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Add NaN and NULL count to MIN/MAX stats #3139

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a1d379a
add nan and nat count to min and max stats
markovskipetar May 28, 2026
640627e
change nat_count to null_count
markovskipetar May 29, 2026
6d0b35b
add tests for null and nan counts
markovskipetar Jun 9, 2026
b173884
add nat to nan count
markovskipetar Jun 9, 2026
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19 changes: 17 additions & 2 deletions cpp/arcticdb/pipeline/column_stats.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -96,6 +96,10 @@ std::string type_to_operator_string(ColumnStatTypeInternal type) {
return "v1_MIN";
case ColumnStatTypeInternal::MAX_V1:
return "v1_MAX";
case ColumnStatTypeInternal::NAN_COUNT_V1:
return "v1_NAN_COUNT";
case ColumnStatTypeInternal::NULL_COUNT_V1:
return "v1_NULL_COUNT";
default:
internal::raise<ErrorCode::E_ASSERTION_FAILURE>("Unknown column stat type requested");
}
Expand Down Expand Up @@ -160,6 +164,8 @@ ColumnStats::ColumnStats(
switch (entry.type()) {
case MIN_V1:
case MAX_V1:
case NAN_COUNT_V1:
case NULL_COUNT_V1:
external_type = ColumnStatType::MINMAX;
break;
case UNKNOWN:
Expand Down Expand Up @@ -209,7 +215,10 @@ namespace {
std::unordered_set<ColumnStatTypeInternal> external_to_internal(ColumnStatType type) {
switch (type) {
case ColumnStatType::MINMAX:
return {ColumnStatTypeInternal::MIN_V1, ColumnStatTypeInternal::MAX_V1};
return {ColumnStatTypeInternal::MIN_V1,
ColumnStatTypeInternal::MAX_V1,
ColumnStatTypeInternal::NAN_COUNT_V1,

@claude claude Bot May 28, 2026

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external_to_internal(MINMAX) now unconditionally returns 4 internal stat types. drop() calls this to construct the list of column names to remove (v1_MIN, v1_MAX, v1_NAN_COUNT, v1_NAT_COUNT). For column stats segments that were written by an older client (only v1_MIN and v1_MAX columns exist), dropping will produce names for columns that aren't in the segment.

Please verify what the downstream consumer of dropped_names does when asked to drop a non-existent column — if it raises, this is a forward-compatibility break that needs handling; if it silently ignores, please add a test that creates column stats with the old format and then drops them with the new client.

ColumnStatTypeInternal::NULL_COUNT_V1};
default:
internal::raise<ErrorCode::E_ASSERTION_FAILURE>("Unknown column stat type");
}
Expand Down Expand Up @@ -294,7 +303,13 @@ std::optional<Clause> ColumnStats::clause() const {
),
ColumnName(
to_segment_column_name(name_and_stat_types.mangled_name, ColumnStatTypeInternal::MAX_V1)
)
),
ColumnName(to_segment_column_name(
name_and_stat_types.mangled_name, ColumnStatTypeInternal::NAN_COUNT_V1
)),
ColumnName(to_segment_column_name(
name_and_stat_types.mangled_name, ColumnStatTypeInternal::NULL_COUNT_V1
))
));
break;
default:
Expand Down
34 changes: 30 additions & 4 deletions cpp/arcticdb/processing/unsorted_aggregation.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,15 @@ void MinMaxAggregatorData::aggregate(const ColumnWithStrings& input_column) {
using type_info = ScalarTypeInfo<decltype(col_tag)>;
using RawType = typename type_info::RawType;
if constexpr (!is_sequence_type(type_info::data_type)) {
// null_count_ tracks rows that are genuinely absent (sparse-map gaps from Arrow
// validity bitmaps). nan_count_ tracks in-band sentinel values found while iterating
// the dense values (NaN for floats, NaT for time types) - see the for_each below.
if (input_column.column_->is_sparse()) {
const auto sparse_gap_count = input_column.column_->last_row() + 1 - input_column.column_->row_count();
if (sparse_gap_count > 0) {
null_count_ += static_cast<uint64_t>(sparse_gap_count);
}
}
auto is_nat_or_nan = []([[maybe_unused]] RawType v) {
if constexpr (is_floating_point_type(type_info::data_type)) {
return std::isnan(v);
Expand All @@ -46,9 +55,12 @@ void MinMaxAggregatorData::aggregate(const ColumnWithStrings& input_column) {
[[maybe_unused]] bool any_nan{false};
arcticdb::for_each<typename type_info::TDT>(*input_column.column_, [&](auto value) {
const auto& curr = static_cast<RawType>(value);
if constexpr (is_floating_point_type(type_info::data_type) || is_time_type(type_info::data_type)) {
// Skip NaN/NaT as they don't generate a stable ordering
// In-band sentinel (NaN for floats, NaT for time types) - count it and skip the
// min/max update so those reflect only real values.
if constexpr (is_floating_point_type(type_info::data_type) ||
is_time_type(type_info::data_type)) {
if (is_nat_or_nan(curr)) {
++nan_count_;
any_nan = true;
return;
}
Expand Down Expand Up @@ -78,8 +90,8 @@ void MinMaxAggregatorData::aggregate(const ColumnWithStrings& input_column) {

