wgtmac commented on code in PR #37400:
URL: https://github.com/apache/arrow/pull/37400#discussion_r1339556198
##########
cpp/src/parquet/properties.h:
##########
@@ -139,6 +139,15 @@ 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 = false;
+static constexpr int32_t DEFAULT_BLOOM_FILTER_NDV = 1024 * 1024;
+static constexpr double DEFAULT_BLOOM_FILTER_FPP = 0.05;
+
+struct PARQUET_EXPORT BloomFilterOptions {
+ /// The number of distinct values to expect to be inserted into the bloom.
Review Comment:
```suggestion
/// Expected number of distinct values to be inserted into the bloom
filter.
```
##########
cpp/src/parquet/properties.h:
##########
@@ -532,6 +559,43 @@ class PARQUET_EXPORT WriterProperties {
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_[path] = std::nullopt;
+ return this;
+ }
+
+ /// Disable bloom filter for the column specified by `path`.
+ /// Default enabled.
+ Builder* disable_bloom_filter(const std::shared_ptr<schema::ColumnPath>&
path) {
+ return this->disable_bloom_filter(path->ToDotString());
+ }
+
+ /// Enable bloom filter options for the column specified by `path`.
+ ///
+ /// Default disabled.
+ ///
+ /// Note: Currently we don't support bloom filter for boolean columns,
+ /// so if enable bloom filter for boolean columns, it will be ignored.
+ Builder* enable_bloom_filter_options(BloomFilterOptions
bloom_filter_options,
+ const std::string& path) {
+ bloom_filter_options_[path] = bloom_filter_options;
+ return this;
+ }
+
+ /// Enable bloom filter options for the column specified by `path`.
+ ///
+ /// Default disabled.
+ ///
+ /// Note: Currently we don't support bloom filter for boolean columns,
+ /// so if enable bloom filter for boolean columns, it will be ignored.
Review Comment:
```suggestion
/// so it will be ignored if the column is of boolean type
```
##########
cpp/src/parquet/properties.h:
##########
@@ -139,6 +139,15 @@ 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 = false;
+static constexpr int32_t DEFAULT_BLOOM_FILTER_NDV = 1024 * 1024;
+static constexpr double DEFAULT_BLOOM_FILTER_FPP = 0.05;
+
+struct PARQUET_EXPORT BloomFilterOptions {
+ /// The number of distinct values to expect to be inserted into the bloom.
+ int32_t ndv = DEFAULT_BLOOM_FILTER_NDV;
+ /// The false positive probability expected from the bloom.
Review Comment:
```suggestion
/// False-positive probability of the bloom filter.
```
##########
cpp/src/parquet/properties.h:
##########
@@ -532,6 +559,43 @@ class PARQUET_EXPORT WriterProperties {
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_[path] = std::nullopt;
+ return this;
+ }
+
+ /// Disable bloom filter for the column specified by `path`.
+ /// Default enabled.
+ Builder* disable_bloom_filter(const std::shared_ptr<schema::ColumnPath>&
path) {
+ return this->disable_bloom_filter(path->ToDotString());
+ }
+
+ /// Enable bloom filter options for the column specified by `path`.
+ ///
+ /// Default disabled.
+ ///
+ /// Note: Currently we don't support bloom filter for boolean columns,
+ /// so if enable bloom filter for boolean columns, it will be ignored.
Review Comment:
```suggestion
/// so it will be ignored if the column is of boolean type
```
##########
cpp/src/parquet/column_writer_test.cc:
##########
@@ -1614,5 +1615,94 @@ TEST(TestColumnWriter, WriteDataPageV2HeaderNullCount) {
}
}
+template <typename TestType>
+class TestBloomFilterWriter : public TestPrimitiveWriter<TestType> {
+ public:
+ void SetUp() override {
+ TestPrimitiveWriter<TestType>::SetUp();
+ builder_ = nullptr;
+ bloom_filter_ = nullptr;
+ }
+
+ std::shared_ptr<TypedColumnWriter<TestType>> BuildWriterWithBloomFilter(
Review Comment:
The default values seem not necessary?
