Fix fallback to sort aggregation for grouping only hash aggregate (ra…

…pidsai#9891) The following fixes what looks like an unintended fallback to sort aggregate introduced in rapidsai#9545 for a grouping only (no aggregation request) case. In the PR, the `std::all_of` function is used to determine whether the aggregation requests would be for struct types. That said, when there are no aggregation requests the `std::all_of` function will return true, causing a fallback to the sort aggregation (relevant code: https://github.com/rapidsai/cudf/pull/9545/files#diff-e409f72ddc11ad10fa0099e21b409b92f12bfac8ba1817266696c34a620aa081R645-R650). I added a benchmark `group_no_requests_benchmark.cu` by mostly copying `group_sum_benchmark.cu` but I changed one critical part. I am re-creating the `groupby` object for each `state`: ``` for (auto _ : state) { cuda_event_timer timer(state, true); cudf::groupby::groupby gb_obj(cudf::table_view({keys}));e auto result = gb_obj.aggregate(requests); } ``` This shows what would happen in the scenario where the `groupby` instance is created each time an aggregate is issued, which would re-create the `helper` each time for the sorted case. If the `groupby` object is not recreated each time, the difference in performance between the before/after cases is negligible. We never recycle a `groupby` instance when using the groupby API from Spark. Posting this as draft for feedback as I am not sure if I handled the benchmark part correctly. This was executed on a T4 GPU. Before the patch: ``` Groupby/BasicNoRequest/10000/manual_time 0.158 ms 0.184 ms 4420 Groupby/BasicNoRequest/1000000/manual_time 1.72 ms 1.74 ms 408 Groupby/BasicNoRequest/10000000/manual_time 18.9 ms 18.9 ms 37 Groupby/BasicNoRequest/100000000/manual_time 198 ms 198 ms 3 ``` <details> <summary>Full output</summary> <p> ``` 2021-12-12T13:41:08+00:00 Running ./GROUPBY_BENCH Run on (64 X 2801.89 MHz CPU s) CPU Caches: L1 Data 32 KiB (x32) L1 Instruction 32 KiB (x32) L2 Unified 1024 KiB (x32) L3 Unified 22528 KiB (x2) Load Average: 1.01, 0.78, 0.42 -------------------------------------------------------------------------------------------- Benchmark Time CPU Iterations -------------------------------------------------------------------------------------------- Groupby/Basic/10000/manual_time 0.117 ms 0.143 ms 5906 Groupby/Basic/1000000/manual_time 0.524 ms 0.542 ms 1352 Groupby/Basic/10000000/manual_time 4.41 ms 4.43 ms 159 Groupby/Basic/100000000/manual_time 50.1 ms 50.1 ms 13 Groupby/PreSorted/1000000/manual_time 0.332 ms 0.350 ms 2118 Groupby/PreSorted/10000000/manual_time 2.22 ms 2.23 ms 315 Groupby/PreSorted/100000000/manual_time 22.2 ms 22.2 ms 30 Groupby/PreSortedNth/1000000/manual_time 0.160 ms 0.188 ms 4381 Groupby/PreSortedNth/10000000/manual_time 0.890 ms 0.917 ms 774 Groupby/PreSortedNth/100000000/manual_time 8.43 ms 8.46 ms 68 Groupby/Shift/1000000/manual_time 0.764 ms 0.785 ms 902 Groupby/Shift/10000000/manual_time 9.51 ms 9.53 ms 63 Groupby/Shift/100000000/manual_time 145 ms 145 ms 4 Groupby/Aggregation/10000/manual_time 1.56 ms 1.58 ms 442 Groupby/Aggregation/16384/manual_time 1.59 ms 1.62 ms 435 Groupby/Aggregation/65536/manual_time 1.73 ms 1.76 ms 404 Groupby/Aggregation/262144/manual_time 2.95 ms 2.98 ms 237 Groupby/Aggregation/1048576/manual_time 9.20 ms 9.23 ms 73 