diff --git a/managed-connectivity/community-contributed-connectors/snowflake-horizon-connector/LICENSE.txt b/managed-connectivity/community-contributed-connectors/snowflake-horizon-connector/LICENSE.txt
new file mode 100644
index 0000000..261eeb9
--- /dev/null
+++ b/managed-connectivity/community-contributed-connectors/snowflake-horizon-connector/LICENSE.txt
@@ -0,0 +1,201 @@
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diff --git a/managed-connectivity/community-contributed-connectors/snowflake-horizon-connector/README.md b/managed-connectivity/community-contributed-connectors/snowflake-horizon-connector/README.md
new file mode 100644
index 0000000..eb358d5
--- /dev/null
+++ b/managed-connectivity/community-contributed-connectors/snowflake-horizon-connector/README.md
@@ -0,0 +1,137 @@
+# Snowflake to Dataplex Metadata Loader
+
+### Introduction:
+
+In today's complex data landscape, organizations increasingly recognize data as a critical asset. The ability to effectively discover, understand, and govern this data is paramount for informed decision-making, regulatory compliance, and innovation. As data ecosystems grow, spanning various platforms and technologies, maintaining a holistic view of data assets becomes challenging.
+
+This connector addresses a key need for many enterprises: bridging the gap between their data warehousing capabilities and the comprehensive data governance and discovery features offered by Google Cloud's Dataplex. Dataplex provides a unified data fabric to manage, monitor, and govern data across diverse environments within Google Cloud.
+
+The **Snowflake Horizon to Dataplex Universal Catalog Connector**, detailed here, is a testament to the power of seamless integration. It's designed to automate metadata synchronization, bringing the rich context of your data into dataplex. This not only enhances data visibility and accessibility for all stakeholders but also strengthens your data governance by centralizing metadata management, lineage tracking, and data quality initiatives.
+
+We believe that by leveraging this connector, you'll unlock new levels of efficiency and empower your teams to truly become data-driven. This guide is your indispensable companion, providing clear, step-by-step instructions and practical insights for a successful implementation.
+
+---
+
+### Step by Step Guide:
+
+This document will show an end to end POC of how to use Snowflake to Dataplex Universal Catalog Loader.
+
+#### Step 1: Setting up Snowflake Environment from where you have to load the metadata.
+To access the Horizon catalog in Snowflake, you will need to use the **ACCOUNT_USAGE** views located under the **SNOWFLAKE** database.
+
+
+
+#### Step 2: Storing the connection details in Secret Manager.
+
+In **Google Cloud Console** -> Navigate to **Secret Manager** -> **Create Secret** ->
+Then you create the following 3 secrets:
+* `snowflake-user-name`
+* `snowflake-user-password`
+* `snowflake-account-uri`
+
+Please note that you have to create these secrets in your GCP Project.
+
+#### Step 3: Setting up the Dataplex Universal Catalog Environment.
+
+You will perform the following one-time setup steps in your GCP Project:
+
+1. **Create an entry group** for the entries that you want to import. Follow the steps from [here](https://docs.cloud.google.com/dataplex/docs/ingest-custom-sources#create-entry-group) and create an entry group named **"snowflakehorizongrp"**
+
+
+2. **Create aspect types** for the aspects that you want to import. Follow the steps from [here](https://docs.cloud.google.com/dataplex/docs/enrich-entries-metadata#create-aspect-type) and create the following aspects types: **"snowhorizondb"**, **"snowhorizonschema"**, **"snowhorizontable"**, **"snowhorizontag"**, **"snowhorizontagref"**, **"snowhorizonindex"**, **"snowhorizonfunction"**. Please note that these names are not mandatory and can be changed as per your requirements as well just that you will have to change these in the script also. If you want to use the script as it is then please use the names as mentioned above.
+* Navigate to Dataplex -> Dataplex Universal Catalog -> Catalog -> "Aspect types & Tag Templates "
+
+
+* You will see two options there as shown above:- "Custom" & "System". Under "Custom", click on "+Create Aspect Type". You will see the following screen:-
+
+
+* Fill the details as below(e.g for snowhorizondb)
+
+
+* Next, Under "Template", click on "Add Field":-
+
+
+* Fill all the details related to that field(e.g DatabaseName):-
+
+
+* Similarly, add all the fields(metadata that you are trying to bring from Snowflake Horizon):-
+
+
+* Similarly, create all the aspect types mentioned above as shown in the below screenshots. Please note that these are sample templates(just for reference purpose only) and you can modify these as per your business usecase. If you plan to execute the python script as it is then please create the Aspect Types as per the below screenshots.
