From c99a37fb804282565204fd1544d145177620c0a3 Mon Sep 17 00:00:00 2001
From: Bradley Dice <bdice@bradleydice.com>
Date: Thu, 23 Dec 2021 17:40:31 -0600
Subject: [PATCH] Remove deprecated method Series.hash_encode. (#9942)

This PR removes the deprecated method `Series.hash_encode`. Resolves #9475. Follows up on #9457, #9381.

This PR also removes libcudf code paths used solely for this Python method.

Users may replace code like `series.hash_encode(stop, use_name=False)` with `series.hash_values(method="murmur3") % stop`.

Authors:
  - Bradley Dice (https://github.com/bdice)

Approvers:
  - Ram (Ramakrishna Prabhu) (https://github.com/rgsl888prabhu)
  - Conor Hoekstra (https://github.com/codereport)

URL: https://github.com/rapidsai/cudf/pull/9942
---
 cpp/include/cudf/detail/hashing.hpp      | 14 ++---
 cpp/include/cudf/hashing.hpp             |  9 +--
 cpp/include/cudf/table/row_operators.cuh | 48 ---------------
 cpp/src/hash/hashing.cu                  |  6 +-
 cpp/src/hash/murmur_hash.cu              | 25 ++------
 cpp/tests/hashing/hash_test.cpp          | 50 +++++++--------
 docs/cudf/source/api_docs/series.rst     |  2 -
 python/cudf/cudf/_lib/cpp/hash.pxd       |  3 +-
 python/cudf/cudf/_lib/hash.pyx           |  4 +-
 python/cudf/cudf/core/frame.py           |  4 +-
 python/cudf/cudf/core/series.py          | 77 ------------------------
 python/cudf/cudf/tests/test_dataframe.py | 38 ------------
 12 files changed, 46 insertions(+), 234 deletions(-)

diff --git a/cpp/include/cudf/detail/hashing.hpp b/cpp/include/cudf/detail/hashing.hpp
index bd5c8a42a51..0fc807593fb 100644
--- a/cpp/include/cudf/detail/hashing.hpp
+++ b/cpp/include/cudf/detail/hashing.hpp
@@ -32,17 +32,15 @@ namespace detail {
  */
 std::unique_ptr<column> hash(
   table_view const& input,
-  hash_id hash_function                        = hash_id::HASH_MURMUR3,
-  cudf::host_span<uint32_t const> initial_hash = {},
-  uint32_t seed                                = 0,
-  rmm::cuda_stream_view stream                 = rmm::cuda_stream_default,
-  rmm::mr::device_memory_resource* mr          = rmm::mr::get_current_device_resource());
+  hash_id hash_function               = hash_id::HASH_MURMUR3,
+  uint32_t seed                       = 0,
+  rmm::cuda_stream_view stream        = rmm::cuda_stream_default,
+  rmm::mr::device_memory_resource* mr = rmm::mr::get_current_device_resource());
 
 std::unique_ptr<column> murmur_hash3_32(
   table_view const& input,
-  cudf::host_span<uint32_t const> initial_hash = {},
-  rmm::cuda_stream_view stream                 = rmm::cuda_stream_default,
-  rmm::mr::device_memory_resource* mr          = rmm::mr::get_current_device_resource());
+  rmm::cuda_stream_view stream        = rmm::cuda_stream_default,
+  rmm::mr::device_memory_resource* mr = rmm::mr::get_current_device_resource());
 
 std::unique_ptr<column> md5_hash(
   table_view const& input,
diff --git a/cpp/include/cudf/hashing.hpp b/cpp/include/cudf/hashing.hpp
index 6b281c3f7f4..cce05042917 100644
--- a/cpp/include/cudf/hashing.hpp
+++ b/cpp/include/cudf/hashing.hpp
@@ -31,8 +31,6 @@ namespace cudf {
  *
  * @param input The table of columns to hash.
  * @param hash_function The hash function enum to use.
- * @param initial_hash Optional host_span of initial hash values for each column.
- * If this span is empty then each element will be hashed as-is.
  * @param seed Optional seed value to use for the hash function.
  * @param mr Device memory resource used to allocate the returned column's device memory.
  *
@@ -40,10 +38,9 @@ namespace cudf {
  */
 std::unique_ptr<column> hash(
   table_view const& input,
-  hash_id hash_function                        = hash_id::HASH_MURMUR3,
-  cudf::host_span<uint32_t const> initial_hash = {},
-  uint32_t seed                                = DEFAULT_HASH_SEED,
-  rmm::mr::device_memory_resource* mr          = rmm::mr::get_current_device_resource());
+  hash_id hash_function               = hash_id::HASH_MURMUR3,
+  uint32_t seed                       = DEFAULT_HASH_SEED,
+  rmm::mr::device_memory_resource* mr = rmm::mr::get_current_device_resource());
 