Groupby/Aggregation/4194304/manual_time 36.3 ms 36.3 ms 19 Groupby/Aggregation/10000000/manual_time 92.0 ms 92.1 ms 7 Groupby/Scan/10000/manual_time 1.56 ms 1.58 ms 447 Groupby/Scan/16384/manual_time 1.62 ms 1.65 ms 429 Groupby/Scan/65536/manual_time 1.85 ms 1.88 ms 378 Groupby/Scan/262144/manual_time 3.54 ms 3.56 ms 197 Groupby/Scan/1048576/manual_time 12.0 ms 12.0 ms 57 Groupby/Scan/4194304/manual_time 48.6 ms 48.6 ms 14 Groupby/Scan/10000000/manual_time 126 ms 126 ms 4 Groupby/BasicNoRequest/10000/manual_time 0.158 ms 0.184 ms 4420 Groupby/BasicNoRequest/1000000/manual_time 1.72 ms 1.74 ms 408 Groupby/BasicNoRequest/10000000/manual_time 18.9 ms 18.9 ms 37 Groupby/BasicNoRequest/100000000/manual_time 198 ms 198 ms 3 Groupby/PreSortedNoRequests/1000000/manual_time 0.194 ms 0.214 ms 3624 Groupby/PreSortedNoRequests/10000000/manual_time 1.25 ms 1.27 ms 571 Groupby/PreSortedNoRequests/100000000/manual_time 12.6 ms 12.7 ms 50 ``` </details> After the patch: ``` Groupby/BasicNoRequest/10000/manual_time 0.058 ms 0.085 ms 11991 Groupby/BasicNoRequest/1000000/manual_time 0.282 ms 0.301 ms 2478 Groupby/BasicNoRequest/10000000/manual_time 2.42 ms 2.44 ms 291 Groupby/BasicNoRequest/100000000/manual_time 29.2 ms 29.2 ms 21 ``` <details> <summary>Full output</summary> <p> ``` 2021-12-12T13:37:50+00:00 Running ./GROUPBY_BENCH Run on (64 X 2654.22 MHz CPU s) CPU Caches: L1 Data 32 KiB (x32) L1 Instruction 32 KiB (x32) L2 Unified 1024 KiB (x32) L3 Unified 22528 KiB (x2) Load Average: 0.64, 0.50, 0.26 -------------------------------------------------------------------------------------------- Benchmark Time CPU Iterations -------------------------------------------------------------------------------------------- Groupby/Basic/10000/manual_time 0.116 ms 0.142 ms 5918 Groupby/Basic/1000000/manual_time 0.523 ms 0.542 ms 1374 Groupby/Basic/10000000/manual_time 4.37 ms 4.39 ms 162 Groupby/Basic/100000000/manual_time 51.4 ms 51.5 ms 10 Groupby/PreSorted/1000000/manual_time 0.331 ms 0.350 ms 2121 Groupby/PreSorted/10000000/manual_time 2.21 ms 2.23 ms 316 Groupby/PreSorted/100000000/manual_time 22.2 ms 22.2 ms 27 Groupby/PreSortedNth/1000000/manual_time 0.160 ms 0.188 ms 4384 Groupby/PreSortedNth/10000000/manual_time 0.888 ms 0.915 ms 775 Groupby/PreSortedNth/100000000/manual_time 8.36 ms 8.39 ms 70 Groupby/Shift/1000000/manual_time 0.764 ms 0.785 ms 904 Groupby/Shift/10000000/manual_time 9.50 ms 9.52 ms 63 Groupby/Shift/100000000/manual_time 146 ms 146 ms 4 Groupby/Aggregation/10000/manual_time 1.53 ms 1.55 ms 446 Groupby/Aggregation/16384/manual_time 1.58 ms 1.61 ms 437 Groupby/Aggregation/65536/manual_time 1.72 ms 1.75 ms 405 Groupby/Aggregation/262144/manual_time 2.93 ms 2.96 ms 236 Groupby/Aggregation/1048576/manual_time 9.18 ms 9.21 ms 74 Groupby/Aggregation/4194304/manual_time 36.2 ms 36.3 ms 19 Groupby/Aggregation/10000000/manual_time 91.5 ms 91.6 ms 7 Groupby/Scan/10000/manual_time 1.55 ms 1.57 ms 452 Groupby/Scan/16384/manual_time 1.60 ms 1.62 ms 434 Groupby/Scan/65536/manual_time 1.84 ms 1.87 ms 379 Groupby/Scan/262144/manual_time 3.54 ms 3.56 ms 198 Groupby/Scan/1048576/manual_time 12.0 ms 12.0 ms 57 Groupby/Scan/4194304/manual_time 48.4 ms 48.4 ms 14 Groupby/Scan/10000000/manual_time 125 ms 125 ms 4 Groupby/BasicNoRequest/10000/manual_time 0.058 ms 0.085 ms 11991 Groupby/BasicNoRequest/1000000/manual_time 