"""Asset checks for app_event to validate data quality.""" import dagster as dg from dagster_snowflake import SnowflakeResource from src.assets.snowflake.raw_table.frontend.app_event.assets import APP_EVENT_TABLE_NAME, WAREHOUSE from src.utils.snowflake.partition_utils import parse_hourly_partition_key # Constants for validation MIN_ROW_COUNT = 0 # Allow partitions with 0 rows MAX_NULL_RATE_USER_ID = 0.50 # Allow up to 50% null USER_ID (anonymous users) MAX_NULL_RATE_ANONYMOUS_ID = 0.05 # Most events should have anonymous_id MAX_NULL_RATE_SESSION_ID = 0.3 # Most events should have session MAX_VOLUME_CHANGE_RATE = 0.10 # Maximum 10% change from previous day @dg.asset_check(asset="app_event", blocking=False) def check_minimum_row_count(context: dg.AssetCheckExecutionContext, snowflake: SnowflakeResource) -> dg.AssetCheckResult: """Ensure minimum row count threshold is met (at least 0 rows).""" partition_key = context.op_execution_context.partition_key p_date, p_hour = parse_hourly_partition_key(partition_key) with snowflake.get_connection() as conn: cursor = conn.cursor() cursor.execute(f"USE WAREHOUSE {WAREHOUSE}") query = f""" SELECT COUNT(*) as row_count FROM {APP_EVENT_TABLE_NAME} WHERE p_date = '{p_date}' and p_hour = {p_hour} """ result = cursor.execute(query).fetchone() row_count = result[0] if result else 0 passed = row_count >= MIN_ROW_COUNT return dg.AssetCheckResult( passed=passed, metadata={ "partition_key": partition_key, "p_date": p_date, "p_hour": p_hour, "row_count": row_count, "min_threshold": MIN_ROW_COUNT, }, description=f"Row count: {row_count:,} (threshold: {MIN_ROW_COUNT:,})" ) @dg.asset_check(asset="app_event", blocking=False) def check_user_id_null_rate(context: dg.AssetCheckExecutionContext, snowflake: SnowflakeResource) -> dg.AssetCheckResult: """Check that USER_ID null rate is below 50% (many users are anonymous).""" partition_key = context.op_execution_context.partition_key p_date, p_hour = parse_hourly_partition_key(partition_key) with snowflake.get_connection() as conn: cursor = conn.cursor() cursor.execute(f"USE WAREHOUSE {WAREHOUSE}") query = f""" SELECT COUNT(*) as total_count, SUM(CASE WHEN USER_ID IS NULL OR USER_ID = '' THEN 1 ELSE 0 END) as null_count FROM {APP_EVENT_TABLE_NAME} WHERE p_date = '{p_date}' and p_hour = {p_hour} """ result = cursor.execute(query).fetchone() total_count = result[0] if result else 0 null_count = result[1] if result and result[1] else 0 null_rate = null_count / total_count if total_count > 0 else 0 passed = null_rate <= MAX_NULL_RATE_USER_ID return dg.AssetCheckResult( passed=passed, metadata={ "partition_key": partition_key, "p_date": p_date, "p_hour": p_hour, "null_count": null_count, "total_count": total_count, "null_rate": f"{null_rate:.2%}", "threshold": f"{MAX_NULL_RATE_USER_ID:.2%}", }, description=f"USER_ID null rate: {null_rate:.2%} (threshold: {MAX_NULL_RATE_USER_ID:.2%})" ) @dg.asset_check(asset="app_event", blocking=False) def check_anonymous_id_null_rate(context: dg.AssetCheckExecutionContext, snowflake: SnowflakeResource) -> dg.AssetCheckResult: """Check that ANONYMOUS_ID null rate is below 1%.""" partition_key = context.op_execution_context.partition_key p_date, p_hour = parse_hourly_partition_key(partition_key) with snowflake.get_connection() as conn: cursor = conn.cursor() cursor.execute(f"USE WAREHOUSE {WAREHOUSE}") query = f""" SELECT COUNT(*) as