GH-50830: [C++][Parquet] Use JsonWriter for LogicalType::ToJSON() by NathanChung4 · Pull Request #50877 · apache/arrow

NathanChung4 · 2026-08-15T16:28:56Z

Rationale for this change

This change was made because it refactored ToJSON() to build JSON through a proper writer instead of hand-built strings, which removes a correctness risk. It also aligns the codebase's ongoing transition away from manual JSON construction.

What changes are included in this PR?

This PR focused on changing the 8 ToJSON() functions from hand built strings to using JsonWriter. In addition, the test files (schema_test.cc, reader_test.cc) were also updated to reflect these changes. Finally, WriteCrsKeyAndValue were no longer needed so it was deleted.

Are these changes tested?

These changes are tested and verified. There was a parquet-schema-test in which 41/41 testcases passed. There was a parquet-reader-test in which 149/154 passed and 5 were skipped as they were unrelated. A Full ctest -R "^parquet-": 11/11 suites passed. And finally the pre-commit (C++ Format + C++ Lint) came out clean.

Are there any user-facing changes?

Yes, there are user-facing changes. ToJSON() now produces compact JSON instead of spaced JSON. It's the same valid JSON, but different exact bytes:

Before: {"Type": "Decimal", "precision": 10, "scale": 4}
After: {"Type":"Decimal","precision":10,"scale":4}

AI Disclosure

Per the AI-generated code guidance: the 8 ToJSON() transitions to JsonWriter, test file changes, the merge conflict resolutions, and the test were produced with Claude Code, and reviewed and verified by me. Correctness was checked by rebuilding and running the relevant test after every single function conversion, not just once at the end. In addition, catching two mistakes early via failing tests (the Decimal attempt that dropped fields, the Int attempt that did the same).

GitHub Issue: [C++] Use JsonWriter consistently in LogicalType::ToJSON() #50830

I changed the 8 ToJSON() functions so that they now use JsonWriter instead of the old hand build strings. I deleted WriteCrsKeyAndValue since it was no longer needed, and I updated the test files to match the changes made in types.cc

Copilot

Pull request overview

Refactors Parquet C++ LogicalType::ToJSON() implementations to consistently use ::arrow::json::JsonWriter rather than manual string/stream construction, resulting in compact JSON output and reduced risk of producing invalid JSON for unescaped values.

Changes:

Replaced hand-built JSON in 8 LogicalType::Impl::*::ToJSON() implementations with JsonWriter-based construction.
Removed the now-unneeded WriteCrsKeyAndValue helper and simplified CRS emission to StringField.
Updated Parquet schema and reader tests to match the new compact JSON formatting.

Reviewed changes

Copilot reviewed 1 out of 3 changed files in this pull request and generated no comments.

File	Description
cpp/src/parquet/types.cc	Converts `LogicalType::ToJSON()` methods to `JsonWriter` and removes manual/stream JSON helper code.
cpp/src/parquet/schema_test.cc	Updates expected `ToJSON()` strings for logical types to match compact JSON output.
cpp/src/parquet/reader_test.cc	Updates expected JSON substrings containing embedded logical-type JSON to match compact formatting.

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Reranko05 · 2026-08-15T16:44:44Z

+  writer.StringField("Type", "Decimal");
+  writer.Key("precision");
+  writer.Int(precision_);
+  writer.Key("scale");


Could we add an IntField() helper to JsonWriter and use it here, similar to StringField() and BoolField()? It would make these conversions a bit cleaner.

Hey Reranko05, thank you for the suggestion and I totally agree with you. I have committed the proposed change, please let me know if you want to change anything or anything

Added IntField() to JsonWriter per Reranko05's PR review suggestion. Updated the 3 different functions: Decimal, Int, and Variant that had the Key() + Int() two call pattern

Copilot

Pull request overview

Copilot reviewed 3 out of 5 changed files in this pull request and generated no new comments.

