lidavidm commented on a change in pull request #12460:
URL: https://github.com/apache/arrow/pull/12460#discussion_r822649084
##########
File path: cpp/src/arrow/compute/kernels/vector_cumulative_sum.cc
##########
@@ -51,8 +51,8 @@ struct CumulativeSum {
}
Status Exec(KernelContext* ctx, const ExecBatch& batch, Datum* out) {
- const ScalarType& start_scalar = checked_cast<const
ScalarType&>(*batch[1].scalar());
- CType start = start_scalar.value;
+ const auto& options =
OptionsWrapper<CumulativeSumOptions<CType>>::Get(ctx);
+ CType start = checked_cast<const ScalarType&>(options.start).value;
Review comment:
Consider using UnboxScalar instead:
https://github.com/apache/arrow/blob/e8a1e1328f3c1bc6bf5ff7ba86057af3e37b634d/cpp/src/arrow/compute/kernels/codegen_internal.h#L325-L328
Though: we should handle when the scalar is null (`!scalar->is_valid`), when
the scalar is `nullptr`, and when the scalar is not of the expected type.
##########
File path: cpp/src/arrow/compute/kernels/vector_cumulative_sum.cc
##########
@@ -0,0 +1,159 @@
+// 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.
+
+#include "arrow/array/array_base.h"
+#include "arrow/compute/api_scalar.h"
+#include "arrow/compute/kernels/common.h"
+#include "arrow/result.h"
+#include "arrow/visit_type_inline.h"
+
+namespace arrow {
+namespace compute {
+namespace internal {
+
+template <typename Type>
+struct CumulativeSum {
+ using CType = TypeTraits<Type>::CType;
+ using ScalarType = TypeTraits<Type>::ScalarType;
+
+ CType Sum(ExecContext* ctx, std::shared_ptr<Array>& input, ArrayData* output,
+ CType start) {
+ CType sum = start;
+ CType* data = checked_cast<CType*>(input->data()->buffers[1]->data());
+ CType* out_values =
checked_cast<CType*>(output->buffers[1]->mutable_data());
+ ArithmeticOptions options;
+ for (size_t i = input->offset; i < input->length; ++i) {
+ if (input->IsValid(i)) {
+ Datum value_datum(data[i]);
+ Datum sum_datum(sum);
+ auto result = Add(value_datum, sum_datum, options, ctx);
+ ScalarType result_scalar = result.ValueOrDie().scalar_as();
+ sum = result_scalar.value;
+ out_values[i] = sum;
+ }
+ }
+
+ return sum;
+ }
+
+ Status Exec(KernelContext* ctx, const ExecBatch& batch, Datum* out) {
+ const auto& options =
OptionsWrapper<CumulativeSumOptions<CType>>::Get(ctx);
+ CType start = checked_cast<const ScalarType&>(options.start).value;
+
+ switch (batch[0].kind()) {
+ case Datum::ARRAY:
+ std::shared_ptr<Array> input = batch[0].make_array();
+ ArrayData* output = out->array().get();
+
+ output->length = input->data()->length;
+ *output->type = std::move(input->type());
+ uint8_t* out_bitmap = output->buffers[0]->mutable_data();
+ int64_t out_offset = input->offset();
+
+ if (input->data()->MayHaveNulls()) {
+ arrow::internal::CopyBitmap(input->null_bitmap_data(),
input->offset(),
+ input->length(), out_bitmap, out_offset);
+ output->null_count = input->null_count();
+ } else {