 /** @} */  // end of group
 }  // namespace cudf
diff --git a/cpp/include/cudf/table/row_operators.cuh b/cpp/include/cudf/table/row_operators.cuh
index 0f3ca073380..32ddd1ef49a 100644
--- a/cpp/include/cudf/table/row_operators.cuh
+++ b/cpp/include/cudf/table/row_operators.cuh
@@ -539,52 +539,4 @@ class row_hasher {
   uint32_t _seed{DEFAULT_HASH_SEED};
 };
 
-/**
- * @brief Computes the hash value of a row in the given table, combined with an
- * initial hash value for each column.
- *
- * @tparam hash_function Hash functor to use for hashing elements.
- * @tparam Nullate A cudf::nullate type describing how to check for nulls.
- */
-template <template <typename> class hash_function, typename Nullate>
-class row_hasher_initial_values {
- public:
-  row_hasher_initial_values() = delete;
-  row_hasher_initial_values(Nullate has_nulls, table_device_view t, hash_value_type* initial_hash)
-    : _table{t}, _initial_hash(initial_hash), _has_nulls{has_nulls}
-  {
-  }
-
-  __device__ auto operator()(size_type row_index) const
-  {
-    auto hash_combiner = [](hash_value_type lhs, hash_value_type rhs) {
-      return hash_function<hash_value_type>{}.hash_combine(lhs, rhs);
-    };
-
-    // Hashes an element in a column and combines with an initial value
-    auto hasher = [=](size_type column_index) {
-      auto hash_value = cudf::type_dispatcher<dispatch_storage_type>(
-        _table.column(column_index).type(),
-        element_hasher<hash_function, Nullate>{_has_nulls},
-        _table.column(column_index),
-        row_index);
-
-      return hash_combiner(_initial_hash[column_index], hash_value);
-    };
-
-    // Hash each element and combine all the hash values together
-    return thrust::transform_reduce(thrust::seq,
-                                    thrust::make_counting_iterator(0),
-                                    thrust::make_counting_iterator(_table.num_columns()),
-                                    hasher,
-                                    hash_value_type{0},
-                                    hash_combiner);
-  }
-
- private:
-  table_device_view _table;
-  hash_value_type* _initial_hash;
-  Nullate _has_nulls;
-};
-
 }  // namespace cudf
diff --git a/cpp/src/hash/hashing.cu b/cpp/src/hash/hashing.cu
index 039652e0012..ac2f06c0ea3 100644
--- a/cpp/src/hash/hashing.cu
+++ b/cpp/src/hash/hashing.cu
@@ -88,13 +88,12 @@ std::unique_ptr<column> serial_murmur_hash3_32(table_view const& input,
 
 std::unique_ptr<column> hash(table_view const& input,
                              hash_id hash_function,
-                             cudf::host_span<uint32_t const> initial_hash,
                              uint32_t seed,
                              rmm::cuda_stream_view stream,
                              rmm::mr::device_memory_resource* mr)
 {
   switch (hash_function) {
-    case (hash_id::HASH_MURMUR3): return murmur_hash3_32(input, initial_hash, stream, mr);
+    case (hash_id::HASH_MURMUR3): return murmur_hash3_32(input, stream, mr);
     case (hash_id::HASH_MD5): return md5_hash(input, stream, mr);
     case (hash_id::HASH_SERIAL_MURMUR3):
       return serial_murmur_hash3_32<MurmurHash3_32>(input, seed, stream, mr);
@@ -108,12 +107,11 @@ std::unique_ptr<column> hash(table_view const& input,
 
 std::unique_ptr<column> hash(table_view const& input,
                              hash_id hash_function,
-                             cudf::host_span<uint32_t const> initial_hash,
                              uint32_t seed,
                              rmm::mr::device_memory_resource* mr)
 {
   CUDF_FUNC_RANGE();
-  return detail::hash(input, hash_function, initial_hash, seed, rmm::cuda_stream_default, mr);
+  return detail::hash(input, hash_function, seed, rmm::cuda_stream_default, mr);
 }
 
