Avoid inserting null elements into join hash table when nulls are tre…

…ated as unequal(#6943) This change mirrors what is done in `groupby` to eliminate null-containing columns from the join hash table if nulls not equal is set. This prevents absolute runaway of the process. I added benchmarks for joins with nulls and I can't even get it to finish without these changes. The 195ms test without nulls takes 2,000,000ms to complete and the larger tests I haven't had the patience to even see complete. With this change, the timings are faster than without nulls proportional to the % of nulls. Meaning half the table is nulls means the query is twice as fast as the non-null version, which makes sense. closes #6052 Authors: - Mike Wilson <[email protected]> - Mike Wilson <[email protected]> Approvers: - Jake Hemstad - Jake Hemstad - null - Mark Harris URL: #6943
rapidsai · Dec 11, 2020 · ab8c931 · ab8c931
1 parent 4c26155
commit ab8c931
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Showing 8 changed files with 108 additions and 39 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -20,6 +20,7 @@
 
 - PR #6922 Fix N/A detection for empty fields in CSV reader
 - PR #6912 Fix rmm_mode=managed parameter for gtests
+- PR #6943 Fix join with nulls not equal performance
 - PR #6945 Fix groupby agg/apply behaviour when no key columns are provided 
 - PR #6942 Fix cudf::merge gtest for dictionary columns
 

diff --git a/cpp/benchmarks/join/join_benchmark.cu b/cpp/benchmarks/join/join_benchmark.cu
@@ -23,6 +23,7 @@
 #include <cudf/table/table.hpp>
 #include <cudf/table/table_view.hpp>
 #include <cudf/utilities/error.hpp>
+#include <cudf_test/base_fixture.hpp>
 #include <cudf_test/column_wrapper.hpp>
 
 #include <fixture/benchmark_fixture.hpp>
@@ -36,7 +37,7 @@ template <typename key_type, typename payload_type>
 class Join : public cudf::benchmark {
 };
 
-template <typename key_type, typename payload_type>
+template <typename key_type, typename payload_type, bool Nullable>
 static void BM_join(benchmark::State &state)
 {
   const cudf::size_type build_table_size{(cudf::size_type)state.range(0)};
@@ -46,11 +47,33 @@ static void BM_join(benchmark::State &state)
   const bool is_build_table_key_unique = true;
 
   // Generate build and probe tables
-
-  auto build_key_column =
-    cudf::make_numeric_column(cudf::data_type(cudf::type_to_id<key_type>()), build_table_size);
-  auto probe_key_column =
-    cudf::make_numeric_column(cudf::data_type(cudf::type_to_id<key_type>()), probe_table_size);
+  cudf::test::UniformRandomGenerator<cudf::size_type> rand_gen(0, build_table_size);
+  auto build_random_null_mask = [&rand_gen](int size) {
+    if (Nullable) {
+      // roughly 25% nulls
+      auto validity = thrust::make_transform_iterator(
+        thrust::make_counting_iterator(0),
+        [&rand_gen](auto i) { return (rand_gen.generate() & 3) == 0; });
+      return cudf::test::detail::make_null_mask(validity, validity + size);
+    } else {
+      return cudf::create_null_mask(size, cudf::mask_state::UNINITIALIZED);
+    }
+  };
+
+  std::unique_ptr<cudf::column> build_key_column = [&]() {
+    return Nullable ? cudf::make_numeric_column(cudf::data_type(cudf::type_to_id<key_type>()),
+                                                build_table_size,
+                                                build_random_null_mask(build_table_size))
+                    : cudf::make_numeric_column(cudf::data_type(cudf::type_to_id<key_type>()),
+                                                build_table_size);
+  }();
+  std::unique_ptr<cudf::column> probe_key_column = [&]() {
+    return Nullable ? cudf::make_numeric_column(cudf::data_type(cudf::type_to_id<key_type>()),
+                                                probe_table_size,
+                                                build_random_null_mask(probe_table_size))
+                    : cudf::make_numeric_column(cudf::data_type(cudf::type_to_id<key_type>()),
+                                                probe_table_size);
+  }();
 
   generate_input_tables<key_type, cudf::size_type>(
     build_key_column->mutable_view().data<key_type>(),
@@ -82,17 +105,23 @@ static void BM_join(benchmark::State &state)
   for (auto _ : state) {
     cuda_event_timer raii(state, true, 0);
 