##########
cpp/src/parquet/column_writer_test.cc:
##########
@@ -1614,5 +1615,94 @@ TEST(TestColumnWriter, WriteDataPageV2HeaderNullCount) {
}
}
+template <typename TestType>
+class TestBloomFilterWriter : public TestPrimitiveWriter<TestType> {
+ public:
+ void SetUp() override {
+ TestPrimitiveWriter<TestType>::SetUp();
+ builder_ = nullptr;
+ bloom_filter_ = nullptr;
+ }
+
+ std::shared_ptr<TypedColumnWriter<TestType>> BuildWriterWithBloomFilter(
+ int64_t output_size = SMALL_SIZE,
+ const ColumnProperties& column_properties = ColumnProperties());
+
+ std::unique_ptr<BloomFilterBuilder> builder_;
+ BloomFilter* bloom_filter_;
+};
+
+template <typename TestType>
+std::shared_ptr<TypedColumnWriter<TestType>>
+TestBloomFilterWriter<TestType>::BuildWriterWithBloomFilter(
+ int64_t output_size, const ColumnProperties& column_properties) {
+ this->sink_ = CreateOutputStream();
+ WriterProperties::Builder wp_builder;
+ if (column_properties.encoding() == Encoding::PLAIN_DICTIONARY ||
+ column_properties.encoding() == Encoding::RLE_DICTIONARY) {
+ wp_builder.enable_dictionary();
+ wp_builder.dictionary_pagesize_limit(DICTIONARY_PAGE_SIZE);
+ } else {
+ wp_builder.disable_dictionary();
+ wp_builder.encoding(column_properties.encoding());
+ }
+ wp_builder.max_statistics_size(column_properties.max_statistics_size());
+ auto path = this->schema_.Column(0)->path();
+ if (column_properties.bloom_filter_enabled()) {
+ wp_builder.enable_bloom_filter_options(
+ column_properties.bloom_filter_options().value(), path);
+ } else {
+ wp_builder.disable_bloom_filter(path);
+ }
+ this->writer_properties_ = wp_builder.build();
+
+ this->metadata_ =
+ ColumnChunkMetaDataBuilder::Make(this->writer_properties_, this->descr_);
+ std::unique_ptr<PageWriter> pager = PageWriter::Open(
+ this->sink_, column_properties.compression(), this->metadata_.get());
+ builder_ = BloomFilterBuilder::Make(&this->schema_,
*this->writer_properties_);
+ // Initial RowGroup
+ builder_->AppendRowGroup();
+ bloom_filter_ = builder_->GetOrCreateBloomFilter(0);
+ std::shared_ptr<ColumnWriter> writer =
+ ColumnWriter::Make(this->metadata_.get(), std::move(pager),
+ this->writer_properties_.get(), bloom_filter_);
+ return std::static_pointer_cast<TypedColumnWriter<TestType>>(writer);
+}
+
+// Note: BooleanType is Excluded.
+using TestBloomFilterTypes = ::testing::Types<Int32Type, Int64Type, Int96Type,
FloatType,
+ DoubleType, ByteArrayType,
FLBAType>;
+
+TYPED_TEST_SUITE(TestBloomFilterWriter, TestBloomFilterTypes);
+
+TYPED_TEST(TestBloomFilterWriter, Basic) {
+ this->GenerateData(SMALL_SIZE);
+ ColumnProperties column_properties;
+ BloomFilterOptions options;
+ options.ndv = 10;
Review Comment:
Should we replace 10 with SMALL_SIZE?
