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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
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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::NAT_COUNT_V1:
return "v1_NAT_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 NAT_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,
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@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::NAT_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::NAT_COUNT_V1
))
));
break;
default:
Expand Down
28 changes: 24 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 @@ -46,9 +46,15 @@ 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
if constexpr (is_floating_point_type(type_info::data_type)) {
if (is_nat_or_nan(curr)) {
++nan_count_;
any_nan = true;
return;
}
} else if constexpr (is_time_type(type_info::data_type)) {
if (is_nat_or_nan(curr)) {
++nat_count_;
any_nan = true;
return;
}
Expand Down Expand Up @@ -78,8 +84,8 @@ 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 +99,30 @@ 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 nat_count_col = std::make_shared<Column>(make_scalar_type(DataType::UINT64), Sparsity::PERMITTED);
nat_count_col->push_back<uint64_t>(nat_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* nat_entry = entry_list.add_entries();
nat_entry->set_stats_seg_offset(3);
nat_entry->set_type(arcticc::pb2::column_stats_pb2::NAT_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), nat_count_col);
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@claude claude Bot May 28, 2026

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finalize now unconditionally writes 4 columns (min, max, nan_count, nat_count) and 4 header entries for the MINMAX stat. This changes the on-disk shape of every MINMAX column-stats segment.

Two concerns that should be addressed before merge:

  1. Backwards-compatibility test missing. There is no test that creates column stats with a pinned older ArcticDB version and then reads/drops/recreates them with this new client. Old segments only contain 2 stat columns; merge_column_stats_segments and ColumnStats::ColumnStats(header, tsd) should be exercised against that shape.
  2. Old client reading new data. Although the proto comment relies on the UNKNOWN = 0 fallback in proto3 for forward-compat, the new client also adds two extra real columns to the segment. Please confirm that an older release reading a segment with the extra v1_NAN_COUNT/v1_NAT_COUNT fields doesn't fail descriptor/field-count assertions, and document the result in the PR description.

});
}

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 nat_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_nat_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_nat_count_(std::move(output_column_name_nat_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_nat_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_nat_count_;
};

class AggregatorDataBase {
Expand Down
2 changes: 2 additions & 0 deletions cpp/proto/arcticc/pb2/column_stats.proto
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Expand Up @@ -23,6 +23,8 @@ enum ColumnStatsType {
// misinterpret the new statistics format.
MIN_V1 = 1;
MAX_V1 = 2;
NAN_COUNT_V1 = 3;
NAT_COUNT_V1 = 4;
}

message StatEntry {
Expand Down
64 changes: 64 additions & 0 deletions python/tests/unit/arcticdb/test_column_stats_creation.py
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Expand Up @@ -274,6 +274,70 @@ def test_column_stats_only_nat_values(lmdb_version_store, any_output_format):
assert raw_stats["v1_MAX(col_1)"].values.view("int64")[0] == nat_sentinel


def test_column_stats_nan_and_nat_counts(lmdb_version_store, any_output_format):
lib = lmdb_version_store
lib._set_output_format_for_pipeline_tests(any_output_format)
sym = "test_column_stats_nan_and_nat_counts"

# Each write/append produces a separate segment, so we get one row per dataframe in the stats.
# float_col counts toward v1_NAN_COUNT, ts_col counts toward v1_NAT_COUNT.
df0 = pd.DataFrame(
{"float_col": [1.0, 2.0], "ts_col": [pd.Timestamp("2020-01-01"), pd.Timestamp("2020-06-01")]},
index=pd.date_range("2000-01-01", periods=2),
)
df1 = pd.DataFrame(
{"float_col": [np.nan, 5.0], "ts_col": [pd.NaT, pd.Timestamp("2021-01-01")]},
index=pd.date_range("2000-01-03", periods=2),
)
df2 = pd.DataFrame(
{"float_col": [np.nan, np.nan], "ts_col": [pd.NaT, pd.NaT]},
index=pd.date_range("2000-01-05", periods=2),
)
df3 = pd.DataFrame(
{"float_col": [1.0, np.nan, 2.0], "ts_col": [pd.Timestamp("2022-01-01"), pd.NaT, pd.Timestamp("2022-06-01")]},
index=pd.date_range("2000-01-07", periods=3),
)
lib.write(sym, df0)
lib.append(sym, df1)
lib.append(sym, df2)
lib.append(sym, df3)

column_stats_dict = {"float_col": {"MINMAX"}, "ts_col": {"MINMAX"}}
lib.create_column_stats(sym, column_stats_dict)

expected_column_stats = index_columns_to_pl(lib, sym).with_columns(
pl.Series("v1_MIN(float_col)", [1.0, 5.0, np.nan, 1.0]),
pl.Series("v1_MAX(float_col)", [2.0, 5.0, np.nan, 2.0]),
pl.Series("v1_NAN_COUNT(float_col)", [0, 1, 2, 1], dtype=pl.UInt64),
pl.Series("v1_NAT_COUNT(float_col)", [0, 0, 0, 0], dtype=pl.UInt64),
pl.Series(
"v1_MIN(ts_col)",
[
pd.Timestamp("2020-01-01").value,
pd.Timestamp("2021-01-01").value,
None,
pd.Timestamp("2022-01-01").value,
],
dtype=pl.Int64,
).cast(pl.Datetime("ns")),
pl.Series(
"v1_MAX(ts_col)",
[
pd.Timestamp("2020-06-01").value,
pd.Timestamp("2021-01-01").value,
None,
pd.Timestamp("2022-06-01").value,
],
dtype=pl.Int64,
).cast(pl.Datetime("ns")),
pl.Series("v1_NAN_COUNT(ts_col)", [0, 0, 0, 0], dtype=pl.UInt64),
pl.Series("v1_NAT_COUNT(ts_col)", [0, 1, 2, 1], dtype=pl.UInt64),
)

column_stats = lib.read_column_stats(sym)
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The new test only covers writing-then-reading with the same (new) client. Please add (or update an existing test) so that the all-NaN / all-NaT segments verify the new v1_NAN_COUNT / v1_NAT_COUNT values directly (e.g. extend test_column_stats_only_nat_values), and add a test for backwards compatibility — column stats written before this change (where only v1_MIN/v1_MAX columns exist) must still be readable, droppable, and mergeable by the new code path.

assert_stats_equal(column_stats, expected_column_stats)


def test_column_stats_as_of(version_store_factory, lib_name, encoding_version, any_output_format):
lib = version_store_factory(
column_group_size=2,
Expand Down
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