Struct to string casting functionality

docs/supported_ops.md

@@ -18175,7 +18175,7 @@ and the accelerator produces the same result.
 <td> </td>
 <td> </td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS (the struct's children must also support being cast to string)</em></td>
 <td> </td>
 <td> </td>
 <td> </td>
@@ -18579,7 +18579,7 @@ and the accelerator produces the same result.
 <td> </td>
 <td> </td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS (the struct's children must also support being cast to string)</em></td>
 <td> </td>
 <td> </td>
 <td> </td>

integration_tests/src/main/python/struct_test.py

@@ -57,3 +57,63 @@ def test_orderby_struct_2(data_gen):
         lambda spark : append_unique_int_col_to_df(spark, unary_op_df(spark, data_gen)),
         'struct_table',
         'select struct_table.a, struct_table.uniq_int from struct_table order by uniq_int')
+
+# conf with legacy cast to string on
+legacy_complex_types_to_string = {'spark.sql.legacy.castComplexTypesToString.enabled': 'true'}
+@pytest.mark.parametrize('data_gen', [StructGen([["first", boolean_gen], ["second", byte_gen], ["third", short_gen], ["fourth", int_gen], ["fifth", long_gen], ["sixth", string_gen], ["seventh", date_gen]])], ids=idfn)
+def test_legacy_cast_struct_to_string(data_gen):
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark : unary_op_df(spark, data_gen).select(
+            f.col('a').cast("STRING")),
+            conf = legacy_complex_types_to_string)
+
+@pytest.mark.parametrize('data_gen', [StructGen([["first", float_gen]])], ids=idfn)
+@pytest.mark.xfail(reason='casting float to string is not an exact match')
+def test_legacy_cast_struct_with_float_to_string(data_gen):
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark : unary_op_df(spark, data_gen).select(
+            f.col('a').cast("STRING")),
+            conf = legacy_complex_types_to_string)
+
+@pytest.mark.parametrize('data_gen', [StructGen([["first", double_gen]])], ids=idfn)
+@pytest.mark.xfail(reason='casting double to string is not an exact match')
+def test_legacy_cast_struct_with_double_to_string(data_gen):
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark : unary_op_df(spark, data_gen).select(
+            f.col('a').cast("STRING")),
+            conf = legacy_complex_types_to_string)
+
+@pytest.mark.parametrize('data_gen', [StructGen([["first", timestamp_gen]])], ids=idfn)
+@pytest.mark.xfail(reason='https://github.com/NVIDIA/spark-rapids/issues/219')
+def test_legacy_cast_struct_with_timestamp_to_string(data_gen):
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark : unary_op_df(spark, data_gen).select(
+            f.col('a').cast("STRING")),
+            conf = legacy_complex_types_to_string)
+
+@pytest.mark.parametrize('data_gen', [StructGen([["first", boolean_gen], ["second", byte_gen], ["third", short_gen], ["fourth", int_gen], ["fifth", long_gen], ["sixth", string_gen], ["seventh", date_gen]])], ids=idfn)
+def test_cast_struct_to_string(data_gen):
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark : unary_op_df(spark, data_gen).select(
+            f.col('a').cast("STRING")))
+
+@pytest.mark.parametrize('data_gen', [StructGen([["first", float_gen]])], ids=idfn)
+@pytest.mark.xfail(reason='casting float to string is not an exact match')
+def test_cast_struct_with_float_to_string(data_gen):
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark : unary_op_df(spark, data_gen).select(
+            f.col('a').cast("STRING")))
+
+@pytest.mark.parametrize('data_gen', [StructGen([["first", double_gen]])], ids=idfn)
+@pytest.mark.xfail(reason='casting double to string is not an exact match')
+def test_cast_struct_with_double_to_string(data_gen):
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark : unary_op_df(spark, data_gen).select(
+            f.col('a').cast("STRING")))
+
+@pytest.mark.parametrize('data_gen', [StructGen([["first", timestamp_gen]])], ids=idfn)
+@pytest.mark.xfail(reason='https://github.com/NVIDIA/spark-rapids/issues/219')
+def test_cast_struct_with_timestamp_to_string(data_gen):
+    assert_gpu_and_cpu_are_equal_collect(
+        lambda spark : unary_op_df(spark, data_gen).select(
+            f.col('a').cast("STRING")))

shims/spark300/src/main/scala/com/nvidia/spark/rapids/shims/spark300/Spark300Shims.scala

@@ -478,6 +478,8 @@ class Spark300Shims extends SparkShims {
     InMemoryFileIndex.shouldFilterOut(path)
   }
 
+  override def getLegacyComplexTypeToString(): Boolean = true
+
   // Arrow version changed between Spark versions
   override def getArrowDataBuf(vec: ValueVector): (ByteBuffer, ReferenceManager) = {
     val arrowBuf = vec.getDataBuffer()

shims/spark311/src/main/scala/com/nvidia/spark/rapids/shims/spark311/Spark311Shims.scala

@@ -424,6 +424,10 @@ class Spark311Shims extends Spark301Shims {
     HadoopFSUtilsShim.shouldIgnorePath(path)
   }
 
+  override def getLegacyComplexTypeToString(): Boolean = {
+    SQLConf.get.getConf(SQLConf.LEGACY_COMPLEX_TYPES_TO_STRING)
+  }
+
   // Arrow version changed between Spark versions
   override def getArrowDataBuf(vec: ValueVector): (ByteBuffer, ReferenceManager) = {
     val arrowBuf = vec.getDataBuffer()

sql-plugin/src/main/scala/com/nvidia/spark/rapids/FloatUtils.scala

@@ -16,11 +16,11 @@
 
 package com.nvidia.spark.rapids
 
-import ai.rapids.cudf.{ColumnVector, DType, Scalar}
+import ai.rapids.cudf.{ColumnVector, ColumnView, DType, Scalar}
 
 object FloatUtils extends Arm {
 
-  def nanToZero(cv: ColumnVector): ColumnVector = {
+  def nanToZero(cv: ColumnView): ColumnVector = {
     if (cv.getType() != DType.FLOAT32 && cv.getType() != DType.FLOAT64) {
       throw new IllegalArgumentException("Only Floats and Doubles allowed")
     }