Merge branch 'main' into separate-snowflake-source

docs/samples/customer360/Customer360.ipynb

@@ -194,8 +194,8 @@
             "    - 'REDIS_PASSWORD'\n",
             "    - 'ADLS_ACCOUNT'\n",
             "    - 'ADLS_KEY'\n",
-            "    - 'WASB_ACCOUNT'\n",
-            "    - 'WASB_KEY'\n",
+            "    - 'BLOB_ACCOUNT'\n",
+            "    - 'BLOB_KEY'\n",
             "    - 'DATABRICKS_WORKSPACE_TOKEN_VALUE '\n",
             "    \n",
             "offline_store:\n",
@@ -328,8 +328,8 @@
             "os.environ['REDIS_PASSWORD'] = ''\n",
             "os.environ['ADLS_ACCOUNT'] = ''\n",
             "os.environ['ADLS_KEY'] = ''\n",
-            "os.environ['WASB_ACCOUNT'] = \"\"\n",
-            "os.environ['WASB_KEY'] = ''\n",
+            "os.environ['BLOB_ACCOUNT'] = \"\"\n",
+            "os.environ['BLOB_KEY'] = ''\n",
             "os.environ['DATABRICKS_WORKSPACE_TOKEN_VALUE'] = ''"
          ]
       },

feathr_project/feathr/client.py

@@ -32,6 +32,7 @@
 from feathr.utils._file_utils import write_to_file
 from feathr.utils.feature_printer import FeaturePrinter
 from feathr.utils.spark_job_params import FeatureGenerationJobParams, FeatureJoinJobParams
+from feathr.definition.source import InputContext
 
 
 class FeathrClient(object):
@@ -633,8 +634,15 @@ def materialize_features(self, settings: MaterializationSettings, execution_conf
             allow_materialize_non_agg_feature: Materializing non-aggregated features (the features without WindowAggTransformation) doesn't output meaningful results so it's by default set to False, but if you really want to materialize non-aggregated features, set this to True.
         """
         feature_list = settings.feature_names
-        if len(feature_list) > 0 and not self._valid_materialize_keys(feature_list):
-            raise RuntimeError(f"Invalid materialization features: {feature_list}, since they have different keys. Currently Feathr only supports materializing features of the same keys.")
+        if len(feature_list) > 0:
+            if 'anchor_list' in dir(self):
+                anchors = [anchor for anchor in self.anchor_list if isinstance(anchor.source, InputContext)]
+                anchor_feature_names = set(feature.name  for anchor in anchors for feature in anchor.features)
+                for feature in feature_list:
+                    if feature in anchor_feature_names:
+                        raise RuntimeError(f"Materializing features that are defined on INPUT_CONTEXT is not supported. {feature} is defined on INPUT_CONTEXT so you should remove it from the feature list in MaterializationSettings.")
+            if not self._valid_materialize_keys(feature_list):
+                raise RuntimeError(f"Invalid materialization features: {feature_list}, since they have different keys. Currently Feathr only supports materializing features of the same keys.")
 
         if not allow_materialize_non_agg_feature:
             # Check if there are non-aggregation features in the list

feathr_project/feathr/constants.py

@@ -28,11 +28,6 @@
 TYPEDEF_ARRAY_DERIVED_FEATURE=f"array<feathr_derived_feature_{REGISTRY_TYPEDEF_VERSION}>"
 TYPEDEF_ARRAY_ANCHOR_FEATURE=f"array<feathr_anchor_feature_{REGISTRY_TYPEDEF_VERSION}>"
 
-# Decouple Feathr MAVEN Version from Feathr Python SDK Version
-import os
-from feathr.version import __version__
-FEATHR_MAVEN_VERSION = os.environ.get("FEATHR_MAVEN_VERSION", __version__)
-FEATHR_MAVEN_ARTIFACT=f"com.linkedin.feathr:feathr_2.12:{FEATHR_MAVEN_VERSION}"
 
 JOIN_CLASS_NAME="com.linkedin.feathr.offline.job.FeatureJoinJob"
 GEN_CLASS_NAME="com.linkedin.feathr.offline.job.FeatureGenJob"

feathr_project/feathr/registry/_feature_registry_purview.py

@@ -758,8 +758,7 @@ def upload_single_entity_to_purview(self,entity:Union[AtlasEntity,AtlasProcess])
             """
             Try to find existing entity/process first, if found, return the existing entity's GUID
             """
-            id = self.get_entity_id(entity.qualifiedName)
-            response =  self.purview_client.get_entity(id)['entities'][0]
+            response =  self.purview_client.get_entity(qualifiedName=entity.qualifiedName)['entities'][0]
             j = entity.to_json()
             if j["typeName"] == response["typeName"]:
                 if j["typeName"] == "Process":

feathr_project/feathr/spark_provider/_databricks_submission.py

@@ -15,6 +15,7 @@
 from databricks_cli.runs.api import RunsApi
 from databricks_cli.sdk.api_client import ApiClient
 from feathr.constants import *
+from feathr.version import get_maven_artifact_fullname
 from feathr.spark_provider._abc import SparkJobLauncher
 from loguru import logger
 from requests.structures import CaseInsensitiveDict
@@ -166,8 +167,8 @@ def submit_feathr_job(self, job_name: str, main_jar_path: str,  main_class_name:
 