+
+* Aspect Type Template For Snowflake Schema:-
+
+
+* Aspect Type Template For Snowflake Index:-
+
+
+* Aspect Type Template For Snowflake Function:-
+
+
+* Aspect Type Template For Snowflake Table:-
+
+
+* Aspect Type Template For Snowflake Tag:-
+
+
+* Aspect Type Template For Snowflake Tag References:-
+
+
+* Finally, you will have all the aspect types created as below:-
+
+
+3. **Create entry types** for the entries that you want to import. Follow the steps from [here](https://docs.cloud.google.com/dataplex/docs/ingest-custom-sources#create-entry-type) and create the following entry types: **"snowhorizondb"**, **"snowhorizonschema"**, **"snowhorizontable"**, **"snowhorizontag"**, **"snowhorizontagref"**, **"snowhorizonindex"**, **"snowhorizonfunction"**. Please note that these names are not mandatory and can be changed as per your requirements as well just that you will have to change these in the script also. If you want to use the script as it is then please use the names as mentioned above.
+* Navigate to Dataplex -> Dataplex Universal Catalog -> Catalog -> "Aspect types & Tag Templates "
+
+
+* You will see two options there as shown above:- "Custom" & "System". Under "Custom", click on "+ Create". You will see the following screen, Fill in the details as below(e.g for snowhorizondb):-
+
+
+* Under, "Required Aspect Type", click on "Choose aspect type" and select the relevant aspect type as created in Step 2 and click on "Save":-
+
+
+
+* Similarly, create all the above mentioned Entry Types and attach the relevant Aspect Type to it(as shown in the below screenshots). Please note that these are sample Entry Types(just for reference purpose only) and you can modify these as per your business usecase. If you plan to execute the python script as it is then please create the Entry Types as per the below screenshots.
+
+* Entry Type For Snowflake Schema:-
+
+
+* Entry Type For Snowflake Index:-
+
+
+* Entry Type For Snowflake Function:-
+
+
+* Entry Type For Snowflake Table:-
+
+
+* Entry Type For Snowflake Tag:-
+
+
+* Entry Type For Snowflake Tag References:-
+
+
+* Finally, you will have all the Entry Types created as below:-
+
+
+#### Step 4: Execute the Python Script to load the Horizon Metadata from Snowflake to Dataplex
+Now you have to execute the Python script: `snowflake_to_dataplex_metadata_loader.py`
+
+Before executing the script, you will have to provide the following details in the first section of the script:
+* PROJECT_ID = 'Enter your Project Name'
+* SNOWFLAKE_WAREHOUSE = 'Enter your Warehouse'
+* SNOWFLAKE_DATABASE = 'Enter your Database'
+* SNOWFLAKE_SCHEMA = 'Enter your Schema'
+
+Also, you will need to provide the following access to the service account:-
+* To read the Snowflake login credentials - Secret Manager Secret Accessor
+* To create and manage the Snowflake metadata entries - Dataplex Catalog Editor
+
+#### Step 5: Validate everything in Dataplex.
+For example, you can validate Snowflake Databases as below:-
+
+* Navigate to Dataplex -> Dataplex Universal Catalog -> Catalog -> Entry Types -> select "snowhorizondb"
+* Next, click on "Sample Entries" and you will see all the Databases from Snowflake here.
+* Click on any of them and validate your entries between Snowflake and Dataplex.
+
+Similarly, you can validate all other metadata as well.