 }  // namespace cudf
diff --git a/cpp/src/hash/murmur_hash.cu b/cpp/src/hash/murmur_hash.cu
index a761d058180..bc8d3577513 100644
--- a/cpp/src/hash/murmur_hash.cu
+++ b/cpp/src/hash/murmur_hash.cu
@@ -29,7 +29,6 @@ namespace cudf {
 namespace detail {
 
 std::unique_ptr<column> murmur_hash3_32(table_view const& input,
-                                        cudf::host_span<uint32_t const> initial_hash,
                                         rmm::cuda_stream_view stream,
                                         rmm::mr::device_memory_resource* mr)
 {
@@ -44,24 +43,12 @@ std::unique_ptr<column> murmur_hash3_32(table_view const& input,
   auto const device_input = table_device_view::create(input, stream);
   auto output_view        = output->mutable_view();
 
-  // Compute the hash value for each row depending on the specified hash function
-  if (!initial_hash.empty()) {
-    CUDF_EXPECTS(initial_hash.size() == size_t(input.num_columns()),
-                 "Expected same size of initial hash values as number of columns");
-    auto device_initial_hash = make_device_uvector_async(initial_hash, stream);
-
-    thrust::tabulate(rmm::exec_policy(stream),
-                     output_view.begin<int32_t>(),
-                     output_view.end<int32_t>(),
-                     row_hasher_initial_values<MurmurHash3_32, nullate::DYNAMIC>(
-                       nullate::DYNAMIC{nullable}, *device_input, device_initial_hash.data()));
-  } else {
-    thrust::tabulate(
-      rmm::exec_policy(stream),
-      output_view.begin<int32_t>(),
-      output_view.end<int32_t>(),
-      row_hasher<MurmurHash3_32, nullate::DYNAMIC>(nullate::DYNAMIC{nullable}, *device_input));
-  }
+  // Compute the hash value for each row
+  thrust::tabulate(
+    rmm::exec_policy(stream),
+    output_view.begin<int32_t>(),
+    output_view.end<int32_t>(),
+    row_hasher<MurmurHash3_32, nullate::DYNAMIC>(nullate::DYNAMIC{nullable}, *device_input));
 
   return output;
 }
diff --git a/cpp/tests/hashing/hash_test.cpp b/cpp/tests/hashing/hash_test.cpp
index ee321b761db..bd6deae9dc4 100644
--- a/cpp/tests/hashing/hash_test.cpp
+++ b/cpp/tests/hashing/hash_test.cpp
@@ -116,13 +116,13 @@ TEST_F(HashTest, MultiValueNulls)
   EXPECT_EQ(input1.num_rows(), output1->size());
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(output1->view(), output2->view());
 
-  auto const serial_output1 = cudf::hash(input1, cudf::hash_id::HASH_SERIAL_MURMUR3, {}, 0);
+  auto const serial_output1 = cudf::hash(input1, cudf::hash_id::HASH_SERIAL_MURMUR3, 0);
   auto const serial_output2 = cudf::hash(input2, cudf::hash_id::HASH_SERIAL_MURMUR3);
 
   EXPECT_EQ(input1.num_rows(), serial_output1->size());
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(serial_output1->view(), serial_output2->view());
 
-  auto const spark_output1 = cudf::hash(input1, cudf::hash_id::HASH_SPARK_MURMUR3, {}, 0);
+  auto const spark_output1 = cudf::hash(input1, cudf::hash_id::HASH_SPARK_MURMUR3, 0);
   auto const spark_output2 = cudf::hash(input2, cudf::hash_id::HASH_SPARK_MURMUR3);
 