SegmentInMemory MinMaxAggregatorData::finalize(const std::vector<ColumnName>& output_column_names) const {
internal::check<ErrorCode::E_ASSERTION_FAILURE>(
output_column_names.size() == 2,
"Expected 2 output column names in MinMaxAggregatorData::finalize, but got {}",
output_column_names.size() == 4,
"Expected 4 output column names in MinMaxAggregatorData::finalize, but got {}",
output_column_names.size()
);
SegmentInMemory seg;
Expand All @@ -93,16 +105,30 @@ SegmentInMemory MinMaxAggregatorData::finalize(const std::vector<ColumnName>& ou
auto max_col = std::make_shared<Column>(make_scalar_type(max_->data_type()), Sparsity::PERMITTED);
max_col->push_back<RawType>(max_->get<RawType>());

auto nan_count_col = std::make_shared<Column>(make_scalar_type(DataType::UINT64), Sparsity::PERMITTED);
nan_count_col->push_back<uint64_t>(nan_count_);

auto null_count_col = std::make_shared<Column>(make_scalar_type(DataType::UINT64), Sparsity::PERMITTED);
null_count_col->push_back<uint64_t>(null_count_);

auto& entry_list = (*header.mutable_stats_by_column())[data_col_offset_];
auto* min_entry = entry_list.add_entries();
min_entry->set_stats_seg_offset(0);
min_entry->set_type(arcticc::pb2::column_stats_pb2::MIN_V1);
auto* max_entry = entry_list.add_entries();
max_entry->set_stats_seg_offset(1);
max_entry->set_type(arcticc::pb2::column_stats_pb2::MAX_V1);
auto* nan_entry = entry_list.add_entries();
nan_entry->set_stats_seg_offset(2);
nan_entry->set_type(arcticc::pb2::column_stats_pb2::NAN_COUNT_V1);
auto* null_entry = entry_list.add_entries();
null_entry->set_stats_seg_offset(3);
null_entry->set_type(arcticc::pb2::column_stats_pb2::NULL_COUNT_V1);

seg.add_column(scalar_field(min_col->type().data_type(), output_column_names[0].value), min_col);
seg.add_column(scalar_field(max_col->type().data_type(), output_column_names[1].value), max_col);
seg.add_column(scalar_field(DataType::UINT64, output_column_names[2].value), nan_count_col);
seg.add_column(scalar_field(DataType::UINT64, output_column_names[3].value), null_count_col);
});
}

Expand Down
16 changes: 13 additions & 3 deletions cpp/arcticdb/processing/unsorted_aggregation.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -24,25 +24,33 @@ class MinMaxAggregatorData {
private:
std::optional<Value> min_;
std::optional<Value> max_;
uint64_t nan_count_{0};
uint64_t null_count_{0};
size_t data_col_offset_;
};

class MinMaxAggregator {
public:
explicit MinMaxAggregator(
ColumnName column_name, size_t data_col_offset, ColumnName output_column_name_min,
ColumnName output_column_name_max
ColumnName output_column_name_max, ColumnName output_column_name_nan_count,
ColumnName output_column_name_null_count
) :
column_name_(std::move(column_name)),
data_col_offset_(data_col_offset),
output_column_name_min_(std::move(output_column_name_min)),
output_column_name_max_(std::move(output_column_name_max)) {}
output_column_name_max_(std::move(output_column_name_max)),
output_column_name_nan_count_(std::move(output_column_name_nan_count)),
output_column_name_null_count_(std::move(output_column_name_null_count)) {}

ARCTICDB_MOVE_COPY_DEFAULT(MinMaxAggregator)

[[nodiscard]] ColumnName get_input_column_name() const { return column_name_; }
[[nodiscard]] std::vector<ColumnName> get_output_column_names() const {
return {output_column_name_min_, output_column_name_max_};
return {output_column_name_min_,
output_column_name_max_,
output_column_name_nan_count_,
output_column_name_null_count_};
}
[[nodiscard]] MinMaxAggregatorData get_aggregator_data() const { return MinMaxAggregatorData(data_col_offset_); }

Expand All @@ -51,6 +59,8 @@ class MinMaxAggregator {
size_t data_col_offset_;
ColumnName output_column_name_min_;
ColumnName output_column_name_max_;
ColumnName output_column_name_nan_count_;
ColumnName output_column_name_null_count_;
};

class AggregatorDataBase {
Expand Down
2 changes: 2 additions & 0 deletions cpp/proto/arcticc/pb2/column_stats.proto
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Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,8 @@ enum ColumnStatsType {
// misinterpret the new statistics format.
MIN_V1 = 1;
MAX_V1 = 2;
NAN_COUNT_V1 = 3;
NULL_COUNT_V1 = 4;
}

message StatEntry {
Expand Down
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