diff --git a/.gitignore b/.gitignore
index ad641bf..21478e6 100644
--- a/.gitignore
+++ b/.gitignore
@@ -12,4 +12,6 @@ terraform.tfstate.backup
 **/derby.log
 **/metastore_db/*
 .env
-.idea
\ No newline at end of file
+.idea
+.venv
+**/.ipynb_checkpoints
diff --git a/module_5_compute_engine/README.md b/module_5_compute_engine/README.md
new file mode 100644
index 0000000..e39b4c9
--- /dev/null
+++ b/module_5_compute_engine/README.md
@@ -0,0 +1,5 @@
+# Feast Compute Engine Demo
+This is a demo of the Feast Compute Engine, which allows you to run feature transformations(filter, aggregation, custom udf etc.) by specified compute engine.
+
+## Install and Run
+Check notebook [compute_example.ipynb](compute_example.ipynb) for more details.
diff --git a/module_5_compute_engine/compute_example.ipynb b/module_5_compute_engine/compute_example.ipynb
new file mode 100644
index 0000000..4bb2514
--- /dev/null
+++ b/module_5_compute_engine/compute_example.ipynb
@@ -0,0 +1,334 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "application/vnd.databricks.v1+cell": {
+     "inputWidgets": {},
+     "nuid": "0c4646a7-272d-44ec-95fe-3480a267e173",
+     "showTitle": false,
+     "title": ""
+    },
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "zsh:1: no matches found: feast[spark,aws,redis]\r\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pip install feast[spark,postgres,snowflake]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
+   "source": [
+    "## Apply feature definition"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.chdir(\"./feature_repo\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/haoxu/dev/feature_store/feast/sdk/python/feast/batch_feature_view.py:93: RuntimeWarning: Batch feature views are experimental features in alpha development. Some functionality may still be unstable so functionality can change in the future.\n",
+      "  warnings.warn(\n",
+      "WARNING: Using incubator modules: jdk.incubator.vector\n",
+      "Using Spark's default log4j profile: org/apache/spark/log4j2-defaults.properties\n",
+      "Setting default log level to \"WARN\".\n",
+      "To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
+      "25/06/10 20:39:37 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable\n",
+      "25/06/10 20:39:38 WARN Utils: Service 'SparkUI' could not bind on port 4040. Attempting port 4041.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "No project found in the repository. Using project name feast_demo_compute_engine defined in feature_store.yaml\n",
+      "Applying changes for project feast_demo_compute_engine\n",
+      "Deploying infrastructure for order_stats\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:py4j.clientserver:Closing down clientserver connection\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "os.system(\"feast apply\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
+   "source": [
+    "## Load Feature store API"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "application/vnd.databricks.v1+cell": {
+     "inputWidgets": {},
+     "nuid": "37baef9e-ffac-4cf9-ab6c-778e0321d544",
+     "showTitle": false,
+     "title": ""
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from feast import FeatureStore\n",
+    "store = FeatureStore(repo_path=\".\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
+   "source": [
+    "## Materialization"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
+   "source": [
+    "### Local"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "application/vnd.databricks.v1+cell": {
+     "inputWidgets": {},
+     "nuid": "83ad34fa-cbd3-4100-8c01-40720ddbc14e",
+     "showTitle": false,
+     "title": ""
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Materializing \u001b[1m\u001b[32m1\u001b[0m feature views from \u001b[1m\u001b[32m1992-04-20 00:00:00+00:00\u001b[0m to \u001b[1m\u001b[32m2025-04-21 00:00:00+00:00\u001b[0m into the \u001b[1m\u001b[32mpostgres\u001b[0m online store.\n",
+      "\n",
+      "\u001b[1m\u001b[32morder_stats\u001b[0m:\n",
+      "Elapsed time: 84.29606699943542 seconds\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datetime import datetime\n",
+    "import time\n",
+    "\n",
+    "start_time = time.time()\n",
+    "store.materialize(\n",
+    "  start_date=datetime(1992,4,20),\n",
+    "  end_date=datetime(2025,4,21),\n",
+    ")\n",
+    "end_time = time.time()\n",
+    "elapsed_time = end_time - start_time\n",