Reranko05

LGTM

Reranko05 · 2026-08-15T17:32:19Z

@kou Can you review this when you have time?

kou · 2026-08-15T22:20:17Z

-     { "Id": "0", "Name": "id", "PhysicalType": "INT32", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "1", "Name": "bool_col", "PhysicalType": "BOOLEAN", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "2", "Name": "tinyint_col", "PhysicalType": "INT32", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "3", "Name": "smallint_col", "PhysicalType": "INT32", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "4", "Name": "int_col", "PhysicalType": "INT32", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "5", "Name": "bigint_col", "PhysicalType": "INT64", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "6", "Name": "float_col", "PhysicalType": "FLOAT", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "7", "Name": "double_col", "PhysicalType": "DOUBLE", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "8", "Name": "date_string_col", "PhysicalType": "BYTE_ARRAY", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "9", "Name": "string_col", "PhysicalType": "BYTE_ARRAY", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} },
-     { "Id": "10", "Name": "timestamp_col", "PhysicalType": "INT96", "ConvertedType": "NONE", "LogicalType": {"Type": "None"} }
+     { "Id": "0", "Name": "id", "PhysicalType": "INT32", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "1", "Name": "bool_col", "PhysicalType": "BOOLEAN", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "2", "Name": "tinyint_col", "PhysicalType": "INT32", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "3", "Name": "smallint_col", "PhysicalType": "INT32", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "4", "Name": "int_col", "PhysicalType": "INT32", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "5", "Name": "bigint_col", "PhysicalType": "INT64", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "6", "Name": "float_col", "PhysicalType": "FLOAT", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "7", "Name": "double_col", "PhysicalType": "DOUBLE", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "8", "Name": "date_string_col", "PhysicalType": "BYTE_ARRAY", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "9", "Name": "string_col", "PhysicalType": "BYTE_ARRAY", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} },
+     { "Id": "10", "Name": "timestamp_col", "PhysicalType": "INT96", "ConvertedType": "NONE", "LogicalType": {"Type":"None"} }


Could you use JsonWriter in

arrow/cpp/src/parquet/printer.cc

Lines 254 to 435 in f64e90a

void ParquetFilePrinter::JSONPrint(std::ostream& stream, std::list<int> selected_columns,

const char* filename) {

const FileMetaData* file_metadata = fileReader->metadata().get();

stream << "{\n";

stream << " \"FileName\": \"" << filename << "\",\n";

stream << " \"Version\": \"" << ParquetVersionToString(file_metadata->version())

<< "\",\n";

stream << " \"CreatedBy\": \"" << file_metadata->created_by() << "\",\n";

stream << " \"TotalRows\": \"" << file_metadata->num_rows() << "\",\n";

stream << " \"NumberOfRowGroups\": \"" << file_metadata->num_row_groups() << "\",\n";

stream << " \"NumberOfRealColumns\": \""

<< file_metadata->schema()->group_node()->field_count() << "\",\n";

stream << " \"NumberOfColumns\": \"" << file_metadata->num_columns() << "\",\n";

if (selected_columns.empty()) {

for (int i = 0; i < file_metadata->num_columns(); i++) {

selected_columns.push_back(i);

}

} else {

for (auto i : selected_columns) {

if (i < 0 || i >= file_metadata->num_columns()) {

throw ParquetException("Selected column is out of range");

}

}

}

stream << " \"Columns\": [\n";

int c = 0;

for (auto i : selected_columns) {

const ColumnDescriptor* descr = file_metadata->schema()->Column(i);

stream << " { \"Id\": \"" << i << "\","

<< " \"Name\": \"" << descr->path()->ToDotString() << "\","

<< " \"PhysicalType\": \""

<< TypeToString(descr->physical_type(), descr->type_length()) << "\","

<< " \"ConvertedType\": \"" << ConvertedTypeToString(descr->converted_type())

<< "\","

<< " \"LogicalType\": " << (descr->logical_type())->ToJSON() << " }";

c++;

if (c != static_cast<int>(selected_columns.size())) {

stream << ",\n";

}

}

stream << "\n ],\n \"RowGroups\": [\n";

for (int r = 0; r < file_metadata->num_row_groups(); ++r) {

stream << " {\n \"Id\": \"" << r << "\", ";

auto group_reader = fileReader->RowGroup(r);

std::unique_ptr<RowGroupMetaData> group_metadata = file_metadata->RowGroup(r);

stream << " \"TotalBytes\": \"" << group_metadata->total_byte_size() << "\", ";

stream << " \"TotalCompressedBytes\": \"" << group_metadata->total_compressed_size()

<< "\", ";

auto row_group_sorting_columns = group_metadata->sorting_columns();

if (!row_group_sorting_columns.empty()) {

stream << " \"SortColumns\": [\n";

for (size_t i = 0; i < row_group_sorting_columns.size(); i++) {

stream << " {\"column_idx\": " << row_group_sorting_columns[i].column_idx

<< ", \"descending\": " << row_group_sorting_columns[i].descending

<< ", \"nulls_first\": " << row_group_sorting_columns[i].nulls_first

<< "}";

if (i + 1 != row_group_sorting_columns.size()) {

stream << ",";