total_count, SUM(CASE WHEN ANONYMOUS_ID IS NULL OR ANONYMOUS_ID = '' THEN 1 ELSE 0 END) as null_count FROM {APP_EVENT_TABLE_NAME} WHERE p_date = '{p_date}' and p_hour = {p_hour} """ result = cursor.execute(query).fetchone() total_count = result[0] if result else 0 null_count = result[1] if result and result[1] else 0 null_rate = null_count / total_count if total_count > 0 else 0 passed = null_rate <= MAX_NULL_RATE_ANONYMOUS_ID return dg.AssetCheckResult( passed=passed, metadata={ "partition_key": partition_key, "p_date": p_date, "p_hour": p_hour, "null_count": null_count, "total_count": total_count, "null_rate": f"{null_rate:.2%}", "threshold": f"{MAX_NULL_RATE_ANONYMOUS_ID:.2%}", }, description=f"ANONYMOUS_ID null rate: {null_rate:.2%} (threshold: {MAX_NULL_RATE_ANONYMOUS_ID:.2%})" ) @dg.asset_check(asset="app_event", blocking=False) def check_session_id_null_rate(context: dg.AssetCheckExecutionContext, snowflake: SnowflakeResource) -> dg.AssetCheckResult: """Check that SESSION_ID null rate is below 5%.""" partition_key = context.op_execution_context.partition_key p_date, p_hour = parse_hourly_partition_key(partition_key) with snowflake.get_connection() as conn: cursor = conn.cursor() cursor.execute(f"USE WAREHOUSE {WAREHOUSE}") query = f""" SELECT COUNT(*) as total_count, SUM(CASE WHEN SESSION_ID IS NULL OR SESSION_ID = '' THEN 1 ELSE 0 END) as null_count FROM {APP_EVENT_TABLE_NAME} WHERE p_date = '{p_date}' and p_hour = {p_hour} """ result = cursor.execute(query).fetchone() total_count = result[0] if result else 0 null_count = result[1] if result and result[1] else 0 null_rate = null_count / total_count if total_count > 0 else 0 passed = null_rate <= MAX_NULL_RATE_SESSION_ID return dg.AssetCheckResult( passed=passed, metadata={ "partition_key": partition_key, "p_date": p_date, "p_hour": p_hour, "null_count": null_count, "total_count": total_count, "null_rate": f"{null_rate:.2%}", "threshold": f"{MAX_NULL_RATE_SESSION_ID:.2%}", }, description=f"SESSION_ID null rate: {null_rate:.2%} (threshold: {MAX_NULL_RATE_SESSION_ID:.2%})" ) @dg.asset_check(asset="app_event", blocking=False) def check_distinct_users_and_sessions(context: dg.AssetCheckExecutionContext, snowflake: SnowflakeResource) -> dg.AssetCheckResult: """Check distinct user and session counts.""" partition_key = context.op_execution_context.partition_key p_date, p_hour = parse_hourly_partition_key(partition_key) with snowflake.get_connection() as conn: cursor = conn.cursor() cursor.execute(f"USE WAREHOUSE {WAREHOUSE}") query = f""" SELECT COUNT(*) as total_count, COUNT(DISTINCT USER_ID) as distinct_users, COUNT(DISTINCT ANONYMOUS_ID) as distinct_anonymous, COUNT(DISTINCT SESSION_ID) as distinct_sessions FROM {APP_EVENT_TABLE_NAME} WHERE p_date = '{p_date}' and p_hour = {p_hour} """ result = cursor.execute(query).fetchone() total_count = result[0] if result else 0 distinct_users = result[1] if result else 0 distinct_anonymous = result[2] if result else 0 distinct_sessions = result[3] if result else 0 # Calculate average events per user/session avg_events_per_user = total_count / distinct_users if distinct_users > 0 else 0 avg_events_per_session = total_count / distinct_sessions if distinct_sessions > 0 else 0 # Pass if we have distinct values (or total_count is 0) passed = total_count == 0 or (distinct_users > 0 or distinct_anonymous > 0) and distinct_sessions > 0 return