diff --git a/CHANGELOG.md b/CHANGELOG.md
index 374e436b882..2725fb643e2 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,23 @@
# Changelog
+# [0.57.0](https://github.com/feast-dev/feast/compare/v0.56.0...v0.57.0) (2025-11-13)
+
+
+### Bug Fixes
+
+* Improve trino to feast type mapping with (real,varchar,timestamp,decimal) ([#5691](https://github.com/feast-dev/feast/issues/5691)) ([f855ad2](https://github.com/feast-dev/feast/commit/f855ad245f1800cb5e591ad0370903f361641037))
+* Materialize API - ODFV views not looked-up (thinks views non existant) - crashes materialize ([#5716](https://github.com/feast-dev/feast/issues/5716)) ([1b050b3](https://github.com/feast-dev/feast/commit/1b050b32fefd1190044087dec504acdcb43a51d5))
+* Support historical feature retrieval with start_date/end_date in RemoteOfflineStore ([#5703](https://github.com/feast-dev/feast/issues/5703)) ([ad32756](https://github.com/feast-dev/feast/commit/ad3275654226f614fa4a40411440d16634f6971c))
+* Thread safe Clickhouse offline store ([#5710](https://github.com/feast-dev/feast/issues/5710)) ([5f446ed](https://github.com/feast-dev/feast/commit/5f446ede403e778264e6a44266ba72e1174e1db9))
+
+
+### Features
+
+* Add annotations to cronjob CRDs ([#5701](https://github.com/feast-dev/feast/issues/5701)) ([be6e6c2](https://github.com/feast-dev/feast/commit/be6e6c2752df669d030ed2c8b66dd2229448490e))
+* Add batch commit mode for MySQL OnlineStore ([#5699](https://github.com/feast-dev/feast/issues/5699)) ([3cfe4eb](https://github.com/feast-dev/feast/commit/3cfe4ebfa9de589fa03c020cadcb4d9de504affa))
+* Add possibility to materialize only latest values, to increase performance ([#5713](https://github.com/feast-dev/feast/issues/5713)) ([8d77b72](https://github.com/feast-dev/feast/commit/8d77b7287b9dea11acad56fed1dada453150785c))
+* Support table format: Iceberg, Delta, and Hudi ([#5650](https://github.com/feast-dev/feast/issues/5650)) ([2915ad1](https://github.com/feast-dev/feast/commit/2915ad18735ee4f749c2e63a6bbf0dd2a922bc96))
+
# [0.56.0](https://github.com/feast-dev/feast/compare/v0.55.0...v0.56.0) (2025-10-27)
diff --git a/docs/SUMMARY.md b/docs/SUMMARY.md
index 2e34687d6c7..c06c3398519 100644
--- a/docs/SUMMARY.md
+++ b/docs/SUMMARY.md
@@ -82,6 +82,7 @@
* [Type System](reference/type-system.md)
* [Data sources](reference/data-sources/README.md)
* [Overview](reference/data-sources/overview.md)
+ * [Table formats](reference/data-sources/table-formats.md)
* [File](reference/data-sources/file.md)
* [Snowflake](reference/data-sources/snowflake.md)
* [BigQuery](reference/data-sources/bigquery.md)
diff --git a/docs/getting-started/components/compute-engine.md b/docs/getting-started/components/compute-engine.md
index baf031b4284..60da1575932 100644
--- a/docs/getting-started/components/compute-engine.md
+++ b/docs/getting-started/components/compute-engine.md
@@ -25,7 +25,7 @@ engines.
| SnowflakeComputeEngine | Runs on Snowflake, designed for scalable feature generation using Snowflake SQL. | ✅ | |
| LambdaComputeEngine | Runs on AWS Lambda, designed for serverless feature generation. | ✅ | |
| FlinkComputeEngine | Runs on Apache Flink, designed for stream processing and real-time feature generation. | ❌ | |
-| RayComputeEngine | Runs on Ray, designed for distributed feature generation and machine learning workloads. | ❌ | |
+| RayComputeEngine | Runs on Ray, designed for distributed feature generation and machine learning workloads. | ✅ | |
```
### Batch Engine
diff --git a/docs/getting-started/genai.md b/docs/getting-started/genai.md
index 9c8f0c955d2..b4bdf1d1dc8 100644
--- a/docs/getting-started/genai.md
+++ b/docs/getting-started/genai.md
@@ -104,6 +104,24 @@ This integration enables:
- Efficiently materializing features to vector databases
- Scaling RAG applications to enterprise-level document repositories
+### Scaling with Ray Integration
+
+Feast integrates with Ray to enable distributed processing for RAG applications:
+
+* **Ray Compute Engine**: Distributed feature computation using Ray's task and actor model
+* **Ray Offline Store**: Process large document collections and generate embeddings at scale
+* **Ray Batch Materialization**: Efficiently materialize features from offline to online stores
+* **Distributed Embedding Generation**: Scale embedding generation across multiple nodes
+
+This integration enables:
+- Distributed processing of large document collections
+- Parallel embedding generation for millions of text chunks
+- Kubernetes-native scaling for RAG applications
+- Efficient resource utilization across multiple nodes
+- Production-ready distributed RAG pipelines
+
+For detailed information on building distributed RAG applications with Feast and Ray, see [Feast + Ray: Distributed Processing for RAG Applications](https://feast.dev/blog/feast-ray-distributed-processing/).
+
## Model Context Protocol (MCP) Support
Feast supports the Model Context Protocol (MCP), which enables AI agents and applications to interact with your feature store through standardized MCP interfaces. This allows seamless integration with LLMs and AI agents for GenAI applications.
@@ -158,6 +176,7 @@ For more detailed information and examples:
* [RAG Tutorial with Docling](../tutorials/rag-with-docling.md)
* [RAG Fine Tuning with Feast and Milvus](../../examples/rag-retriever/README.md)
* [Milvus Quickstart Example](https://github.com/feast-dev/feast/tree/master/examples/rag/milvus-quickstart.ipynb)
+* [Feast + Ray: Distributed Processing for RAG Applications](https://feast.dev/blog/feast-ray-distributed-processing/)
* [MCP Feature Store Example](../../examples/mcp_feature_store/)
* [MCP Feature Server Reference](../reference/feature-servers/mcp-feature-server.md)
* [Spark Data Source](../reference/data-sources/spark.md)
diff --git a/docs/reference/compute-engine/ray.md b/docs/reference/compute-engine/ray.md
index 5547901b873..22b1e1a4700 100644
--- a/docs/reference/compute-engine/ray.md
+++ b/docs/reference/compute-engine/ray.md
@@ -2,6 +2,24 @@
The Ray compute engine is a distributed compute implementation that leverages [Ray](https://www.ray.io/) for executing feature pipelines including transformations, aggregations, joins, and materializations. It provides scalable and efficient distributed processing for both `materialize()` and `get_historical_features()` operations.
+## Quick Start with Ray Template
+
+### Ray RAG Template - Batch Embedding at Scale
+
+For RAG (Retrieval-Augmented Generation) applications with distributed embedding generation:
+
+```bash
+feast init -t ray_rag my_rag_project
+cd my_rag_project/feature_repo
+```
+
+The Ray RAG template demonstrates:
+- **Parallel Embedding Generation**: Uses Ray compute engine to generate embeddings across multiple workers
+- **Vector Search Integration**: Works with Milvus for semantic similarity search
+- **Complete RAG Pipeline**: Data → Embeddings → Search workflow
+
+The Ray compute engine automatically distributes the embedding generation across available workers, making it ideal for processing large datasets efficiently.
+
## Overview
The Ray compute engine provides:
@@ -365,6 +383,8 @@ batch_engine:
### With Feature Transformations
+#### On-Demand Transformations
+
```python
from feast import FeatureView, Field
from feast.types import Float64
@@ -385,4 +405,27 @@ features = store.get_historical_features(
)
```
+#### Ray Native Transformations
+
+For distributed transformations that leverage Ray's dataset and parallel processing capabilities, use `mode="ray"` in your `BatchFeatureView`:
+
+```python
+# Feature view with Ray transformation mode
+document_embeddings_view = BatchFeatureView(
+ name="document_embeddings",
+ entities=[document],
+ mode="ray", # Enable Ray native transformation
+ ttl=timedelta(days=365),
+ schema=[
+ Field(name="document_id", dtype=String),
+ Field(name="embedding", dtype=Array(Float32), vector_index=True),
+ Field(name="movie_name", dtype=String),
+ Field(name="movie_director", dtype=String),
+ ],
+ source=movies_source,
+ udf=generate_embeddings_ray_native,
+ online=True,
+)
+```
+
For more information, see the [Ray documentation](https://docs.ray.io/en/latest/) and [Ray Data guide](https://docs.ray.io/en/latest/data/getting-started.html).