}

stream << '\n';

}

stream << " ], ";

}

stream << " \"Rows\": \"" << group_metadata->num_rows() << "\",\n";

// Print column metadata

stream << " \"ColumnChunks\": [\n";

int c1 = 0;

for (auto i : selected_columns) {

auto column_chunk = group_metadata->ColumnChunk(i);

std::shared_ptr<Statistics> stats = column_chunk->statistics();

const ColumnDescriptor* descr = file_metadata->schema()->Column(i);

stream << " {\"Id\": \"" << i << "\", \"Values\": \""

<< column_chunk->num_values() << "\", "

<< "\"StatsSet\": ";

if (column_chunk->is_stats_set()) {

stream << R"("True", "Stats": {)";

if (stats->HasNullCount()) {

stream << R"("NumNulls": ")" << stats->null_count() << "\"";

}

if (stats->HasDistinctCount()) {

stream << ", "

<< R"("DistinctValues": ")" << stats->distinct_count() << "\"";

}

if (stats->HasMinMax()) {

std::string min = stats->EncodeMin(), max = stats->EncodeMax();

stream << ", "

<< R"("Max": ")"

<< FormatStatValue(descr->physical_type(), max, descr->logical_type())

<< "\", "

<< R"("Min": ")"

<< FormatStatValue(descr->physical_type(), min, descr->logical_type())

<< "\"";

if (stats->is_max_value_exact().has_value()) {

stream << ", "

<< R"("IsMaxValueExact": ")"

<< (stats->is_max_value_exact().value() ? "True" : "False") << "\"";

} else {

stream << ", "

<< R"("IsMaxValueExact": "unknown")";

}

if (stats->is_min_value_exact().has_value()) {

stream << ", "

<< R"("IsMinValueExact": ")"

<< (stats->is_min_value_exact().value() ? "True" : "False") << "\"";

} else {

stream << ", "

<< R"("IsMinValueExact": "unknown")";

}

}

stream << " },";

} else {

stream << "\"False\",";

}

stream << "\n \"Compression\": \""

<< ::arrow::internal::AsciiToUpper(

Codec::GetCodecAsString(column_chunk->compression()))

<< R"(", "Encodings": )";

stream << "\"";

if (column_chunk->encoding_stats().empty()) {

for (auto encoding : column_chunk->encodings()) {

stream << EncodingToString(encoding) << " ";

}

} else {

PrintPageEncodingStats(stream, column_chunk->encoding_stats());

}

stream << "\"";

stream << ", "

<< R"("UncompressedSize": ")" << column_chunk->total_uncompressed_size()

<< R"(", "CompressedSize": ")" << column_chunk->total_compressed_size()

<< "\"";

if (column_chunk->bloom_filter_offset()) {

// Output BloomFilter {offset, length}

stream << ", \"BloomFilter\": {"

<< R"("offset": ")" << column_chunk->bloom_filter_offset().value() << "\"";

if (column_chunk->bloom_filter_length()) {

stream << R"(, "length": ")" << column_chunk->bloom_filter_length().value()

<< "\"";

}

stream << "}";

}

if (column_chunk->GetColumnIndexLocation()) {

auto location = column_chunk->GetColumnIndexLocation().value();

// Output ColumnIndex {offset, length}

stream << ", \"ColumnIndex\": {"

<< R"("offset": ")" << location.offset;

stream << R"(", "length": ")" << location.length;

stream << "\"}";

}

if (column_chunk->GetOffsetIndexLocation()) {

auto location = column_chunk->GetOffsetIndexLocation().value();

// Output OffsetIndex {offset, length}

stream << ", \"OffsetIndex\": {"

<< R"("offset": ")" << location.offset << "\"";

stream << R"(, "length": ")" << location.length << "\"";

stream << "}";

}

// end of a ColumnChunk

stream << " }";

c1++;

if (c1 != static_cast<int>(selected_columns.size())) {

stream << ",\n";

}

}

stream << "\n ]\n }";

if ((r + 1) != static_cast<int>(file_metadata->num_row_groups())) {

stream << ",\n";

}

}

stream << "\n ]\n}\n";

}

too?

It seems that we can use https://github.com/simdjson/simdjson/blob/master/doc/builder.md#pretty-formatted-fractured-json for it.