   EXPECT_EQ(input1.num_rows(), spark_output1->size());
@@ -147,13 +147,13 @@ TYPED_TEST(HashTestTyped, Equality)
   EXPECT_EQ(input.num_rows(), output1->size());
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(output1->view(), output2->view());
 
-  auto const serial_output1 = cudf::hash(input, cudf::hash_id::HASH_SERIAL_MURMUR3, {}, 0);
+  auto const serial_output1 = cudf::hash(input, cudf::hash_id::HASH_SERIAL_MURMUR3, 0);
   auto const serial_output2 = cudf::hash(input, cudf::hash_id::HASH_SERIAL_MURMUR3);
 
   EXPECT_EQ(input.num_rows(), serial_output1->size());
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(serial_output1->view(), serial_output2->view());
 
-  auto const spark_output1 = cudf::hash(input, cudf::hash_id::HASH_SPARK_MURMUR3, {}, 0);
+  auto const spark_output1 = cudf::hash(input, cudf::hash_id::HASH_SPARK_MURMUR3, 0);
   auto const spark_output2 = cudf::hash(input, cudf::hash_id::HASH_SPARK_MURMUR3);
 
   EXPECT_EQ(input.num_rows(), spark_output1->size());
@@ -177,13 +177,13 @@ TYPED_TEST(HashTestTyped, EqualityNulls)
   EXPECT_EQ(input1.num_rows(), output1->size());
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(output1->view(), output2->view());
 
-  auto const serial_output1 = cudf::hash(input1, cudf::hash_id::HASH_SERIAL_MURMUR3, {}, 0);
+  auto const serial_output1 = cudf::hash(input1, cudf::hash_id::HASH_SERIAL_MURMUR3, 0);
   auto const serial_output2 = cudf::hash(input2, cudf::hash_id::HASH_SERIAL_MURMUR3);
 
   EXPECT_EQ(input1.num_rows(), serial_output1->size());
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(serial_output1->view(), serial_output2->view());
 
-  auto const spark_output1 = cudf::hash(input1, cudf::hash_id::HASH_SPARK_MURMUR3, {}, 0);
+  auto const spark_output1 = cudf::hash(input1, cudf::hash_id::HASH_SPARK_MURMUR3, 0);
   auto const spark_output2 = cudf::hash(input2, cudf::hash_id::HASH_SPARK_MURMUR3);
 
   EXPECT_EQ(input1.num_rows(), spark_output1->size());
@@ -222,7 +222,7 @@ TYPED_TEST(HashTestFloatTyped, TestExtremes)
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(*hash_col, *hash_col_neg_nan, verbosity);
 
   constexpr auto serial_hasher   = cudf::hash_id::HASH_SERIAL_MURMUR3;
-  auto const serial_col          = cudf::hash(table_col, serial_hasher, {}, 0);
+  auto const serial_col          = cudf::hash(table_col, serial_hasher, 0);
   auto const serial_col_neg_zero = cudf::hash(table_col_neg_zero, serial_hasher);
   auto const serial_col_neg_nan  = cudf::hash(table_col_neg_nan, serial_hasher);
 
@@ -231,7 +231,7 @@ TYPED_TEST(HashTestFloatTyped, TestExtremes)
 
   // Spark hash is sensitive to 0 and -0
   constexpr auto spark_hasher  = cudf::hash_id::HASH_SPARK_MURMUR3;
-  auto const spark_col         = cudf::hash(table_col, spark_hasher, {}, 0);
+  auto const spark_col         = cudf::hash(table_col, spark_hasher, 0);
   auto const spark_col_neg_nan = cudf::hash(table_col_neg_nan, spark_hasher);
 
