zanmato1984 commented on code in PR #45001:
URL: https://github.com/apache/arrow/pull/45001#discussion_r1883314088
##########
cpp/src/arrow/compute/kernels/CMakeLists.txt:
##########
@@ -87,6 +88,7 @@ add_arrow_benchmark(scalar_round_benchmark PREFIX
"arrow-compute")
add_arrow_benchmark(scalar_set_lookup_benchmark PREFIX "arrow-compute")
add_arrow_benchmark(scalar_string_benchmark PREFIX "arrow-compute")
add_arrow_benchmark(scalar_temporal_benchmark PREFIX "arrow-compute")
+add_arrow_benchmark(scalar_hash_benchmark PREFIX "arrow-compute")
Review Comment:
Keep alphabetical order for this one too.
##########
cpp/src/arrow/compute/kernels/CMakeLists.txt:
##########
@@ -73,6 +73,7 @@ add_arrow_compute_test(scalar_utility_test
scalar_random_test.cc
scalar_set_lookup_test.cc
scalar_validity_test.cc
+ scalar_hash_test.cc
Review Comment:
```suggestion
scalar_hash_test.cc
scalar_random_test.cc
scalar_set_lookup_test.cc
scalar_validity_test.cc
```
##########
cpp/src/arrow/compute/kernels/CMakeLists.txt:
##########
@@ -73,6 +73,7 @@ add_arrow_compute_test(scalar_utility_test
scalar_random_test.cc
scalar_set_lookup_test.cc
scalar_validity_test.cc
+ scalar_hash_test.cc
Review Comment:
Might want to keep source list in alphabetical.
##########
cpp/src/arrow/compute/api_scalar.cc:
##########
@@ -934,6 +934,12 @@ Result<Datum> MapLookup(const Datum& arg, MapLookupOptions
options, ExecContext*
return CallFunction("map_lookup", {arg}, &options, ctx);
}
+// ----------------------------------------------------------------------
+// Hash functions
+Result<Datum> Hash64(const Datum& input_array, ExecContext* ctx) {
+ return CallFunction("hash_64", {input_array}, ctx);
Review Comment:
Should we consider naming it `hash64` instead of `hash_64`?
##########
cpp/src/arrow/compute/api_scalar.h:
##########
@@ -1776,5 +1776,21 @@ ARROW_EXPORT Result<Datum> NanosecondsBetween(const
Datum& left, const Datum& ri
/// \note API not yet finalized
ARROW_EXPORT Result<Datum> MapLookup(const Datum& map, MapLookupOptions
options,
ExecContext* ctx = NULLPTR);
+
+/// \brief Construct a hash value for each row of the input.
+///
+/// The result is an Array of length equal to the length of the input;
however, the output
+/// shall be a UInt64Array, with each element being a hash constructed from
each row of
+/// the input. If the input Array is a NestedArray, this means that each
"attribute" or
+/// "field" of the input NestedArray corresponding to the same "row" will
collectively
+/// produce a single uint64_t hash. At the moment, this function does not take
options,
+/// though these may be added in the future.
+///
+/// \param[in] input_array input data to hash
+/// \param[in] ctx function execution context, optional
Review Comment:
```suggestion
/// \param[in] ctx function execution context, optional
```
##########
cpp/src/arrow/compute/kernels/scalar_hash.cc:
##########
@@ -0,0 +1,204 @@
+// 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 <algorithm>
+
+#include "arrow/array/array_base.h"
+#include "arrow/array/builder_primitive.h"
+#include "arrow/compute/kernels/common_internal.h"
+#include "arrow/compute/key_hash_internal.h"
+#include "arrow/compute/light_array_internal.h"
+#include "arrow/compute/util.h"
+#include "arrow/result.h"
+
+namespace arrow {
+namespace compute {
+namespace internal {
+
+// Define symbols visible within `arrow::compute::internal` in this file;
+// these symbols are not visible outside of this file.