\ No newline at end of file
diff --git a/docs/reference/data-sources/spark.md b/docs/reference/data-sources/spark.md
index 99d5902667a..8967e8bd181 100644
--- a/docs/reference/data-sources/spark.md
+++ b/docs/reference/data-sources/spark.md
@@ -4,6 +4,8 @@
Spark data sources are tables or files that can be loaded from some Spark store (e.g. Hive or in-memory). They can also be specified by a SQL query.
+**New in Feast:** SparkSource now supports advanced table formats including **Apache Iceberg**, **Delta Lake**, and **Apache Hudi**, enabling ACID transactions, time travel, and schema evolution capabilities. See the [Table Formats guide](table-formats.md) for detailed documentation.
+
## Disclaimer
The Spark data source does not achieve full test coverage.
@@ -11,6 +13,8 @@ Please do not assume complete stability.
## Examples
+### Basic Examples
+
Using a table reference from SparkSession (for example, either in-memory or a Hive Metastore):
```python
@@ -51,8 +55,77 @@ my_spark_source = SparkSource(
)
```
+### Table Format Examples
+
+SparkSource supports advanced table formats for modern data lakehouse architectures. For detailed documentation, configuration options, and best practices, see the **[Table Formats guide](table-formats.md)**.
+
+#### Apache Iceberg
+
+```python
+from feast.infra.offline_stores.contrib.spark_offline_store.spark_source import SparkSource
+from feast.table_format import IcebergFormat
+
+iceberg_format = IcebergFormat(
+ catalog="my_catalog",
+ namespace="my_database"
+)
+
+my_spark_source = SparkSource(
+ name="user_features",
+ path="my_catalog.my_database.user_table",
+ table_format=iceberg_format,
+ timestamp_field="event_timestamp"
+)
+```
+
+#### Delta Lake
+
+```python
+from feast.infra.offline_stores.contrib.spark_offline_store.spark_source import SparkSource
+from feast.table_format import DeltaFormat
+
+delta_format = DeltaFormat()
+
+my_spark_source = SparkSource(
+ name="transaction_features",
+ path="s3://my-bucket/delta-tables/transactions",
+ table_format=delta_format,
+ timestamp_field="transaction_timestamp"
+)
+```
+
+#### Apache Hudi
+
+```python
+from feast.infra.offline_stores.contrib.spark_offline_store.spark_source import SparkSource
+from feast.table_format import HudiFormat
+
+hudi_format = HudiFormat(
+ table_type="COPY_ON_WRITE",
+ record_key="user_id",
+ precombine_field="updated_at"
+)
+
+my_spark_source = SparkSource(
+ name="user_profiles",
+ path="s3://my-bucket/hudi-tables/user_profiles",
+ table_format=hudi_format,
+ timestamp_field="event_timestamp"
+)
+```
+
+For advanced configuration including time travel, incremental queries, and performance tuning, see the **[Table Formats guide](table-formats.md)**.
+
+## Configuration Options
+
The full set of configuration options is available [here](https://rtd.feast.dev/en/master/#feast.infra.offline_stores.contrib.spark_offline_store.spark_source.SparkSource).
+### Table Format Options
+
+- **IcebergFormat**: See [Table Formats - Iceberg](table-formats.md#apache-iceberg)
+- **DeltaFormat**: See [Table Formats - Delta Lake](table-formats.md#delta-lake)
+- **HudiFormat**: See [Table Formats - Hudi](table-formats.md#apache-hudi)
+
## Supported Types
Spark data sources support all eight primitive types and their corresponding array types.
diff --git a/docs/reference/data-sources/table-formats.md b/docs/reference/data-sources/table-formats.md
new file mode 100644
index 00000000000..f00e6f80c5f
--- /dev/null
+++ b/docs/reference/data-sources/table-formats.md
@@ -0,0 +1,357 @@
+# Table Formats
+
+## Overview
+
+Table formats are metadata and transaction layers built on top of data storage formats (like Parquet). They provide advanced capabilities for managing large-scale data lakes, including ACID transactions, time travel, schema evolution, and efficient data management.
+
+Feast supports modern table formats to enable data lakehouse architectures with your feature store.
+
+## Supported Table Formats
+
+### Apache Iceberg
+
+[Apache Iceberg](https://iceberg.apache.org/) is an open table format designed for huge analytic datasets. It provides:
+- **ACID transactions**: Atomic commits with snapshot isolation
+- **Time travel**: Query data as of any snapshot
+- **Schema evolution**: Add, drop, rename, or reorder columns safely
+- **Hidden partitioning**: Partitioning is transparent to users
+- **Performance**: Advanced pruning and filtering
+
+#### Basic Configuration
+
+```python
+from feast.table_format import IcebergFormat
+
+iceberg_format = IcebergFormat(
+ catalog="my_catalog",
+ namespace="my_database"
+)
+```
+
+#### Configuration Options
+
+| Parameter | Type | Description |
+|-----------|------|-------------|
+| `catalog` | `str` (optional) | Iceberg catalog name |
+| `namespace` | `str` (optional) | Namespace/schema within the catalog |
+| `properties` | `dict` (optional) | Additional Iceberg configuration properties |
+
+#### Common Properties
+
+```python
+iceberg_format = IcebergFormat(
+ catalog="spark_catalog",
+ namespace="production",
+ properties={
+ # Snapshot selection
+ "snapshot-id": "123456789",
+ "as-of-timestamp": "1609459200000", # Unix timestamp in ms
+
+ # Performance tuning
+ "read.split.target-size": "134217728", # 128 MB splits
+ "read.parquet.vectorization.enabled": "true",
+
+ # Advanced configuration
+ "io-impl": "org.apache.iceberg.hadoop.HadoopFileIO",
+ "warehouse": "s3://my-bucket/warehouse"
+ }
+)
+```
+
+#### Time Travel Example
+
+```python
+# Read from a specific snapshot
+iceberg_format = IcebergFormat(
+ catalog="spark_catalog",
+ namespace="lakehouse"
+)
+iceberg_format.set_property("snapshot-id", "7896524153287651133")
+
+# Or read as of a timestamp
+iceberg_format.set_property("as-of-timestamp", "1609459200000")
+```
+
+### Delta Lake
+
+[Delta Lake](https://delta.io/) is an open-source storage layer that brings ACID transactions to Apache Spark and big data workloads. It provides:
+- **ACID transactions**: Serializable isolation for reads and writes
+- **Time travel**: Access and revert to earlier versions
+- **Schema enforcement**: Prevent bad data from corrupting tables
+- **Unified batch and streaming**: Process data incrementally
+- **Audit history**: Full history of all changes
+
+#### Basic Configuration
+
+```python
+from feast.table_format import DeltaFormat
+
+delta_format = DeltaFormat()
+```
+
+#### Configuration Options
+
+| Parameter | Type | Description |
+|-----------|------|-------------|
+| `checkpoint_location` | `str` (optional) | Location for Delta transaction log checkpoints |
+| `properties` | `dict` (optional) | Additional Delta configuration properties |
+
+#### Common Properties
+
+```python
+delta_format = DeltaFormat(
+ checkpoint_location="s3://my-bucket/checkpoints",
+ properties={
+ # Time travel
+ "versionAsOf": "5",
+ "timestampAsOf": "2024-01-01 00:00:00",
+
+ # Performance optimization
+ "delta.autoOptimize.optimizeWrite": "true",
+ "delta.autoOptimize.autoCompact": "true",
+
+ # Data skipping
+ "delta.dataSkippingNumIndexedCols": "32",
+
+ # Z-ordering
+ "delta.autoOptimize.zOrderCols": "event_timestamp"
+ }
+)
+```
+
+#### Time Travel Example
+
+```python
+# Read from a specific version
+delta_format = DeltaFormat()
+delta_format.set_property("versionAsOf", "10")
+
+# Or read as of a timestamp
+delta_format = DeltaFormat()
+delta_format.set_property("timestampAsOf", "2024-01-15 12:00:00")
+```
+
+### Apache Hudi
+
+[Apache Hudi](https://hudi.apache.org/) (Hadoop Upserts Deletes and Incrementals) is a data lake storage framework for simplifying incremental data processing. It provides:
+- **Upserts and deletes**: Efficient record-level updates
+- **Incremental queries**: Process only changed data
+- **Time travel**: Query historical versions
+- **Multiple table types**: Optimize for read vs. write workloads
+- **Change data capture**: Track data changes over time
+
+#### Basic Configuration
+
+```python
+from feast.table_format import HudiFormat
+
+hudi_format = HudiFormat(
+ table_type="COPY_ON_WRITE",
+ record_key="user_id",
+ precombine_field="updated_at"
+)
+```
+
+#### Configuration Options
+
+| Parameter | Type | Description |