\ No newline at end of file
diff --git a/managed-connectivity/community-contributed-connectors/snowflake-horizon-connector/custom-connector/snowflake_to_dataplex_metadata_loader.py b/managed-connectivity/community-contributed-connectors/snowflake-horizon-connector/custom-connector/snowflake_to_dataplex_metadata_loader.py
new file mode 100644
index 0000000..93cf543
--- /dev/null
+++ b/managed-connectivity/community-contributed-connectors/snowflake-horizon-connector/custom-connector/snowflake_to_dataplex_metadata_loader.py
@@ -0,0 +1,562 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Install necessary libraries if not already present in the environment
+!pip install --user google-cloud-bigquery google-cloud-storage google-cloud-dataplex google-api-core functions-framework
+
+!pip install --force-reinstall google-cloud-dataplex
+
+!pip install snowflake-connector-python pandas
+
+pip install snowflake-connector-python google-cloud-secret-manager
+
+#User Inputs
+PROJECT_ID = "Enter your Project Name"
+SNOWFLAKE_WAREHOUSE = "Enter your Warehouse"
+SNOWFLAKE_DATABASE = "Enter your Database"
+SNOWFLAKE_SCHEMA = "Enter your Schema"
+DATAPLEX_LOCATION = "Enter dataplex location"
+
+from google.cloud import secretmanager
+
+import snowflake.connector
+import pandas as pd
+
+import os
+from google.cloud import bigquery
+from google.cloud import storage
+from google.cloud import dataplex_v1
+import datetime
+from google.protobuf import struct_pb2
+
+from google.cloud.dataplex_v1.types import Schema
+from google.protobuf import json_format
+import json
+
+def access_secret_version(secret_id, PROJECT_ID, version_id="latest"):
+ client = secretmanager.SecretManagerServiceClient()
+ name = f"projects/{PROJECT_ID}/secrets/{secret_id}/versions/{version_id}"
+ response = client.access_secret_version(request={"name": name})
+ return response.payload.data.decode("UTF-8")
+
+SNOWFLAKE_USER_NAME = access_secret_version(
+ secret_id="snowflake-user-name",
+ PROJECT_ID=f"{PROJECT_ID}"
+ )
+SNOWFLAKE_PASSWORD = access_secret_version(
+ secret_id="snowflake-user-password",
+ PROJECT_ID=f"{PROJECT_ID}"
+ )
+SNOWFLAKE_ACCOUNT_URI = access_secret_version(
+ secret_id="snowflake-account-uri",
+ PROJECT_ID=f"{PROJECT_ID}"
+ )
+
+
+# fetch the details from Secret Manager
+SNOWFLAKE_ACCOUNT = SNOWFLAKE_ACCOUNT_URI
+SNOWFLAKE_USER = SNOWFLAKE_USER_NAME
+SNOWFLAKE_PASSWORD = SNOWFLAKE_PASSWORD
+
+try:
+ conn = snowflake.connector.connect(
+ user=SNOWFLAKE_USER,
+ password=SNOWFLAKE_PASSWORD,
+ account=SNOWFLAKE_ACCOUNT,
+ warehouse=SNOWFLAKE_WAREHOUSE,
+ database=SNOWFLAKE_DATABASE,
+ schema=SNOWFLAKE_SCHEMA
+ )
+ print("Successfully connected to Snowflake!")
+except Exception as e:
+ print(f"Error connecting to Snowflake: {e}")
+
+# Query 1: DATABASE
+try:
+ cursor_db = conn.cursor()
+ query_db = "select * from snowflake.account_usage.databases;"
+ cursor_db.execute(query_db)
+
+ # Fetch all results and load into a Pandas DataFrame
+ df_db = pd.DataFrame(cursor_db.fetchall(), columns=[col[0] for col in cursor_db.description])
+ print("\n--- Output for ACCOUNT_USUAGE.DATABASES ---")
+ print(df_db.head()) # Print first few rows
+ print(f"Total rows for DATABASE: {len(df_db)}")
+
+except Exception as e:
+ print(f"Error executing DATABASE query: {e}")
+finally:
+ if 'cursor_db' in locals() and cursor_db:
+ cursor_db.close()
+
+
+dataplex_client = dataplex_v1.DataplexServiceClient()
+
+for _, row in df_db.iterrows():
+ DATABASE_NAME = row['DATABASE_NAME']
+ DATABASE_OWNER = row['DATABASE_OWNER']
+ DATABASE_COMMENT = row['COMMENT']
+ DATABASE_CREATED = str(row['CREATED'])
+ DATABASE_LAST_ALTERED = str(row['LAST_ALTERED'])
+ DATABASE_TYPE = row['TYPE']
+ print(DATABASE_NAME,DATABASE_OWNER,DATABASE_COMMENT,DATABASE_CREATED,DATABASE_LAST_ALTERED,DATABASE_TYPE)
+ print(type(DATABASE_CREATED))
+ entry_id = f"{DATABASE_NAME}".replace('.', '-').replace(' ', '_').upper()
+ entry_id = entry_id[:40].strip('-').strip('_')
+ print(entry_id)
+
+ entry_group_id = "snowflakehorizongrp" #enter your entry group id that you created in Step 3 of the README File.
+ entry_type_id = "snowhorizondb" #enter your entry type id that you created in Step 3 of the README File.
