BufferedFloat16;
  const auto nan_f16 = F16(std::numeric_limits<Float16>::quiet_NaN());
  const auto min_f16 = F16(-4.0f);
  const auto max_f16 = F16(+3.0f);

  const auto min = FLBA{min_f16.bytes()};
  const auto max = FLBA{max_f16.bytes()};

  std::array<F16, kNumValues> all_nans_f16 = {nan_f16, nan_f16, nan_f16, nan_f16,
                                              nan_f16, nan_f16, nan_f16, nan_f16};
  std::array<F16, kNumValues> some_nans_f16 = {
      nan_f16, max_f16, F16(-3.0f), F16(-1.0f), nan_f16, F16(+2.0f), min_f16, nan_f16};
  std::array<F16, kNumValues> other_nans_f16 = some_nans_f16;
  other_nans_f16[0] = F16(+1.5f);  // +1.5

  auto prepare_values = [](const auto& values) -> std::vector<FLBA> {
    std::vector<FLBA> out(values.size());
    std::transform(values.begin(), values.end(), out.begin(),
                   [](const F16& f16) { return FLBA{f16.bytes()}; });
    return out;
  };

  auto all_nans = prepare_values(all_nans_f16);
  auto some_nans = prepare_values(some_nans_f16);
  auto other_nans = prepare_values(other_nans_f16);

  uint8_t valid_bitmap = 0x7F;  // 0b01111111
  // NaNs excluded
  uint8_t valid_bitmap_no_nans = 0x6E;  // 0b01101110

  this->CheckNaNs(&descr, all_nans, some_nans, other_nans, min, max, valid_bitmap,
                  valid_bitmap_no_nans);
}

using FloatingPointTypes = ::testing::Types<FloatType, DoubleType, Float16LogicalType>;

TYPED_TEST_SUITE(TestFloatStatistics, FloatingPointTypes);

TYPED_TEST(TestFloatStatistics, NegativeZeros) { this->TestNegativeZeroes(); }
TYPED_TEST(TestFloatStatistics, NaNs) { this->TestNaNs(); }

// ARROW-7376
TEST(TestStatisticsSortOrderFloatNaN, NaNAndNullsInfiniteLoop) {
  constexpr int kNumValues = 8;
  NodePtr node = PrimitiveNode::Make("nan_float", Repetition::OPTIONAL, Type::FLOAT);
  ColumnDescriptor descr(node, 1, 1);

  constexpr float nan = std::numeric_limits<float>::quiet_NaN();
  std::array<float, kNumValues> nans_but_last{nan, nan, nan, nan, nan, nan, nan, 0.0f};

  uint8_t all_but_last_valid = 0x7F;  // 0b01111111
  auto stats = MakeStatistics<FloatType>(&descr);
  AssertUnsetMinMax(stats, nans_but_last, &all_but_last_valid);
}

// Test read statistics for column with UNKNOWN sort order
TEST(TestStatisticsSortOrder, UNKNOWN) {
  std::string dir_string(test::get_data_dir());
  std::stringstream ss;
  ss << dir_string << "/int96_from_spark.parquet";
  auto path = ss.str();

  // The file contains a single column of INT96 type (deprecated)
  // with SortOrder UNKNOWN.
  // It contains 6 values with a single null value.
  // The null_count statistics value is preserved.
  auto file_reader = ParquetFileReader::OpenFile(path);
  auto rg_reader = file_reader->RowGroup(0);
  auto metadata = rg_reader->metadata();
  auto column_schema = metadata->schema()->Column(0);
  ASSERT_EQ(SortOrder::UNKNOWN, column_schema->sort_order());

  auto column_chunk = metadata->ColumnChunk(0);
  ASSERT_TRUE(column_chunk->is_stats_set());

  std::shared_ptr<EncodedStatistics> enc_stats = column_chunk->encoded_statistics();
  ASSERT_TRUE(enc_stats->has_null_count);
  ASSERT_FALSE(enc_stats->has_distinct_count);
  ASSERT_FALSE(enc_stats->has_min);
  ASSERT_FALSE(enc_stats->has_max);
  ASSERT_EQ(1, enc_stats->null_count);
  ASSERT_FALSE(enc_stats->is_max_value_exact.has_value());
  ASSERT_FALSE(enc_stats->is_min_value_exact.has_value());
}

// Test statistics for binary column with UNSIGNED sort order
TEST(TestStatisticsSortOrderMinMax, Unsigned) {
  std::string dir_string(test::get_data_dir());
  std::stringstream ss;
  ss << dir_string << "/binary.parquet";
  auto path = ss.str();

  // The file is generated by parquet-mr 1.10.0, the first version that
  // supports correct statistics for binary data (see PARQUET-1025). It
  // contains a single column of binary type. Data is just single byte values
  // from 0x00 to 0x0B.
  auto file_reader = ParquetFileReader::OpenFile(path);
  auto rg_reader = file_reader->RowGroup(0);
  auto metadata = rg_reader->metadata();
  auto column_schema = metadata->schema()->Column(0);
  ASSERT_EQ(SortOrder::UNSIGNED, column_schema->sort_order());

  auto column_chunk = metadata->ColumnChunk(0);
  ASSERT_TRUE(column_chunk->is_stats_set());

  std::shared_ptr<Statistics> stats = column_chunk->statistics();
  ASSERT_TRUE(stats != NULL);
  ASSERT_EQ(0, stats->null_count());
  ASSERT_EQ(12, stats->num_values());
  ASSERT_EQ(0x00, stats->EncodeMin()[0]);
  ASSERT_EQ(0x0b, stats->EncodeMax()[0]);
  std::shared_ptr<EncodedStatistics> enc_stats = column_chunk->encoded_statistics();
  ASSERT_FALSE(enc_stats->is_max_value_exact.has_value());
  ASSERT_FALSE(enc_stats->is_min_value_exact.has_value());
}

