mapleFU commented on code in PR #37400:
URL: https://github.com/apache/arrow/pull/37400#discussion_r1843148451
##########
cpp/src/parquet/properties.h:
##########
@@ -564,6 +591,43 @@ 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.
Review Comment:
That's my fault!
##########
cpp/src/parquet/arrow/arrow_reader_writer_test.cc:
##########
@@ -5723,5 +5731,213 @@ 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 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(nullptr, bloom_filter);
+ } else {
+ ASSERT_NE(nullptr, bloom_filter);
+ 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) {
+ auto schema = ::arrow::schema(
+ {::arrow::field("c0", ::arrow::int64()), ::arrow::field("c1",
::arrow::utf8())});
+ 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 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());
+ std::vector<int64_t> row_group_row_count{4, 2};
+ int64_t current_row = 0;
+ int64_t bloom_filter_idx = 0; // current index in `bloom_filters_`
+ for (int64_t row_group_id = 0; row_group_id < 2; ++row_group_id) {
+ {
+ ASSERT_NE(nullptr, bloom_filters_[bloom_filter_idx]);
+ auto col = table->column(0)->Slice(current_row,
row_group_row_count[row_group_id]);
+
VerifyBloomFilter<::arrow::Int64Type>(bloom_filters_[bloom_filter_idx].get(),
*col);
+ ++bloom_filter_idx;
+ }
+ {
+ ASSERT_NE(nullptr, bloom_filters_[bloom_filter_idx]);
+ auto col = table->column(1)->Slice(current_row,
row_group_row_count[row_group_id]);
+
VerifyBloomFilter<::arrow::StringType>(bloom_filters_[bloom_filter_idx].get(),
+ *col);
+ ++bloom_filter_idx;
+ }
+ current_row += row_group_row_count[row_group_id];
+ }
+}
+
+TEST_F(ParquetBloomFilterRoundTripTest, SimpleRoundTripDictionary) {
+ auto origin_schema = ::arrow::schema(
+ {::arrow::field("c0", ::arrow::int64()), ::arrow::field("c1",
::arrow::utf8())});
+ auto schema = ::arrow::schema(
+ {::arrow::field("c0", ::arrow::dictionary(::arrow::int64(),
::arrow::int64())),
+ ::arrow::field("c1", ::arrow::dictionary(::arrow::int64(),
::arrow::utf8()))});
+ bloom_filters_.clear();
+ 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();
+ std::vector<std::string> contents = {R"([
+ [1, "a"],
+ [2, "b"],
+ [3, "c"],
+ [null, "d"],
+ [5, null],
+ [6, "f"]
+ ])"};
+ auto table = ::arrow::TableFromJSON(schema, contents);
+ auto non_dict_table = ::arrow::TableFromJSON(origin_schema, contents);
Review Comment:
done
##########
cpp/src/parquet/bloom_filter.h:
##########
@@ -167,6 +167,31 @@ class PARQUET_EXPORT BloomFilter {
virtual ~BloomFilter() = default;
+ // Variant of const reference argument to facilitate template
+
+ /// Compute hash for ByteArray value by using its plain encoding result.
+ ///
+ /// @param value the value to hash.
+ uint64_t Hash(const ByteArray& value) const { return Hash(&value); }
Review Comment:
done
##########
cpp/src/parquet/bloom_filter_builder.cc:
##########
@@ -0,0 +1,158 @@
+// 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"
+
+#include <map>
+#include <utility>
+#include <vector>
+
+#include "arrow/io/interfaces.h"
+
+#include "parquet/bloom_filter.h"
+#include "parquet/exception.h"
+#include "parquet/metadata.h"
+#include "parquet/properties.h"
+
+namespace parquet::internal {
+
+namespace {
+/// Column encryption for bloom filter is not implemented yet.
+class BloomFilterBuilderImpl : public BloomFilterBuilder {
+ public:
+ explicit BloomFilterBuilderImpl(const SchemaDescriptor* schema,
+ const WriterProperties* properties)
+ : schema_(schema), properties_(properties) {}
+ /// Append a new row group to host all incoming bloom filters.
+ void AppendRowGroup() override;
+
+ BloomFilter* GetOrCreateBloomFilter(int32_t column_ordinal) override;
+
+ /// Serialize all bloom filters with header and bitset in the order of row
group and
+ /// column id. The side effect is that it deletes all bloom filters after
they have
+ /// been flushed.
+ void WriteTo(::arrow::io::OutputStream* sink, BloomFilterLocation* location)
override;
+
+ BloomFilterBuilderImpl(const BloomFilterBuilderImpl&) = delete;
+ BloomFilterBuilderImpl(BloomFilterBuilderImpl&&) = default;
+
+ private:
+ /// Make sure column ordinal is not out of bound and the builder is in good
state.
+ void CheckState(int32_t column_ordinal) const {
+ if (finished_) {
+ throw ParquetException("BloomFilterBuilder is already finished.");
+ }
+ if (column_ordinal < 0 || column_ordinal >= schema_->num_columns()) {
+ throw ParquetException("Invalid column ordinal: ", column_ordinal);
+ }
+ if (file_bloom_filters_.empty()) {
+ throw ParquetException("No row group appended to BloomFilterBuilder.");
+ }
+ if (schema_->Column(column_ordinal)->physical_type() == Type::BOOLEAN) {
+ throw ParquetException("BloomFilterBuilder does not support boolean
type.");
+ }
+ }
+
+ const SchemaDescriptor* schema_;
+ const WriterProperties* properties_;
+ bool finished_ = false;
+
+ using RowGroupBloomFilters = std::map<int32_t, std::unique_ptr<BloomFilter>>;
+ // Using unique_ptr because the `std::unique_ptr<BloomFilter>` is not
copyable.
+ // MSVC has the issue below: https://github.com/microsoft/STL/issues/1036
+ // So we use `std::unique_ptr<std::map<>>` to avoid the issue.
+ std::vector<std::unique_ptr<RowGroupBloomFilters>> file_bloom_filters_;
+};
+
+void BloomFilterBuilderImpl::AppendRowGroup() {
+ if (finished_) {
+ throw ParquetException(
+ "Cannot call AppendRowGroup() to finished BloomFilterBuilder.");
+ }
+ file_bloom_filters_.emplace_back(std::make_unique<RowGroupBloomFilters>());
+}
+
+BloomFilter* BloomFilterBuilderImpl::GetOrCreateBloomFilter(int32_t
column_ordinal) {
+ CheckState(column_ordinal);
+ const ColumnDescriptor* column_descr = schema_->Column(column_ordinal);
+ DCHECK_NE(column_descr->physical_type(), Type::BOOLEAN);
+ auto bloom_filter_options_opt =
properties_->bloom_filter_options(column_descr->path());
Review Comment:
Yes, `bloom_filter_options_opt` is so lightweight, copying it is ok here?
##########
cpp/src/parquet/column_writer.cc:
##########
@@ -2363,12 +2390,153 @@ 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:
done
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