+ name = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}/entries/{entry_id}"
+ print(name)
+ entry_type = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryTypes/{entry_type_id}"
+ print(entry_type)
+ aspects={
+ f"{PROJECT_ID}.{DATAPLEX_LOCATION}.{entry_type_id}": dataplex_v1.Aspect(
+ aspect_type=f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/aspectTypes/{entry_type_id}",
+ data=struct_pb2.Struct(
+ fields={
+ "databasename": struct_pb2.Value(string_value=f"{DATABASE_NAME}"),
+ "databaseowner": struct_pb2.Value(string_value=f"{DATABASE_OWNER}"),
+ "databasecomment": struct_pb2.Value(string_value=f"{DATABASE_COMMENT}"),
+ "databasecreated": struct_pb2.Value(string_value=f"{DATABASE_CREATED}"),
+ "databaselastaltered": struct_pb2.Value(string_value=f"{DATABASE_LAST_ALTERED}"),
+ "databasetype": struct_pb2.Value(string_value=f"{DATABASE_TYPE}"),
+ }
+ ),
+ )
+ }
+ print(aspects)
+
+ entry = dataplex_v1.Entry()
+ entry.name = name
+ entry.entry_type = entry_type
+ entry.aspects = aspects
+ parent = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}"
+ print(parent)
+ client = dataplex_v1.CatalogServiceClient()
+ response = client.create_entry(parent=parent, entry=entry, entry_id=entry_id)
+ print("Database successfully loaded in Dataplex")
+
+# Query 2: SCHEMA
+try:
+ cursor_schema = conn.cursor()
+ query_schema = "select * from snowflake.account_usage.schemata;"
+ cursor_schema.execute(query_schema)
+
+ # Fetch all results and load into a Pandas DataFrame
+ df_schema = pd.DataFrame(cursor_schema.fetchall(), columns=[col[0] for col in cursor_schema.description])
+ print("\n--- Output for ACCOUNT_USUAGE.SCHEMA ---")
+ print(df_schema.head()) # Print first few rows
+ print(f"Total rows for SCHEMA: {len(df_schema)}")
+
+except Exception as e:
+ print(f"Error executing SCHEMA query: {e}")
+finally:
+ if 'cursor_schema' in locals() and cursor_schema:
+ cursor_schema.close()
+
+for _, row in df_schema.iterrows():
+ SCHEMA_NAME = row['SCHEMA_NAME']
+ SCHEMA_OWNER = row['SCHEMA_OWNER']
+ SCHEMA_COMMENT = row['COMMENT']
+ SCHEMA_CREATED = str(row['CREATED'])
+ SCHEMA_LAST_ALTERED = str(row['LAST_ALTERED'])
+ SCHEMA_TYPE = row['SCHEMA_TYPE']
+ SCHEMA_CATALOG_NAME = row['CATALOG_NAME']
+ print(SCHEMA_NAME,SCHEMA_OWNER,SCHEMA_COMMENT,SCHEMA_CREATED,SCHEMA_LAST_ALTERED,SCHEMA_TYPE,SCHEMA_CATALOG_NAME)
+ print(type(SCHEMA_CREATED))
+ entry_id = f"{SCHEMA_NAME}".replace('.', '-').replace(' ', '_').upper()
+ entry_id = entry_id[:40].strip('-').strip('_')
+ print(entry_id)
+
+ entry_group_id = "snowflakehorizongrp" #enter your entry group id that you created in Step 3 of the README File.
+ entry_type_id = "snowhorizonschema" #enter your entry type id that you created in Step 3 of the README File.
+ name = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}/entries/{entry_id}"
+ print(name)
+ entry_type = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryTypes/{entry_type_id}"
+ print(entry_type)
+ aspects={
+ f"{PROJECT_ID}.{DATAPLEX_LOCATION}.{entry_type_id}": dataplex_v1.Aspect(
+ aspect_type=f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/aspectTypes/{entry_type_id}",
+ data=struct_pb2.Struct(
+ fields={
+ "schemaname": struct_pb2.Value(string_value=f"{SCHEMA_NAME}"),
+ "schemaowner": struct_pb2.Value(string_value=f"{SCHEMA_OWNER}"),
+ "schemacomment": struct_pb2.Value(string_value=f"{SCHEMA_COMMENT}"),
+ "schemacreated": struct_pb2.Value(string_value=f"{SCHEMA_CREATED}"),
+ "schemalastaltered": struct_pb2.Value(string_value=f"{SCHEMA_LAST_ALTERED}"),
+ "schematype": struct_pb2.Value(string_value=f"{SCHEMA_TYPE}"),
+ "schemacatalogname": struct_pb2.Value(string_value=f"{SCHEMA_CATALOG_NAME}"),
+ }
+ ),
+ )
+ }
+ print(aspects)
+
+ entry = dataplex_v1.Entry()
+ entry.name = name
+ entry.entry_type = entry_type
+ entry.aspects = aspects
+ parent = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}"
+ print(parent)
+ client = dataplex_v1.CatalogServiceClient()
+ response = client.create_entry(parent=parent, entry=entry, entry_id=entry_id)
+ print("Schema successfully loaded in Dataplex")
+
+# Final Query 3: TABLES & COLUMNS
+try:
+ cursor_table = conn.cursor()
+ query_table = "select distinct table_name from (select a.*,b.tag_name, b.tag_value from snowflake.account_usage.columns as a left join snowflake.account_usage.tag_references as b on a.column_name = b.column_name);"
