edponce commented on a change in pull request #11257:
URL: https://github.com/apache/arrow/pull/11257#discussion_r718153840
##########
File path: cpp/src/arrow/compute/kernels/aggregate_basic.cc
##########
@@ -121,6 +122,84 @@ Result<std::unique_ptr<KernelState>>
CountInit(KernelContext*,
static_cast<const CountOptions&>(*args.options));
}
+// ----------------------------------------------------------------------
+// Distinct Count implementation
+
+template <typename Type>
+struct CountDistinctImpl : public ScalarAggregator {
+ using MemoTable = typename arrow::internal::HashTraits<Type>::MemoTableType;
+
+ explicit CountDistinctImpl(MemoryPool* memory_pool, CountOptions options)
+ : options(std::move(options)), memo_table_(new MemoTable(memory_pool,
0)) {}
+
+ Status Consume(KernelContext*, const ExecBatch& batch) override {
+ if (batch[0].is_array()) {
+ const ArrayData& arr = *batch[0].array();
+ auto visit_null = [&]() {
+ if (this->nulls > 0) return Status::OK();
+ ++this->nulls;
+ return Status::OK();
+ };
+ auto visit_value = [&](typename Type::c_type arg) {
+ int y;
Review comment:
Nit: Instead of using `typename Type::c_type`, we can define an alias at
top of class
```c++
using c_type = typename Type::c_type
```
but since it is only used here then it is ok. It is just a common pattern in
Arrow codebase.
##########
File path: cpp/src/arrow/compute/kernels/aggregate_basic.cc
##########
@@ -121,6 +122,84 @@ Result<std::unique_ptr<KernelState>>
CountInit(KernelContext*,
static_cast<const CountOptions&>(*args.options));
}
+// ----------------------------------------------------------------------
+// Distinct Count implementation
+
+template <typename Type>
+struct CountDistinctImpl : public ScalarAggregator {
+ using MemoTable = typename arrow::internal::HashTraits<Type>::MemoTableType;
+
+ explicit CountDistinctImpl(MemoryPool* memory_pool, CountOptions options)
+ : options(std::move(options)), memo_table_(new MemoTable(memory_pool,
0)) {}
+
+ Status Consume(KernelContext*, const ExecBatch& batch) override {
+ if (batch[0].is_array()) {
+ const ArrayData& arr = *batch[0].array();
+ auto visit_null = [&]() {
+ if (this->nulls > 0) return Status::OK();
+ ++this->nulls;
+ return Status::OK();
+ };
+ auto visit_value = [&](typename Type::c_type arg) {
+ int y;
+ RETURN_NOT_OK(memo_table_->GetOrInsert(arg, &y));
+ return Status::OK();
+ };
+ RETURN_NOT_OK(VisitArrayDataInline<Type>(arr, visit_value, visit_null));
+ this->non_nulls += this->memo_table_->size();
+ } else {
+ const Scalar& input = *batch[0].scalar();
+ this->nulls += !input.is_valid * batch.length;
+ this->non_nulls += input.is_valid * batch.length;
+ }
Review comment:
If `batch.length > 1`, then `this->nulls` can be greater than 1 for
which will result in an incorrect value in `Finalize()`. We can limit the value
to 1 in `Finalize()`.
##########
File path: cpp/src/arrow/compute/kernels/aggregate_basic.cc
##########
@@ -754,6 +839,30 @@ void RegisterScalarAggregateBasic(FunctionRegistry*
registry) {
aggregate::CountInit, func.get());
DCHECK_OK(registry->AddFunction(std::move(func)));
+ func = std::make_shared<ScalarAggregateFunction>(
+ "count_distinct", Arity::Unary(), &count_distinct_doc,
&default_count_options);
+
+ // Takes any input, outputs int64 scalar
+ aggregate::AddCountDistinctKernel<Int8Type>(int8(), func.get());
+ aggregate::AddCountDistinctKernel<Int16Type>(int16(), func.get());
+ aggregate::AddCountDistinctKernel<Int32Type>(int32(), func.get());
+ aggregate::AddCountDistinctKernel<Date32Type>(date32(), func.get());
+ aggregate::AddCountDistinctKernel<Int64Type>(int64(), func.get());
Review comment:
You are providing explicit input types because you need them for the
[`ArrayDataInlineVisitor`](https://github.com/apache/arrow/blob/master/cpp/src/arrow/visitor_inline.h#L141)
invoked via
[`VisitorArrayDataInline`](https://github.com/apache/arrow/blob/master/cpp/src/arrow/visitor_inline.h#L326).
Note that `ArrayDataInlineVisitor` only checks for the base type, so we can
possibly register less number of kernels by leveraging [implicit
casting](https://arrow.apache.org/docs/cpp/compute.html#implicit-casts).