+|-----------|------|-------------|
+| `table_type` | `str` (optional) | `COPY_ON_WRITE` or `MERGE_ON_READ` |
+| `record_key` | `str` (optional) | Field(s) that uniquely identify a record |
+| `precombine_field` | `str` (optional) | Field used to determine the latest version |
+| `properties` | `dict` (optional) | Additional Hudi configuration properties |
+
+#### Table Types
+
+**COPY_ON_WRITE (COW)**
+- Stores data in columnar format (Parquet)
+- Updates create new file versions
+- Best for **read-heavy workloads**
+- Lower query latency
+
+```python
+hudi_format = HudiFormat(
+ table_type="COPY_ON_WRITE",
+ record_key="id",
+ precombine_field="timestamp"
+)
+```
+
+**MERGE_ON_READ (MOR)**
+- Uses columnar + row-based formats
+- Updates written to delta logs
+- Best for **write-heavy workloads**
+- Lower write latency
+
+```python
+hudi_format = HudiFormat(
+ table_type="MERGE_ON_READ",
+ record_key="id",
+ precombine_field="timestamp"
+)
+```
+
+#### Common Properties
+
+```python
+hudi_format = HudiFormat(
+ table_type="COPY_ON_WRITE",
+ record_key="user_id",
+ precombine_field="updated_at",
+ properties={
+ # Query type
+ "hoodie.datasource.query.type": "snapshot", # or "incremental"
+
+ # Incremental queries
+ "hoodie.datasource.read.begin.instanttime": "20240101000000",
+ "hoodie.datasource.read.end.instanttime": "20240102000000",
+
+ # Indexing
+ "hoodie.index.type": "BLOOM",
+
+ # Compaction (for MOR tables)
+ "hoodie.compact.inline": "true",
+ "hoodie.compact.inline.max.delta.commits": "5",
+
+ # Clustering
+ "hoodie.clustering.inline": "true"
+ }
+)
+```
+
+#### Incremental Query Example
+
+```python
+# Process only new/changed data
+hudi_format = HudiFormat(
+ table_type="COPY_ON_WRITE",
+ record_key="id",
+ precombine_field="timestamp",
+ properties={
+ "hoodie.datasource.query.type": "incremental",
+ "hoodie.datasource.read.begin.instanttime": "20240101000000",
+ "hoodie.datasource.read.end.instanttime": "20240102000000"
+ }
+)
+```
+
+## Table Format vs File Format
+
+It's important to understand the distinction:
+
+| Aspect | File Format | Table Format |
+|--------|-------------|--------------|
+| **What it is** | Physical encoding of data | Metadata and transaction layer |
+| **Examples** | Parquet, Avro, ORC, CSV | Iceberg, Delta Lake, Hudi |
+| **Handles** | Data serialization | ACID, versioning, schema evolution |
+| **Layer** | Storage layer | Metadata layer |
+
+### Can be used together
+
+```python
+# Table format (metadata layer) built on top of file format (storage layer)
+from feast.infra.offline_stores.contrib.spark_offline_store.spark_source import SparkSource
+from feast.table_format import IcebergFormat
+
+iceberg = IcebergFormat(catalog="my_catalog", namespace="db")
+
+source = SparkSource(
+ name="features",
+ path="catalog.db.table",
+ file_format="parquet", # Underlying storage format
+ table_format=iceberg, # Table metadata format
+ timestamp_field="event_timestamp"
+)
+```
+
+## Benefits of Table Formats
+
+### Reliability
+- **ACID transactions**: Ensure data consistency across concurrent operations
+- **Automatic retries**: Handle transient failures gracefully
+- **Schema validation**: Prevent incompatible schema changes
+- **Data quality**: Constraints and validation rules
+
+### Performance
+- **Data skipping**: Read only relevant files based on metadata
+- **Partition pruning**: Skip entire partitions based on predicates
+- **Compaction**: Merge small files for better performance
+- **Columnar pruning**: Read only necessary columns
+- **Indexing**: Advanced indexing for fast lookups
+
+### Flexibility
+- **Schema evolution**: Add, remove, or modify columns without rewriting data
+- **Time travel**: Access historical data states for auditing or debugging
+- **Incremental processing**: Process only changed data efficiently
+- **Multiple readers/writers**: Concurrent access without conflicts
+
+## Choosing the Right Table Format
+
+| Use Case | Recommended Format | Why |
+|----------|-------------------|-----|
+| Large-scale analytics with frequent schema changes | **Iceberg** | Best schema evolution, hidden partitioning, mature ecosystem |
+| Streaming + batch workloads | **Delta Lake** | Unified architecture, strong integration with Spark, good docs |
+| CDC and upsert-heavy workloads | **Hudi** | Efficient record-level updates, incremental queries |
+| Read-heavy analytics | **Iceberg or Delta** | Excellent query performance |
+| Write-heavy transactional | **Hudi (MOR)** | Optimized for fast writes |
+| Multi-engine support | **Iceberg** | Widest engine support (Spark, Flink, Trino, etc.) |
+
+## Best Practices
+
+### 1. Choose Appropriate Partitioning
+```python
+# Iceberg - hidden partitioning
+iceberg_format.set_property("partition-spec", "days(event_timestamp)")
+
+# Delta - explicit partitioning in data source
+# Hudi - configure via properties
+hudi_format.set_property("hoodie.datasource.write.partitionpath.field", "date")
+```
+
+### 2. Enable Optimization Features
+```python
+# Delta auto-optimize
+delta_format.set_property("delta.autoOptimize.optimizeWrite", "true")
+delta_format.set_property("delta.autoOptimize.autoCompact", "true")
+
+# Hudi compaction
+hudi_format.set_property("hoodie.compact.inline", "true")
+```
+
+### 3. Manage Table History
+```python
+# Regularly clean up old snapshots/versions
+# For Iceberg: Use expire_snapshots() procedure
+# For Delta: Use VACUUM command
+# For Hudi: Configure retention policies
+```
+
+### 4. Monitor Metadata Size
+- Table formats maintain metadata for all operations
+- Monitor metadata size and clean up old versions
+- Configure retention policies based on your needs
+
+### 5. Test Schema Evolution
+```python
+# Always test schema changes in non-production first
+# Ensure backward compatibility
+# Use proper migration procedures
+```
+
+## Data Source Support
+
+Currently, table formats are supported with:
+- [Spark data source](spark.md) - Full support for Iceberg, Delta, and Hudi
+
+Future support planned for:
+- BigQuery (Iceberg)
+- Snowflake (Iceberg)
+- Other data sources
+
+## See Also
+
+- [Spark Data Source](spark.md)
+- [Apache Iceberg Documentation](https://iceberg.apache.org/docs/latest/)
+- [Delta Lake Documentation](https://docs.delta.io/latest/index.html)
+- [Apache Hudi Documentation](https://hudi.apache.org/docs/overview)
+- [Python API Reference - TableFormat](https://rtd.feast.dev/en/master/#feast.table_format)
\ No newline at end of file
diff --git a/docs/reference/offline-stores/README.md b/docs/reference/offline-stores/README.md
index ab25fe9a276..b5e2bccbdd1 100644
--- a/docs/reference/offline-stores/README.md
+++ b/docs/reference/offline-stores/README.md
@@ -45,3 +45,7 @@ Please see [Offline Store](../../getting-started/components/offline-store.md) fo
{% content-ref url="mssql.md" %}
[mssql.md](mssql.md)
{% endcontent-ref %}
+
+{% content-ref url="ray.md" %}
+[ray.md](ray.md)
+{% endcontent-ref %}
diff --git a/docs/reference/offline-stores/overview.md b/docs/reference/offline-stores/overview.md
index 191ccd21a64..24d37da22f1 100644
--- a/docs/reference/offline-stores/overview.md
+++ b/docs/reference/offline-stores/overview.md
@@ -26,33 +26,33 @@ The first three of these methods all return a `RetrievalJob` specific to an offl
## Functionality Matrix
There are currently four core offline store implementations: `DaskOfflineStore`, `BigQueryOfflineStore`, `SnowflakeOfflineStore`, and `RedshiftOfflineStore`.
-There are several additional implementations contributed by the Feast community (`PostgreSQLOfflineStore`, `SparkOfflineStore`, and `TrinoOfflineStore`), which are not guaranteed to be stable or to match the functionality of the core implementations.
+There are several additional implementations contributed by the Feast community (`PostgreSQLOfflineStore`, `SparkOfflineStore`, `TrinoOfflineStore`, and `RayOfflineStore`), which are not guaranteed to be stable or to match the functionality of the core implementations.
Details for each specific offline store, such as how to configure it in a `feature_store.yaml`, can be found [here](README.md).
Below is a matrix indicating which offline stores support which methods.