+ cursor_table.execute(query_table)
+
+ # Fetch all results and load into a Pandas DataFrame
+ df_table = pd.DataFrame(cursor_table.fetchall(), columns=[col[0] for col in cursor_table.description])
+ print("\n--- Output for ACCOUNT_USUAGE.TABLES ---")
+ print(df_table.head()) # Print first few rows
+ print(f"Total rows for TABLE: {len(df_table)}")
+
+except Exception as e:
+ print(f"Error executing TABLE query: {e}")
+finally:
+ if 'cursor_table' in locals() and cursor_table:
+ cursor_table.close()
+
+# Final Query 3: Table & COLUMNS
+for _, row in df_table.iterrows():
+ TABLE_NAME = row['TABLE_NAME']
+ C_TABLE_NAME = f"'{TABLE_NAME}'"
+ print(C_TABLE_NAME)
+ try:
+ cursor_columns = conn.cursor()
+ query_columns = f"select a.*,b.tag_name, b.tag_value,CASE WHEN a.DATA_TYPE IN ('TEXT', 'STRING') THEN 'STRING' WHEN a.DATA_TYPE = 'DATE' THEN 'DATETIME' WHEN a.DATA_TYPE IN ('NUMBER', 'INTEGER') THEN 'NUMBER' ELSE a.DATA_TYPE END AS metadataType from snowflake.account_usage.columns as a left join snowflake.account_usage.tag_references as b on a.column_name = b.column_name where a.TABLE_NAME = {C_TABLE_NAME};"
+ cursor_columns.execute(query_columns)
+
+ # Fetch all results and load into a Pandas DataFrame
+ df_columns = pd.DataFrame(cursor_columns.fetchall(), columns=[col[0] for col in cursor_columns.description])
+ print("\n--- Output for ACCOUNT_USUAGE.COLUMNS ---")
+ print(df_columns.head()) # Print first few rows
+ print(f"Total rows for COLUMNS: {len(df_columns)}")
+
+ except Exception as e:
+ print(f"Error executing COLUMNS query: {e}")
+ finally:
+ if 'cursor_columns' in locals() and cursor_columns:
+ cursor_columns.close()
+ entry_id = TABLE_NAME
+ print(entry_id)
+ entry_group_id = "snowflakehorizongrp" #enter your entry group id that you created in Step 3 of the README File.
+ entry_type_id = "snowtesttable" #enter your entry type id that you created in Step 3 of the README File.
+ name = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}/entries/{entry_id}"
+ print(name)
+ entry_type = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryTypes/{entry_type_id}"
+ print(entry_type)
+ schema_json = {
+ "fields": []
+ }
+ for index, row in df_columns.iterrows():
+ field = {
+ "name": row['COLUMN_NAME'],
+ "dataType": row['DATA_TYPE'],
+ "metadataType": row['METADATATYPE'],
+ "mode": "NULLABLE"
+ }
+ schema_json["fields"].append(field)
+ print(json.dumps(schema_json, indent=2))
+
+ aspects={
+ "dataplex-types.global.schema": dataplex_v1.Aspect(
+ aspect_type="projects/dataplex-types/locations/global/aspectTypes/schema",
+ data= schema_json,)
+ }
+ print(aspects)
+ entry = dataplex_v1.Entry()
+ entry.name = name
+ entry.entry_type = entry_type
+ entry.aspects = aspects
+ parent = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}"
+ print(parent)
+ client = dataplex_v1.CatalogServiceClient()
+ response = client.create_entry(parent=parent, entry=entry, entry_id=entry_id)
+ print("column entry created successfully")
+
+# Query 4: TAGS
+try:
+ cursor_tags = conn.cursor()
+ query_tags = "select * from snowflake.account_usage.tags;"
+ cursor_tags.execute(query_tags)
+
+ # Fetch all results and load into a Pandas DataFrame
+ df_tags = pd.DataFrame(cursor_tags.fetchall(), columns=[col[0] for col in cursor_tags.description])
+ print("\n--- Output for ACCOUNT_USUAGE.TAGS ---")
+ print(df_tags.head()) # Print first few rows
+ print(f"Total rows for TAGS: {len(df_tags)}")
+
+except Exception as e:
+ print(f"Error executing TAGS query: {e}")
+finally:
+ if 'cursor_tags' in locals() and cursor_tags:
+ cursor_tags.close()
+
+for _, row in df_tags.iterrows():
+ TAG_NAME = row['TAG_NAME']
+ TAG_SCHEMA = row['TAG_SCHEMA']
+ TAG_DATABASE = row['TAG_DATABASE']
+ TAG_OWNER = row['TAG_OWNER']
+ TAG_COMMENT = row['TAG_COMMENT']
+ TAG_CREATED = str(row['CREATED'])
+ TAG_LAST_ALTERED = str(row['LAST_ALTERED'])
+ TAG_ALLOWED_VALUES = str(row['ALLOWED_VALUES'])
+ print(TAG_NAME,TAG_SCHEMA,TAG_DATABASE,TAG_OWNER,TAG_COMMENT,TAG_CREATED,TAG_LAST_ALTERED,TAG_ALLOWED_VALUES)
+ print(type(TAG_ALLOWED_VALUES))
+ entry_id = f"{TAG_NAME}".replace('.', '-').replace(' ', '_').upper()
+ entry_id = entry_id[:40].strip('-').strip('_')
+ print(entry_id)
+
+ entry_group_id = "snowflakehorizongrp" #enter your entry group id that you created in Step 3 of the README File.
