Add cudf::strings::contains_multiple

cpp/CMakeLists.txt

@@ -664,6 +664,7 @@ add_library(
   src/strings/replace/replace_slice.cu
   src/strings/reverse.cu
   src/strings/scan/scan_inclusive.cu
+  src/strings/search/contains_multiple.cu
   src/strings/search/findall.cu
   src/strings/search/find.cu
   src/strings/search/find_multiple.cu

cpp/benchmarks/CMakeLists.txt

@@ -380,6 +380,7 @@ ConfigureNVBench(
   string/count.cpp
   string/extract.cpp
   string/find.cpp
+  string/find_multiple.cpp
   string/gather.cpp
   string/join_strings.cpp
   string/lengths.cpp

cpp/benchmarks/string/find.cpp

@@ -19,11 +19,8 @@
 
 #include <cudf_test/column_wrapper.hpp>
 
-#include <cudf/filling.hpp>
 #include <cudf/scalar/scalar.hpp>
-#include <cudf/strings/combine.hpp>
 #include <cudf/strings/find.hpp>
-#include <cudf/strings/find_multiple.hpp>
 #include <cudf/strings/strings_column_view.hpp>
 #include <cudf/utilities/default_stream.hpp>
 
@@ -49,15 +46,13 @@ static void bench_find_string(nvbench::state& state)
   auto const col    = build_input_column(n_rows, row_width, hit_rate);
   auto const input  = cudf::strings_column_view(col->view());
 
-  std::vector<std::string> h_targets({"5W", "5W43", "0987 5W43"});
-  cudf::string_scalar target(h_targets[2]);
-  cudf::test::strings_column_wrapper targets(h_targets.begin(), h_targets.end());
+  cudf::string_scalar target("0987 5W43");
 
   state.set_cuda_stream(nvbench::make_cuda_stream_view(stream.value()));
   auto const chars_size = input.chars_size(stream);
   state.add_element_count(chars_size, "chars_size");
   state.add_global_memory_reads<nvbench::int8_t>(chars_size);
-  if (api.substr(0, 4) == "find") {
+  if (api == "find") {
     state.add_global_memory_writes<nvbench::int32_t>(input.size());
   } else {
     state.add_global_memory_writes<nvbench::int8_t>(input.size());
@@ -66,10 +61,6 @@ static void bench_find_string(nvbench::state& state)
   if (api == "find") {
     state.exec(nvbench::exec_tag::sync,
                [&](nvbench::launch& launch) { cudf::strings::find(input, target); });
-  } else if (api == "find_multi") {
-    state.exec(nvbench::exec_tag::sync, [&](nvbench::launch& launch) {
-      cudf::strings::find_multiple(input, cudf::strings_column_view(targets));
-    });
   } else if (api == "contains") {
     state.exec(nvbench::exec_tag::sync,
                [&](nvbench::launch& launch) { cudf::strings::contains(input, target); });
@@ -84,7 +75,7 @@ static void bench_find_string(nvbench::state& state)
 
 NVBENCH_BENCH(bench_find_string)
   .set_name("find_string")
-  .add_string_axis("api", {"find", "find_multi", "contains", "starts_with", "ends_with"})
+  .add_string_axis("api", {"find", "contains", "starts_with", "ends_with"})
   .add_int64_axis("row_width", {32, 64, 128, 256, 512, 1024})
   .add_int64_axis("num_rows", {260'000, 1'953'000, 16'777'216})
   .add_int64_axis("hit_rate", {20, 80});  // percentage