-    auto result =
-      cudf::inner_join(probe_table, build_table, columns_to_join, columns_to_join, {{0, 0}});
+    auto result = cudf::inner_join(probe_table,
+                                   build_table,
+                                   columns_to_join,
+                                   columns_to_join,
+                                   {{0, 0}},
+                                   cudf::null_equality::UNEQUAL);
   }
 }
 
-#define JOIN_BENCHMARK_DEFINE(name, key_type, payload_type)       \
-  BENCHMARK_TEMPLATE_DEFINE_F(Join, name, key_type, payload_type) \
-  (::benchmark::State & st) { BM_join<key_type, payload_type>(st); }
+#define JOIN_BENCHMARK_DEFINE(name, key_type, payload_type, nullable) \
+  BENCHMARK_TEMPLATE_DEFINE_F(Join, name, key_type, payload_type)     \
+  (::benchmark::State & st) { BM_join<key_type, payload_type, nullable>(st); }
 
-JOIN_BENCHMARK_DEFINE(join_32bit, int32_t, int32_t);
-JOIN_BENCHMARK_DEFINE(join_64bit, int64_t, int64_t);
+JOIN_BENCHMARK_DEFINE(join_32bit, int32_t, int32_t, false);
+JOIN_BENCHMARK_DEFINE(join_64bit, int64_t, int64_t, false);
+JOIN_BENCHMARK_DEFINE(join_32bit_nulls, int32_t, int32_t, true);
+JOIN_BENCHMARK_DEFINE(join_64bit_nulls, int64_t, int64_t, true);
 
 BENCHMARK_REGISTER_F(Join, join_32bit)
   ->Unit(benchmark::kMillisecond)
@@ -111,3 +140,21 @@ BENCHMARK_REGISTER_F(Join, join_64bit)
   ->Args({50'000'000, 50'000'000})
   ->Args({40'000'000, 120'000'000})
   ->UseManualTime();
+
+BENCHMARK_REGISTER_F(Join, join_32bit_nulls)
+  ->Unit(benchmark::kMillisecond)
+  ->Args({100'000, 100'000})
+  ->Args({100'000, 400'000})
+  ->Args({100'000, 1'000'000})
+  ->Args({10'000'000, 10'000'000})
+  ->Args({10'000'000, 40'000'000})
+  ->Args({10'000'000, 100'000'000})
+  ->Args({100'000'000, 100'000'000})
+  ->Args({80'000'000, 240'000'000})
+  ->UseManualTime();
+
+BENCHMARK_REGISTER_F(Join, join_64bit_nulls)
+  ->Unit(benchmark::kMillisecond)
+  ->Args({50'000'000, 50'000'000})
+  ->Args({40'000'000, 120'000'000})
+  ->UseManualTime();
diff --git a/cpp/include/cudf/join.hpp b/cpp/include/cudf/join.hpp
@@ -394,10 +394,12 @@ class hash_join {
    *
    * @param build The build table, from which the hash table is built.
    * @param build_on The column indices from `build` to join on.
+   * @param compare_nulls Controls whether null join-key values should match or not.
    * @param stream CUDA stream used for device memory operations and kernel launches
    */
   hash_join(cudf::table_view const& build,
             std::vector<size_type> const& build_on,
+            null_equality compare_nulls,
             rmm::cuda_stream_view stream = rmm::cuda_stream_default);
 
   /**

diff --git a/cpp/src/join/hash_join.cu b/cpp/src/join/hash_join.cu
@@ -198,18 +198,21 @@ get_left_join_indices_complement(rmm::device_vector<size_type> &right_indices,
  * @throw std::out_of_range if elements of `build_on` exceed the number of columns in the `build`
  * table.
  *
- * @param build_table Table of build side columns to join.
+ * @param build Table of columns used to build join hash.
+ * @param compare_nulls Controls whether null join-key values should match or not.
  * @param stream CUDA stream used for device memory operations and kernel launches.
  *
  * @return Built hash table.
  */
 std::unique_ptr<multimap_type, std::function<void(multimap_type *)>> build_join_hash_table(
-  cudf::table_device_view build_table, rmm::cuda_stream_view stream)
+  cudf::table_view const &build, null_equality compare_nulls, rmm::cuda_stream_view stream)
 {
-  CUDF_EXPECTS(0 != build_table.num_columns(), "Selected build dataset is empty");
-  CUDF_EXPECTS(0 != build_table.num_rows(), "Build side table has no rows");
+  auto build_device_table = cudf::table_device_view::create(build, stream);
 