+namespace {
+
+// Function documentation
+const FunctionDoc hash_64_doc{
+ "Construct a hash for every element of the input argument",
+ ("An element-wise function that uses an xxHash-like algorithm.\n"
+ "This function is not suitable for cryptographic purposes.\n"
+ "Hash results are 64-bit and emitted for each valid row.\n"
+ "Null (or invalid) rows emit a null in the output."),
+ {"hash_input"}};
+
+// ------------------------------
+// Kernel implementations
+// It is expected that HashArrowType is either UInt32Type or UInt64Type
(default)
+// template <typename HashArrowType = UInt64Type>
+struct FastHashScalar {
+ static Result<KeyColumnArray> ToColumnArray(
+ const ArraySpan& array, LightContext* ctx,
+ const uint8_t* list_values_buffer = nullptr) {
+ KeyColumnMetadata metadata;
+ const uint8_t* validity_buffer = nullptr;
+ const uint8_t* fixed_length_buffer = nullptr;
+ const uint8_t* var_length_buffer = nullptr;
+
+ if (array.GetBuffer(0) != nullptr) {
+ validity_buffer = array.GetBuffer(0)->data();
+ }
+ if (array.GetBuffer(1) != nullptr) {
+ fixed_length_buffer = array.GetBuffer(1)->data();
+ }
+
+ auto type_id = array.type->id();
+ if (type_id == Type::NA) {
+ metadata = KeyColumnMetadata(true, 0, true);
+ } else if (type_id == Type::BOOL) {
+ metadata = KeyColumnMetadata(true, 0);
+ } else if (is_fixed_width(type_id)) {
+ metadata = KeyColumnMetadata(true, array.type->bit_width() / 8);
+ } else if (is_binary_like(type_id)) {
+ metadata = KeyColumnMetadata(false, sizeof(uint32_t));
+ var_length_buffer = array.GetBuffer(2)->data();
+ } else if (is_large_binary_like(type_id)) {
+ metadata = KeyColumnMetadata(false, sizeof(uint64_t));
+ var_length_buffer = array.GetBuffer(2)->data();
+ } else if (type_id == Type::MAP) {
+ metadata = KeyColumnMetadata(false, sizeof(uint32_t));
+ var_length_buffer = list_values_buffer;
+ } else if (type_id == Type::LIST) {
+ metadata = KeyColumnMetadata(false, sizeof(uint32_t));
+ var_length_buffer = list_values_buffer;
+ } else if (type_id == Type::LARGE_LIST) {
+ metadata = KeyColumnMetadata(false, sizeof(uint64_t));
+ var_length_buffer = list_values_buffer;
+ } else if (type_id == Type::FIXED_SIZE_LIST) {
+ auto list_type = checked_cast<const FixedSizeListType*>(array.type);
+ metadata = KeyColumnMetadata(true, list_type->list_size());
+ fixed_length_buffer = list_values_buffer;
+ } else {
+ return Status::TypeError("Unsupported column data type ",
array.type->name(),
+ " used with hash_64 compute kernel");
+ }
+
+ return KeyColumnArray(metadata, array.length, validity_buffer,
fixed_length_buffer,
+ var_length_buffer);
+ }
+
+ static Result<std::shared_ptr<ArrayData>> HashChild(const ArraySpan& array,
+ const ArraySpan& child,
+ LightContext* hash_ctx,
+ MemoryPool* memory_pool)
{
+ auto buffer_size = child.length * sizeof(uint64_t);
+ ARROW_ASSIGN_OR_RAISE(auto buffer, AllocateBuffer(buffer_size,
memory_pool));
+ ARROW_RETURN_NOT_OK(
+ HashArray(child, hash_ctx, memory_pool,
buffer->mutable_data_as<uint64_t>()));
+ return ArrayData::Make(uint64(), child.length,
+ {array.GetBuffer(0), std::move(buffer)},
array.null_count);
+ }
+
+ static Status HashArray(const ArraySpan& array, LightContext* hash_ctx,
+ MemoryPool* memory_pool, uint64_t* out) {
+ // KeyColumnArray objects are being passed to the hashing utility
+ std::vector<KeyColumnArray> columns(1);
+ // ensure that we keep the converted child arrays alive because
KeyColumnArray
+ // only provides a view into the original array data
+ std::vector<std::shared_ptr<ArrayData>> children;
+
+ auto type_id = array.type->id();
+ if (type_id == Type::STRUCT) {
+ columns.reserve(array.child_data.size());
+ for (size_t i = 0; i < array.child_data.size(); i++) {
+ auto child = array.child_data[i];
+ if (is_nested(child.type->id())) {
+ ARROW_ASSIGN_OR_RAISE(auto child_hashes,