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(*spark_col, *spark_col_neg_nan);
@@ -269,8 +269,8 @@ TEST_F(SerialMurmurHash3Test, MultiValueWithSeeds)
   auto const combo2 = cudf::table_view({strings_col, ints_col, bools_col2});
 
   constexpr auto hasher   = cudf::hash_id::HASH_SERIAL_MURMUR3;
-  auto const strings_hash = cudf::hash(cudf::table_view({strings_col}), hasher, {}, 314);
-  auto const ints_hash    = cudf::hash(cudf::table_view({ints_col}), hasher, {}, 42);
+  auto const strings_hash = cudf::hash(cudf::table_view({strings_col}), hasher, 314);
+  auto const ints_hash    = cudf::hash(cudf::table_view({ints_col}), hasher, 42);
   auto const combo1_hash  = cudf::hash(combo1, hasher, {});
   auto const combo2_hash  = cudf::hash(combo2, hasher, {});
   auto const structs_hash = cudf::hash(cudf::table_view({structs_col}), hasher, {});
@@ -396,20 +396,20 @@ TEST_F(SparkMurmurHash3Test, MultiValueWithSeeds)
   fixed_width_column_wrapper<bool> const bools_col2({0, 1, 2, 255, 0});
 
   constexpr auto hasher      = cudf::hash_id::HASH_SPARK_MURMUR3;
-  auto const hash_structs    = cudf::hash(cudf::table_view({structs_col}), hasher, {}, 42);
-  auto const hash_strings    = cudf::hash(cudf::table_view({strings_col}), hasher, {}, 314);
-  auto const hash_doubles    = cudf::hash(cudf::table_view({doubles_col}), hasher, {}, 42);
-  auto const hash_timestamps = cudf::hash(cudf::table_view({timestamps_col}), hasher, {}, 42);
-  auto const hash_decimal64  = cudf::hash(cudf::table_view({decimal64_col}), hasher, {}, 42);
-  auto const hash_longs      = cudf::hash(cudf::table_view({longs_col}), hasher, {}, 42);
-  auto const hash_floats     = cudf::hash(cudf::table_view({floats_col}), hasher, {}, 42);
-  auto const hash_dates      = cudf::hash(cudf::table_view({dates_col}), hasher, {}, 42);
-  auto const hash_decimal32  = cudf::hash(cudf::table_view({decimal32_col}), hasher, {}, 42);
-  auto const hash_ints       = cudf::hash(cudf::table_view({ints_col}), hasher, {}, 42);
-  auto const hash_shorts     = cudf::hash(cudf::table_view({shorts_col}), hasher, {}, 42);
-  auto const hash_bytes      = cudf::hash(cudf::table_view({bytes_col}), hasher, {}, 42);
-  auto const hash_bools1     = cudf::hash(cudf::table_view({bools_col1}), hasher, {}, 42);
-  auto const hash_bools2     = cudf::hash(cudf::table_view({bools_col2}), hasher, {}, 42);
+  auto const hash_structs    = cudf::hash(cudf::table_view({structs_col}), hasher, 42);
+  auto const hash_strings    = cudf::hash(cudf::table_view({strings_col}), hasher, 314);
+  auto const hash_doubles    = cudf::hash(cudf::table_view({doubles_col}), hasher, 42);
+  auto const hash_timestamps = cudf::hash(cudf::table_view({timestamps_col}), hasher, 42);
+  auto const hash_decimal64  = cudf::hash(cudf::table_view({decimal64_col}), hasher, 42);
+  auto const hash_longs      = cudf::hash(cudf::table_view({longs_col}), hasher, 42);
+  auto const hash_floats     = cudf::hash(cudf::table_view({floats_col}), hasher, 42);
+  auto const hash_dates      = cudf::hash(cudf::table_view({dates_col}), hasher, 42);
+  auto const hash_decimal32  = cudf::hash(cudf::table_view({decimal32_col}), hasher, 42);
+  auto const hash_ints       = cudf::hash(cudf::table_view({ints_col}), hasher, 42);
+  auto const hash_shorts     = cudf::hash(cudf::table_view({shorts_col}), hasher, 42);
+  auto const hash_bytes      = cudf::hash(cudf::table_view({bytes_col}), hasher, 42);
+  auto const hash_bools1     = cudf::hash(cudf::table_view({bools_col1}), hasher, 42);
+  auto const hash_bools2     = cudf::hash(cudf::table_view({bools_col2}), hasher, 42);
 