// Test statistics for binary column with truncated max and min values
TEST(TestEncodedStatistics, TruncatedMinMax) {
  std::string dir_string(test::get_data_dir());
  std::stringstream ss;
  ss << dir_string << "/binary_truncated_min_max.parquet";
  auto path = ss.str();

  // The file is generated by parquet-rs 55.1.0. It
  // contains six columns of utf-8 and binary type. statistics_truncate_length
  // is set to 2. Columns 0 and 1 will have truncation of min and max value,
  // columns 2 and 3 will have truncation of min value only.
  // Columns 4 and 5 will have no truncation where is_min_value_exact and
  // is_max_value_exact are set to true.
  // More file details in:
  // https://github.com/apache/parquet-testing/tree/master/data#binary-truncated-min-and-max-statistics
  auto file_reader = ParquetFileReader::OpenFile(path);
  auto rg_reader = file_reader->RowGroup(0);
  auto metadata = rg_reader->metadata();
  auto column_schema = metadata->schema()->Column(0);
  ASSERT_EQ(SortOrder::UNSIGNED, column_schema->sort_order());
  ASSERT_EQ(6, metadata->num_columns());

  for (int num_column = 0; num_column < metadata->num_columns(); ++num_column) {
    auto column_chunk = metadata->ColumnChunk(num_column);
    ASSERT_TRUE(column_chunk->is_stats_set());

    std::shared_ptr<EncodedStatistics> encoded_statistics =
        column_chunk->encoded_statistics();
    ASSERT_TRUE(encoded_statistics != NULL);
    ASSERT_EQ(0, encoded_statistics->null_count);
    EXPECT_EQ("Al", encoded_statistics->min());
    ASSERT_TRUE(encoded_statistics->is_max_value_exact.has_value());
    ASSERT_TRUE(encoded_statistics->is_min_value_exact.has_value());
    switch (num_column) {
      case 2:
        // Max couldn't truncate the utf-8 string longer than 2 bytes
        EXPECT_EQ("🚀Kevin Bacon", encoded_statistics->max());
        ASSERT_TRUE(encoded_statistics->is_max_value_exact.value());
        ASSERT_FALSE(encoded_statistics->is_min_value_exact.value());
        break;
      case 3:
        // Max couldn't truncate 0xFFFF binary string
        EXPECT_EQ("\xFF\xFF\x1\x2", encoded_statistics->max());
        ASSERT_TRUE(encoded_statistics->is_max_value_exact.value());
        ASSERT_FALSE(encoded_statistics->is_min_value_exact.value());
        break;
      case 4:
      case 5:
        // Min and Max are not truncated, fit on 2 bytes
        EXPECT_EQ("Ke", encoded_statistics->max());
        ASSERT_TRUE(encoded_statistics->is_max_value_exact.value());
        ASSERT_TRUE(encoded_statistics->is_min_value_exact.value());
        break;
      default:
        // Max truncated to 2 bytes on columns 0 and 1
        EXPECT_EQ("Kf", encoded_statistics->max());
        ASSERT_FALSE(encoded_statistics->is_max_value_exact.value());
        ASSERT_FALSE(encoded_statistics->is_min_value_exact.value());
    }
  }
}

TEST(TestEncodedStatistics, CopySafe) {
  EncodedStatistics encoded_statistics;
  encoded_statistics.set_max("abc");
  ASSERT_TRUE(encoded_statistics.has_max);
  encoded_statistics.is_max_value_exact = true;
  ASSERT_TRUE(encoded_statistics.is_max_value_exact.has_value());

  encoded_statistics.set_min("abc");
  ASSERT_TRUE(encoded_statistics.has_min);
  encoded_statistics.is_min_value_exact = true;
  ASSERT_TRUE(encoded_statistics.is_min_value_exact.has_value());

  EncodedStatistics copy_statistics = encoded_statistics;
  copy_statistics.set_max("abcd");
  copy_statistics.set_min("a");
  copy_statistics.is_max_value_exact = false;
  copy_statistics.is_min_value_exact = false;

  EXPECT_EQ("abc", encoded_statistics.min());
  EXPECT_EQ("abc", encoded_statistics.max());
  EXPECT_EQ(encoded_statistics.is_min_value_exact, std::make_optional(true));
  EXPECT_EQ(encoded_statistics.is_max_value_exact, std::make_optional(true));
}

TEST(TestEncodedStatistics, ApplyStatSizeLimits) {
  EncodedStatistics encoded_statistics;
  encoded_statistics.set_min("a");
  ASSERT_TRUE(encoded_statistics.has_min);

  encoded_statistics.set_max("abc");
  ASSERT_TRUE(encoded_statistics.has_max);

  encoded_statistics.ApplyStatSizeLimits(2);

  ASSERT_TRUE(encoded_statistics.has_min);
  ASSERT_EQ("a", encoded_statistics.min());
  ASSERT_FALSE(encoded_statistics.has_max);

  NodePtr node =
      PrimitiveNode::Make("StringColumn", Repetition::REQUIRED, Type::BYTE_ARRAY);
  ColumnDescriptor descr(node, 0, 0);
  std::shared_ptr<TypedStatistics<::parquet::ByteArrayType>> statistics =
      std::dynamic_pointer_cast<TypedStatistics<::parquet::ByteArrayType>>(
          Statistics::Make(&descr, &encoded_statistics,
                           /*num_values=*/1000));
  // GH-43382: HasMinMax should be false if one of min/max is not set.
  EXPECT_FALSE(statistics->HasMinMax());
}

}  // namespace test
}  // namespace parquet