-| | Dask | BigQuery | Snowflake | Redshift | Postgres | Spark | Trino | Couchbase |
-| :-------------------------------- | :-- | :-- | :-- | :-- | :-- | :-- | :-- | :-- |
-| `get_historical_features` | yes | yes | yes | yes | yes | yes | yes | yes |
-| `pull_latest_from_table_or_query` | yes | yes | yes | yes | yes | yes | yes | yes |
-| `pull_all_from_table_or_query` | yes | yes | yes | yes | yes | yes | yes | yes |
-| `offline_write_batch` | yes | yes | yes | yes | no | no | no | no |
-| `write_logged_features` | yes | yes | yes | yes | no | no | no | no |
+|| | Dask | BigQuery | Snowflake | Redshift | Postgres | Spark | Trino | Couchbase | Ray |
+|| :-------------------------------- | :-- | :-- | :-- | :-- | :-- | :-- | :-- | :-- | :-- |
+|| `get_historical_features` | yes | yes | yes | yes | yes | yes | yes | yes | yes |
+|| `pull_latest_from_table_or_query` | yes | yes | yes | yes | yes | yes | yes | yes | yes |
+|| `pull_all_from_table_or_query` | yes | yes | yes | yes | yes | yes | yes | yes | yes |
+|| `offline_write_batch` | yes | yes | yes | yes | no | no | no | no | yes |
+|| `write_logged_features` | yes | yes | yes | yes | no | no | no | no | yes |
Below is a matrix indicating which `RetrievalJob`s support what functionality.
-| | Dask | BigQuery | Snowflake | Redshift | Postgres | Spark | Trino | DuckDB | Couchbase |
-| --------------------------------- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
-| export to dataframe | yes | yes | yes | yes | yes | yes | yes | yes | yes |
-| export to arrow table | yes | yes | yes | yes | yes | yes | yes | yes | yes |
-| export to arrow batches | no | no | no | yes | no | no | no | no | no |
-| export to SQL | no | yes | yes | yes | yes | no | yes | no | yes |
-| export to data lake (S3, GCS, etc.) | no | no | yes | no | yes | no | no | no | yes |
-| export to data warehouse | no | yes | yes | yes | yes | no | no | no | yes |
-| export as Spark dataframe | no | no | yes | no | no | yes | no | no | no |
-| local execution of Python-based on-demand transforms | yes | yes | yes | yes | yes | no | yes | yes | yes |
-| remote execution of Python-based on-demand transforms | no | no | no | no | no | no | no | no | no |
-| persist results in the offline store | yes | yes | yes | yes | yes | yes | no | yes | yes |
-| preview the query plan before execution | yes | yes | yes | yes | yes | yes | yes | no | yes |
-| read partitioned data | yes | yes | yes | yes | yes | yes | yes | yes | yes |
+|| | Dask | BigQuery | Snowflake | Redshift | Postgres | Spark | Trino | DuckDB | Couchbase | Ray |
+|| --------------------------------- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+|| export to dataframe | yes | yes | yes | yes | yes | yes | yes | yes | yes | yes |
+|| export to arrow table | yes | yes | yes | yes | yes | yes | yes | yes | yes | yes |
+|| export to arrow batches | no | no | no | yes | no | no | no | no | no | no |
+|| export to SQL | no | yes | yes | yes | yes | no | yes | no | yes | no |
+|| export to data lake (S3, GCS, etc.) | no | no | yes | no | yes | no | no | no | yes | yes |
+|| export to data warehouse | no | yes | yes | yes | yes | no | no | no | yes | no |
+|| export as Spark dataframe | no | no | yes | no | no | yes | no | no | no | no |
+|| local execution of Python-based on-demand transforms | yes | yes | yes | yes | yes | no | yes | yes | yes | yes |
+|| remote execution of Python-based on-demand transforms | no | no | no | no | no | no | no | no | no | no |
+|| persist results in the offline store | yes | yes | yes | yes | yes | yes | no | yes | yes | yes |
+|| preview the query plan before execution | yes | yes | yes | yes | yes | yes | yes | no | yes | yes |
+|| read partitioned data | yes | yes | yes | yes | yes | yes | yes | yes | yes | yes |
\ No newline at end of file
diff --git a/docs/reference/offline-stores/ray.md b/docs/reference/offline-stores/ray.md
index a46102ee132..89040f05c94 100644
--- a/docs/reference/offline-stores/ray.md
+++ b/docs/reference/offline-stores/ray.md
@@ -5,6 +5,23 @@
The Ray offline store is a data I/O implementation that leverages [Ray](https://www.ray.io/) for reading and writing data from various sources. It focuses on efficient data access operations, while complex feature computation is handled by the [Ray Compute Engine](../compute-engine/ray.md).
+## Quick Start with Ray Template
+
+The easiest way to get started with Ray offline store is to use the built-in Ray template:
+
+```bash
+feast init -t ray my_ray_project
+cd my_ray_project/feature_repo
+```
+
+This template includes:
+- Pre-configured Ray offline store and compute engine setup
+- Sample feature definitions optimized for Ray processing
+- Demo workflow showcasing Ray capabilities
+- Resource settings for local development
+
+The template provides a complete working example with sample datasets and demonstrates both Ray offline store data I/O operations and Ray compute engine distributed processing.
+
## Overview
The Ray offline store provides:
diff --git a/docs/reference/online-stores/mysql.md b/docs/reference/online-stores/mysql.md
index 8868e64279d..2f9650f8916 100644
--- a/docs/reference/online-stores/mysql.md
+++ b/docs/reference/online-stores/mysql.md
@@ -28,6 +28,28 @@ online_store:
The full set of configuration options is available in [MySQLOnlineStoreConfig](https://rtd.feast.dev/en/master/#feast.infra.online_stores.mysql_online_store.MySQLOnlineStoreConfig).
+## Batch write mode
+By default, the MySQL online store performs row-by-row insert and commit for each feature record. While this ensures per-record atomicity, it can lead to significant overhead on write operations — especially on distributed SQL databases (for example, TiDB, which is MySQL-compatible and uses a consensus protocol).
+
+To improve writing performance, you can enable batch write mode by setting `batch_write` to `true` and `batch_size`, which executes multiple insert queries in batches and commits them together per batch instead of committing each record individually.
+
+{% code title="feature_store.yaml" %}
+```yaml
+project: my_feature_repo
+registry: data/registry.db
+provider: local
+online_store:
+ type: mysql
+ host: DB_HOST
+ port: DB_PORT
+ database: DB_NAME
+ user: DB_USERNAME
+ password: DB_PASSWORD
+ batch_write: true
+ batch_size: 100
+```
+{% endcode %}
+
## Functionality Matrix
The set of functionality supported by online stores is described in detail [here](overview.md#functionality).