+ entry_type_id = "snowhorizontag" #enter your entry type id that you created in Step 3 of the README File.
+ name = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}/entries/{entry_id}"
+ print(name)
+ entry_type = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryTypes/{entry_type_id}"
+ print(entry_type)
+ aspects={
+ f"{PROJECT_ID}.{DATAPLEX_LOCATION}.{entry_type_id}": dataplex_v1.Aspect(
+ aspect_type=f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/aspectTypes/{entry_type_id}",
+ data=struct_pb2.Struct(
+ fields={
+ "tagname": struct_pb2.Value(string_value=f"{TAG_NAME}"),
+ "tagschema": struct_pb2.Value(string_value=f"{TAG_SCHEMA}"),
+ "tagdatabase": struct_pb2.Value(string_value=f"{TAG_DATABASE}"),
+ "tagowner": struct_pb2.Value(string_value=f"{TAG_OWNER}"),
+ "tagcomment": struct_pb2.Value(string_value=f"{TAG_COMMENT}"),
+ "tagcreated": struct_pb2.Value(string_value=f"{TAG_CREATED}"),
+ "taglastaltered": struct_pb2.Value(string_value=f"{TAG_LAST_ALTERED}"),
+ "tagallowedvalues": struct_pb2.Value(string_value=f"{TAG_ALLOWED_VALUES}"),
+ }
+ ),
+ )
+ }
+ print(aspects)
+
+ entry = dataplex_v1.Entry()
+ entry.name = name
+ entry.entry_type = entry_type
+ entry.aspects = aspects
+ parent = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}"
+ print(parent)
+ client = dataplex_v1.CatalogServiceClient()
+ response = client.create_entry(parent=parent, entry=entry, entry_id=entry_id)
+ print("Tag successfully loaded in Dataplex")
+
+# Query 5: TAG REFERENCES
+try:
+ cursor_tagsref = conn.cursor()
+ query_tagsref = "select * from SNOWFLAKE.ACCOUNT_USAGE.TAG_REFERENCES;"
+ cursor_tagsref.execute(query_tagsref)
+
+ # Fetch all results and load into a Pandas DataFrame
+ df_tagsref = pd.DataFrame(cursor_tagsref.fetchall(), columns=[col[0] for col in cursor_tagsref.description])
+ print("\n--- Output for ACCOUNT_USUAGE.TAGSREF ---")
+ print(df_tagsref.head()) # Print first few rows
+ print(f"Total rows for TAGSREF: {len(df_tagsref)}")
+
+except Exception as e:
+ print(f"Error executing TAGSREF query: {e}")
+finally:
+ if 'cursor_tagsref' in locals() and cursor_tagsref:
+ cursor_tagsref.close()
+
+for _, row in df_tagsref.iterrows():
+ TAG_NAME = row['TAG_NAME']
+ TAG_SCHEMA = row['TAG_SCHEMA']
+ TAG_DATABASE = row['TAG_DATABASE']
+ TABLE_NAME = row['OBJECT_NAME']
+ COLUMN_NAME = row['COLUMN_NAME']
+ TAG_VALUE = row['TAG_VALUE']
+ ENTRY_ID = f"{TAG_NAME}"[:10]
+ ENTRY_ID = f"{ENTRY_ID}{COLUMN_NAME}"
+ print(TAG_NAME,TAG_SCHEMA,TAG_DATABASE,TABLE_NAME,COLUMN_NAME,TAG_VALUE)
+ entry_id = f"{ENTRY_ID}".replace('.', '-').replace(' ', '_').upper()
+ entry_id = entry_id[:40].strip('-').strip('_')
+ print(entry_id)
+
+ entry_group_id = "snowflakehorizongrp" #enter your entry group id that you created in Step 3 of the README File.