+    "print(f\"Elapsed time: {elapsed_time} seconds\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Retrieve feature data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'O_CUSTKEY': [397082], 'O_TOTALPRICE': [304962.84375]}"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "store.get_online_features(\n",
+    "    features=[\"order_stats:O_TOTALPRICE\"],\n",
+    "    entity_rows=[{\"O_CUSTKEY\": 397082}]\n",
+    ").to_dict()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Spark"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Materializing \u001b[1m\u001b[32m1\u001b[0m feature views from \u001b[1m\u001b[32m1992-04-20 00:00:00+00:00\u001b[0m to \u001b[1m\u001b[32m2025-04-21 00:00:00+00:00\u001b[0m into the \u001b[1m\u001b[32mpostgres\u001b[0m online store.\n",
+      "\n",
+      "\u001b[1m\u001b[32morder_stats\u001b[0m:\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[Stage 8:===================================================>     (10 + 1) / 11]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Elapsed time: 90.78104996681213 seconds\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "                                                                                "
+     ]
+    }
+   ],
+   "source": [
+    "# Run in local mode\n",
+    "from datetime import datetime\n",
+    "import time\n",
+    "\n",
+    "start_time = time.time()\n",
+    "store.materialize(\n",
+    "  start_date=datetime(1992,4,20),\n",
+    "  end_date=datetime(2025,4,21),\n",
+    ")\n",
+    "end_time = time.time()\n",
+    "elapsed_time = end_time - start_time\n",
+    "print(f\"Elapsed time: {elapsed_time} seconds\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "application/vnd.databricks.v1+notebook": {
+   "dashboards": [],
+   "language": "python",
+   "notebookMetadata": {
+    "mostRecentlyExecutedCommandWithImplicitDF": {
+     "commandId": 402528431658022,
+     "dataframes": [
+      "_sqldf"
+     ]
+    },
+    "pythonIndentUnit": 2
+   },
+   "notebookName": "Feast demo",
+   "notebookOrigID": 1254642919516165,
+   "widgets": {}
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.9"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "7d634b9af180bcb32a446a43848522733ff8f5bbf0cc46dba1a83bede04bf237"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/module_5_compute_engine/feature_repo/data_sources.py b/module_5_compute_engine/feature_repo/data_sources.py
new file mode 100644
index 0000000..00a4184
--- /dev/null
+++ b/module_5_compute_engine/feature_repo/data_sources.py
@@ -0,0 +1,25 @@
+from feast import (
+    Field,
+    FileSource,
+    PushSource,
+    RequestSource,
+    SnowflakeSource
+)
+from feast.types import Int64, Float32
+
+# driver_stats = SparkSource(
+#     name="driver_stats_source",
+#     path="../data/driver_stats_lat_lon.parquet",
+#     timestamp_field="event_timestamp",
+#     created_timestamp_column="created",
+#     description="A table describing the stats of a driver based on hourly logs",
+#     owner="test2@gmail.com",
+# )
+
+
+tpch_sf = SnowflakeSource(
+    database="SNOWFLAKE_SAMPLE_DATA",
+    schema="TPCH_SF10",
+    table="ORDERS",
+    timestamp_field="O_ORDERDATE"
+)
\ No newline at end of file
diff --git a/module_5_compute_engine/feature_repo/entities.py b/module_5_compute_engine/feature_repo/entities.py
new file mode 100644
index 0000000..8bd44b4
--- /dev/null
+++ b/module_5_compute_engine/feature_repo/entities.py
@@ -0,0 +1,11 @@
+from feast import (
+    Entity,
+    ValueType,
+)
+
+customer = Entity(
+    name="customer",
+    join_keys=["O_CUSTKEY"],
+    value_type=ValueType.INT64,
+    description="Custoemr id",
+)
diff --git a/module_5_compute_engine/feature_repo/feature_services.py b/module_5_compute_engine/feature_repo/feature_services.py
new file mode 100644
index 0000000..3b442ec
--- /dev/null
+++ b/module_5_compute_engine/feature_repo/feature_services.py
@@ -0,0 +1,9 @@
+from feast import FeatureService
+
+from features import *
+#
+# feature_service = FeatureService(
+#     name="model_v1",
+#     features=[bfv[["conv_rate"]]],
+#     owner="test3@gmail.com",
+# )
diff --git a/module_5_compute_engine/feature_repo/feature_store.yaml b/module_5_compute_engine/feature_repo/feature_store.yaml
new file mode 100644
index 0000000..2b076cd
--- /dev/null
+++ b/module_5_compute_engine/feature_repo/feature_store.yaml
@@ -0,0 +1,33 @@
+project: feast_demo_compute_engine
+provider: local
+registry:
+  registry_type: sql
+  path: postgresql+psycopg://@localhost:5432/feast
+online_store:
+  type: postgres
+  host: 127.0.0.1
+  port: 5432
+  database: feast
+  user: ""
+  password: ""
+offline_store:
+  type: snowflake.offline