diff --git a/infra/charts/feast-feature-server/Chart.yaml b/infra/charts/feast-feature-server/Chart.yaml
index eaf14f21fe6..70f98bf8190 100644
--- a/infra/charts/feast-feature-server/Chart.yaml
+++ b/infra/charts/feast-feature-server/Chart.yaml
@@ -2,7 +2,7 @@ apiVersion: v2
name: feast-feature-server
description: Feast Feature Server in Go or Python
type: application
-version: 0.56.0
+version: 0.57.0
keywords:
- machine learning
- big data
diff --git a/infra/charts/feast-feature-server/README.md b/infra/charts/feast-feature-server/README.md
index e73be95a909..48dcac6904f 100644
--- a/infra/charts/feast-feature-server/README.md
+++ b/infra/charts/feast-feature-server/README.md
@@ -1,6 +1,6 @@
# Feast Python / Go Feature Server Helm Charts
-Current chart version is `0.56.0`
+Current chart version is `0.57.0`
## Installation
@@ -42,7 +42,7 @@ See [here](https://github.com/feast-dev/feast/tree/master/examples/python-helm-d
| fullnameOverride | string | `""` | |
| image.pullPolicy | string | `"IfNotPresent"` | |
| image.repository | string | `"quay.io/feastdev/feature-server"` | Docker image for Feature Server repository |
-| image.tag | string | `"0.56.0"` | The Docker image tag (can be overwritten if custom feature server deps are needed for on demand transforms) |
+| image.tag | string | `"0.57.0"` | The Docker image tag (can be overwritten if custom feature server deps are needed for on demand transforms) |
| imagePullSecrets | list | `[]` | |
| livenessProbe.initialDelaySeconds | int | `30` | |
| livenessProbe.periodSeconds | int | `30` | |
diff --git a/infra/charts/feast-feature-server/values.yaml b/infra/charts/feast-feature-server/values.yaml
index 0f94b5bc579..452a4579f5c 100644
--- a/infra/charts/feast-feature-server/values.yaml
+++ b/infra/charts/feast-feature-server/values.yaml
@@ -9,7 +9,7 @@ image:
repository: quay.io/feastdev/feature-server
pullPolicy: IfNotPresent
# image.tag -- The Docker image tag (can be overwritten if custom feature server deps are needed for on demand transforms)
- tag: 0.56.0
+ tag: 0.57.0
logLevel: "WARNING" # Set log level DEBUG, INFO, WARNING, ERROR, and CRITICAL (case-insensitive)
diff --git a/infra/charts/feast/Chart.yaml b/infra/charts/feast/Chart.yaml
index 307e01563cd..d5c4ed68f1b 100644
--- a/infra/charts/feast/Chart.yaml
+++ b/infra/charts/feast/Chart.yaml
@@ -1,7 +1,7 @@
apiVersion: v1
description: Feature store for machine learning
name: feast
-version: 0.56.0
+version: 0.57.0
keywords:
- machine learning
- big data
diff --git a/infra/charts/feast/README.md b/infra/charts/feast/README.md
index dca35b67065..91493736a07 100644
--- a/infra/charts/feast/README.md
+++ b/infra/charts/feast/README.md
@@ -8,7 +8,7 @@ This repo contains Helm charts for Feast Java components that are being installe
## Chart: Feast
-Feature store for machine learning Current chart version is `0.56.0`
+Feature store for machine learning Current chart version is `0.57.0`
## Installation
@@ -65,8 +65,8 @@ See [here](https://github.com/feast-dev/feast/tree/master/examples/java-demo) fo
| Repository | Name | Version |
|------------|------|---------|
| https://charts.helm.sh/stable | redis | 10.5.6 |
-| https://feast-helm-charts.storage.googleapis.com | feature-server(feature-server) | 0.56.0 |
-| https://feast-helm-charts.storage.googleapis.com | transformation-service(transformation-service) | 0.56.0 |
+| https://feast-helm-charts.storage.googleapis.com | feature-server(feature-server) | 0.57.0 |
+| https://feast-helm-charts.storage.googleapis.com | transformation-service(transformation-service) | 0.57.0 |
## Values
diff --git a/infra/charts/feast/charts/feature-server/Chart.yaml b/infra/charts/feast/charts/feature-server/Chart.yaml
index 43a7e41c3ab..99f22582d38 100644
--- a/infra/charts/feast/charts/feature-server/Chart.yaml
+++ b/infra/charts/feast/charts/feature-server/Chart.yaml
@@ -1,8 +1,8 @@
apiVersion: v1
description: "Feast Feature Server: Online feature serving service for Feast"
name: feature-server
-version: 0.56.0
-appVersion: v0.56.0
+version: 0.57.0
+appVersion: v0.57.0
keywords:
- machine learning
- big data
diff --git a/infra/charts/feast/charts/feature-server/README.md b/infra/charts/feast/charts/feature-server/README.md
index 46159a543c5..21b234dd245 100644
--- a/infra/charts/feast/charts/feature-server/README.md
+++ b/infra/charts/feast/charts/feature-server/README.md
@@ -1,6 +1,6 @@
# feature-server
- 
+ 
Feast Feature Server: Online feature serving service for Feast
@@ -17,7 +17,7 @@ Feast Feature Server: Online feature serving service for Feast
| envOverrides | object | `{}` | Extra environment variables to set |
| image.pullPolicy | string | `"IfNotPresent"` | Image pull policy |
| image.repository | string | `"quay.io/feastdev/feature-server-java"` | Docker image for Feature Server repository |
-| image.tag | string | `"0.56.0"` | Image tag |
+| image.tag | string | `"0.57.0"` | Image tag |
| ingress.grpc.annotations | object | `{}` | Extra annotations for the ingress |
| ingress.grpc.auth.enabled | bool | `false` | Flag to enable auth |
| ingress.grpc.class | string | `"nginx"` | Which ingress controller to use |
diff --git a/infra/charts/feast/charts/feature-server/values.yaml b/infra/charts/feast/charts/feature-server/values.yaml
index c054158be62..d0a74ad3ba5 100644
--- a/infra/charts/feast/charts/feature-server/values.yaml
+++ b/infra/charts/feast/charts/feature-server/values.yaml
@@ -5,7 +5,7 @@ image:
# image.repository -- Docker image for Feature Server repository
repository: quay.io/feastdev/feature-server-java
# image.tag -- Image tag
- tag: 0.56.0
+ tag: 0.57.0
# image.pullPolicy -- Image pull policy
pullPolicy: IfNotPresent
diff --git a/infra/charts/feast/charts/transformation-service/Chart.yaml b/infra/charts/feast/charts/transformation-service/Chart.yaml
index 10c15403d9d..83690118ff3 100644
--- a/infra/charts/feast/charts/transformation-service/Chart.yaml
+++ b/infra/charts/feast/charts/transformation-service/Chart.yaml
@@ -1,8 +1,8 @@
apiVersion: v1
description: "Transformation service: to compute on-demand features"
name: transformation-service
-version: 0.56.0
-appVersion: v0.56.0
+version: 0.57.0
+appVersion: v0.57.0
keywords:
- machine learning
- big data
diff --git a/infra/charts/feast/charts/transformation-service/README.md b/infra/charts/feast/charts/transformation-service/README.md
index 716d5f9332b..23a4e2e491c 100644
--- a/infra/charts/feast/charts/transformation-service/README.md
+++ b/infra/charts/feast/charts/transformation-service/README.md
@@ -1,6 +1,6 @@
# transformation-service
- 
+ 
Transformation service: to compute on-demand features
@@ -13,7 +13,7 @@ Transformation service: to compute on-demand features
| envOverrides | object | `{}` | Extra environment variables to set |
| image.pullPolicy | string | `"IfNotPresent"` | Image pull policy |
| image.repository | string | `"quay.io/feastdev/feature-transformation-server"` | Docker image for Transformation Server repository |
-| image.tag | string | `"0.56.0"` | Image tag |
+| image.tag | string | `"0.57.0"` | Image tag |
| nodeSelector | object | `{}` | Node labels for pod assignment |
| podLabels | object | `{}` | Labels to be added to Feast Serving pods |
| replicaCount | int | `1` | Number of pods that will be created |
diff --git a/infra/charts/feast/charts/transformation-service/values.yaml b/infra/charts/feast/charts/transformation-service/values.yaml
index fe805f0bed1..fad48630231 100644
--- a/infra/charts/feast/charts/transformation-service/values.yaml
+++ b/infra/charts/feast/charts/transformation-service/values.yaml
@@ -5,7 +5,7 @@ image:
# image.repository -- Docker image for Transformation Server repository
repository: quay.io/feastdev/feature-transformation-server
# image.tag -- Image tag
- tag: 0.56.0
+ tag: 0.57.0
# image.pullPolicy -- Image pull policy
pullPolicy: IfNotPresent
diff --git a/infra/charts/feast/requirements.yaml b/infra/charts/feast/requirements.yaml
index 2ef611c9a0e..e55c068f904 100644
--- a/infra/charts/feast/requirements.yaml
+++ b/infra/charts/feast/requirements.yaml
@@ -1,12 +1,12 @@
dependencies:
- name: feature-server
alias: feature-server
- version: 0.56.0
+ version: 0.57.0
condition: feature-server.enabled
repository: https://feast-helm-charts.storage.googleapis.com
- name: transformation-service
alias: transformation-service
- version: 0.56.0
+ version: 0.57.0
condition: transformation-service.enabled
repository: https://feast-helm-charts.storage.googleapis.com
- name: redis
diff --git a/infra/feast-operator/Makefile b/infra/feast-operator/Makefile
index 9541ed99656..809b8d12c63 100644
--- a/infra/feast-operator/Makefile
+++ b/infra/feast-operator/Makefile
@@ -3,7 +3,7 @@
# To re-generate a bundle for another specific version without changing the standard setup, you can:
# - use the VERSION as arg of the bundle target (e.g make bundle VERSION=0.0.2)
# - use environment variables to overwrite this value (e.g export VERSION=0.0.2)
-VERSION ?= 0.56.0
+VERSION ?= 0.57.0
# CHANNELS define the bundle channels used in the bundle.
# Add a new line here if you would like to change its default config. (E.g CHANNELS = "candidate,fast,stable")
diff --git a/infra/feast-operator/api/feastversion/version.go b/infra/feast-operator/api/feastversion/version.go
index 9279475e53d..1e3985859ee 100644
--- a/infra/feast-operator/api/feastversion/version.go
+++ b/infra/feast-operator/api/feastversion/version.go
@@ -17,4 +17,4 @@ limitations under the License.
package feastversion
// Feast release version. Keep on line #20, this is critical to release CI
-const FeastVersion = "0.56.0"
+const FeastVersion = "0.57.0"
diff --git a/infra/feast-operator/api/v1alpha1/featurestore_types.go b/infra/feast-operator/api/v1alpha1/featurestore_types.go
index 9250309b1cc..243827a487c 100644
--- a/infra/feast-operator/api/v1alpha1/featurestore_types.go
+++ b/infra/feast-operator/api/v1alpha1/featurestore_types.go
@@ -111,6 +111,9 @@ type FeastInitOptions struct {
// FeastCronJob defines a CronJob to execute against a Feature Store deployment.
type FeastCronJob struct {
+ // Annotations to be added to the CronJob metadata.
