Example to build custom application and link to libcudf

cpp/example/4stock_5day.csv

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+Company,Date,Open,High,Low,Close,Volume
+MSFT,2021-03-03,232.16000366210938,233.5800018310547,227.25999450683594,227.55999755859375,33950400.0
+MSFT,2021-03-04,226.74000549316406,232.49000549316406,224.25999450683594,226.72999572753906,44584200.0
+MSFT,2021-03-05,229.52000427246094,233.27000427246094,226.4600067138672,231.60000610351562,41842100.0
+MSFT,2021-03-08,231.3699951171875,233.3699951171875,227.1300048828125,227.38999938964844,35245900.0
+MSFT,2021-03-09,232.8800048828125,235.3800048828125,231.6699981689453,233.77999877929688,33034000.0
+GOOG,2021-03-03,2067.2099609375,2088.51806640625,2010.0,2026.7099609375,1483100.0
+GOOG,2021-03-04,2023.3699951171875,2089.239990234375,2020.27001953125,2049.090087890625,2116100.0
+GOOG,2021-03-05,2073.1201171875,2118.110107421875,2046.4150390625,2108.5400390625,2193800.0
+GOOG,2021-03-08,2101.1298828125,2128.81005859375,2021.6099853515625,2024.1700439453125,1646000.0
+GOOG,2021-03-09,2070.0,2078.0400390625,2047.8299560546875,2052.699951171875,1696400.0
+AMZN,2021-03-03,3081.179931640625,3107.780029296875,2995.0,3005.0,3967200.0
+AMZN,2021-03-04,3012.0,3058.1298828125,2945.429931640625,2977.570068359375,5458700.0
+AMZN,2021-03-05,3005.0,3009.0,2881.0,3000.4599609375,5383400.0
+AMZN,2021-03-08,3015.0,3064.590087890625,2951.31005859375,2951.949951171875,4178500.0
+AMZN,2021-03-09,3017.989990234375,3090.9599609375,3005.14990234375,3062.85009765625,4023500.0
+AAPL,2021-03-03,124.80999755859375,125.70999908447266,121.83999633789062,122.05999755859375,112430400.0
+AAPL,2021-03-04,121.75,123.5999984741211,118.62000274658203,120.12999725341797,177275300.0
+AAPL,2021-03-05,120.9800033569336,121.94000244140625,117.56999969482422,121.41999816894531,153590400.0
+AAPL,2021-03-08,120.93000030517578,121.0,116.20999908447266,116.36000061035156,153918600.0
+AAPL,2021-03-09,119.02999877929688,122.05999755859375,118.79000091552734,121.08999633789062,129159600.0

cpp/example/CMakeLists.txt

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+cmake_minimum_required(VERSION 3.18)
+
+project(libcudf_example VERSION 0.0.1 LANGUAGES C CXX CUDA)
+
+set(CMAKE_CXX_STANDARD 14)
+set(CMAKE_CUDA_ARCHITECTURES "")
+set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
+
+set(CPM_DOWNLOAD_VERSION 0.27.2) 
+set(CPM_DOWNLOAD_LOCATION "${CMAKE_BINARY_DIR}/cmake/CPM_${CPM_DOWNLOAD_VERSION}.cmake")
+
+if(NOT (EXISTS ${CPM_DOWNLOAD_LOCATION}))
+    message(STATUS "Downloading CPM.cmake")
+    file(DOWNLOAD https://github.com/TheLartians/CPM.cmake/releases/download/v${CPM_DOWNLOAD_VERSION}/CPM.cmake ${CPM_DOWNLOAD_LOCATION})
+endif()
+
+include(${CPM_DOWNLOAD_LOCATION})
+
+CPMAddPackage(NAME  cudf
+    GIT_REPOSITORY  https://github.com/rapidsai/cudf
+    GIT_TAG         branch-0.19
+    GIT_SHALLOW     TRUE
+    SOURCE_SUBDIR   cpp
+    OPTIONS         "BUILD_TESTS OFF"
+                    "BUILD_BENCHMARKS OFF"
+                    "ARROW_STATIC_LIB ON"
+                    "JITIFY_USE_CACHE ON"
+                    "CUDA_STATIC_RUNTIME ON"
+                    "DISABLE_DEPRECATION_WARNING ON"
+)
+
+# Configure your project here
+add_executable(${PROJECT_NAME} "src/process_csv.cpp")
+target_link_libraries(${PROJECT_NAME} cudf::cudf)