-  const size_type build_table_num_rows{build_table.num_rows()};
+  CUDF_EXPECTS(0 != build_device_table->num_columns(), "Selected build dataset is empty");
+  CUDF_EXPECTS(0 != build_device_table->num_rows(), "Build side table has no rows");
+
+  size_type const build_table_num_rows{build_device_table->num_rows()};
   size_t const hash_table_size = compute_hash_table_size(build_table_num_rows);
 
   auto hash_table = multimap_type::create(hash_table_size,
@@ -219,12 +222,19 @@ std::unique_ptr<multimap_type, std::function<void(multimap_type *)>> build_join_
                                           multimap_type::key_equal(),
                                           multimap_type::allocator_type());
 
-  row_hash hash_build{build_table};
+  row_hash hash_build{*build_device_table};
   rmm::device_scalar<int> failure(0, stream);
   constexpr int block_size{DEFAULT_JOIN_BLOCK_SIZE};
   detail::grid_1d config(build_table_num_rows, block_size);
+  auto const row_bitmask = (compare_nulls == null_equality::EQUAL)
+                             ? rmm::device_buffer{0, stream}
+                             : cudf::detail::bitmask_and(build, stream);
   build_hash_table<<<config.num_blocks, config.num_threads_per_block, 0, stream.value()>>>(
-    *hash_table, hash_build, build_table_num_rows, failure.data());
+    *hash_table,
+    hash_build,
+    build_table_num_rows,
+    static_cast<bitmask_type const *>(row_bitmask.data()),
+    failure.data());
   // Check error code from the kernel
   if (failure.value(stream) == 1) { CUDF_FAIL("Hash Table insert failure."); }
 
@@ -488,6 +498,7 @@ hash_join::hash_join_impl::~hash_join_impl() = default;
 
 hash_join::hash_join_impl::hash_join_impl(cudf::table_view const &build,
                                           std::vector<size_type> const &build_on,
+                                          null_equality compare_nulls,
                                           rmm::cuda_stream_view stream)
   : _build(build),
     _build_selected(build.select(build_on)),
@@ -501,8 +512,7 @@ hash_join::hash_join_impl::hash_join_impl(cudf::table_view const &build,
 
   if (_build_on.empty() || 0 == build.num_rows()) { return; }
 
-  auto build_table = cudf::table_device_view::create(_build_selected, stream);
-  _hash_table      = build_join_hash_table(*build_table, stream);
+  _hash_table = build_join_hash_table(_build_selected, compare_nulls, stream);
 }
 
 std::pair<std::unique_ptr<cudf::table>, std::unique_ptr<cudf::table>>

diff --git a/cpp/src/join/hash_join.cuh b/cpp/src/join/hash_join.cuh
@@ -224,9 +224,11 @@ struct hash_join::hash_join_impl {
    *
    * @param build The build table, from which the hash table is built.
    * @param build_on The column indices from `build` to join on.
+   * @param compare_nulls Controls whether null join-key values should match or not.
    */
   hash_join_impl(cudf::table_view const& build,
                  std::vector<size_type> const& build_on,
+                 null_equality compare_nulls,
                  rmm::cuda_stream_view stream = rmm::cuda_stream_default);
 
   std::pair<std::unique_ptr<cudf::table>, std::unique_ptr<cudf::table>> inner_join(

diff --git a/cpp/src/join/join.cu b/cpp/src/join/join.cu
@@ -51,7 +51,7 @@ std::unique_ptr<table> inner_join(
   // building/probing the hash map. Because building is typically more expensive than probing, we
   // build the hash map from the smaller table.
   if (right.num_rows() > left.num_rows()) {
-    cudf::hash_join hj_obj(left, left_on, stream);
+    cudf::hash_join hj_obj(left, left_on, compare_nulls, stream);
     auto actual_columns_in_common = columns_in_common;
     std::for_each(actual_columns_in_common.begin(), actual_columns_in_common.end(), [](auto& pair) {
       std::swap(pair.first, pair.second);
@@ -66,7 +66,7 @@ std::unique_ptr<table> inner_join(
     return cudf::detail::combine_table_pair(std::move(probe_build_pair.second),
                                             std::move(probe_build_pair.first));
   } else {
-    cudf::hash_join hj_obj(right, right_on, stream);
+    cudf::hash_join hj_obj(right, right_on, compare_nulls, stream);
     auto probe_build_pair = hj_obj.inner_join(left,
                                               left_on,
                                               columns_in_common,
@@ -99,7 +99,7 @@ std::unique_ptr<table> left_join(
   table_view const left  = scatter_columns(matched.second.front(), left_on, left_input);
   table_view const right = scatter_columns(matched.second.back(), right_on, right_input);
 
