-- Create API integration
CREATE OR REPLACE API INTEGRATION aws_api_integration
  API_PROVIDER = aws_api_gateway
  API_AWS_ROLE_ARN = 'arn:aws:iam::123456789012:role/snowflake-api-role'
  API_ALLOWED_PREFIXES = ('https://abc123.execute-api.us-east-1.amazonaws.com/prod')
  ENABLED = TRUE;

-- Check integration status
DESC INTEGRATION aws_api_integration;

CREATE OR REPLACE API INTEGRATION azure_api_integration
  API_PROVIDER = azure_api_management
  AZURE_TENANT_ID = 'your-tenant-id'
  AZURE_AD_APPLICATION_ID = 'your-app-id'
  API_ALLOWED_PREFIXES = ('https://myapim.azure-api.net/')
  ENABLED = TRUE;

CREATE OR REPLACE API INTEGRATION gcp_api_integration
  API_PROVIDER = google_cloud
  GCP_SERVICE_ACCOUNT = 'snowflake@my-project.iam.gserviceaccount.com'
  API_ALLOWED_PREFIXES = ('https://my-gateway-abc123.uc.r.appspot.com/')
  ENABLED = TRUE;

CREATE OR REPLACE EXTERNAL FUNCTION sentiment_analysis(text VARCHAR)
  RETURNS VARCHAR
  API_INTEGRATION = aws_api_integration
  MAX_BATCH_ROWS = 100
  AS 'https://abc123.execute-api.us-east-1.amazonaws.com/prod/sentiment';

CREATE OR REPLACE EXTERNAL FUNCTION translate_text(
  input_text VARCHAR,
  source_lang VARCHAR,
  target_lang VARCHAR
)
  RETURNS TABLE (translated_text VARCHAR, confidence DECIMAL(5,4))
  API_INTEGRATION = azure_api_integration
  MAX_BATCH_ROWS = 50
  AS 'https://myapim.azure-api.net/translate';

-- Simple call
SELECT
  customer_feedback,
  sentiment_analysis(customer_feedback) as sentiment
FROM feedback_table;

-- Table function call
SELECT
  f.translated_text,
  f.confidence
FROM my_table,
LATERAL TABLE(translate_text(text, 'en', 'es')) f;

import json
import boto3
from datetime import datetime

def lambda_handler(event, context):
    """
    Snowflake External Function Handler
    Receives batch of rows and returns results
    """
    # Parse Snowflake request
    rows = event['data']
    results = []
    
    for row in rows:
        row_number = row[0]
        input_data = row[1:]
        
        # Custom processing logic
        result = process_data(input_data)
        
        results.append({
            'row_number': row_number,
            'data': [result]
        })
    
    return {'data': results}

def process_data(data):
    # Custom business logic here
    # Example: sentiment analysis, translation, etc.
    return {"processed": True, "timestamp": datetime.utcnow().isoformat()}

-- Create function with error handling
CREATE OR REPLACE EXTERNAL FUNCTION safe_api_call(input VARCHAR)
  RETURNS VARCHAR
  API_INTEGRATION = aws_api_integration
  MAX_BATCH_ROWS = 100
  AS 'https://api.example.com/process';

-- Handle errors in queries
SELECT
  input_data,
  safe_api_call(input_data) as result
FROM my_table
WHERE safe_api_call(input_data) IS NOT NULL;

-- Check function invocations
SELECT *
FROM TABLE(INFORMATION_SCHEMA.EXTERNAL_FUNCTION_INVOCATION_HISTORY(
  START_TIME => DATEADD(hour, -24, CURRENT_TIMESTAMP()),
  END_TIME => CURRENT_TIMESTAMP()
))
ORDER BY START_TIME DESC;