##########
cpp/src/parquet/properties.h:
##########
@@ -186,6 +195,17 @@ class PARQUET_EXPORT ColumnProperties {
page_index_enabled_ = page_index_enabled;
}
+ void set_bloom_filter_options(std::optional<BloomFilterOptions>
bloom_filter_options) {
+ if (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 between 0.0 and
1.0, got " +
Review Comment:
```suggestion
"Bloom filter false-positive probability must fall in [0.0,
1.0], got " +
```
##########
cpp/src/parquet/column_writer.cc:
##########
@@ -2322,12 +2347,133 @@ Status
TypedColumnWriterImpl<FLBAType>::WriteArrowDense(
return Status::OK();
}
+template <typename DType>
+void TypedColumnWriterImpl<DType>::UpdateBloomFilter(const T* values,
+ int64_t num_values) {
+ if (bloom_filter_) {
+ std::array<uint64_t, kHashBatchSize> hashes;
+ for (int64_t i = 0; i < num_values; i += kHashBatchSize) {
+ int64_t current_hash_batch_size = std::min(kHashBatchSize, num_values -
i);
+ bloom_filter_->Hashes(values, static_cast<int>(current_hash_batch_size),
+ hashes.data());
+ bloom_filter_->InsertHashes(hashes.data(),
+ static_cast<int>(current_hash_batch_size));
+ }
+ }
+}
+
+template <>
+void TypedColumnWriterImpl<FLBAType>::UpdateBloomFilter(const FLBA* values,
+ int64_t num_values) {
+ if (bloom_filter_) {
+ std::array<uint64_t, kHashBatchSize> hashes;
+ for (int64_t i = 0; i < num_values; i += kHashBatchSize) {
+ int64_t current_hash_batch_size = std::min(kHashBatchSize, num_values -
i);
+ bloom_filter_->Hashes(values, descr_->type_length(),
+ static_cast<int>(current_hash_batch_size),
hashes.data());
+ bloom_filter_->InsertHashes(hashes.data(),
+ static_cast<int>(current_hash_batch_size));
+ }
+ }
+}
+
+template <>
+void TypedColumnWriterImpl<BooleanType>::UpdateBloomFilter(const bool*,
int64_t) {
+ DCHECK(bloom_filter_ == nullptr);
Review Comment:
Should we throw an Unreachable here?
##########
cpp/src/parquet/column_writer_test.cc:
##########
@@ -1614,5 +1615,94 @@ TEST(TestColumnWriter, WriteDataPageV2HeaderNullCount) {
}
}
+template <typename TestType>
+class TestBloomFilterWriter : public TestPrimitiveWriter<TestType> {
+ public:
+ void SetUp() override {
+ TestPrimitiveWriter<TestType>::SetUp();
+ builder_ = nullptr;
+ bloom_filter_ = nullptr;
+ }
+
+ std::shared_ptr<TypedColumnWriter<TestType>> BuildWriterWithBloomFilter(
+ int64_t output_size = SMALL_SIZE,
+ const ColumnProperties& column_properties = ColumnProperties());
+
+ std::unique_ptr<BloomFilterBuilder> builder_;
+ BloomFilter* bloom_filter_;
+};
+
+template <typename TestType>
+std::shared_ptr<TypedColumnWriter<TestType>>
+TestBloomFilterWriter<TestType>::BuildWriterWithBloomFilter(
+ int64_t output_size, const ColumnProperties& column_properties) {
+ this->sink_ = CreateOutputStream();
+ WriterProperties::Builder wp_builder;
+ if (column_properties.encoding() == Encoding::PLAIN_DICTIONARY ||
Review Comment:
Do we actually need lines between 1641 and 1648?
##########
cpp/src/parquet/bloom_filter_builder.cc:
##########
@@ -0,0 +1,154 @@
+// 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.
+
+// This module defines an abstract interface for iterating through pages in a
+// Parquet column chunk within a row group. It could be extended in the future
+// to iterate through all data pages in all chunks in a file.
+
+#include "parquet/bloom_filter_builder.h"
Review Comment:
Move this to below line 30?