+ Annotations map[string]string `json:"annotations,omitempty"`
+
// Specification of the desired behavior of a job.
JobSpec *JobSpec `json:"jobSpec,omitempty"`
ContainerConfigs *CronJobContainerConfigs `json:"containerConfigs,omitempty"`
diff --git a/infra/feast-operator/api/v1alpha1/zz_generated.deepcopy.go b/infra/feast-operator/api/v1alpha1/zz_generated.deepcopy.go
index 7ea04929b3d..15c61cc86d6 100644
--- a/infra/feast-operator/api/v1alpha1/zz_generated.deepcopy.go
+++ b/infra/feast-operator/api/v1alpha1/zz_generated.deepcopy.go
@@ -114,6 +114,13 @@ func (in *DefaultCtrConfigs) DeepCopy() *DefaultCtrConfigs {
// DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.
func (in *FeastCronJob) DeepCopyInto(out *FeastCronJob) {
*out = *in
+ if in.Annotations != nil {
+ in, out := &in.Annotations, &out.Annotations
+ *out = make(map[string]string, len(*in))
+ for key, val := range *in {
+ (*out)[key] = val
+ }
+ }
if in.JobSpec != nil {
in, out := &in.JobSpec, &out.JobSpec
*out = new(JobSpec)
diff --git a/infra/feast-operator/bundle/manifests/feast-operator.clusterserviceversion.yaml b/infra/feast-operator/bundle/manifests/feast-operator.clusterserviceversion.yaml
index 78205683183..244f9565905 100644
--- a/infra/feast-operator/bundle/manifests/feast-operator.clusterserviceversion.yaml
+++ b/infra/feast-operator/bundle/manifests/feast-operator.clusterserviceversion.yaml
@@ -50,10 +50,10 @@ metadata:
}
]
capabilities: Basic Install
- createdAt: "2025-10-27T20:28:39Z"
+ createdAt: "2025-11-13T20:26:23Z"
operators.operatorframework.io/builder: operator-sdk-v1.38.0
operators.operatorframework.io/project_layout: go.kubebuilder.io/v4
- name: feast-operator.v0.56.0
+ name: feast-operator.v0.57.0
namespace: placeholder
spec:
apiservicedefinitions: {}
@@ -225,10 +225,10 @@ spec:
- /manager
env:
- name: RELATED_IMAGE_FEATURE_SERVER
- value: quay.io/feastdev/feature-server:0.56.0
+ value: quay.io/feastdev/feature-server:0.57.0
- name: RELATED_IMAGE_CRON_JOB
value: quay.io/openshift/origin-cli:4.17
- image: quay.io/feastdev/feast-operator:0.56.0
+ image: quay.io/feastdev/feast-operator:0.57.0
livenessProbe:
httpGet:
path: /healthz
@@ -318,8 +318,8 @@ spec:
name: Feast Community
url: https://lf-aidata.atlassian.net/wiki/spaces/FEAST/
relatedImages:
- - image: quay.io/feastdev/feature-server:0.56.0
+ - image: quay.io/feastdev/feature-server:0.57.0
name: feature-server
- image: quay.io/openshift/origin-cli:4.17
name: cron-job
- version: 0.56.0
+ version: 0.57.0
diff --git a/infra/feast-operator/bundle/manifests/feast.dev_featurestores.yaml b/infra/feast-operator/bundle/manifests/feast.dev_featurestores.yaml
index 9c0c09d141a..3a99b2e7a70 100644
--- a/infra/feast-operator/bundle/manifests/feast.dev_featurestores.yaml
+++ b/infra/feast-operator/bundle/manifests/feast.dev_featurestores.yaml
@@ -87,6 +87,11 @@ spec:
description: FeastCronJob defines a CronJob to execute against a Feature
Store deployment.
properties:
+ annotations:
+ additionalProperties:
+ type: string
+ description: Annotations to be added to the CronJob metadata.
+ type: object
concurrencyPolicy:
description: Specifies how to treat concurrent executions of a
Job.
@@ -4063,6 +4068,11 @@ spec:
description: FeastCronJob defines a CronJob to execute against
a Feature Store deployment.
properties:
+ annotations:
+ additionalProperties:
+ type: string
+ description: Annotations to be added to the CronJob metadata.
+ type: object
concurrencyPolicy:
description: Specifies how to treat concurrent executions
of a Job.
diff --git a/infra/feast-operator/config/component_metadata.yaml b/infra/feast-operator/config/component_metadata.yaml
index cda672ead9a..fd776ac19bb 100644
--- a/infra/feast-operator/config/component_metadata.yaml
+++ b/infra/feast-operator/config/component_metadata.yaml
@@ -1,5 +1,5 @@
# This file is required to configure Feast release information for ODH/RHOAI Operator
releases:
- name: Feast
- version: 0.56.0
+ version: 0.57.0
repoUrl: https://github.com/feast-dev/feast
diff --git a/infra/feast-operator/config/crd/bases/feast.dev_featurestores.yaml b/infra/feast-operator/config/crd/bases/feast.dev_featurestores.yaml
index c964d46c27d..9264cfecf49 100644
--- a/infra/feast-operator/config/crd/bases/feast.dev_featurestores.yaml
+++ b/infra/feast-operator/config/crd/bases/feast.dev_featurestores.yaml
@@ -87,6 +87,11 @@ spec:
description: FeastCronJob defines a CronJob to execute against a Feature
Store deployment.
properties:
+ annotations:
+ additionalProperties:
+ type: string
+ description: Annotations to be added to the CronJob metadata.
+ type: object
concurrencyPolicy:
description: Specifies how to treat concurrent executions of a
Job.
@@ -4063,6 +4068,11 @@ spec:
description: FeastCronJob defines a CronJob to execute against
a Feature Store deployment.
properties:
+ annotations:
+ additionalProperties:
+ type: string
+ description: Annotations to be added to the CronJob metadata.
+ type: object
concurrencyPolicy:
description: Specifies how to treat concurrent executions
of a Job.
diff --git a/infra/feast-operator/config/default/related_image_fs_patch.yaml b/infra/feast-operator/config/default/related_image_fs_patch.yaml
index 30cd7d3616f..e954af1876e 100644
--- a/infra/feast-operator/config/default/related_image_fs_patch.yaml
+++ b/infra/feast-operator/config/default/related_image_fs_patch.yaml
@@ -2,7 +2,7 @@
path: "/spec/template/spec/containers/0/env/0"
value:
name: RELATED_IMAGE_FEATURE_SERVER
- value: quay.io/feastdev/feature-server:0.56.0
+ value: quay.io/feastdev/feature-server:0.57.0
- op: replace
path: "/spec/template/spec/containers/0/env/1"
value:
diff --git a/infra/feast-operator/config/manager/kustomization.yaml b/infra/feast-operator/config/manager/kustomization.yaml
index 80aaa3faf28..8b3405fb024 100644
--- a/infra/feast-operator/config/manager/kustomization.yaml
+++ b/infra/feast-operator/config/manager/kustomization.yaml
@@ -5,4 +5,4 @@ kind: Kustomization
images:
- name: controller
newName: quay.io/feastdev/feast-operator
- newTag: 0.56.0
+ newTag: 0.57.0
diff --git a/infra/feast-operator/config/overlays/odh/params.env b/infra/feast-operator/config/overlays/odh/params.env
index b112bb2d854..2e8ed43f3a2 100644
--- a/infra/feast-operator/config/overlays/odh/params.env
+++ b/infra/feast-operator/config/overlays/odh/params.env
@@ -1,3 +1,3 @@
-RELATED_IMAGE_FEAST_OPERATOR=quay.io/feastdev/feast-operator:0.56.0
-RELATED_IMAGE_FEATURE_SERVER=quay.io/feastdev/feature-server:0.56.0
+RELATED_IMAGE_FEAST_OPERATOR=quay.io/feastdev/feast-operator:0.57.0
+RELATED_IMAGE_FEATURE_SERVER=quay.io/feastdev/feature-server:0.57.0
RELATED_IMAGE_CRON_JOB=quay.io/openshift/origin-cli:4.17
diff --git a/infra/feast-operator/config/overlays/rhoai/params.env b/infra/feast-operator/config/overlays/rhoai/params.env
index f548227235d..c54ad85aa02 100644
--- a/infra/feast-operator/config/overlays/rhoai/params.env
+++ b/infra/feast-operator/config/overlays/rhoai/params.env
@@ -1,3 +1,3 @@
-RELATED_IMAGE_FEAST_OPERATOR=quay.io/feastdev/feast-operator:0.56.0
-RELATED_IMAGE_FEATURE_SERVER=quay.io/feastdev/feature-server:0.56.0
+RELATED_IMAGE_FEAST_OPERATOR=quay.io/feastdev/feast-operator:0.57.0
+RELATED_IMAGE_FEATURE_SERVER=quay.io/feastdev/feature-server:0.57.0
RELATED_IMAGE_CRON_JOB=registry.redhat.io/openshift4/ose-cli@sha256:bc35a9fc663baf0d6493cc57e89e77a240a36c43cf38fb78d8e61d3b87cf5cc5
\ No newline at end of file
diff --git a/infra/feast-operator/dist/install.yaml b/infra/feast-operator/dist/install.yaml
index 58886675ec1..4b725af55eb 100644
--- a/infra/feast-operator/dist/install.yaml
+++ b/infra/feast-operator/dist/install.yaml
@@ -95,6 +95,11 @@ spec:
description: FeastCronJob defines a CronJob to execute against a Feature
Store deployment.
properties:
+ annotations:
+ additionalProperties:
+ type: string
+ description: Annotations to be added to the CronJob metadata.