+ HashChild(array, child, hash_ctx,
memory_pool));
+ children.push_back(child_hashes);
+ ARROW_ASSIGN_OR_RAISE(columns[i], ToColumnArray(*child_hashes,
hash_ctx));
+ } else {
+ ARROW_ASSIGN_OR_RAISE(columns[i], ToColumnArray(child, hash_ctx));
+ }
+ }
+ } else if (is_list_like(type_id)) {
+ auto values = array.child_data[0];
+ ARROW_ASSIGN_OR_RAISE(auto value_hashes,
+ HashChild(array, values, hash_ctx, memory_pool));
+ children.push_back(value_hashes);
+ ARROW_ASSIGN_OR_RAISE(
+ columns[0], ToColumnArray(array, hash_ctx,
value_hashes->buffers[1]->data()));
+ } else {
+ ARROW_ASSIGN_OR_RAISE(columns[0], ToColumnArray(array, hash_ctx));
+ }
+ Hashing64::HashMultiColumn(columns, hash_ctx, out);
+ return Status::OK();
+ }
+
+ static Status Exec(KernelContext* ctx, const ExecSpan& input_arg,
ExecResult* out) {
+ if (input_arg.num_values() != 1 || !input_arg[0].is_array()) {
+ return Status::Invalid("FastHash currently supports a single array
input");
+ }
+ ArraySpan hash_input = input_arg[0].array;
+
+ auto exec_ctx = default_exec_context();
+ if (ctx && ctx->exec_context()) {
+ exec_ctx = ctx->exec_context();
+ }
+
+ // Initialize stack-based memory allocator used by Hashing32 and Hashing64
+ util::TempVectorStack stack_memallocator;
+ ARROW_RETURN_NOT_OK(
+ stack_memallocator.Init(exec_ctx->memory_pool(),
+ 3 * sizeof(int32_t) *
util::MiniBatch::kMiniBatchLength));
+
+ // Prepare context used by Hashing32 and Hashing64
+ LightContext hash_ctx;
+ hash_ctx.hardware_flags = exec_ctx->cpu_info()->hardware_flags();
+ hash_ctx.stack = &stack_memallocator;
+
+ // Call the hashing function, overloaded based on OutputCType
+ ArraySpan* result_span = out->array_span_mutable();
+ uint64_t* result_ptr = result_span->GetValues<uint64_t>(1);
+ ARROW_RETURN_NOT_OK(
+ HashArray(hash_input, &hash_ctx, exec_ctx->memory_pool(), result_ptr));
+
+ return Status::OK();
+ }
+};
+
+// ------------------------------
+// Function construction and kernel registration
+std::shared_ptr<ScalarFunction> RegisterKernelsFastHash64() {
+ // Create function instance
+ auto fn_hash_64 =
+ std::make_shared<ScalarFunction>("hash_64", Arity::Unary(), hash_64_doc);
+
+ // Add 64-bit hash kernel
+ ScalarKernel kernel({InputType()}, OutputType(uint64()),
FastHashScalar::Exec);
+ kernel.null_handling = NullHandling::OUTPUT_NOT_NULL;
Review Comment:
Is this correct? The function doc says this function emits null for null
input so this should be `NullHandling::INTERSECTION` (defaulted)?
##########
docs/source/cpp/compute.rst:
##########
@@ -1231,6 +1231,26 @@ Containment tests
* \(8) Output is true iff :member:`MatchSubstringOptions::pattern`
matches the corresponding input element at any position.
+
+Hash Functions
+~~~~~~~~~~~~~~
+
+Not to be confused with the "group by" functions, Hash functions produce an
array of hash
+values corresponding to the length of the input. Currently, these functions
take a single
+array as input.
+
++-----------------------+-------+-----------------------------------+-------------+---------------+-------+
+| Function name | Arity | Input types | Output
type | Options class | Notes |
++=======================+=======+===================================+=============+===============+=======+
+| hash_64 | Unary | Any | UInt64
| | \(1) |
++-----------------------+-------+-----------------------------------+-------------+---------------+-------+
Review Comment:
```suggestion
+---------------+-------+-------------+-------------+---------------+-------+
| Function name | Arity | Input types | Output type | Options class | Notes |
+===============+=======+=============+=============+===============+=======+
| hash_64 | Unary | Any | UInt64 | | \(1) |
+---------------+-------+-------------+-------------+---------------+-------+
```
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