##########
cpp/src/parquet/column_writer.cc:
##########
@@ -2322,12 +2347,133 @@ Status
TypedColumnWriterImpl<FLBAType>::WriteArrowDense(
return Status::OK();
}
+template <typename DType>
+void TypedColumnWriterImpl<DType>::UpdateBloomFilter(const T* values,
+ int64_t num_values) {
+ if (bloom_filter_) {
+ std::array<uint64_t, kHashBatchSize> hashes;
+ for (int64_t i = 0; i < num_values; i += kHashBatchSize) {
+ int64_t current_hash_batch_size = std::min(kHashBatchSize, num_values -
i);
+ bloom_filter_->Hashes(values, static_cast<int>(current_hash_batch_size),
+ hashes.data());
+ bloom_filter_->InsertHashes(hashes.data(),
+ static_cast<int>(current_hash_batch_size));
+ }
+ }
+}
+
+template <>
+void TypedColumnWriterImpl<FLBAType>::UpdateBloomFilter(const FLBA* values,
+ int64_t num_values) {
+ if (bloom_filter_) {
+ std::array<uint64_t, kHashBatchSize> hashes;
+ for (int64_t i = 0; i < num_values; i += kHashBatchSize) {
+ int64_t current_hash_batch_size = std::min(kHashBatchSize, num_values -
i);
+ bloom_filter_->Hashes(values, descr_->type_length(),
+ static_cast<int>(current_hash_batch_size),
hashes.data());
+ bloom_filter_->InsertHashes(hashes.data(),
+ static_cast<int>(current_hash_batch_size));
+ }
+ }
+}
+
+template <>
+void TypedColumnWriterImpl<BooleanType>::UpdateBloomFilter(const bool*,
int64_t) {
+ DCHECK(bloom_filter_ == nullptr);
+}
+
+template <typename DType>
+void TypedColumnWriterImpl<DType>::UpdateBloomFilterSpaced(const T* values,
+ int64_t num_values,
+ const uint8_t*
valid_bits,
+ int64_t
valid_bits_offset) {
+ if (bloom_filter_) {
+ std::array<uint64_t, kHashBatchSize> hashes;
+ ::arrow::internal::VisitSetBitRunsVoid(
+ valid_bits, valid_bits_offset, num_values, [&](int64_t position,
int64_t length) {
+ for (int64_t i = 0; i < length; i += kHashBatchSize) {
+ auto current_hash_batch_size = std::min(kHashBatchSize, length -
i);
+ bloom_filter_->Hashes(values + i + position,
+ static_cast<int>(current_hash_batch_size),
+ hashes.data());
+ bloom_filter_->InsertHashes(hashes.data(),
+
static_cast<int>(current_hash_batch_size));
+ }
+ });
+ }
+}
+
+template <>
+void TypedColumnWriterImpl<BooleanType>::UpdateBloomFilterSpaced(const bool*,
int64_t,
+ const
uint8_t*,
+ int64_t) {
+ DCHECK(bloom_filter_ == nullptr);
Review Comment:
ditto
##########
cpp/src/parquet/column_writer.cc:
##########
@@ -2322,12 +2347,133 @@ Status
TypedColumnWriterImpl<FLBAType>::WriteArrowDense(
return Status::OK();
}
+template <typename DType>
+void TypedColumnWriterImpl<DType>::UpdateBloomFilter(const T* values,
+ int64_t num_values) {
+ if (bloom_filter_) {
+ std::array<uint64_t, kHashBatchSize> hashes;
+ for (int64_t i = 0; i < num_values; i += kHashBatchSize) {
+ int64_t current_hash_batch_size = std::min(kHashBatchSize, num_values -
i);
+ bloom_filter_->Hashes(values, static_cast<int>(current_hash_batch_size),
+ hashes.data());
+ bloom_filter_->InsertHashes(hashes.data(),
+ static_cast<int>(current_hash_batch_size));
+ }
+ }
+}
+
+template <>
+void TypedColumnWriterImpl<FLBAType>::UpdateBloomFilter(const FLBA* values,
+ int64_t num_values) {
+ if (bloom_filter_) {
+ std::array<uint64_t, kHashBatchSize> hashes;
+ for (int64_t i = 0; i < num_values; i += kHashBatchSize) {
