Add to_arrow_device() functions that accept views (#15465)

Adds the following new interop functions
```
unique_device_array_t to_arrow_device(cudf::table_view const& table, 
                                      rmm::cuda_stream_view stream,
                                      rmm::device_async_resource_ref mr);
unique_device_array_t to_arrow_device(cudf::column_view const& col, 
                                      rmm::cuda_stream_view stream,
                                      rmm::device_async_resource_ref mr);
```
Also refactors some common code with the ownership transfer version of these APIs.
And moves the `to_arrow_schema()` functions to a separate .cpp file.

Authors:
  - David Wendt (https://github.com/davidwendt)

Approvers:
  - Matt Topol (https://github.com/zeroshade)
  - Nghia Truong (https://github.com/ttnghia)
  - Vyas Ramasubramani (https://github.com/vyasr)

URL: #15465

cpp/CMakeLists.txt

@@ -359,6 +359,8 @@ add_library(
   src/interop/from_arrow.cu
   src/interop/to_arrow.cu
   src/interop/to_arrow_device.cu
+  src/interop/to_arrow_schema.cpp
+  src/interop/to_arrow_utilities.cpp
   src/interop/detail/arrow_allocator.cpp
   src/io/avro/avro.cpp
   src/io/avro/avro_gpu.cu

cpp/include/cudf/interop.hpp

@@ -258,6 +258,70 @@ unique_device_array_t to_arrow_device(
   rmm::cuda_stream_view stream      = cudf::get_default_stream(),
   rmm::device_async_resource_ref mr = rmm::mr::get_current_device_resource());
 
+/**
+ * @brief Create `ArrowDeviceArray` from a table view
+ *
+ * Populates the C struct ArrowDeviceArray performing copies only if necessary.
+ * This wraps the data on the GPU device and gives a view of the table data
+ * to the ArrowDeviceArray struct. If the caller frees the data referenced by
+ * the table_view, using the returned object results in undefined behavior.
+ *
+ * After calling this function, the release callback on the returned ArrowDeviceArray
+ * must be called to clean up any memory created during conversion.
+ *
+ * @note For decimals, since the precision is not stored for them in libcudf
+ * it will be converted to an Arrow decimal128 with the widest-precision the cudf decimal type
+ * supports. For example, numeric::decimal32 will be converted to Arrow decimal128 of the precision
+ * 9 which is the maximum precision for 32-bit types. Similarly, numeric::decimal128 will be
+ * converted to Arrow decimal128 of the precision 38.
+ *
+ * Copies will be performed in the cases where cudf differs from Arrow:
+ * - BOOL8: Arrow uses a bitmap and cudf uses 1 byte per value
+ * - DECIMAL32 and DECIMAL64: Converted to Arrow decimal128
+ * - STRING: Arrow expects a single value int32 offset child array for empty strings columns
+ *
+ * @param table Input table
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ * @param mr Device memory resource used for any allocations during conversion
+ * @return ArrowDeviceArray which will have ownership of any copied data
+ */
+unique_device_array_t to_arrow_device(
+  cudf::table_view const& table,
+  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
+  rmm::device_async_resource_ref mr = rmm::mr::get_current_device_resource());
+
+/**
+ * @brief Create `ArrowDeviceArray` from a column view
+ *
+ * Populates the C struct ArrowDeviceArray performing copies only if necessary.
+ * This wraps the data on the GPU device and gives a view of the column data
+ * to the ArrowDeviceArray struct. If the caller frees the data referenced by
+ * the column_view, using the returned object results in undefined behavior.
+ *
+ * After calling this function, the release callback on the returned ArrowDeviceArray
+ * must be called to clean up any memory created during conversion.
+ *
+ * @note For decimals, since the precision is not stored for them in libcudf
+ * it will be converted to an Arrow decimal128 with the widest-precision the cudf decimal type
+ * supports. For example, numeric::decimal32 will be converted to Arrow decimal128 of the precision
+ * 9 which is the maximum precision for 32-bit types. Similar, numeric::decimal128 will be
+ * converted to Arrow decimal128 of the precision 38.
+ *
+ * Copies will be performed in the cases where cudf differs from Arrow:
+ * - BOOL8: Arrow uses a bitmap and cudf uses 1 byte per value
+ * - DECIMAL32 and DECIMAL64: Converted to Arrow decimal128
+ * - STRING: Arrow expects a single value int32 offset child array for empty strings columns
+ *
+ * @param col Input column
+ * @param stream CUDA stream used for device memory operations and kernel launches
+ * @param mr Device memory resource used for any allocations during conversion
+ * @return ArrowDeviceArray which will have ownership of any copied data
+ */
+unique_device_array_t to_arrow_device(
+  cudf::column_view const& col,
+  rmm::cuda_stream_view stream      = cudf::get_default_stream(),
+  rmm::device_async_resource_ref mr = rmm::mr::get_current_device_resource());
+
 /**
  * @brief Create `cudf::table` from given arrow Table input
  *
@@ -266,7 +330,6 @@ unique_device_array_t to_arrow_device(
  * @param mr    Device memory resource used to allocate `cudf::table`
  * @return cudf table generated from given arrow Table
  */
-
 std::unique_ptr<table> from_arrow(
   arrow::Table const& input,
   rmm::cuda_stream_view stream      = cudf::get_default_stream(),
@@ -280,7 +343,6 @@ std::unique_ptr<table> from_arrow(
  * @param mr    Device memory resource used to allocate `cudf::scalar`
  * @return cudf scalar generated from given arrow Scalar
  */
-
 std::unique_ptr<cudf::scalar> from_arrow(
   arrow::Scalar const& input,
   rmm::cuda_stream_view stream      = cudf::get_default_stream(),