Add Unix Timestamp value type

docs/specs/offline_store_format.md

@@ -36,14 +36,16 @@ Here's how Feast types map to Pandas types for Feast APIs that take in or return
 | BYTES | `bytes` |
 | STRING | `str` , `category`|
 | INT32 | `int32`, `uint32` |
-| INT64 | `int64`, `uint64`, `datetime64[ns]`, `datetime64[ns, tz]` |
+| INT64 | `int64`, `uint64` |
+| UNIX_TIMESTAMP | `datetime64[ns]`, `datetime64[ns, tz]` |
 | DOUBLE | `float64` |
 | FLOAT | `float32` |
 | BOOL | `bool`|
 | BYTES\_LIST | `list[bytes]` |
 | STRING\_LIST | `list[str]`|
 | INT32\_LIST | `list[int]`|
 | INT64\_LIST | `list[int]`|
+| UNIX_TIMESTAMP\_LIST | `list[unix_timestamp]`|
 | DOUBLE\_LIST | `list[float]`|
 | FLOAT\_LIST | `list[float]`|
 | BOOL\_LIST | `list[bool]`|
@@ -52,7 +54,7 @@ Note that this mapping is non-injective, that is more than one Pandas type may c
 
 Feast array types are mapped to a pandas column with object dtype, that contains a Python array of corresponding type.
 
-Another thing to note is Feast doesn't support timestamp type for entity and feature columns. Values of datetime type in pandas dataframe are converted to int64 if they are found in entity and feature columns.
+Another thing to note is Feast doesn't support timestamp type for entity and feature columns. Values of datetime type in pandas dataframe are converted to int64 if they are found in entity and feature columns. In order to easily differentiate int64 to timestamp features, there is a UNIX_TIMESTAMP type that is an int64 under the hood.  
 
 #### BigQuery types
 Here's how Feast types map to BigQuery types when using BigQuery for offline storage when reading data from BigQuery to the online store:
@@ -64,13 +66,15 @@ Here's how Feast types map to BigQuery types when using BigQuery for offline sto
 | STRING | `STRING` |
 | INT32 | `INT64 / INTEGER` |
 | INT64 | `INT64 / INTEGER` |
+| UNIX_TIMESTAMP | `INT64 / INTEGER` |
 | DOUBLE | `FLOAT64 / FLOAT` |
 | FLOAT | `FLOAT64 / FLOAT` |
 | BOOL | `BOOL`|
 | BYTES\_LIST | `ARRAY<BYTES>` |
 | STRING\_LIST | `ARRAY<STRING>`|
 | INT32\_LIST | `ARRAY<INT64>`|
 | INT64\_LIST | `ARRAY<INT64>`|
+| UNIX_TIMESTAMP\_LIST | `ARRAY<INT64>`|
 | DOUBLE\_LIST | `ARRAY<FLOAT64>`|
 | FLOAT\_LIST | `ARRAY<FLOAT64>`|
 | BOOL\_LIST | `ARRAY<BOOL>`|

docs/specs/online_store_format.md

@@ -107,13 +107,15 @@ message ValueType {
     DOUBLE = 5;
     FLOAT = 6;
     BOOL = 7;
+    UNIX_TIMESTAMP = 8;
     BYTES_LIST = 11;
     STRING_LIST = 12;
     INT32_LIST = 13;
     INT64_LIST = 14;
     DOUBLE_LIST = 15;
     FLOAT_LIST = 16;
     BOOL_LIST = 17;
+    UNIX_TIMESTAMP_LIST = 18;
   }
 }
 
@@ -128,13 +130,15 @@ message Value {
     double double_val = 5;
     float float_val = 6;
     bool bool_val = 7;
+    int64 unix_timestamp_val = 8;
     BytesList bytes_list_val = 11;
     StringList string_list_val = 12;
     Int32List int32_list_val = 13;
     Int64List int64_list_val = 14;
     DoubleList double_list_val = 15;
     FloatList float_list_val = 16;
     BoolList bool_list_val = 17;
+    Int64List unix_timestamp_list_val = 18;
   }
 }
 

protos/feast/types/Value.proto

@@ -32,13 +32,15 @@ message ValueType {
     DOUBLE = 5;
     FLOAT = 6;
     BOOL = 7;
+    UNIX_TIMESTAMP = 8;
     BYTES_LIST = 11;
     STRING_LIST = 12;
     INT32_LIST = 13;
     INT64_LIST = 14;
     DOUBLE_LIST = 15;
     FLOAT_LIST = 16;
     BOOL_LIST = 17;
+    UNIX_TIMESTAMP_LIST = 18;
   }
 }
 
@@ -53,13 +55,15 @@ message Value {
     double double_val = 5;
     float float_val = 6;
     bool bool_val = 7;
+    int64 unix_timestamp_val = 8;
     BytesList bytes_list_val = 11;
     StringList string_list_val = 12;
     Int32List int32_list_val = 13;
     Int64List int64_list_val = 14;
     DoubleList double_list_val = 15;
     FloatList float_list_val = 16;
     BoolList bool_list_val = 17;
+    Int64List unix_timestamp_list_val = 18;
   }
 }
 

sdk/python/feast/type_map.py

@@ -107,9 +107,9 @@ def python_type_to_feast_value_type(
         "uint8": ValueType.INT32,
         "int8": ValueType.INT32,
         "bool": ValueType.BOOL,
-        "timedelta": ValueType.INT64,
-        "datetime64[ns]": ValueType.INT64,
-        "datetime64[ns, tz]": ValueType.INT64,
+        "timedelta": ValueType.UNIX_TIMESTAMP,
+        "datetime64[ns]": ValueType.UNIX_TIMESTAMP,
+        "datetime64[ns, tz]": ValueType.UNIX_TIMESTAMP,
         "category": ValueType.STRING,
     }
 