         # the feathr main jar file is anyway needed regardless it's pyspark or scala spark
         if not main_jar_path:
-            logger.info(f"Main JAR file is not set, using default package '{FEATHR_MAVEN_ARTIFACT}' from Maven")
-            submission_params['libraries'][0]['maven'] = { "coordinates": FEATHR_MAVEN_ARTIFACT }
+            logger.info(f"Main JAR file is not set, using default package '{get_maven_artifact_fullname()}' from Maven")
+            submission_params['libraries'][0]['maven'] = { "coordinates": get_maven_artifact_fullname() }
         else:
             submission_params['libraries'][0]['jar'] = self.upload_or_get_cloud_path(main_jar_path)
         # see here for the submission parameter definition https://docs.microsoft.com/en-us/azure/databricks/dev-tools/api/2.0/jobs#--request-structure-6

feathr_project/feathr/spark_provider/_localspark_submission.py

@@ -10,7 +10,7 @@
 from loguru import logger
 from pyspark import *
 
-from feathr.constants import FEATHR_MAVEN_ARTIFACT
+from feathr.version import get_maven_artifact_fullname
 from feathr.spark_provider._abc import SparkJobLauncher
 
 
@@ -77,7 +77,7 @@ def submit_feathr_job(
 
         # Get conf and package arguments
         cfg = configuration.copy() if configuration else {}
-        maven_dependency = f"{cfg.pop('spark.jars.packages', self.packages)},{FEATHR_MAVEN_ARTIFACT}"
+        maven_dependency = f"{cfg.pop('spark.jars.packages', self.packages)},{get_maven_artifact_fullname()}"
         spark_args = self._init_args(job_name=job_name, confs=cfg)
 
         if not main_jar_path:
@@ -86,7 +86,7 @@ def submit_feathr_job(
                 # This is a JAR job
                 # Azure Synapse/Livy doesn't allow JAR job starts from Maven directly, we must have a jar file uploaded.
                 # so we have to use a dummy jar as the main file.
-                logger.info(f"Main JAR file is not set, using default package '{FEATHR_MAVEN_ARTIFACT}' from Maven")
+                logger.info(f"Main JAR file is not set, using default package '{get_maven_artifact_fullname()}' from Maven")
                 # Use the no-op jar as the main file
                 # This is a dummy jar which contains only one `org.example.Noop` class with one empty `main` function
                 # which does nothing

feathr_project/feathr/spark_provider/_synapse_submission.py

@@ -22,6 +22,7 @@
 
 from feathr.spark_provider._abc import SparkJobLauncher
 from feathr.constants import *
+from feathr.version import get_maven_artifact_fullname
 
 class LivyStates(Enum):
     """ Adapt LivyStates over to relax the dependency for azure-synapse-spark pacakge.
@@ -114,12 +115,12 @@ def submit_feathr_job(self, job_name: str, main_jar_path: str = None,  main_clas
         if not main_jar_path:
             # We don't have the main jar, use Maven
             # Add Maven dependency to the job configuration
-            logger.info(f"Main JAR file is not set, using default package '{FEATHR_MAVEN_ARTIFACT}' from Maven")
+            logger.info(f"Main JAR file is not set, using default package '{get_maven_artifact_fullname()}' from Maven")
             if "spark.jars.packages" in cfg:
                 cfg["spark.jars.packages"] = ",".join(
-                    [cfg["spark.jars.packages"], FEATHR_MAVEN_ARTIFACT])
+                    [cfg["spark.jars.packages"], get_maven_artifact_fullname()])
             else:
-                cfg["spark.jars.packages"] = FEATHR_MAVEN_ARTIFACT
+                cfg["spark.jars.packages"] = get_maven_artifact_fullname()
 
             if not python_files:
                 # This is a JAR job

feathr_project/feathr/version.py

@@ -1 +1,10 @@
-__version__ = "0.9.0-rc2"
+__version__ = "0.9.0-rc2"
+
+def get_version():
+    return __version__
+
+# Decouple Feathr MAVEN Version from Feathr Python SDK Version
+import os
+def get_maven_artifact_fullname():
+    maven_artifact_version = os.environ.get("MAVEN_ARTIFACT_VERSION", __version__)
+    return f"com.linkedin.feathr:feathr_2.12:{maven_artifact_version}"

feathr_project/feathrcli/data/feathr_user_workspace/feathr_config.yaml

@@ -25,8 +25,8 @@ project_config:
     # the environemnt variables are optional, however you will need them if you want to use some of the services:
     - ADLS_ACCOUNT
     - ADLS_KEY
-    - WASB_ACCOUNT
-    - WASB_KEY
+    - BLOB_ACCOUNT
+    - BLOB_KEY
     - S3_ACCESS_KEY
     - S3_SECRET_KEY
     - JDBC_TABLE
@@ -41,7 +41,7 @@ offline_store:
     adls_enabled: true
 