dg.AssetCheckResult( passed=passed, metadata={ "partition_key": partition_key, "p_date": p_date, "p_hour": p_hour, "total_count": total_count, "distinct_users": distinct_users, "distinct_anonymous": distinct_anonymous, "distinct_sessions": distinct_sessions, "avg_events_per_user": round(avg_events_per_user, 2), "avg_events_per_session": round(avg_events_per_session, 2), }, description=f"Users: {distinct_users:,}, Anonymous: {distinct_anonymous:,}, Sessions: {distinct_sessions:,}" ) @dg.asset_check(asset="app_event", blocking=False) def check_day_over_day_volume(context: dg.AssetCheckExecutionContext, snowflake: SnowflakeResource) -> dg.AssetCheckResult: """Check that daily data volume doesn't decrease more than 20% from previous day.""" partition_key = context.op_execution_context.partition_key p_date, p_hour = parse_hourly_partition_key(partition_key) # Maximum allowed decrease rate (20%) MAX_DECREASE_RATE = 0.20 with snowflake.get_connection() as conn: cursor = conn.cursor() cursor.execute(f"USE WAREHOUSE {WAREHOUSE}") # Get both today's and yesterday's count in one query query = f""" SELECT SUM(CASE WHEN p_date = '{p_date}' THEN 1 ELSE 0 END) as today_count, SUM(CASE WHEN p_date = DATEADD(day, -1, '{p_date}'::date) THEN 1 ELSE 0 END) as yesterday_count FROM {APP_EVENT_TABLE_NAME} WHERE p_date IN ('{p_date}', DATEADD(day, -1, '{p_date}'::date)) AND p_hour = {p_hour} """ result = cursor.execute(query).fetchone() today_count = result[0] if result and result[0] else 0 yesterday_count = result[1] if result and result[1] else 0 # Calculate change if yesterday_count == 0: # If no data yesterday, skip this check return dg.AssetCheckResult( passed=True, metadata={ "partition_key": partition_key, "p_date": p_date, "p_hour": p_hour, "today_count": today_count, "yesterday_count": yesterday_count, "change_rate": None, }, description=f"No data from yesterday to compare. Today: {today_count:,}" ) # Check if volume increased or stayed same - always pass if today_count >= yesterday_count: change_rate = (today_count - yesterday_count) / yesterday_count return dg.AssetCheckResult( passed=True, metadata={ "partition_key": partition_key, "p_date": p_date, "p_hour": p_hour, "today_count": today_count, "yesterday_count": yesterday_count, "change_rate": round(change_rate, 4), "change_percentage": f"+{round(change_rate * 100, 2)}%", }, description=f"Volume increased or stable: +{round(change_rate * 100, 2)}%. Today: {today_count:,}, Yesterday: {yesterday_count:,}" ) # Volume decreased - check if decrease is within acceptable range decrease_rate = (yesterday_count - today_count) / yesterday_count passed = decrease_rate <= MAX_DECREASE_RATE return dg.AssetCheckResult( passed=passed, metadata={ "partition_key": partition_key, "p_date": p_date, "p_hour": p_hour, "today_count": today_count, "yesterday_count": yesterday_count, "decrease_rate": round(decrease_rate, 4), "decrease_percentage": f"-{round(decrease_rate * 100, 2)}%", "max_allowed_decrease": f"{MAX_DECREASE_RATE * 100}%", }, description=f"Volume decreased: -{round(decrease_rate * 100, 2)}% (threshold: -{MAX_DECREASE_RATE * 100}%). Today: {today_count:,}, Yesterday: {yesterday_count:,}" ) # Export all asset checks asset_checks = [ check_minimum_row_count, check_user_id_null_rate, check_anonymous_id_null_rate, check_session_id_null_rate, check_distinct_users_and_sessions, check_day_over_day_volume, ] __all__ = ["asset_checks"]