@@ -252,6 +252,18 @@ def _python_value_to_proto_value(feast_value_type, value) -> ProtoValue:
                 )
             )
 
+        if feast_value_type == ValueType.UNIX_TIMESTAMP_LIST:
+            return ProtoValue(
+                int64_list_val=Int64List(
+                    val=[
+                        item
+                        if type(item) in [np.int64, np.int32]
+                        else _type_err(item, np.int64)
+                        for item in value
+                    ]
+                )
+            )
+
         if feast_value_type == ValueType.STRING_LIST:
             return ProtoValue(
                 string_list_val=StringList(
@@ -296,6 +308,8 @@ def _python_value_to_proto_value(feast_value_type, value) -> ProtoValue:
             return ProtoValue(int32_val=int(value))
         elif feast_value_type == ValueType.INT64:
             return ProtoValue(int64_val=int(value))
+        elif feast_value_type == ValueType.UNIX_TIMESTAMP:
+            return ProtoValue(int64_val=int(value))
         elif feast_value_type == ValueType.FLOAT:
             return ProtoValue(float_val=float(value))
         elif feast_value_type == ValueType.DOUBLE:

sdk/python/feast/value_type.py

@@ -29,13 +29,15 @@ class ValueType(enum.Enum):
     DOUBLE = 5
     FLOAT = 6
     BOOL = 7
+    UNIX_TIMESTAMP = 8
     BYTES_LIST = 11
     STRING_LIST = 12
     INT32_LIST = 13
     INT64_LIST = 14
     DOUBLE_LIST = 15
     FLOAT_LIST = 16
     BOOL_LIST = 17
+    UNIX_TIMESTAMP_LIST = 18
 
     def to_tfx_schema_feature_type(self):
         if self.value in [
@@ -49,9 +51,14 @@ def to_tfx_schema_feature_type(self):
             ValueType.DOUBLE_LIST.value,
             ValueType.FLOAT_LIST.value,
             ValueType.BOOL_LIST.value,
+            ValueType.UNIX_TIMESTAMP_LIST.value,
         ]:
             return schema_pb2.FeatureType.BYTES
-        elif self.value in [ValueType.INT32.value, ValueType.INT64.value]:
+        elif self.value in [
+            ValueType.INT32.value,
+            ValueType.INT64.value,
+            ValueType.UNIX_TIMESTAMP.value,
+        ]:
             return schema_pb2.FeatureType.INT
         elif self.value in [ValueType.DOUBLE.value, ValueType.FLOAT.value]:
             return schema_pb2.FeatureType.FLOAT

sdk/python/tensorflow_metadata/proto/v0/path_pb2.pyi

@@ -2,23 +2,45 @@
 @generated by mypy-protobuf.  Do not edit manually!
 isort:skip_file
 """
-import builtins
-import google.protobuf.descriptor
-import google.protobuf.internal.containers
-import google.protobuf.message
-import typing
-import typing_extensions
+from google.protobuf.descriptor import (
+    Descriptor as google___protobuf___descriptor___Descriptor,
+    FileDescriptor as google___protobuf___descriptor___FileDescriptor,
+)
 
-DESCRIPTOR: google.protobuf.descriptor.FileDescriptor = ...
+from google.protobuf.internal.containers import (
+    RepeatedScalarFieldContainer as google___protobuf___internal___containers___RepeatedScalarFieldContainer,
+)
 
-class Path(google.protobuf.message.Message):
-    DESCRIPTOR: google.protobuf.descriptor.Descriptor = ...
-    STEP_FIELD_NUMBER: builtins.int
-    step: google.protobuf.internal.containers.RepeatedScalarFieldContainer[typing.Text] = ...
+from google.protobuf.message import (
+    Message as google___protobuf___message___Message,
+)
+
+from typing import (
+    Iterable as typing___Iterable,
+    Optional as typing___Optional,
+    Text as typing___Text,
+)
+
+from typing_extensions import (
+    Literal as typing_extensions___Literal,
+)
+
+
+builtin___bool = bool
+builtin___bytes = bytes
+builtin___float = float
+builtin___int = int
+
+
+DESCRIPTOR: google___protobuf___descriptor___FileDescriptor = ...
+
+class Path(google___protobuf___message___Message):
+    DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
+    step: google___protobuf___internal___containers___RepeatedScalarFieldContainer[typing___Text] = ...
 
     def __init__(self,
         *,
-        step : typing.Optional[typing.Iterable[typing.Text]] = ...,
+        step : typing___Optional[typing___Iterable[typing___Text]] = None,
         ) -> None: ...
-    def ClearField(self, field_name: typing_extensions.Literal[u"step",b"step"]) -> None: ...
-global___Path = Path
+    def ClearField(self, field_name: typing_extensions___Literal[u"step",b"step"]) -> None: ...
+type___Path = Path