+ int64_t current_hash_batch_size = std::min(kHashBatchSize, num_values -
i);
+ bloom_filter_->Hashes(values, descr_->type_length(),
+ static_cast<int>(current_hash_batch_size),
hashes.data());
+ bloom_filter_->InsertHashes(hashes.data(),
+ static_cast<int>(current_hash_batch_size));
+ }
+ }
+}
+
+template <>
+void TypedColumnWriterImpl<BooleanType>::UpdateBloomFilter(const bool*,
int64_t) {
+ DCHECK(bloom_filter_ == nullptr);
+}
+
+template <typename DType>
+void TypedColumnWriterImpl<DType>::UpdateBloomFilterSpaced(const T* values,
+ int64_t num_values,
+ const uint8_t*
valid_bits,
+ int64_t
valid_bits_offset) {
+ if (bloom_filter_) {
+ std::array<uint64_t, kHashBatchSize> hashes;
+ ::arrow::internal::VisitSetBitRunsVoid(
+ valid_bits, valid_bits_offset, num_values, [&](int64_t position,
int64_t length) {
+ for (int64_t i = 0; i < length; i += kHashBatchSize) {
+ auto current_hash_batch_size = std::min(kHashBatchSize, length -
i);
+ bloom_filter_->Hashes(values + i + position,
+ static_cast<int>(current_hash_batch_size),
+ hashes.data());
+ bloom_filter_->InsertHashes(hashes.data(),
+
static_cast<int>(current_hash_batch_size));
+ }
+ });
+ }
+}
+
+template <>
+void TypedColumnWriterImpl<BooleanType>::UpdateBloomFilterSpaced(const bool*,
int64_t,
+ const
uint8_t*,
+ int64_t) {
+ DCHECK(bloom_filter_ == nullptr);
+}
+
+template <>
+void TypedColumnWriterImpl<FLBAType>::UpdateBloomFilterSpaced(const FLBA*
values,
+ int64_t
num_values,
+ const uint8_t*
valid_bits,
+ int64_t
valid_bits_offset) {
+ if (bloom_filter_) {
+ std::array<uint64_t, kHashBatchSize> hashes;
+ ::arrow::internal::VisitSetBitRunsVoid(
+ valid_bits, valid_bits_offset, num_values, [&](int64_t position,
int64_t length) {
+ for (int64_t i = 0; i < length; i += kHashBatchSize) {
+ auto current_hash_batch_size = std::min(kHashBatchSize, length -
i);
+ bloom_filter_->Hashes(values + i + position, descr_->type_length(),
+ static_cast<int>(current_hash_batch_size),
+ hashes.data());
+ bloom_filter_->InsertHashes(hashes.data(),
+
static_cast<int>(current_hash_batch_size));
+ }
+ });
+ }
+}
+
+template <typename ArrayType>
+void UpdateBinaryBloomFilter(BloomFilter* bloom_filter, const ArrayType&
array) {
+ PARQUET_THROW_NOT_OK(::arrow::VisitArraySpanInline<typename
ArrayType::TypeClass>(
+ *array.data(),
+ [&](const std::string_view& view) {
+ bloom_filter->InsertHash(bloom_filter->Hash(view));
+ return Status::OK();
+ },
+ []() { return Status::OK(); }));
+}
+
+template <>
+void TypedColumnWriterImpl<ByteArrayType>::UpdateBloomFilterArray(
+ const ::arrow::Array& values) {
+ if (bloom_filter_) {
+ if (!::arrow::is_base_binary_like(values.type_id())) {
+ throw ParquetException("Only BaseBinaryArray and subclasses supported");
+ }
+
+ if (::arrow::is_binary_like(values.type_id())) {
+ UpdateBinaryBloomFilter(bloom_filter_,
+ checked_cast<const
::arrow::BinaryArray&>(values));
+ } else {
+ DCHECK(::arrow::is_large_binary_like(values.type_id()));
+ UpdateBinaryBloomFilter(bloom_filter_,
+ checked_cast<const
::arrow::LargeBinaryArray&>(values));
+ }
+ }
+}
+
+template <typename DType>
+void TypedColumnWriterImpl<DType>::UpdateBloomFilterArray(const
::arrow::Array& values) {
+ // Only ByteArray type would write ::arrow::Array directly.