+ bit_util::SetBitsTo(out_bitmap, out_offset, input->length(), true);
+ output->null_count = 0;
+ }
+
+ Sum(ctx->exec_context(), input, output, start);
+ return Status::OK();
+ case Datum::CHUNKED_ARRAY:
+ const auto& input = batch[0].chunked_array();
+
+ ArrayVector out_chunks;
+ for (const auto& chunk : input->chunks()) {
+ auto out_chunk = std::make_shared<ArrayData>(
+ chunk->type(), chunk->length(), chunk->null_count(),
chunk->offset());
+
+ uint8_t* out_chunk_bitmap = out_chunk->buffers[0]->mutable_data();
+ if (chunk->data()->MayHaveNulls()) {
+ arrow::internal::CopyBitmap(chunk->null_bitmap_data(),
chunk->offset(),
+ chunk->length(), out_chunk_bitmap,
+ out_chunk->offset());
+ out_chunk->null_count = chunk->null_count();
+ } else {
+ bit_util::SetBitsTo(out_chunk_bitmap, out_chunk->offset(),
chunk->length(),
+ true);
+ out_chunk->null_count = 0;
+ }
+
+ CType last_value = Sum(ctx->exec_context(), chunk, out_chunk, start);
+ start = last_value;
+ out_chunks.push_back(MakeArray(std::move(out_chunk)));
+ }
+
+ *out->chunked_array() = ChunkedArray(out_chunks, input->type());
+ return Status::OK();
+ default:
+ return Status::NotImplemented(
+ "Unsupported input type for function 'cumulative_sum': ",
+ batch[0].ToString());
+ }
+ }
+
+ static std::shared_ptr<KernelSignature> GetSignature(detail::GetTypeId
get_id) {
+ return KernelSignature::Make({InputType::Array(get_id.id)},
OutputType(FirstType));
+ }
+};
+
+const FunctionDoc cumulative_sum_doc(
+ "Compute the cumulative sum over an array of numbers",
+ ("`values` must be an array of numeric type values.\n"
+ "`start` is a single value of the same type.\n"
+ "Return an array which is the cumulative sum computed over `values.`\n"
+ "Null entries remain in place but are not used in calucating sum.\n"
+ "`start` is an optional starting sum of computation."),
+ {"values", "start"});
+
+void RegisterVectorCumulativeSum(FunctionRegistry* registry) {
+ auto cumulative_sum = std::make_shared<VectorFunction>(
+ "cumulative_sum", Arity::Binary(), &cumulative_sum_doc);
+
+ auto add_kernel = [&](detail::GetTypeId get_id, ArrayKernelExec exec) {
+ VectorKernel kernel;
+ kernel.can_execute_chunkwise = true;
Review comment:
Hmm, can this kernel work chunkwise? We'll have to make sure to test this
##########
File path: cpp/src/arrow/compute/api_vector.h
##########
@@ -188,6 +188,17 @@ class ARROW_EXPORT PartitionNthOptions : public
FunctionOptions {
NullPlacement null_placement;
};
+/// \brief Options for cumulative sum function
+class ARROW_EXPORT CumulativeSumOptions : public FunctionOptions {
+ public:
+ explicit CumulativeSumOptions(std::shared_ptr<Scalar> start);
+ CumulativeSumOptions() :
CumulativeSumOptions(std::make_shared<NullScalar>()) {}
Review comment:
`nullptr` might be a better default?
##########
File path: cpp/src/arrow/compute/kernels/vector_cumulative_sum.cc
##########
@@ -0,0 +1,159 @@
+// 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.