cpp/example/Dockerfile

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+FROM nvidia/cuda:11.1.1-devel-ubuntu18.04
+ARG PARALLEL_LEVEL=8
+
+# Install basic cudf dependencies
+RUN GCC_VERSION=9 \
+ && apt update -y \
+ && apt install -y software-properties-common \
+ && add-apt-repository -y ppa:git-core/ppa \
+ && add-apt-repository -y ppa:ubuntu-toolchain-r/test \
+ && apt install -y \
+    gcc-${GCC_VERSION} g++-${GCC_VERSION} \
+    git nano sudo wget ninja-build bash-completion \
+    # CMake dependencies
+    curl libssl-dev libcurl4-openssl-dev zlib1g-dev \
+    # cuDF dependencies
+    libboost-filesystem-dev \
+ && apt autoremove -y \
+ && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* \
+ # Remove any existing gcc and g++ alternatives
+ && update-alternatives --remove-all cc  >/dev/null 2>&1 || true \
+ && update-alternatives --remove-all c++ >/dev/null 2>&1 || true \
+ && update-alternatives --remove-all gcc >/dev/null 2>&1 || true \
+ && update-alternatives --remove-all g++ >/dev/null 2>&1 || true \
+ && update-alternatives --remove-all gcov >/dev/null 2>&1 || true \
+ && update-alternatives \
+    --install /usr/bin/gcc gcc /usr/bin/gcc-${GCC_VERSION} 100 \
+    --slave /usr/bin/cc cc /usr/bin/gcc-${GCC_VERSION} \
+    --slave /usr/bin/g++ g++ /usr/bin/g++-${GCC_VERSION} \
+    --slave /usr/bin/c++ c++ /usr/bin/g++-${GCC_VERSION} \
+    --slave /usr/bin/gcov gcov /usr/bin/gcov-${GCC_VERSION} \
+ # Set gcc-${GCC_VERSION} as the default gcc
+ && update-alternatives --set gcc /usr/bin/gcc-${GCC_VERSION}
+
+ARG CMAKE_VERSION=3.18.5
+
+# Install CMake
+RUN cd /tmp \
+ && curl -fsSLO --compressed "https://github.com/Kitware/CMake/releases/download/v$CMAKE_VERSION/cmake-$CMAKE_VERSION.tar.gz" -o /tmp/cmake-$CMAKE_VERSION.tar.gz \
+ && tar -xvzf /tmp/cmake-$CMAKE_VERSION.tar.gz && cd /tmp/cmake-$CMAKE_VERSION \
+ && /tmp/cmake-$CMAKE_VERSION/bootstrap \
+    --system-curl \
+    --parallel=$PARALLEL_LEVEL \
+ && make install -j$PARALLEL_LEVEL \
+ && cd /tmp && rm -rf /tmp/cmake-$CMAKE_VERSION*
+
+ENV CUDA_HOME="/usr/local/cuda"
+
+RUN mkdir -p /workspace
+WORKDIR /workspace

cpp/example/README.md

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+# Basic Standalone libcudf C++ application
+
+This simple C++ example demonstrates a basic libcudf use case and provides a
+minimal example of building your own application based on libcudf using CMake.
+
+The example source code loads a csv file that contains stock prices from 4
+companies spanning across 5 days, computes the average of the closing price
+for each company and writes the result in csv format.
+
+## How to compile and execute
+
+The compilation process is automated by a Dockerfile included in the project.
+
+Prerequisites:
+- docker (API >= 1.40 to support --gpus)
+- nvidia driver >= 450.80.02 (to support cudatoolkit 11.1)
+
+### Step 1: build environment in docker
+```bash
+docker build . -t rapidsenv
+```
+
+### Step 2: start the container
+```bash
+docker run -t -d -v $PWD:/workspace --gpus all --name rapidsenvrt rapidsenv
+```
+
+### (When active container running) Configure project
+```bash
+docker exec rapidsenvrt sh -c "cmake -S . -B build/"
+```
+
+### (When active container running) Build project
+```bash
+docker exec rapidsenvrt sh -c "cmake --build build/ --parallel $PARALLEL_LEVEL"
+```
+The first time running this command will take a long time because it will build
+libcudf on the host machine. It may be sped up by configuring the proper
+`PARALLEL_LEVEL` number.
+
+### (When active container running) Execute binary
+```bash
+docker exec rapidsenvrt sh -c "build/libcudf_example"
+```

cpp/example/src/process_csv.cpp

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+#include <cudf/aggregation.hpp>
+#include <cudf/groupby.hpp>
+#include <cudf/io/csv.hpp>
+#include <cudf/table/table.hpp>
+
+#include <rmm/mr/device/cuda_memory_resource.hpp>
+#include <rmm/mr/device/per_device_resource.hpp>
+
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+std::unique_ptr<cudf::table> read_csv(std::string const& file_path)
+{
+  auto source_info    = cudf::io::source_info(file_path);
+  auto builder        = cudf::io::csv_reader_options::builder(source_info);
+  auto options        = builder.build();
+  auto data_with_meta = cudf::io::read_csv(options);
+  return std::move(data_with_meta.tbl);
+}
+
+void write_csv(cudf::table_view const& tbl_view, std::string const& file_path)
+{
+  auto sink_info = cudf::io::sink_info(file_path);
+  auto builder   = cudf::io::csv_writer_options::builder(sink_info, tbl_view);
+  auto options   = builder.build();
+  cudf::io::write_csv(options);
+}
+
+std::unique_ptr<cudf::table> average_closing_price(cudf::table_view stock_info_table)
+{
+  // Schema: | Company | Date | Open | High | Low | Close | Volume |
+  auto keys = cudf::table_view{{stock_info_table.column(0)}};  // Company
+  auto val  = stock_info_table.column(5);                      // Close
+
+  // Compute the average of each company's closing price with entire column
+  cudf::groupby::groupby grpby_obj(keys);
+  cudf::groupby::aggregation_request agg_request{val, {}};
+  agg_request.aggregations.push_back(cudf::make_mean_aggregation());
+  std::vector<cudf::groupby::aggregation_request> requests;
+  requests.push_back(std::move(agg_request));
+
+  auto agg_results = grpby_obj.aggregate(requests);
+
+  // Assemble the result
+  auto result_key = std::move(agg_results.first);
+  auto result_val = std::move(agg_results.second[0].results[0]);
+  std::vector<cudf::column_view> columns{result_key->get_column(0), *result_val};
+  return std::make_unique<cudf::table>(cudf::table_view(columns));
+}
+
+int main(int argc, char** argv)
+{
+  // Init cuda memory resource
+  rmm::mr::cuda_memory_resource cuda_mr;
+  rmm::mr::set_current_device_resource(&cuda_mr);
+
+  // Read data
+  auto stock_info_table = read_csv("4stock_5day.csv");
+
+  // Process
+  auto result = average_closing_price(*stock_info_table);
+
+  // Write out result
+  write_csv(*result, "4stock_5day_avg_close.csv");
+
+  return 0;
+}