+ ParquetException::NYI("Unreachable");
Review Comment:
Use ::arrow::Unreachable()?
##########
cpp/src/parquet/arrow/arrow_reader_writer_test.cc:
##########
@@ -5584,5 +5592,95 @@ TEST_F(ParquetPageIndexRoundTripTest, EnablePerColumn) {
/*null_counts=*/{0}}));
}
+class ParquetBloomFilterRoundTripTest : public ::testing::Test,
+ public ParquetIndexRoundTripTest {
+ public:
+ void ReadBloomFilters(int expect_num_row_groups,
+ const std::set<int>& expect_columns_without_filter =
{}) {
+ auto read_properties = default_arrow_reader_properties();
Review Comment:
read_properties is not used.
##########
cpp/src/parquet/arrow/arrow_reader_writer_test.cc:
##########
@@ -5584,5 +5592,95 @@ TEST_F(ParquetPageIndexRoundTripTest, EnablePerColumn) {
/*null_counts=*/{0}}));
}
+class ParquetBloomFilterRoundTripTest : public ::testing::Test,
+ public ParquetIndexRoundTripTest {
+ public:
+ void ReadBloomFilters(int expect_num_row_groups,
+ const std::set<int>& expect_columns_without_filter =
{}) {
Review Comment:
It seems that expect_columns_without_filter is not necessary if there is
only one test case.
##########
cpp/src/parquet/arrow/arrow_reader_writer_test.cc:
##########
@@ -5584,5 +5592,95 @@ TEST_F(ParquetPageIndexRoundTripTest, EnablePerColumn) {
/*null_counts=*/{0}}));
}
+class ParquetBloomFilterRoundTripTest : public ::testing::Test,
+ public ParquetIndexRoundTripTest {
+ public:
+ void ReadBloomFilters(int expect_num_row_groups,
+ const std::set<int>& expect_columns_without_filter =
{}) {
+ auto read_properties = default_arrow_reader_properties();
+ auto reader =
ParquetFileReader::Open(std::make_shared<BufferReader>(buffer_));
+
+ auto metadata = reader->metadata();
+ ASSERT_EQ(expect_num_row_groups, metadata->num_row_groups());
+
+ auto& bloom_filter_reader = reader->GetBloomFilterReader();
+
+ for (int rg = 0; rg < metadata->num_row_groups(); ++rg) {
+ auto row_group_reader = bloom_filter_reader.RowGroup(rg);
+ ASSERT_NE(row_group_reader, nullptr);
+
+ for (int col = 0; col < metadata->num_columns(); ++col) {
+ bool expect_no_bloom_filter = expect_columns_without_filter.find(col)
!=
+ expect_columns_without_filter.cend();
+
+ auto bloom_filter = row_group_reader->GetColumnBloomFilter(col);
+ if (expect_no_bloom_filter) {
+ ASSERT_EQ(bloom_filter, nullptr);
+ } else {
+ bloom_filters_.push_back(std::move(bloom_filter));
+ }
+ }
+ }
+ }
+
+ template <typename ArrowType>
+ void VerifyBloomFilter(const BloomFilter* bloom_filter,
+ const ::arrow::ChunkedArray& chunked_array) {
+ for (auto value : ::arrow::stl::Iterate<ArrowType>(chunked_array)) {
+ if (value == std::nullopt) {
+ continue;
+ }
+ EXPECT_TRUE(bloom_filter->FindHash(bloom_filter->Hash(value.value())));
+ }
+ }
+
+ protected:
+ std::vector<std::unique_ptr<BloomFilter>> bloom_filters_;
+};
+
+TEST_F(ParquetBloomFilterRoundTripTest, SimpleRoundTrip) {
+ BloomFilterOptions options;
+ options.ndv = 100;
+ auto writer_properties = WriterProperties::Builder()
+ .enable_bloom_filter_options(options, "c0")
+ ->enable_bloom_filter_options(options, "c1")
+ ->max_row_group_length(4)
+ ->build();
+ auto schema = ::arrow::schema(
+ {::arrow::field("c0", ::arrow::int64()), ::arrow::field("c1",
::arrow::utf8())});
+ auto table = ::arrow::TableFromJSON(schema, {R"([
+ [1, "a"],
+ [2, "b"],
+ [3, "c"],
+ [null, "d"],
+ [5, null],
+ [6, "f"]
+ ])"});
+ WriteFile(writer_properties, table);
+
+ ReadBloomFilters(/*expect_num_row_groups=*/2);
+ ASSERT_EQ(4, bloom_filters_.size());
Review Comment:
These lines have repeated a lot. Could we put all sliced arrays in a single
place and then use a for loop to verify them?
