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fix: Fix type mapping spark #4071

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merged 8 commits into from
Apr 15, 2024
Merged

fix: Fix type mapping spark #4071

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2f37e07
feat: Enable Arrow-based columnar data transfers
ElliotNguyen68 Mar 19, 2024
8eb0c59
Merge branch 'feast-dev:master' into master
ElliotNguyen68 Mar 21, 2024
c1c9990
fix: Add __eq__, __hash__ to SparkSource for comparision
ElliotNguyen68 Mar 21, 2024
add7f3a
chore: simplify the logic
ElliotNguyen68 Mar 21, 2024
6cba191
Merge branch 'feast-dev:master' into master
ElliotNguyen68 Mar 23, 2024
21e5434
Merge branch 'feast-dev:master' into master
ElliotNguyen68 Apr 3, 2024
5bc1ec6
feat: Add decimal datatype to spark mapping to feast data type
ElliotNguyen68 Apr 8, 2024
8dc98b3
feat: add array decimal
ElliotNguyen68 Apr 10, 2024
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8 changes: 7 additions & 1 deletion sdk/python/feast/type_map.py
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Original file line number Diff line number Diff line change
Expand Up @@ -752,7 +752,7 @@ def _non_empty_value(value: Any) -> bool:

def spark_to_feast_value_type(spark_type_as_str: str) -> ValueType:
# TODO not all spark types are convertible
# Current non-convertible types: interval, map, struct, structfield, decimal, binary
# Current non-convertible types: interval, map, struct, structfield, binary
type_map: Dict[str, ValueType] = {
"null": ValueType.UNKNOWN,
"byte": ValueType.BYTES,
Expand All @@ -762,6 +762,7 @@ def spark_to_feast_value_type(spark_type_as_str: str) -> ValueType:
"bigint": ValueType.INT64,
"long": ValueType.INT64,
"double": ValueType.DOUBLE,
"decimal": ValueType.DOUBLE,
"float": ValueType.FLOAT,
"boolean": ValueType.BOOL,
"timestamp": ValueType.UNIX_TIMESTAMP,
Expand All @@ -770,10 +771,15 @@ def spark_to_feast_value_type(spark_type_as_str: str) -> ValueType:
"array<int>": ValueType.INT32_LIST,
"array<bigint>": ValueType.INT64_LIST,
"array<double>": ValueType.DOUBLE_LIST,
"array<decimal>": ValueType.DOUBLE_LIST,
"array<float>": ValueType.FLOAT_LIST,
"array<boolean>": ValueType.BOOL_LIST,
"array<timestamp>": ValueType.UNIX_TIMESTAMP_LIST,
}
if spark_type_as_str.startswith("decimal"):
spark_type_as_str = "decimal"
if spark_type_as_str.startswith("array<decimal"):
spark_type_as_str = "array<decimal>"
# TODO: Find better way of doing this.
if not isinstance(spark_type_as_str, str) or spark_type_as_str not in type_map:
return ValueType.NULL
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