+
+#include "arrow/array/array_base.h"
+#include "arrow/compute/api_scalar.h"
+#include "arrow/compute/kernels/common.h"
+#include "arrow/result.h"
+#include "arrow/visit_type_inline.h"
+
+namespace arrow {
+namespace compute {
+namespace internal {
+
+template <typename Type>
+struct CumulativeSum {
+ using CType = TypeTraits<Type>::CType;
+ using ScalarType = TypeTraits<Type>::ScalarType;
+
+ CType Sum(ExecContext* ctx, std::shared_ptr<Array>& input, ArrayData* output,
+ CType start) {
+ CType sum = start;
+ CType* data = checked_cast<CType*>(input->data()->buffers[1]->data());
+ CType* out_values =
checked_cast<CType*>(output->buffers[1]->mutable_data());
+ ArithmeticOptions options;
+ for (size_t i = input->offset; i < input->length; ++i) {
+ if (input->IsValid(i)) {
+ Datum value_datum(data[i]);
+ Datum sum_datum(sum);
+ auto result = Add(value_datum, sum_datum, options, ctx);
+ ScalarType result_scalar = result.ValueOrDie().scalar_as();
+ sum = result_scalar.value;
+ out_values[i] = sum;
+ }
+ }
+
+ return sum;
+ }
+
+ Status Exec(KernelContext* ctx, const ExecBatch& batch, Datum* out) {
+ const auto& options =
OptionsWrapper<CumulativeSumOptions<CType>>::Get(ctx);
+ CType start = checked_cast<const ScalarType&>(options.start).value;
+
+ switch (batch[0].kind()) {
+ case Datum::ARRAY:
+ std::shared_ptr<Array> input = batch[0].make_array();
+ ArrayData* output = out->array().get();
+
+ output->length = input->data()->length;
+ *output->type = std::move(input->type());
+ uint8_t* out_bitmap = output->buffers[0]->mutable_data();
+ int64_t out_offset = input->offset();
+
+ if (input->data()->MayHaveNulls()) {
+ arrow::internal::CopyBitmap(input->null_bitmap_data(),
input->offset(),
+ input->length(), out_bitmap, out_offset);
+ output->null_count = input->null_count();
+ } else {
+ bit_util::SetBitsTo(out_bitmap, out_offset, input->length(), true);
+ output->null_count = 0;
+ }
+
+ Sum(ctx->exec_context(), input, output, start);
+ return Status::OK();
+ case Datum::CHUNKED_ARRAY:
+ const auto& input = batch[0].chunked_array();
+
+ ArrayVector out_chunks;
+ for (const auto& chunk : input->chunks()) {
+ auto out_chunk = std::make_shared<ArrayData>(
+ chunk->type(), chunk->length(), chunk->null_count(),
chunk->offset());
+
+ uint8_t* out_chunk_bitmap = out_chunk->buffers[0]->mutable_data();
+ if (chunk->data()->MayHaveNulls()) {
+ arrow::internal::CopyBitmap(chunk->null_bitmap_data(),
chunk->offset(),
+ chunk->length(), out_chunk_bitmap,
+ out_chunk->offset());
+ out_chunk->null_count = chunk->null_count();
+ } else {
+ bit_util::SetBitsTo(out_chunk_bitmap, out_chunk->offset(),
chunk->length(),
+ true);
+ out_chunk->null_count = 0;
+ }
+
+ CType last_value = Sum(ctx->exec_context(), chunk, out_chunk, start);
+ start = last_value;
+ out_chunks.push_back(MakeArray(std::move(out_chunk)));
+ }
+
+ *out->chunked_array() = ChunkedArray(out_chunks, input->type());
+ return Status::OK();
+ default:
+ return Status::NotImplemented(
+ "Unsupported input type for function 'cumulative_sum': ",
+ batch[0].ToString());
+ }
+ }
+
+ static std::shared_ptr<KernelSignature> GetSignature(detail::GetTypeId
get_id) {
+ return KernelSignature::Make({InputType::Array(get_id.id)},
OutputType(FirstType));
+ }
+};
+
+const FunctionDoc cumulative_sum_doc(
+ "Compute the cumulative sum over an array of numbers",
+ ("`values` must be an array of numeric type values.\n"
+ "`start` is a single value of the same type.\n"
+ "Return an array which is the cumulative sum computed over `values.`\n"
+ "Null entries remain in place but are not used in calucating sum.\n"
+ "`start` is an optional starting sum of computation."),
+ {"values", "start"});
+
+void RegisterVectorCumulativeSum(FunctionRegistry* registry) {
+ auto cumulative_sum = std::make_shared<VectorFunction>(
+ "cumulative_sum", Arity::Binary(), &cumulative_sum_doc);
+
+ auto add_kernel = [&](detail::GetTypeId get_id, ArrayKernelExec exec) {
+ VectorKernel kernel;
+ kernel.can_execute_chunkwise = true;
+ kernel.null_handling = NullHandling::type::INTERSECTION;
+ kernel.mem_allocation = MemAllocation::type::PREALLOCATE;
+ kernel.signature = CumulativeSum<NumberType>::GetSignature(get_id.id);
Review comment:
We can just inline this here instead of having a separate function.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