   # paths starts with wasb:// or wasbs://
-  # WASB_ACCOUNT and WASB_KEY should be set in environment variable
+  # BLOB_ACCOUNT and BLOB_KEY should be set in environment variable
   wasb:
     wasb_enabled: true
 
@@ -118,8 +118,8 @@ feature_registry:
     delimiter: "__"
     # controls whether the type system will be initialized or not. Usually this is only required to be executed once.
     type_system_initialization: false
-    
-    
+
+
 secrets:
   azure_key_vault:
     name: feathrazuretest3-kv

feathr_project/test/test_feature_materialization.py

@@ -18,6 +18,8 @@
 from test_fixture import basic_test_setup
 from test_fixture import get_online_test_table_name
 from test_utils.constants import Constants
+from logging import raiseExceptions
+import pytest
 
 def test_feature_materialization_config():
     backfill_time = BackfillTime(start=datetime(2020, 5, 20), end=datetime(2020, 5,20), step=timedelta(days=1))
@@ -255,4 +257,21 @@ def test_delete_feature_from_redis():
     res = client.get_online_features(online_test_table, '265', ['f_location_avg_fare'])
 
     assert len(res) == 1
-    assert res[0] == None
+    assert res[0] == None
+
+def test_feature_list_on_input_context():
+    with pytest.raises(RuntimeError) as e_info:
+        test_workspace_dir = Path(__file__).parent.resolve() / "test_user_workspace"
+
+        client: FeathrClient = basic_test_setup(os.path.join(test_workspace_dir, "feathr_config.yaml"))
+        online_test_table = get_online_test_table_name('nycTaxiCITableDeletion')
+        redisSink = RedisSink(table_name=online_test_table)
+        settings = MaterializationSettings(name="py_udf",
+                                       sinks=[redisSink],
+                                       feature_names=[
+                                           "f_location_avg_fare",
+                                           "f_day_of_week"
+                                       ])
+        client.materialize_features(settings, allow_materialize_non_agg_feature=True)
+    assert e_info is not None
+    assert e_info.value.args[0] == "Materializing features that are defined on INPUT_CONTEXT is not supported. f_day_of_week is defined on INPUT_CONTEXT so you should remove it from the feature list in MaterializationSettings."  

feathr_project/test/test_user_workspace/feathr_config.yaml

@@ -25,8 +25,8 @@ project_config:
     # the environemnt variables are optional, however you will need them if you want to use some of the services:
     - ADLS_ACCOUNT
     - ADLS_KEY
-    - WASB_ACCOUNT
-    - WASB_KEY
+    - BLOB_ACCOUNT
+    - BLOB_KEY
     - S3_ACCESS_KEY
     - S3_SECRET_KEY
     - JDBC_TABLE
@@ -41,7 +41,7 @@ offline_store:
     adls_enabled: true
 
   # paths starts with wasb:// or wasbs://
-  # WASB_ACCOUNT and WASB_KEY should be set in environment variable
+  # BLOB_ACCOUNT and BLOB_KEY should be set in environment variable
   wasb:
     wasb_enabled: true
 

feathr_project/test/test_user_workspace/feathr_config_local.yaml

@@ -17,8 +17,8 @@ project_config:
     # the environemnt variables are optional, however you will need them if you want to use some of the services:
     - ADLS_ACCOUNT
     - ADLS_KEY
-    - WASB_ACCOUNT
-    - WASB_KEY
+    - BLOB_ACCOUNT
+    - BLOB_KEY
     - S3_ACCESS_KEY
     - S3_SECRET_KEY
     - JDBC_TABLE

feathr_project/test/test_user_workspace/feathr_config_maven.yaml

@@ -25,8 +25,8 @@ project_config:
     # the environemnt variables are optional, however you will need them if you want to use some of the services:
     - ADLS_ACCOUNT
     - ADLS_KEY
-    - WASB_ACCOUNT
-    - WASB_KEY
+    - BLOB_ACCOUNT
+    - BLOB_KEY
     - S3_ACCESS_KEY
     - S3_SECRET_KEY
     - JDBC_TABLE
@@ -41,7 +41,7 @@ offline_store:
     adls_enabled: true
 
   # paths starts with wasb:// or wasbs://
-  # WASB_ACCOUNT and WASB_KEY should be set in environment variable
+  # BLOB_ACCOUNT and BLOB_KEY should be set in environment variable
   wasb:
     wasb_enabled: true