+  account: ${SNOWFLAKE_ACCOUNT}
+  user: ${SNOWFLAKE_USER}
+  password: ${SNOWFLAKE_PASSWORD}
+  role: PUBLIC
+  warehouse: COMPUTE_WH
+  database: SNOWFLAKE_SAMPLE_DATA
+  schema: TPCH_SF10
+batch_engine:
+  type: "spark.engine"
+  spark_conf:
+    spark.master: "local[*]"
+    spark.ui.enabled: "false"
+    spark.eventLog.enabled: "false"
+    spark.sql.catalogImplementation: "hive"
+    spark.sql.parser.quotedRegexColumnNames: "true"
+    spark.sql.session.timeZone: "UTC"
+    spark.sql.execution.arrow.fallback.enabled: "true"
+    spark.sql.execution.arrow.pyspark.enabled: "true"
+    partitions: 2
\ No newline at end of file
diff --git a/module_5_compute_engine/feature_repo/features.py b/module_5_compute_engine/feature_repo/features.py
new file mode 100644
index 0000000..18be34b
--- /dev/null
+++ b/module_5_compute_engine/feature_repo/features.py
@@ -0,0 +1,30 @@
+from datetime import timedelta
+
+from feast import (
+    BatchFeatureView,
+)
+import pyspark
+from feast.types import String
+
+from data_sources import *
+from entities import *
+
+
+def transform_feature(inputs: pyspark.sql.DataFrame):
+    return inputs
+
+
+bfv = BatchFeatureView(
+    name="order_stats",
+    description="Hourly features",
+    entities=[customer],
+    schema=[
+        Field(name="O_TOTALPRICE", dtype=Float32),
+        Field(name="O_ORDERSTATUS", dtype=String),
+    ],
+    udf=transform_feature,
+    online=True,
+    source=tpch_sf,
+    tags={"production": "True"},
+    owner="test2@gmail.com",
+)
diff --git a/module_5_compute_engine/poetry.lock b/module_5_compute_engine/poetry.lock
new file mode 100644
index 0000000..d027346
--- /dev/null
+++ b/module_5_compute_engine/poetry.lock
@@ -0,0 +1,4025 @@
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
+]
+
+[[package]]
+name = "anyio"
+version = "4.9.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c"},
+    {file = "anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""}
+
+[package.extras]
+doc = ["Sphinx (>=8.2,<9.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"]
+test = ["anyio[trio]", "blockbuster (>=1.5.23)", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"]
+trio = ["trio (>=0.26.1)"]
+
+[[package]]
+name = "appnope"
+version = "0.1.4"
+description = "Disable App Nap on macOS >= 10.9"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"},
+    {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"},
+]
+
+[[package]]
+name = "argon2-cffi"
+version = "25.1.0"
+description = "Argon2 for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "argon2_cffi-25.1.0-py3-none-any.whl", hash = "sha256:fdc8b074db390fccb6eb4a3604ae7231f219aa669a2652e0f20e16ba513d5741"},
+    {file = "argon2_cffi-25.1.0.tar.gz", hash = "sha256:694ae5cc8a42f4c4e2bf2ca0e64e51e23a040c6a517a85074683d3959e1346c1"},
+]
+
+[package.dependencies]
+argon2-cffi-bindings = "*"
+
+[[package]]
+name = "argon2-cffi-bindings"
+version = "21.2.0"
+description = "Low-level CFFI bindings for Argon2"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "argon2-cffi-bindings-21.2.0.tar.gz", hash = "sha256:bb89ceffa6c791807d1305ceb77dbfacc5aa499891d2c55661c6459651fc39e3"},
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+description = "Jupyter interactive widgets for Jupyter Notebook"
+optional = false
+python-versions = ">=3.7"
+files = [
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+[[package]]
+name = "zipp"
+version = "3.23.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.9"
+files = [
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+]
+
+[package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
+type = ["pytest-mypy"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.10"
+content-hash = "54430dc7ffc18f4993bce61758aca73ad21d200aa0f1b42db06ad8ef00d35c47"
diff --git a/module_5_compute_engine/pyproject.toml b/module_5_compute_engine/pyproject.toml
new file mode 100644
index 0000000..73ac866
--- /dev/null
+++ b/module_5_compute_engine/pyproject.toml
@@ -0,0 +1,24 @@
+[tool.poetry]
+name = "feast-compute-engine"
+version = "0.1.0"
+description = "A demo of using Feast compute engine"
+authors = ["Hao Xu"]
+readme = "README.md"
+
+[tool.poetry.dependencies]
+python = "^3.10"
+# change to use feast after release 0.50.0
+feast = {path = "../../feast", develop = true}
+pandas = "2.2.3"
+numpy = "1.26.4"
+setuptools = "^80.9.0"
+pyspark = "^4.0.0"
+jupyter = "^1.1.1"
+psycopg = "^3.2.9"
+psycopg-pool = "^3.2.6"
+cryptography = "^45.0.4"
+snowflake-connector-python = "^3.15.0"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"