##########
File path: python/pyarrow/tests/test_compute.py
##########
@@ -2217,3 +2217,12 @@ def test_list_element():
result = pa.compute.list_element(lists, index)
expected = pa.array([{'a': 5.6, 'b': 6}, {'a': .6, 'b': 8}], element_type)
assert result.equals(expected)
+
+
+def test_count_distinct():
+ seed = datetime.now()
+ samples = [seed.replace(year=y) for y in range(1992, 2092)]
+ arr = pa.array(samples, pa.timestamp("ns"))
+ result = pa.compute.count_distinct(arr)
+ expected = pa.scalar(len(samples), type=pa.int64())
Review comment:
Add tests using the `CountOptions`, see
[`count`](https://github.com/apache/arrow/blob/master/python/pyarrow/tests/test_compute.py#L1839).
##########
File path: cpp/src/arrow/compute/kernels/aggregate_test.cc
##########
@@ -873,6 +873,65 @@ TYPED_TEST(TestRandomNumericCountKernel, RandomArrayCount)
{
}
}
+//
+// Count Distinct
+//
+
+class TestCountDistinctKernel : public ::testing::Test {
+ protected:
+ void SetUp() override {
+ only_valid = CountOptions(CountOptions::ONLY_VALID);
+ only_null = CountOptions(CountOptions::ONLY_NULL);
+ all = CountOptions(CountOptions::ALL);
+ }
+
+ const Datum& expected(int64_t value) {
+ expected_values[value] = Datum(static_cast<int64_t>(value));
+ return expected_values.at(value);
+ }
+
+ CountOptions only_valid;
+ CountOptions only_null;
+ CountOptions all;
+
+ private:
+ std::map<int64_t, Datum> expected_values;
+};
+
+TEST_F(TestCountDistinctKernel, NumericArrowTypesWithNulls) {
+ auto sample = "[1, 1, 2, 2, 5, 8, 9, 9, 9, 10, 6, 6]";
+ auto sample_nulls = "[null, 8, null, null, 6, null, 8]";
+ for (auto ty : NumericTypes()) {
+ auto input = ArrayFromJSON(ty, sample);
+ CheckScalar("count_distinct", {input}, expected(7), &only_valid);
+ CheckScalar("count_distinct", {input}, expected(0), &only_null);
+ CheckScalar("count_distinct", {input}, expected(7), &all);
+ auto input_nulls = ArrayFromJSON(ty, sample_nulls);
+ CheckScalar("count_distinct", {input_nulls}, expected(2), &only_valid);
+ CheckScalar("count_distinct", {input_nulls}, expected(1), &only_null);
+ CheckScalar("count_distinct", {input_nulls}, expected(3), &all);
+ }
+}
+
+TEST_F(TestCountDistinctKernel, RandomValidsStdMap) {
+ UInt32Builder builder;
+ std::map<uint32_t, int64_t> hashmap;
+ auto visit_null = [&]() { return Status::OK(); };
+ auto visit_value = [&](uint32_t arg) {
Review comment:
`visit_null` does not needs the ampersand, there are no variables being
binded.
##########
File path: cpp/src/arrow/compute/kernels/aggregate_basic.cc
##########
@@ -121,6 +122,84 @@ Result<std::unique_ptr<KernelState>>
CountInit(KernelContext*,
static_cast<const CountOptions&>(*args.options));
}
+// ----------------------------------------------------------------------
+// Distinct Count implementation
+
+template <typename Type>
+struct CountDistinctImpl : public ScalarAggregator {
+ using MemoTable = typename arrow::internal::HashTraits<Type>::MemoTableType;
+
+ explicit CountDistinctImpl(MemoryPool* memory_pool, CountOptions options)
+ : options(std::move(options)), memo_table_(new MemoTable(memory_pool,
0)) {}
+
+ Status Consume(KernelContext*, const ExecBatch& batch) override {
+ if (batch[0].is_array()) {
+ const ArrayData& arr = *batch[0].array();
+ auto visit_null = [&]() {
+ if (this->nulls > 0) return Status::OK();
+ ++this->nulls;
+ return Status::OK();
+ };
Review comment:
Since we need to traverse the array for building the `memo_table` and if
we accumulate the `nulls`, then we could potentially update the null count of
`arr` as a side-effect, but ... allow such side-effect? cc @lidavidm
##########
File path: cpp/src/arrow/compute/kernels/aggregate_test.cc
##########
@@ -873,6 +873,65 @@ TYPED_TEST(TestRandomNumericCountKernel, RandomArrayCount)
{
}
}
+//
+// Count Distinct
+//
+
+class TestCountDistinctKernel : public ::testing::Test {
+ protected:
+ void SetUp() override {
+ only_valid = CountOptions(CountOptions::ONLY_VALID);
+ only_null = CountOptions(CountOptions::ONLY_NULL);
+ all = CountOptions(CountOptions::ALL);
+ }
+
+ const Datum& expected(int64_t value) {
+ expected_values[value] = Datum(static_cast<int64_t>(value));
+ return expected_values.at(value);
+ }
+
+ CountOptions only_valid;
+ CountOptions only_null;
+ CountOptions all;
+
+ private:
+ std::map<int64_t, Datum> expected_values;
+};
+
+TEST_F(TestCountDistinctKernel, NumericArrowTypesWithNulls) {
+ auto sample = "[1, 1, 2, 2, 5, 8, 9, 9, 9, 10, 6, 6]";
Review comment:
Also add tests for non-numeric types.