+ entry_type_id = "snowhorizontagref" #enter your entry type id that you created in Step 3 of the README File.
+ name = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}/entries/{entry_id}"
+ print(name)
+ entry_type = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryTypes/{entry_type_id}"
+ print(entry_type)
+ aspects={
+ f"{PROJECT_ID}.{DATAPLEX_LOCATION}.{entry_type_id}": dataplex_v1.Aspect(
+ aspect_type=f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/aspectTypes/{entry_type_id}",
+ data=struct_pb2.Struct(
+ fields={
+ "tagname": struct_pb2.Value(string_value=f"{TAG_NAME}"),
+ "tagschema": struct_pb2.Value(string_value=f"{TAG_SCHEMA}"),
+ "tagdatabase": struct_pb2.Value(string_value=f"{TAG_DATABASE}"),
+ "tablename": struct_pb2.Value(string_value=f"{TABLE_NAME}"),
+ "columnname": struct_pb2.Value(string_value=f"{COLUMN_NAME}"),
+ "tagvalue": struct_pb2.Value(string_value=f"{TAG_VALUE}"),
+ }
+ ),
+ )
+ }
+ print(aspects)
+ entry = dataplex_v1.Entry()
+ entry.name = name
+ entry.entry_type = entry_type
+ entry.aspects = aspects
+ parent = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}"
+ print(parent)
+ client = dataplex_v1.CatalogServiceClient()
+ response = client.create_entry(parent=parent, entry=entry, entry_id=entry_id)
+ print("Tag successfully loaded in Dataplex")
+
+# Query 6: INDEXES
+try:
+ cursor_indexes = conn.cursor()
+ query_indexes = "select * from snowflake.account_usage.indexes;"
+ cursor_indexes.execute(query_indexes)
+
+ # Fetch all results and load into a Pandas DataFrame
+ df_indexes = pd.DataFrame(cursor_indexes.fetchall(), columns=[col[0] for col in cursor_indexes.description])
+ print("\n--- Output for ACCOUNT_USUAGE.INDEXES ---")
+ print(df_indexes.head()) # Print first few rows
+ print(f"Total rows for INDEXES: {len(df_indexes)}")
+
+except Exception as e:
+ print(f"Error executing INDEXES query: {e}")
+finally:
+ if 'cursor_indexes' in locals() and cursor_indexes:
+ cursor_indexes.close()
+
+for _, row in df_indexes.iterrows():
+ INDEX_NAME = row['NAME']
+ TABLE_NAME = row['TABLE_NAME']
+ SCHEMA_NAME = row['SCHEMA_NAME']
+ DATABASE_NAME = row['DATABASE_NAME']
+ INDEX_CREATED = str(row['CREATED'])
+ print(INDEX_NAME,TABLE_NAME,SCHEMA_NAME,DATABASE_NAME,INDEX_CREATED)
+ print(type(INDEX_CREATED))
+ entry_id = f"{INDEX_NAME}".replace('.', '-').replace(' ', '_').upper()
+ entry_id = entry_id[:40].strip('-').strip('_')
+ print(entry_id)
+
+ entry_group_id = "snowflakehorizongrp" #enter your entry group id that you created in Step 3 of the README File.
+ entry_type_id = "snowhorizonindex" #enter your entry type id that you created in Step 3 of the README File.