0.282 ms 0.301 ms 2478 Groupby/BasicNoRequest/10000000/manual_time 2.42 ms 2.44 ms 291 Groupby/BasicNoRequest/100000000/manual_time 29.2 ms 29.2 ms 21 Groupby/PreSortedNoRequests/1000000/manual_time 0.195 ms 0.215 ms 3604 Groupby/PreSortedNoRequests/10000000/manual_time 1.25 ms 1.27 ms 575 Groupby/PreSortedNoRequests/100000000/manual_time 12.7 ms 12.8 ms 50 ``` </details> Authors: - Alessandro Bellina (https://github.com/abellina) Approvers: - Jake Hemstad (https://github.com/jrhemstad) - Nghia Truong (https://github.com/ttnghia) - Conor Hoekstra (https://github.com/codereport) URL: rapidsai#9891
abellina · Dec 14, 2021 · 8fbc469 · 8fbc469
1 parent 0930f71
commit 8fbc469
Show file tree

Hide file tree

Showing 3 changed files with 131 additions and 19 deletions.
diff --git a/cpp/benchmarks/CMakeLists.txt b/cpp/benchmarks/CMakeLists.txt
@@ -156,8 +156,12 @@ ConfigureBench(FILL_BENCH filling/repeat_benchmark.cpp)
 # ##################################################################################################
 # * groupby benchmark -----------------------------------------------------------------------------
 ConfigureBench(
-  GROUPBY_BENCH groupby/group_sum_benchmark.cu groupby/group_nth_benchmark.cu
-  groupby/group_shift_benchmark.cu groupby/group_struct_benchmark.cu
+  GROUPBY_BENCH
+  groupby/group_sum_benchmark.cu
+  groupby/group_nth_benchmark.cu
+  groupby/group_shift_benchmark.cu
+  groupby/group_struct_benchmark.cu
+  groupby/group_no_requests_benchmark.cu
 )
 
 # ##################################################################################################

diff --git a/cpp/benchmarks/groupby/group_no_requests_benchmark.cu b/cpp/benchmarks/groupby/group_no_requests_benchmark.cu
@@ -0,0 +1,115 @@
+/*
+ * Copyright (c) 2021, NVIDIA CORPORATION.
+ *
+ * Licensed 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 <cudf/copying.hpp>
+#include <cudf/detail/aggregation/aggregation.hpp>
+#include <cudf/groupby.hpp>
+#include <cudf/sorting.hpp>
+#include <cudf/table/table.hpp>
+#include <cudf_test/column_wrapper.hpp>
+#include <fixture/benchmark_fixture.hpp>
+#include <synchronization/synchronization.hpp>
+
+#include <memory>
+#include <random>
+
+class Groupby : public cudf::benchmark {
+};
+
+// TODO: put it in a struct so `uniform` can be remade with different min, max
+template <typename T>
+T random_int(T min, T max)
+{
+  static unsigned seed = 13377331;
+  static std::mt19937 engine{seed};
+  static std::uniform_int_distribution<T> uniform{min, max};
+
+  return uniform(engine);
+}
+
+void BM_basic_no_requests(benchmark::State& state)
+{
+  using wrapper = cudf::test::fixed_width_column_wrapper<int64_t>;
+
+  const cudf::size_type column_size{(cudf::size_type)state.range(0)};
+
+  auto data_it = cudf::detail::make_counting_transform_iterator(
+    0, [=](cudf::size_type row) { return random_int(0, 100); });
+
+  wrapper keys(data_it, data_it + column_size);
+  wrapper vals(data_it, data_it + column_size);
+
+  std::vector<cudf::groupby::aggregation_request> requests;
+
+  for (auto _ : state) {
+    cuda_event_timer timer(state, true);
+    cudf::groupby::groupby gb_obj(cudf::table_view({keys}));
+    auto result = gb_obj.aggregate(requests);
+  }
+}
+
+BENCHMARK_DEFINE_F(Groupby, BasicNoRequest)(::benchmark::State& state)
+{
+  BM_basic_no_requests(state);