##########
File path: cpp/src/arrow/compute/kernels/aggregate_basic.cc
##########
@@ -121,6 +122,84 @@ Result<std::unique_ptr<KernelState>>
CountInit(KernelContext*,
static_cast<const CountOptions&>(*args.options));
}
+// ----------------------------------------------------------------------
+// Distinct Count implementation
+
+template <typename Type>
+struct CountDistinctImpl : public ScalarAggregator {
+ using MemoTable = typename arrow::internal::HashTraits<Type>::MemoTableType;
+
+ explicit CountDistinctImpl(MemoryPool* memory_pool, CountOptions options)
+ : options(std::move(options)), memo_table_(new MemoTable(memory_pool,
0)) {}
+
+ Status Consume(KernelContext*, const ExecBatch& batch) override {
+ if (batch[0].is_array()) {
+ const ArrayData& arr = *batch[0].array();
+ auto visit_null = [&]() {
+ if (this->nulls > 0) return Status::OK();
+ ++this->nulls;
+ return Status::OK();
+ };
+ auto visit_value = [&](typename Type::c_type arg) {
+ int y;
+ RETURN_NOT_OK(memo_table_->GetOrInsert(arg, &y));
+ return Status::OK();
+ };
+ RETURN_NOT_OK(VisitArrayDataInline<Type>(arr, visit_value, visit_null));
+ this->non_nulls += this->memo_table_->size();
+ } else {
+ const Scalar& input = *batch[0].scalar();
+ this->nulls += !input.is_valid * batch.length;
+ this->non_nulls += input.is_valid * batch.length;
+ }
+ return Status::OK();
+ }
+
+ Status MergeFrom(KernelContext*, KernelState&& src) override {
+ const auto& other_state = checked_cast<const CountDistinctImpl&>(src);
+ this->non_nulls += other_state.non_nulls;
+ this->nulls += other_state.nulls;
+ return Status::OK();
+ }
+
+ Status Finalize(KernelContext* ctx, Datum* out) override {
+ const auto& state = checked_cast<const CountDistinctImpl&>(*ctx->state());
+ switch (state.options.mode) {
+ case CountOptions::ONLY_VALID:
+ *out = Datum(state.non_nulls);
+ break;
+ case CountOptions::ALL:
+ *out = Datum(state.non_nulls + state.nulls);
+ break;
Review comment:
If `this->nulls` are being accumulated then use `std::min(state.nulls,
1)` for its value.
##########
File path: cpp/src/arrow/compute/kernels/aggregate_test.cc
##########
@@ -873,6 +873,65 @@ TYPED_TEST(TestRandomNumericCountKernel, RandomArrayCount)
{
}
}
+//
+// Count Distinct
+//
+
+class TestCountDistinctKernel : public ::testing::Test {
+ protected:
+ void SetUp() override {
+ only_valid = CountOptions(CountOptions::ONLY_VALID);
+ only_null = CountOptions(CountOptions::ONLY_NULL);
+ all = CountOptions(CountOptions::ALL);
+ }
+
+ const Datum& expected(int64_t value) {
+ expected_values[value] = Datum(static_cast<int64_t>(value));
+ return expected_values.at(value);
Review comment:
Not sure I understand the rationale here. You are basically storing and
returning `Datum(value)`?
##########
File path: cpp/src/arrow/compute/kernels/aggregate_basic.cc
##########
@@ -121,6 +122,84 @@ Result<std::unique_ptr<KernelState>>
CountInit(KernelContext*,
static_cast<const CountOptions&>(*args.options));
}
+// ----------------------------------------------------------------------
+// Distinct Count implementation
+
+template <typename Type>
+struct CountDistinctImpl : public ScalarAggregator {
+ using MemoTable = typename arrow::internal::HashTraits<Type>::MemoTableType;
Review comment:
There could be a base class for aggregate `CountImpl` that includes
`options, non_nulls, nulls, and MergeFrom()` with virtual `Consume() and
Finalize()`, but maybe it is overkill.
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