+ type: object
concurrencyPolicy:
description: Specifies how to treat concurrent executions of a
Job.
@@ -4071,6 +4076,11 @@ spec:
description: FeastCronJob defines a CronJob to execute against
a Feature Store deployment.
properties:
+ annotations:
+ additionalProperties:
+ type: string
+ description: Annotations to be added to the CronJob metadata.
+ type: object
concurrencyPolicy:
description: Specifies how to treat concurrent executions
of a Job.
@@ -8483,10 +8493,10 @@ spec:
- /manager
env:
- name: RELATED_IMAGE_FEATURE_SERVER
- value: quay.io/feastdev/feature-server:0.56.0
+ value: quay.io/feastdev/feature-server:0.57.0
- name: RELATED_IMAGE_CRON_JOB
value: quay.io/openshift/origin-cli:4.17
- image: quay.io/feastdev/feast-operator:0.56.0
+ image: quay.io/feastdev/feast-operator:0.57.0
livenessProbe:
httpGet:
path: /healthz
diff --git a/infra/feast-operator/dist/operator-e2e-tests b/infra/feast-operator/dist/operator-e2e-tests
index 2a8e2a02352..0734ab81a9e 100755
Binary files a/infra/feast-operator/dist/operator-e2e-tests and b/infra/feast-operator/dist/operator-e2e-tests differ
diff --git a/infra/feast-operator/docs/api/markdown/ref.md b/infra/feast-operator/docs/api/markdown/ref.md
index fac7ebfa784..6016a70a1b8 100644
--- a/infra/feast-operator/docs/api/markdown/ref.md
+++ b/infra/feast-operator/docs/api/markdown/ref.md
@@ -98,6 +98,7 @@ _Appears in:_
| Field | Description |
| --- | --- |
+| `annotations` _object (keys:string, values:string)_ | Annotations to be added to the CronJob metadata. |
| `jobSpec` _[JobSpec](#jobspec)_ | Specification of the desired behavior of a job. |
| `containerConfigs` _[CronJobContainerConfigs](#cronjobcontainerconfigs)_ | |
| `schedule` _string_ | The schedule in Cron format, see https://en.wikipedia.org/wiki/Cron. |
diff --git a/infra/feast-operator/internal/controller/services/cronjob.go b/infra/feast-operator/internal/controller/services/cronjob.go
index f15200d22ec..b368133b113 100644
--- a/infra/feast-operator/internal/controller/services/cronjob.go
+++ b/infra/feast-operator/internal/controller/services/cronjob.go
@@ -54,6 +54,12 @@ func (feast *FeastServices) initCronJob() *batchv1.CronJob {
func (feast *FeastServices) setCronJob(cronJob *batchv1.CronJob) error {
appliedCronJob := feast.Handler.FeatureStore.Status.Applied.CronJob
cronJob.Labels = feast.getFeastTypeLabels(CronJobFeastType)
+ if appliedCronJob.Annotations != nil {
+ cronJob.Annotations = make(map[string]string, len(appliedCronJob.Annotations))
+ for k, v := range appliedCronJob.Annotations {
+ cronJob.Annotations[k] = v
+ }
+ }
cronJob.Spec = batchv1.CronJobSpec{
Schedule: appliedCronJob.Schedule,
JobTemplate: batchv1.JobTemplateSpec{
diff --git a/infra/feast-operator/test/api/featurestore_types_test.go b/infra/feast-operator/test/api/featurestore_types_test.go
index 83ac2906ec0..e8b08b549d0 100644
--- a/infra/feast-operator/test/api/featurestore_types_test.go
+++ b/infra/feast-operator/test/api/featurestore_types_test.go
@@ -438,6 +438,35 @@ func registryWithGRPCFalse(featureStore *feastdevv1alpha1.FeatureStore) *feastde
return fsCopy
}
+func cronJobWithAnnotations(featureStore *feastdevv1alpha1.FeatureStore) *feastdevv1alpha1.FeatureStore {
+ fsCopy := featureStore.DeepCopy()
+ fsCopy.Spec.CronJob = &feastdevv1alpha1.FeastCronJob{
+ Annotations: map[string]string{
+ "test-annotation": "test-value",
+ "another-annotation": "another-value",
+ },
+ Schedule: "0 0 * * *",
+ }
+ return fsCopy
+}
+
+func cronJobWithEmptyAnnotations(featureStore *feastdevv1alpha1.FeatureStore) *feastdevv1alpha1.FeatureStore {
+ fsCopy := featureStore.DeepCopy()
+ fsCopy.Spec.CronJob = &feastdevv1alpha1.FeastCronJob{
+ Annotations: map[string]string{},
+ Schedule: "0 0 * * *",
+ }
+ return fsCopy
+}
+
+func cronJobWithoutAnnotations(featureStore *feastdevv1alpha1.FeatureStore) *feastdevv1alpha1.FeatureStore {
+ fsCopy := featureStore.DeepCopy()
+ fsCopy.Spec.CronJob = &feastdevv1alpha1.FeastCronJob{
+ Schedule: "0 0 * * *",
+ }
+ return fsCopy
+}
+
func quotedSlice(stringSlice []string) string {
quotedSlice := make([]string, len(stringSlice))
@@ -645,4 +674,76 @@ var _ = Describe("FeatureStore API", func() {
})
})
})
+
+ Context("When creating a CronJob", func() {
+ ctx := context.Background()
+
+ BeforeEach(func() {
+ By("verifying the custom resource FeatureStore is not there")
+ resource := &feastdevv1alpha1.FeatureStore{}
+ err := k8sClient.Get(ctx, typeNamespacedName, resource)
+ Expect(err != nil && errors.IsNotFound(err)).To(BeTrue())
+ })
+ AfterEach(func() {
+ By("Cleaning up the test resource")
+ resource := &feastdevv1alpha1.FeatureStore{}
+ err := k8sClient.Get(ctx, typeNamespacedName, resource)
+ if err == nil {
+ Expect(k8sClient.Delete(ctx, resource)).To(Succeed())
+ }
+ err = k8sClient.Get(ctx, typeNamespacedName, resource)
+ Expect(err != nil && errors.IsNotFound(err)).To(BeTrue())
+ })
+
+ Context("with annotations", func() {
+ It("should succeed when annotations are provided", func() {
+ featurestore := createFeatureStore()
+ resource := cronJobWithAnnotations(featurestore)
+ Expect(k8sClient.Create(ctx, resource)).To(Succeed())
+ })
+
+ It("should succeed when annotations are empty", func() {
+ featurestore := createFeatureStore()
+ resource := cronJobWithEmptyAnnotations(featurestore)
+ Expect(k8sClient.Create(ctx, resource)).To(Succeed())
+ })
+
+ It("should succeed when annotations are not specified", func() {
+ featurestore := createFeatureStore()
+ resource := cronJobWithoutAnnotations(featurestore)
+ Expect(k8sClient.Create(ctx, resource)).To(Succeed())
+ })
+
+ It("should apply the annotations correctly in the status", func() {
+ featurestore := createFeatureStore()
+ resource := cronJobWithAnnotations(featurestore)
+ services.ApplyDefaultsToStatus(resource)
+
+ Expect(resource.Status.Applied.CronJob).NotTo(BeNil())
+ Expect(resource.Status.Applied.CronJob.Annotations).NotTo(BeNil())
+ Expect(resource.Status.Applied.CronJob.Annotations).To(HaveLen(2))
+ Expect(resource.Status.Applied.CronJob.Annotations["test-annotation"]).To(Equal("test-value"))
+ Expect(resource.Status.Applied.CronJob.Annotations["another-annotation"]).To(Equal("another-value"))
+ })
+
+ It("should keep empty annotations in the status", func() {
+ featurestore := createFeatureStore()
+ resource := cronJobWithEmptyAnnotations(featurestore)
+ services.ApplyDefaultsToStatus(resource)
+
+ Expect(resource.Status.Applied.CronJob).NotTo(BeNil())
+ Expect(resource.Status.Applied.CronJob.Annotations).NotTo(BeNil())