-  cudf::hash_join hj_obj(right, right_on, stream);
+  cudf::hash_join hj_obj(right, right_on, compare_nulls, stream);
   return hj_obj.left_join(left, left_on, columns_in_common, compare_nulls, stream, mr);
 }
 
@@ -123,7 +123,7 @@ std::unique_ptr<table> full_join(
   table_view const left  = scatter_columns(matched.second.front(), left_on, left_input);
   table_view const right = scatter_columns(matched.second.back(), right_on, right_input);
 
-  cudf::hash_join hj_obj(right, right_on, stream);
+  cudf::hash_join hj_obj(right, right_on, compare_nulls, stream);
   return hj_obj.full_join(left, left_on, columns_in_common, compare_nulls, stream, mr);
 }
 
@@ -133,8 +133,9 @@ hash_join::~hash_join() = default;
 
 hash_join::hash_join(cudf::table_view const& build,
                      std::vector<size_type> const& build_on,
+                     null_equality compare_nulls,
                      rmm::cuda_stream_view stream)
-  : impl{std::make_unique<const hash_join::hash_join_impl>(build, build_on, stream)}
+  : impl{std::make_unique<const hash_join::hash_join_impl>(build, build_on, compare_nulls, stream)}
 {
 }
 

diff --git a/cpp/src/join/join_kernels.cuh b/cpp/src/join/join_kernels.cuh
@@ -17,6 +17,7 @@
 #pragma once
 
 #include <cub/cub.cuh>
+#include <cudf/detail/null_mask.hpp>
 #include <cudf/detail/utilities/cuda.cuh>
 #include <cudf/table/table_device_view.cuh>
 
@@ -71,28 +72,33 @@ constexpr auto remap_sentinel_hash(H hash, S sentinel)
  * @param[in,out] multi_map The hash table to be built to insert rows into
  * @param[in] hash_build Row hasher for the build table
  * @param[in] build_table_num_rows The number of rows in the build table
+ * @param[in] row_bitmask Bitmask where bit `i` indicates the presence of a null
+ * value in row `i` of input keys. This is nullptr if nulls are equal.
  * @param[out] error Pointer used to set an error code if the insert fails
  */
 template <typename multimap_type>
 __global__ void build_hash_table(multimap_type multi_map,
                                  row_hash hash_build,
                                  const cudf::size_type build_table_num_rows,
+                                 bitmask_type const* row_bitmask,
                                  int* error)
 {
   cudf::size_type i = threadIdx.x + blockIdx.x * blockDim.x;
 
   while (i < build_table_num_rows) {
-    // Compute the hash value of this row
-    auto const row_hash_value = remap_sentinel_hash(hash_build(i), multi_map.get_unused_key());
-
-    // Insert the (row hash value, row index) into the map
-    // using the row hash value to determine the location in the
-    // hash map where the new pair should be inserted
-    const auto insert_location =
-      multi_map.insert(thrust::make_pair(row_hash_value, i), true, row_hash_value);
-
-    // If the insert failed, set the error code accordingly
-    if (multi_map.end() == insert_location) { *error = 1; }
+    if (!row_bitmask || cudf::bit_is_set(row_bitmask, i)) {
+      // Compute the hash value of this row
+      auto const row_hash_value = remap_sentinel_hash(hash_build(i), multi_map.get_unused_key());
+
+      // Insert the (row hash value, row index) into the map
+      // using the row hash value to determine the location in the
+      // hash map where the new pair should be inserted
+      auto const insert_location =
+        multi_map.insert(thrust::make_pair(row_hash_value, i), true, row_hash_value);
+
+      // If the insert failed, set the error code accordingly
+      if (multi_map.end() == insert_location) { *error = 1; }
+    }
     i += blockDim.x * gridDim.x;
   }
 }

diff --git a/cpp/tests/join/join_tests.cpp b/cpp/tests/join/join_tests.cpp
@@ -1120,7 +1120,7 @@ TEST_F(JoinTest, HashJoinSequentialProbes)
 
   Table t1(std::move(cols1));
 
-  cudf::hash_join hash_join(t1, {0, 1});
+  cudf::hash_join hash_join(t1, {0, 1}, cudf::null_equality::EQUAL);
 
   {
     CVector cols0;