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(*hash_structs, hash_structs_expected, verbosity);
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(*hash_strings, hash_strings_expected, verbosity);
@@ -439,7 +439,7 @@ TEST_F(SparkMurmurHash3Test, MultiValueWithSeeds)
                                                 shorts_col,
                                                 bytes_col,
                                                 bools_col2});
-  auto const hash_combined  = cudf::hash(combined_table, hasher, {}, 42);
+  auto const hash_combined  = cudf::hash(combined_table, hasher, 42);
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(*hash_combined, hash_combined_expected, verbosity);
 }
 
diff --git a/docs/cudf/source/api_docs/series.rst b/docs/cudf/source/api_docs/series.rst
index 6dc38d985f8..e0dc4bd4f46 100644
--- a/docs/cudf/source/api_docs/series.rst
+++ b/docs/cudf/source/api_docs/series.rst
@@ -422,6 +422,4 @@ Serialization / IO / conversion
    Series.from_categorical
    Series.from_masked_array
    Series.from_pandas
-   Series.hash_encode
    Series.hash_values
-   
diff --git a/python/cudf/cudf/_lib/cpp/hash.pxd b/python/cudf/cudf/_lib/cpp/hash.pxd
index f07a6c0f046..fd9992152a6 100644
--- a/python/cudf/cudf/_lib/cpp/hash.pxd
+++ b/python/cudf/cudf/_lib/cpp/hash.pxd
@@ -13,7 +13,6 @@ from cudf._lib.cpp.table.table_view cimport table_view
 cdef extern from "cudf/hashing.hpp" namespace "cudf" nogil:
     cdef unique_ptr[column] hash "cudf::hash" (
         const table_view& input,
-        const libcudf_types.hash_id& hash_function,
-        const vector[uint32_t]& initial_hash,
+        const libcudf_types.hash_id hash_function,
         const uint32_t seed
     ) except +
diff --git a/python/cudf/cudf/_lib/hash.pyx b/python/cudf/cudf/_lib/hash.pyx
index 9b34a049cac..adc48159aac 100644
--- a/python/cudf/cudf/_lib/hash.pyx
+++ b/python/cudf/cudf/_lib/hash.pyx
@@ -54,8 +54,7 @@ def hash_partition(source_table, object columns_to_hash,
     )
 
 
-def hash(source_table, str method, object initial_hash=None, int seed=0):
-    cdef vector[uint32_t] c_initial_hash = initial_hash or []
+def hash(source_table, str method, int seed=0):
     cdef table_view c_source_view = table_view_from_table(
         source_table, ignore_index=True)
     cdef unique_ptr[column] c_result
@@ -71,7 +70,6 @@ def hash(source_table, str method, object initial_hash=None, int seed=0):
             cpp_hash(
                 c_source_view,
                 c_hash_function,
-                c_initial_hash,
                 seed
             )
         )
diff --git a/python/cudf/cudf/core/frame.py b/python/cudf/cudf/core/frame.py
index c85ed0c8555..c83b06707a4 100644
--- a/python/cudf/cudf/core/frame.py
+++ b/python/cudf/cudf/core/frame.py
@@ -580,8 +580,8 @@ def _gather(
         result._copy_type_metadata(self)
         return result
 
-    def _hash(self, method, initial_hash=None):
-        return libcudf.hash.hash(self, method, initial_hash)
+    def _hash(self, method):
+        return libcudf.hash.hash(self, method)
 
     def _hash_partition(
         self, columns_to_hash, num_partitions, keep_index=True
diff --git a/python/cudf/cudf/core/series.py b/python/cudf/cudf/core/series.py
index 036c8c1ee00..4ec7c3df076 100644
--- a/python/cudf/cudf/core/series.py
+++ b/python/cudf/cudf/core/series.py
@@ -7,7 +7,6 @@
 import pickle
 import warnings
 from collections import abc as abc
-from hashlib import sha256
 from numbers import Number
 from shutil import get_terminal_size
 from typing import Any, MutableMapping, Optional, Set, Union
@@ -3144,82 +3143,6 @@ def hash_values(self, method="murmur3"):
             {None: self._hash(method=method)}, index=self.index
         )
 