+ Expect(resource.Status.Applied.CronJob.Annotations).To(BeEmpty())
+ })
+
+ It("should have nil annotations in status when not specified", func() {
+ featurestore := createFeatureStore()
+ resource := cronJobWithoutAnnotations(featurestore)
+ services.ApplyDefaultsToStatus(resource)
+
+ Expect(resource.Status.Applied.CronJob).NotTo(BeNil())
+ Expect(resource.Status.Applied.CronJob.Annotations).To(BeNil())
+ })
+ })
+ })
})
diff --git a/infra/feast-operator/test/e2e_rhoai/resources/custom-nb.yaml b/infra/feast-operator/test/e2e_rhoai/resources/custom-nb.yaml
index 8c91cdc5f34..f23fd5f008f 100644
--- a/infra/feast-operator/test/e2e_rhoai/resources/custom-nb.yaml
+++ b/infra/feast-operator/test/e2e_rhoai/resources/custom-nb.yaml
@@ -9,9 +9,8 @@ apiVersion: kubeflow.org/v1
kind: Notebook
metadata:
annotations:
- notebooks.opendatahub.io/inject-oauth: "true"
+ notebooks.opendatahub.io/inject-auth: "true"
notebooks.opendatahub.io/last-size-selection: Small
- notebooks.opendatahub.io/oauth-logout-url: https://odh-dashboard-{{.OpenDataHubNamespace}}.{{.IngressDomain}}/notebookController/kube-3aadmin/home
opendatahub.io/link: https://jupyter-nb-kube-3aadmin-{{.Namespace}}.{{.IngressDomain}}/notebook/{{.Namespace}}/jupyter-nb-kube-3aadmin
opendatahub.io/username: {{.Username}}
generation: 1
@@ -78,80 +77,12 @@ spec:
- mountPath: /opt/app-root/notebooks
name: {{.NotebookConfigMapName}}
workingDir: /opt/app-root/src
- - args:
- - --provider=openshift
- - --https-address=:8443
- - --http-address=
- - --openshift-service-account=jupyter-nb-kube-3aadmin
- - --cookie-secret-file=/etc/oauth/config/cookie_secret
- - --cookie-expire=24h0m0s
- - --tls-cert=/etc/tls/private/tls.crt
- - --tls-key=/etc/tls/private/tls.key
- - --upstream=http://localhost:8888
- - --upstream-ca=/var/run/secrets/kubernetes.io/serviceaccount/ca.crt
- - --skip-auth-regex=^(?:/notebook/test-feast-wb/jupyter-nb-kube-3aadmin)?/api$
- - --email-domain=*
- - --skip-provider-button
- - --openshift-sar={"verb":"get","resource":"notebooks","resourceAPIGroup":"kubeflow.org","resourceName":"jupyter-nb-kube-3aadmin","namespace":$(NAMESPACE)}
- - --logout-url=https://odh-dashboard-{{.OpenDataHubNamespace}}.{{.IngressDomain}}/notebookController/kube-3aadmin/home
- env:
- - name: NAMESPACE
- valueFrom:
- fieldRef:
- fieldPath: metadata.namespace
- image: registry.redhat.io/openshift4/ose-oauth-proxy:v4.10
- imagePullPolicy: Always
- livenessProbe:
- failureThreshold: 3
- httpGet:
- path: /oauth/healthz
- port: oauth-proxy
- scheme: HTTPS
- initialDelaySeconds: 30
- periodSeconds: 5
- successThreshold: 1
- timeoutSeconds: 1
- name: oauth-proxy
- ports:
- - containerPort: 8443
- name: oauth-proxy
- protocol: TCP
- readinessProbe:
- failureThreshold: 3
- httpGet:
- path: /oauth/healthz
- port: oauth-proxy
- scheme: HTTPS
- initialDelaySeconds: 5
- periodSeconds: 5
- successThreshold: 1
- timeoutSeconds: 1
- resources:
- limits:
- cpu: 100m
- memory: 64Mi
- requests:
- cpu: 100m
- memory: 64Mi
- volumeMounts:
- - mountPath: /etc/oauth/config
- name: oauth-config
- - mountPath: /etc/tls/private
- name: tls-certificates
enableServiceLinks: false
- serviceAccountName: jupyter-nb-kube-3aadmin
+ serviceAccountName: default
volumes:
- name: jupyterhub-nb-kube-3aadmin-pvc
persistentVolumeClaim:
claimName: {{.NotebookPVC}}
- - name: oauth-config
- secret:
- defaultMode: 420
- secretName: jupyter-nb-kube-3aadmin-oauth-config
- - name: tls-certificates
- secret:
- defaultMode: 420
- secretName: jupyter-nb-kube-3aadmin-tls
- name: {{.NotebookConfigMapName}}
configMap:
name: {{.NotebookConfigMapName}}
diff --git a/infra/feast-operator/test/testdata/feast_integration_test_crs/feast.yaml b/infra/feast-operator/test/testdata/feast_integration_test_crs/feast.yaml
index 8d311ab1de1..4a834c63e34 100644
--- a/infra/feast-operator/test/testdata/feast_integration_test_crs/feast.yaml
+++ b/infra/feast-operator/test/testdata/feast_integration_test_crs/feast.yaml
@@ -7,7 +7,7 @@ stringData:
redis: |
connection_string: redis.test-ns-feast.svc.cluster.local:6379
sql: |
- path: postgresql+psycopg://${POSTGRES_USER}:${POSTGRES_PASSWORD}@postgres.test-ns-feast.svc.cluster.local:5432/${POSTGRES_DB}
+ path: postgresql+psycopg://${POSTGRESQL_USER}:${POSTGRESQL_PASSWORD}@postgres.test-ns-feast.svc.cluster.local:5432/${POSTGRESQL_DATABASE}
cache_ttl_seconds: 60
sqlalchemy_config_kwargs:
echo: false
diff --git a/infra/feast-operator/test/testdata/feast_integration_test_crs/postgres.yaml b/infra/feast-operator/test/testdata/feast_integration_test_crs/postgres.yaml
index f6799e1c700..8fbb11cf1cd 100644
--- a/infra/feast-operator/test/testdata/feast_integration_test_crs/postgres.yaml
+++ b/infra/feast-operator/test/testdata/feast_integration_test_crs/postgres.yaml
@@ -4,9 +4,9 @@ metadata:
name: postgres-secret
namespace: test-ns-feast
stringData:
- POSTGRES_DB: feast
- POSTGRES_USER: feast
- POSTGRES_PASSWORD: feast
+ POSTGRESQL_DATABASE: feast
+ POSTGRESQL_USER: feast
+ POSTGRESQL_PASSWORD: feast
---
apiVersion: apps/v1
kind: Deployment
@@ -25,7 +25,7 @@ spec:
spec:
containers:
- name: postgres
- image: 'postgres:16-alpine'
+ image: 'quay.io/sclorg/postgresql-16-c9s@sha256:5879226a0fd2ea295df6836cc30ab624d2a1c51b81b3406284885604e10ddefe'
ports:
- containerPort: 5432
envFrom:
diff --git a/infra/feast-operator/test/testdata/feast_integration_test_crs/redis.yaml b/infra/feast-operator/test/testdata/feast_integration_test_crs/redis.yaml
index 57f2765e97e..cd88fb88fe5 100644
--- a/infra/feast-operator/test/testdata/feast_integration_test_crs/redis.yaml
+++ b/infra/feast-operator/test/testdata/feast_integration_test_crs/redis.yaml
@@ -15,7 +15,7 @@ spec:
spec:
containers:
- name: redis
- image: 'quay.io/sclorg/redis-7-c9s'
+ image: 'quay.io/sclorg/redis-7-c9s@sha256:ce07d358cea749e67bcc77f73b2c5244d771ac0781ed20d7ebb2ba271c169173'
ports:
- containerPort: 6379
env:
diff --git a/infra/website/docs/blog/feast-ray-distributed-processing.md b/infra/website/docs/blog/feast-ray-distributed-processing.md
new file mode 100644
index 00000000000..cc637da4e68
--- /dev/null
+++ b/infra/website/docs/blog/feast-ray-distributed-processing.md
@@ -0,0 +1,226 @@
+---
+title: "Scaling ML with Feast and Ray: Distributed Processing for Modern AI Applications"
+description: "Learn how Feast's integration with Ray enables distributed processing for both traditional feature engineering and modern RAG applications, with support for Kubernetes deployment through KubeRay."
+date: 2025-10-29
+authors: ["Nikhil Kathole"]
+---
+
+
+
+
+
+
