Signed-off-by: ntkathole <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

Signed-off-by: RutujaPathade <[email protected]>

Signed-off-by: RutujaPathade <[email protected]>

…+ join nodes (feast-dev#6395)

* fix: Apply field mapping to join keys in local compute engine nodes

When a batch source defines a `field_mapping` that renames an entity join
key (e.g. `USERID` -> `user_id`), the source-read node renames the columns
on the pulled Arrow table to their mapped names. Downstream `LocalDedupNode`
and `LocalJoinNode` then look up the *pre-mapping* names from
`column_info.join_keys`, which raises `KeyError: Index(['USERID'])` during
materialization (or returns an empty join).

Add a `join_keys_columns` property on `ColumnInfo` that mirrors the existing
`timestamp_column` / `created_timestamp_column` properties — returning join
keys translated through `field_mapping` — and use it from the dedup and
join nodes.

Fixes feast-dev#5942.

Signed-off-by: 1fanwang <[email protected]>

* test: also cover LocalJoinNode field_mapping case

Signed-off-by: 1fanwang <[email protected]>

---------

Signed-off-by: 1fanwang <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

…east-dev#6354)

Signed-off-by: ntkathole <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

…e examples

Signed-off-by: jvincent-mongodb <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

The requested_features parameter was accepted by online_read and
online_read_async but never used -- DynamoDB always fetched all
features stored in the values map regardless. Add a
ProjectionExpression to BatchGetItem requests when requested_features
is provided, reducing data transfer, latency, and read costs.

Fixes feast-dev#6058

Signed-off-by: Jonathan Wrede <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

The return dict contains both str and Dict[str, str] values, so the
return type must be Dict[str, Any] not Dict[str, str].

Signed-off-by: Jonathan Wrede <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

…ev#6381)

* fix(trino): Clean up temporary entity tables after retrieval

TrinoOfflineStore.get_historical_features() creates a temporary table
for the entity DataFrame but never drops it, leaking tables
indefinitely. Apply the same context manager pattern used by
BigQuery, Redshift, and Athena offline stores: wrap the query in a
generator that issues DROP TABLE IF EXISTS in a finally block.

Fixes feast-dev#6306

Signed-off-by: Jonathan Wrede <[email protected]>

* fix: sort imports for ruff compliance

Signed-off-by: Jonathan Wrede <[email protected]>

* fix: decouple temp table cleanup from query access

Avoid dropping the temporary entity table on to_sql() calls.
Previously, every method used a context manager that dropped
the table on exit, so calling to_sql() before to_df() would
destroy the table and cause subsequent queries to fail.

Now the query is stored as a plain string and cleanup is
handled by a dedicated _drop_temp_table() method called only
after query execution (to_df, to_trino). A __del__ fallback
ensures cleanup if execution methods are never called. The
_cleaned_up flag makes the drop idempotent.

Signed-off-by: Jonathan Wrede <[email protected]>

---------

Signed-off-by: Jonathan Wrede <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

…6362)

* feat(bigquery): Support DATE-type event timestamp columns

When the event_timestamp column in BigQuery is a DATE type, the
generated SQL wraps comparison values in TIMESTAMP(), causing a type
mismatch error. This adds a timestamp_field_type parameter to
BigQuerySource that, when set to "DATE", generates DATE() comparisons
instead.

Closes feast-dev#2530 (part 2)

Signed-off-by: Jonathan Wrede <[email protected]>

* fix(bigquery): Use protobuf 4.25.x compatible generated code

The proto files were regenerated with protobuf 6.31.1 / grpcio-tools
1.80.0, which imports runtime_version -- a module that does not exist
in protobuf 4.25.x used by the project. Revert generated code to
4.25.1 format while keeping the new timestamp_field_type field.

Signed-off-by: Jonathan Wrede <[email protected]>

* fix(bigquery): Add Literal type annotation for cast_style

Mypy infers str from the ternary expression; annotate with the
exact Literal union so the call to get_timestamp_filter_sql passes
type checking.

Signed-off-by: Jonathan Wrede <[email protected]>

* fix: Make timestamp_field_type default to None in FeatureViewQueryContext

Callers that do not use DATE-typed timestamp fields (e.g. Spark offline
store tests) should not be forced to pass timestamp_field_type. Adding
a default keeps the new field backward-compatible.

Signed-off-by: Jonathan Wrede <[email protected]>

* fix: Keep timestamp_field_type required in FeatureViewQueryContext

A default value on timestamp_field_type breaks the
SparkFeatureViewQueryContext subclass because its non-default fields
(min_date_partition, max_date_partition) would follow a field with a
default. Instead, keep it required and update the Spark test to pass it.

Signed-off-by: Jonathan Wrede <[email protected]>

* fix: regenerate protos matching upstream mypy-protobuf style

Reset all non-DataSource generated files to match master.
Only DataSource_pb2.py and DataSource_pb2.pyi contain our
timestamp_field_type additions (field 28). The .pyi stub
is hand-edited to match the existing import style used on
master.

Signed-off-by: Jonathan Wrede <[email protected]>

---------

Signed-off-by: Jonathan Wrede <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

Signed-off-by: ntkathole <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

Mount the existing REST registry routers under /registry on the feature
server so that fastapi_mcp automatically exposes registry introspection
(list/get for entities, feature views, data sources, feature services,
permissions, projects, saved datasets, lineage, search) as MCP tools.

The RegistryServer is created in-process from store.registry — no
external registry server is required. Auth is enforced via
inject_user_details on every mounted router.

Made-with: Cursor
Signed-off-by: Chaitany patel <[email protected]>
Made-with: Cursor
Signed-off-by: RutujaPathade <[email protected]>

…elds

Signed-off-by: RutujaPathade <[email protected]>

…chine to be opt-in

Signed-off-by: RutujaPathade <[email protected]>

Signed-off-by: RutujaPathade <[email protected]>

Signed-off-by: RutujaPathade <[email protected]>

Signed-off-by: RutujaPathade <[email protected]>

Co-authored-by: Nikhil Kathole <[email protected]>
Signed-off-by: RutujaPathade <[email protected]>

Signed-off-by: RutujaPathade <[email protected]>

Signed-off-by: RutujaPathade <[email protected]>

Signed-off-by: RutujaPathade <[email protected]>