NathanChung4 requested review from pitrou and wgtmac as code owners August 15, 2026 16:28

Copilot AI lite review requested due to automatic review settings August 15, 2026 16:28

github-actions Bot added Component: Parquet Component: C++ awaiting review Awaiting review labels Aug 15, 2026

Copilot started reviewing on behalf of NathanChung4 August 15, 2026 16:29 View session

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Add IntField() to JsonWriter per review feedback

6b4a769

Added IntField() to JsonWriter per Reranko05's PR review suggestion. Updated the 3 different functions: Decimal, Int, and Variant that had the Key() + Int() two call pattern

Copilot AI review requested due to automatic review settings August 15, 2026 16:57

Copilot started reviewing on behalf of NathanChung4 August 15, 2026 16:57 View session

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Reranko05 approved these changes Aug 15, 2026

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GH-50830: [C++][Parquet] Use JsonWriter for LogicalType::ToJSON() - #50877

GH-50830: [C++][Parquet] Use JsonWriter for LogicalType::ToJSON()#50877
NathanChung4 wants to merge 2 commits into
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NathanChung4:gh50830-logicaltype-tojson-jsonwriter

NathanChung4 commented Aug 15, 2026 •

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	void ParquetFilePrinter::JSONPrint(std::ostream& stream, std::list<int> selected_columns,
	const char* filename) {
	const FileMetaData* file_metadata = fileReader->metadata().get();
	stream << "{\n";
	stream << " \"FileName\": \"" << filename << "\",\n";
	stream << " \"Version\": \"" << ParquetVersionToString(file_metadata->version())
	<< "\",\n";
	stream << " \"CreatedBy\": \"" << file_metadata->created_by() << "\",\n";
	stream << " \"TotalRows\": \"" << file_metadata->num_rows() << "\",\n";
	stream << " \"NumberOfRowGroups\": \"" << file_metadata->num_row_groups() << "\",\n";
	stream << " \"NumberOfRealColumns\": \""
	<< file_metadata->schema()->group_node()->field_count() << "\",\n";
	stream << " \"NumberOfColumns\": \"" << file_metadata->num_columns() << "\",\n";

	if (selected_columns.empty()) {
	for (int i = 0; i < file_metadata->num_columns(); i++) {
	selected_columns.push_back(i);
	}
	} else {
	for (auto i : selected_columns) {
	if (i < 0 \|\| i >= file_metadata->num_columns()) {
	throw ParquetException("Selected column is out of range");
	}
	}
	}

	stream << " \"Columns\": [\n";
	int c = 0;
	for (auto i : selected_columns) {
	const ColumnDescriptor* descr = file_metadata->schema()->Column(i);
	stream << " { \"Id\": \"" << i << "\","
	<< " \"Name\": \"" << descr->path()->ToDotString() << "\","
	<< " \"PhysicalType\": \""
	<< TypeToString(descr->physical_type(), descr->type_length()) << "\","
	<< " \"ConvertedType\": \"" << ConvertedTypeToString(descr->converted_type())
	<< "\","
	<< " \"LogicalType\": " << (descr->logical_type())->ToJSON() << " }";
	c++;
	if (c != static_cast<int>(selected_columns.size())) {
	stream << ",\n";
	}
	}

	stream << "\n ],\n \"RowGroups\": [\n";
	for (int r = 0; r < file_metadata->num_row_groups(); ++r) {
	stream << " {\n \"Id\": \"" << r << "\", ";

	auto group_reader = fileReader->RowGroup(r);
	std::unique_ptr<RowGroupMetaData> group_metadata = file_metadata->RowGroup(r);

	stream << " \"TotalBytes\": \"" << group_metadata->total_byte_size() << "\", ";
	stream << " \"TotalCompressedBytes\": \"" << group_metadata->total_compressed_size()
	<< "\", ";
	auto row_group_sorting_columns = group_metadata->sorting_columns();
	if (!row_group_sorting_columns.empty()) {
	stream << " \"SortColumns\": [\n";
	for (size_t i = 0; i < row_group_sorting_columns.size(); i++) {
	stream << " {\"column_idx\": " << row_group_sorting_columns[i].column_idx
	<< ", \"descending\": " << row_group_sorting_columns[i].descending
	<< ", \"nulls_first\": " << row_group_sorting_columns[i].nulls_first
	<< "}";
	if (i + 1 != row_group_sorting_columns.size()) {
	stream << ",";
	}
	stream << '\n';
	}
	stream << " ], ";
	}
	stream << " \"Rows\": \"" << group_metadata->num_rows() << "\",\n";