cpp/benchmarks/string/find_multiple.cpp

@@ -0,0 +1,86 @@
+/*
+ * Copyright (c) 2021-2024, 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 <benchmarks/common/generate_input.hpp>
+#include <benchmarks/fixture/benchmark_fixture.hpp>
+
+#include <cudf_test/column_wrapper.hpp>
+
+#include <cudf/strings/find.hpp>
+#include <cudf/strings/find_multiple.hpp>
+#include <cudf/strings/strings_column_view.hpp>
+#include <cudf/utilities/default_stream.hpp>
+
+#include <nvbench/nvbench.cuh>
+
+std::unique_ptr<cudf::column> build_input_column(cudf::size_type n_rows,
+                                                 cudf::size_type row_width,
+                                                 int32_t hit_rate);
+
+static void bench_find_string(nvbench::state& state)
+{
+  auto const n_rows       = static_cast<cudf::size_type>(state.get_int64("num_rows"));
+  auto const row_width    = static_cast<cudf::size_type>(state.get_int64("row_width"));
+  auto const hit_rate     = static_cast<cudf::size_type>(state.get_int64("hit_rate"));
+  auto const target_count = static_cast<cudf::size_type>(state.get_int64("targets"));
+  auto const api          = state.get_string("api");
+
+  if (static_cast<std::size_t>(n_rows) * static_cast<std::size_t>(row_width) >=
+      static_cast<std::size_t>(std::numeric_limits<cudf::size_type>::max())) {
+    state.skip("Skip benchmarks greater than size_type limit");
+  }
+
+  auto const stream = cudf::get_default_stream();
+  auto const col    = build_input_column(n_rows, row_width, hit_rate);
+  auto const input  = cudf::strings_column_view(col->view());
+
+  // Note that these all match the first row of the raw_data in build_input_column.
+  // This is so the hit_rate can properly accounted for.
+  std::vector<std::string> target_data(
+    {" abc", "W43", "0987 5W43", "123 abc", "23 abc", "3 abc", "7 5W43", "87 5W43", "987 5W43"});
+  auto h_targets = std::vector<std::string>{};
+  for (cudf::size_type i = 0; i < target_count; i++) {
+    h_targets.emplace_back(target_data[i % target_data.size()]);
+  }
+  cudf::test::strings_column_wrapper targets(h_targets.begin(), h_targets.end());
+
+  state.set_cuda_stream(nvbench::make_cuda_stream_view(stream.value()));
+  auto const chars_size = input.chars_size(stream);
+  state.add_global_memory_reads<nvbench::int8_t>(chars_size);
+  if (api == "find") {
+    state.add_global_memory_writes<nvbench::int32_t>(input.size());
+  } else {
+    state.add_global_memory_writes<nvbench::int8_t>(input.size());
+  }
+
+  if (api == "find") {
+    state.exec(nvbench::exec_tag::sync, [&](nvbench::launch& launch) {
+      cudf::strings::find_multiple(input, cudf::strings_column_view(targets));
+    });
+  } else if (api == "contains") {
+    state.exec(nvbench::exec_tag::sync, [&](nvbench::launch& launch) {
+      cudf::strings::contains_multiple(input, cudf::strings_column_view(targets));
+    });
+  }
+}
+
+NVBENCH_BENCH(bench_find_string)
+  .set_name("find_multiple")
+  .add_string_axis("api", {"find", "contains"})
+  .add_int64_axis("targets", {10, 20, 40})
+  .add_int64_axis("row_width", {32, 64, 128, 256, 512, 1024})
+  .add_int64_axis("num_rows", {260'000, 1'953'000, 16'777'216})
+  .add_int64_axis("hit_rate", {20, 80});  // percentage

cpp/include/cudf/strings/find_multiple.hpp

@@ -28,8 +28,42 @@ namespace strings {
  */
 
 /**
- * @brief Returns a lists column with character position values where each
- * of the target strings are found in each string.
+ * @brief Searches for the given target strings within each string in the provided column
+ *
+ * Each column in the result table corresponds to the result for the target string at the same
+ * ordinal. i.e. 0th column is the BOOL8 column result for the 0th target string, 1th for 1th,
+ * etc.
+ *
+ * If the target is not found for a string, false is returned for that entry in the output column.
+ * If the target is an empty string, true is returned for all non-null entries in the output column.
+ *
+ * Any null input strings return corresponding null entries in the output columns.
+ *
+ * @code{.pseudo}
+ * input = ["a", "b", "c"]
+ * targets = ["a", "c"]
+ * output is a table with two boolean columns:
+ *   column 0: [true, false, false]
+ *   column 1: [false, false, true]
+ * @endcode
+ *
+ * @throw std::invalid_argument if `targets` is empty or contains nulls
+ *
+ * @param input Strings instance for this operation
+ * @param targets UTF-8 encoded strings to search for in each string in `input`
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ * @param mr Device memory resource used to allocate the returned column's device memory
+ * @return Table of BOOL8 columns
+ */
+std::unique_ptr<table> contains_multiple(
+  strings_column_view const& input,
+  strings_column_view const& targets,
+  rmm::cuda_stream_view stream        = cudf::get_default_stream(),
+  rmm::mr::device_memory_resource* mr = rmm::mr::get_current_device_resource());
+
+/**
+ * @brief Searches for the given target strings within each string in the provided column
+ * and returns the position the targets were found
  *
  * The size of the output column is `input.size()`.
  * Each row of the output column is of size `targets.size()`.
@@ -45,7 +79,7 @@ namespace strings {
  *           [-1,-1, 1 ]}  // for "def": "a" and "b" not found, "e" at  pos 1
  * @endcode
  *
- * @throw cudf::logic_error if `targets` is empty or contains nulls
+ * @throw std::invalid_argument if `targets` is empty or contains nulls
  *
  * @param input Strings instance for this operation
  * @param targets Strings to search for in each string