-    def hash_encode(self, stop, use_name=False):
-        """Encode column values as ints in [0, stop) using hash function.
-
-        This method is deprecated. Replace ``series.hash_encode(stop,
-        use_name=False)`` with ``series.hash_values(method="murmur3") % stop``.
-
-        Parameters
-        ----------
-        stop : int
-            The upper bound on the encoding range.
-        use_name : bool
-            If ``True`` then combine hashed column values
-            with hashed column name. This is useful for when the same
-            values in different columns should be encoded
-            with different hashed values.
-
-        Returns
-        -------
-        result : Series
-            The encoded Series.
-
-        Examples
-        --------
-        >>> import cudf
-        >>> series = cudf.Series([10, 120, 30])
-        >>> series.hash_encode(stop=200)
-        0     53
-        1     51
-        2    124
-        dtype: int32
-
-        You can choose to include name while hash
-        encoding by specifying `use_name=True`
-
-        >>> series.hash_encode(stop=200, use_name=True)
-        0    131
-        1     29
-        2     76
-        dtype: int32
-        """
-        warnings.warn(
-            "The `hash_encode` method will be removed in a future cuDF "
-            "release. Replace `series.hash_encode(stop, use_name=False)` "
-            'with `series.hash_values(method="murmur3") % stop`.',
-            FutureWarning,
-        )
-
-        if not stop > 0:
-            raise ValueError("stop must be a positive integer.")
-
-        if use_name:
-            name_hasher = sha256()
-            name_hasher.update(str(self.name).encode())
-            name_hash_bytes = name_hasher.digest()[:4]
-            name_hash_int = (
-                int.from_bytes(name_hash_bytes, "little", signed=False)
-                & 0xFFFFFFFF
-            )
-            initial_hash = [name_hash_int]
-        else:
-            initial_hash = None
-
-        hashed_values = Series._from_data(
-            {
-                self.name: self._hash(
-                    method="murmur3", initial_hash=initial_hash
-                )
-            },
-            self.index,
-        )
-
-        if hashed_values.has_nulls:
-            raise ValueError("Column must have no nulls.")
-
-        return hashed_values % stop
-
     def quantile(
         self, q=0.5, interpolation="linear", exact=True, quant_index=True
     ):
diff --git a/python/cudf/cudf/tests/test_dataframe.py b/python/cudf/cudf/tests/test_dataframe.py
index ab0856fad1e..78560ee6723 100644
--- a/python/cudf/cudf/tests/test_dataframe.py
+++ b/python/cudf/cudf/tests/test_dataframe.py
@@ -2237,44 +2237,6 @@ def test_arrow_pandas_compat(pdf, gdf, preserve_index):
     assert_eq(pdf2, gdf2)
 
 
-@pytest.mark.parametrize("nrows", [1, 8, 100, 1000, 100000])
-def test_series_hash_encode(nrows):
-    data = np.asarray(range(nrows))
-    # Python hash returns different value which sometimes
-    # results in enc_with_name_arr and enc_arr to be same.
-    # And there is no other better way to make hash return same value.
-    # So using an integer name to get constant value back from hash.
-    s = cudf.Series(data, name=1)
-    num_features = 1000
-
-    with pytest.warns(FutureWarning):
-        encoded_series = s.hash_encode(num_features)
-    assert isinstance(encoded_series, cudf.Series)
-    enc_arr = encoded_series.to_numpy()
-    assert np.all(enc_arr >= 0)
-    assert np.max(enc_arr) < num_features
-
-    with pytest.warns(FutureWarning):
-        enc_with_name_arr = s.hash_encode(
-            num_features, use_name=True
-        ).to_numpy()
-    assert enc_with_name_arr[0] != enc_arr[0]
-
-
-def test_series_hash_encode_reproducible_results():
-    # Regression test to ensure that hash_encode outputs are reproducible
-    data = cudf.Series([0, 1, 2])
-    with pytest.warns(FutureWarning):
-        hash_result = data.hash_encode(stop=2 ** 16, use_name=False)
-    expected_result = cudf.Series([42165, 55037, 7341])
-    assert_eq(hash_result, expected_result)
-
-    with pytest.warns(FutureWarning):
-        hash_result_with_name = data.hash_encode(stop=2 ** 16, use_name=True)
-    expected_result_with_name = cudf.Series([36137, 39649, 58673])
-    assert_eq(hash_result_with_name, expected_result_with_name)
-
-
 @pytest.mark.parametrize("dtype", NUMERIC_TYPES + ["bool"])
 def test_cuda_array_interface(dtype):