+ name = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}/entries/{entry_id}"
+ print(name)
+ entry_type = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryTypes/{entry_type_id}"
+ print(entry_type)
+ aspects={
+ f"{PROJECT_ID}.{DATAPLEX_LOCATION}.{entry_type_id}": dataplex_v1.Aspect(
+ aspect_type=f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/aspectTypes/{entry_type_id}",
+ data=struct_pb2.Struct(
+ fields={
+ "indexname": struct_pb2.Value(string_value=f"{INDEX_NAME}"),
+ "tablename": struct_pb2.Value(string_value=f"{TABLE_NAME}"),
+ "schemaname": struct_pb2.Value(string_value=f"{SCHEMA_NAME}"),
+ "databasename": struct_pb2.Value(string_value=f"{DATABASE_NAME}"),
+ "indexcreated": struct_pb2.Value(string_value=f"{INDEX_CREATED}"),
+ }
+ ),
+ )
+ }
+ print(aspects)
+
+ entry = dataplex_v1.Entry()
+ entry.name = name
+ entry.entry_type = entry_type
+ entry.aspects = aspects
+ parent = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}"
+ print(parent)
+ client = dataplex_v1.CatalogServiceClient()
+ response = client.create_entry(parent=parent, entry=entry, entry_id=entry_id)
+ print("Index successfully loaded in Dataplex")
+
+# Query 7: FUNCTIONS
+try:
+ cursor_function = conn.cursor()
+ query_function = "select * from snowflake.account_usage.functions;"
+ cursor_function.execute(query_function)
+
+ # Fetch all results and load into a Pandas DataFrame
+ df_function = pd.DataFrame(cursor_function.fetchall(), columns=[col[0] for col in cursor_function.description])
+ print("\n--- Output for ACCOUNT_USUAGE.FUNCTIONS ---")
+ print(df_function.head()) # Print first few rows
+ print(f"Total rows for FUNCTIONS: {len(df_function)}")
+
+except Exception as e:
+ print(f"Error executing FUNCTIONS query: {e}")
+finally:
+ if 'cursor_function' in locals() and cursor_function:
+ cursor_function.close()
+
+for _, row in df_function.iterrows():
+ FUNCTION_NAME = row['FUNCTION_NAME']
+ FUNCTION_SCHEMA = row['FUNCTION_SCHEMA']
+ FUNCTION_CATALOG = row['FUNCTION_CATALOG']
+ FUNCTION_OWNER = row['FUNCTION_OWNER']
+ ARGUMENT_SIGNATURE = str(row['ARGUMENT_SIGNATURE'])
+ DATA_TYPE = str(row['DATA_TYPE'])
+ FUNCTION_LANGUAGE = row['FUNCTION_LANGUAGE']
+ FUNCTION_DEFINITION = str(row['FUNCTION_DEFINITION'])
+ FUNCTION_CREATED = str(row['CREATED'])
+ FUNCTION_LAST_ALTERED = str(row['LAST_ALTERED'])
+ FUNCTION_COMMENT = row['COMMENT']
+ print(FUNCTION_NAME,FUNCTION_SCHEMA,FUNCTION_CATALOG,FUNCTION_OWNER,ARGUMENT_SIGNATURE,DATA_TYPE,FUNCTION_LANGUAGE,FUNCTION_DEFINITION,FUNCTION_CREATED,FUNCTION_LAST_ALTERED,FUNCTION_COMMENT)
+ print(type(FUNCTION_CREATED))
+ entry_id = f"{FUNCTION_NAME}".replace('.', '-').replace(' ', '_').upper()
+ entry_id = entry_id[:40].strip('-').strip('_')
+ print(entry_id)
+
+ entry_group_id = "snowflakehorizongrp" #enter your entry group id that you created in Step 3 of the README File.
+ entry_type_id = "snowhorizonfunction" #enter your entry type id that you created in Step 3 of the README File.
+ name = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}/entries/{entry_id}"
+ print(name)
+ entry_type = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryTypes/{entry_type_id}"
+ print(entry_type)
+ aspects={
+ f"{PROJECT_ID}.{DATAPLEX_LOCATION}.{entry_type_id}": dataplex_v1.Aspect(
+ aspect_type=f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/aspectTypes/{entry_type_id}",
+ data=struct_pb2.Struct(
+ fields={
+ "functionname": struct_pb2.Value(string_value=f"{FUNCTION_NAME}"),
+ "functionschema": struct_pb2.Value(string_value=f"{FUNCTION_SCHEMA}"),
+ "functioncatalog": struct_pb2.Value(string_value=f"{FUNCTION_CATALOG}"),
+ "functionowner": struct_pb2.Value(string_value=f"{FUNCTION_OWNER}"),
+ "argumentsignature": struct_pb2.Value(string_value=f"{ARGUMENT_SIGNATURE}"),
+ "datatype": struct_pb2.Value(string_value=f"{DATA_TYPE}"),
+ "functionlanguage": struct_pb2.Value(string_value=f"{FUNCTION_LANGUAGE}"),
+ "functiondefinition": struct_pb2.Value(string_value=f"{FUNCTION_DEFINITION}"),
+ "functioncreated": struct_pb2.Value(string_value=f"{FUNCTION_CREATED}"),
+ "functionlastaltered": struct_pb2.Value(string_value=f"{FUNCTION_LAST_ALTERED}"),
+ "functioncomment": struct_pb2.Value(string_value=f"{FUNCTION_COMMENT}"),
+ }
+ ),
+ )
+ }
+ print(aspects)
+
+ entry = dataplex_v1.Entry()
+ entry.name = name
+ entry.entry_type = entry_type
+ entry.aspects = aspects
+ parent = f"projects/{PROJECT_ID}/locations/{DATAPLEX_LOCATION}/entryGroups/{entry_group_id}"
+ print(parent)
+ client = dataplex_v1.CatalogServiceClient()
+ response = client.create_entry(parent=parent, entry=entry, entry_id=entry_id)
+ print("Function successfully loaded in Dataplex")
+
+#all done
\ No newline at end of file
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