+}
+
+BENCHMARK_REGISTER_F(Groupby, BasicNoRequest)
+  ->UseManualTime()
+  ->Unit(benchmark::kMillisecond)
+  ->Arg(10000)
+  ->Arg(1000000)
+  ->Arg(10000000)
+  ->Arg(100000000);
+
+void BM_pre_sorted_no_requests(benchmark::State& state)
+{
+  using wrapper = cudf::test::fixed_width_column_wrapper<int64_t>;
+
+  const cudf::size_type column_size{(cudf::size_type)state.range(0)};
+
+  auto data_it = cudf::detail::make_counting_transform_iterator(
+    0, [=](cudf::size_type row) { return random_int(0, 100); });
+  auto valid_it = cudf::detail::make_counting_transform_iterator(
+    0, [=](cudf::size_type row) { return random_int(0, 100) < 90; });
+
+  wrapper keys(data_it, data_it + column_size);
+  wrapper vals(data_it, data_it + column_size, valid_it);
+
+  auto keys_table  = cudf::table_view({keys});
+  auto sort_order  = cudf::sorted_order(keys_table);
+  auto sorted_keys = cudf::gather(keys_table, *sort_order);
+  // No need to sort values using sort_order because they were generated randomly
+
+  std::vector<cudf::groupby::aggregation_request> requests;
+
+  for (auto _ : state) {
+    cuda_event_timer timer(state, true);
+    cudf::groupby::groupby gb_obj(*sorted_keys, cudf::null_policy::EXCLUDE, cudf::sorted::YES);
+    auto result = gb_obj.aggregate(requests);
+  }
+}
+
+BENCHMARK_DEFINE_F(Groupby, PreSortedNoRequests)(::benchmark::State& state)
+{
+  BM_pre_sorted_no_requests(state);
+}
+
+BENCHMARK_REGISTER_F(Groupby, PreSortedNoRequests)
+  ->UseManualTime()
+  ->Unit(benchmark::kMillisecond)
+  ->Arg(1000000)
+  ->Arg(10000000)
+  ->Arg(100000000);
diff --git a/cpp/src/groupby/hash/groupby.cu b/cpp/src/groupby/hash/groupby.cu
@@ -635,23 +635,16 @@ std::unique_ptr<table> groupby_null_templated(table_view const& keys,
  */
 bool can_use_hash_groupby(table_view const& keys, host_span<aggregation_request const> requests)
 {
-  auto const all_hash_aggregations =
-    std::all_of(requests.begin(), requests.end(), [](aggregation_request const& r) {
-      return cudf::has_atomic_support(r.values.type()) and
-             std::all_of(r.aggregations.begin(), r.aggregations.end(), [](auto const& a) {
-               return is_hash_aggregation(a->kind);
-             });
-    });
-
-  // Currently, structs are not supported in any of hash-based aggregations.
-  // Therefore, if any request contains structs then we must fallback to sort-based aggregations.
-  // TODO: Support structs in hash-based aggregations.
-  auto const has_struct =
-    std::all_of(requests.begin(), requests.end(), [](aggregation_request const& r) {
-      return r.values.type().id() == type_id::STRUCT;
-    });
-
-  return all_hash_aggregations && !has_struct;
+  return std::all_of(requests.begin(), requests.end(), [](aggregation_request const& r) {
+    // Currently, structs are not supported in any of hash-based aggregations.
+    // Therefore, if any request contains structs then we must fallback to sort-based aggregations.
+    // TODO: Support structs in hash-based aggregations.
+    return not(r.values.type().id() == type_id::STRUCT) and
+           cudf::has_atomic_support(r.values.type()) and
+           std::all_of(r.aggregations.begin(), r.aggregations.end(), [](auto const& a) {
+             return is_hash_aggregation(a->kind);
+           });
+  });
 }
 
 // Hash-based groupby