##########
cpp/src/parquet/bloom_filter_reader_writer_test.cc:
##########
@@ -0,0 +1,149 @@
+// 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 <arrow/testing/gtest_util.h>
+#include <gtest/gtest.h>
+
+#include "parquet/bloom_filter.h"
+#include "parquet/bloom_filter_builder.h"
+#include "parquet/bloom_filter_reader.h"
+#include "parquet/file_reader.h"
+#include "parquet/test_util.h"
+
+namespace parquet::test {
+
+TEST(BloomFilterReader, ReadBloomFilter) {
+ std::string dir_string(parquet::test::get_data_dir());
Review Comment:
```suggestion
std::string dir_string(get_data_dir());
```
##########
cpp/src/parquet/bloom_filter_reader_writer_test.cc:
##########
@@ -0,0 +1,149 @@
+// 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 <arrow/testing/gtest_util.h>
Review Comment:
```suggestion
#include "arrow/testing/gtest_util.h"
```
##########
cpp/src/parquet/bloom_filter_reader_writer_test.cc:
##########
@@ -0,0 +1,149 @@
+// 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 <arrow/testing/gtest_util.h>
+#include <gtest/gtest.h>
+
+#include "parquet/bloom_filter.h"
+#include "parquet/bloom_filter_builder.h"
+#include "parquet/bloom_filter_reader.h"
+#include "parquet/file_reader.h"
+#include "parquet/test_util.h"
+
+namespace parquet::test {
+
+TEST(BloomFilterReader, ReadBloomFilter) {
+ std::string dir_string(parquet::test::get_data_dir());
+ std::string path = dir_string + "/data_index_bloom_encoding_stats.parquet";
+ auto reader = ParquetFileReader::OpenFile(path, false);
+ auto file_metadata = reader->metadata();
+ EXPECT_FALSE(file_metadata->is_encryption_algorithm_set());
+ auto& bloom_filter_reader = reader->GetBloomFilterReader();
+ auto row_group_0 = bloom_filter_reader.RowGroup(0);
+ ASSERT_NE(nullptr, row_group_0);
+ EXPECT_THROW(bloom_filter_reader.RowGroup(1), ParquetException);
+ auto bloom_filter = row_group_0->GetColumnBloomFilter(0);
+ ASSERT_NE(nullptr, bloom_filter);
+ EXPECT_THROW(row_group_0->GetColumnBloomFilter(1), ParquetException);
+
+ // assert exists
+ {
+ std::string_view sv = "Hello";
+ ByteArray ba{sv};
+ EXPECT_TRUE(bloom_filter->FindHash(bloom_filter->Hash(&ba)));
+ }
+
+ // no exists
+ {
+ std::string_view sv = "NOT_EXISTS";
+ ByteArray ba{sv};
+ EXPECT_FALSE(bloom_filter->FindHash(bloom_filter->Hash(&ba)));
+ }
+}
+
+TEST(BloomFilterReader, FileNotHaveBloomFilter) {
+ // Can still get a BloomFilterReader and a RowGroupBloomFilter
+ // reader, but cannot get a non-null BloomFilter.
+ std::string dir_string(parquet::test::get_data_dir());
Review Comment:
```suggestion
std::string dir_string(get_data_dir());
```
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