	// Print column metadata
	stream << " \"ColumnChunks\": [\n";
	int c1 = 0;
	for (auto i : selected_columns) {
	auto column_chunk = group_metadata->ColumnChunk(i);
	std::shared_ptr<Statistics> stats = column_chunk->statistics();

	const ColumnDescriptor* descr = file_metadata->schema()->Column(i);
	stream << " {\"Id\": \"" << i << "\", \"Values\": \""
	<< column_chunk->num_values() << "\", "
	<< "\"StatsSet\": ";
	if (column_chunk->is_stats_set()) {
	stream << R"("True", "Stats": {)";
	if (stats->HasNullCount()) {
	stream << R"("NumNulls": ")" << stats->null_count() << "\"";
	}
	if (stats->HasDistinctCount()) {
	stream << ", "
	<< R"("DistinctValues": ")" << stats->distinct_count() << "\"";
	}
	if (stats->HasMinMax()) {
	std::string min = stats->EncodeMin(), max = stats->EncodeMax();
	stream << ", "
	<< R"("Max": ")"
	<< FormatStatValue(descr->physical_type(), max, descr->logical_type())
	<< "\", "
	<< R"("Min": ")"
	<< FormatStatValue(descr->physical_type(), min, descr->logical_type())
	<< "\"";
	if (stats->is_max_value_exact().has_value()) {
	stream << ", "
	<< R"("IsMaxValueExact": ")"
	<< (stats->is_max_value_exact().value() ? "True" : "False") << "\"";
	} else {
	stream << ", "
	<< R"("IsMaxValueExact": "unknown")";
	}
	if (stats->is_min_value_exact().has_value()) {
	stream << ", "
	<< R"("IsMinValueExact": ")"
	<< (stats->is_min_value_exact().value() ? "True" : "False") << "\"";
	} else {
	stream << ", "
	<< R"("IsMinValueExact": "unknown")";
	}
	}
	stream << " },";
	} else {
	stream << "\"False\",";
	}
	stream << "\n \"Compression\": \""
	<< ::arrow::internal::AsciiToUpper(
	Codec::GetCodecAsString(column_chunk->compression()))
	<< R"(", "Encodings": )";
	stream << "\"";
	if (column_chunk->encoding_stats().empty()) {
	for (auto encoding : column_chunk->encodings()) {
	stream << EncodingToString(encoding) << " ";
	}
	} else {
	PrintPageEncodingStats(stream, column_chunk->encoding_stats());
	}
	stream << "\"";
	stream << ", "
	<< R"("UncompressedSize": ")" << column_chunk->total_uncompressed_size()
	<< R"(", "CompressedSize": ")" << column_chunk->total_compressed_size()
	<< "\"";

	if (column_chunk->bloom_filter_offset()) {
	// Output BloomFilter {offset, length}
	stream << ", \"BloomFilter\": {"
	<< R"("offset": ")" << column_chunk->bloom_filter_offset().value() << "\"";
	if (column_chunk->bloom_filter_length()) {
	stream << R"(, "length": ")" << column_chunk->bloom_filter_length().value()
	<< "\"";
	}
	stream << "}";
	}

	if (column_chunk->GetColumnIndexLocation()) {
	auto location = column_chunk->GetColumnIndexLocation().value();
	// Output ColumnIndex {offset, length}
	stream << ", \"ColumnIndex\": {"
	<< R"("offset": ")" << location.offset;
	stream << R"(", "length": ")" << location.length;
	stream << "\"}";
	}

	if (column_chunk->GetOffsetIndexLocation()) {
	auto location = column_chunk->GetOffsetIndexLocation().value();
	// Output OffsetIndex {offset, length}
	stream << ", \"OffsetIndex\": {"
	<< R"("offset": ")" << location.offset << "\"";
	stream << R"(, "length": ")" << location.length << "\"";
	stream << "}";
	}

	// end of a ColumnChunk
	stream << " }";
	c1++;
	if (c1 != static_cast<int>(selected_columns.size())) {
	stream << ",\n";
	}
	}

	stream << "\n ]\n }";
	if ((r + 1) != static_cast<int>(file_metadata->num_row_groups())) {
	stream << ",\n";
	}
	}
	stream << "\n ]\n}\n";
	}

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NathanChung4 commented Aug 15, 2026 •

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