Superset是否支持查询缓存？企业重复查询优化需求

Absolutely! Superset comes with built-in query caching capabilities that are perfect for solving the exact issue you’re dealing with—redundant, identical queries across your enterprise for Athena, Redshift, and other data sources. This feature not only speeds up query/dashboard load times but can also cut down on costs for pay-per-query services like Athena.

How It Works & Core Features #

• Flexible Cache Storage: You can configure Superset to use backend stores like Redis, Memcached, or the default SQLAlchemy backend (though Redis/Memcached are strongly recommended for enterprise-scale performance).
• Granular TTL Control:
  • Database-level: Set a default cache time-to-live (TTL) for all queries against a specific database (e.g., 1 hour for Redshift, 4 hours for less-frequently updated Athena datasets).
  • Chart/dashboard-level: Override the default TTL for individual charts or dashboards if needed—great for data that updates more or less often than the database default.
• Cache Invalidation: Cached results automatically expire after their TTL, but you can also manually invalidate specific cached queries or clear the entire cache whenever you know underlying data has been updated (e.g., after a nightly ETL job).

Quick Setup Steps #

1. First, get your cache backend running (e.g., spin up a Redis instance in your environment).
2. Update your superset_config.py file to enable caching and point to your backend:

   # Example Redis configuration
   from flask_caching.backends.rediscache import RedisCache
   
   CACHE_CONFIG = {
       'CACHE_TYPE': 'RedisCache',
       'CACHE_REDIS_URL': 'redis://your-redis-host:6379/0',
       'CACHE_DEFAULT_TIMEOUT': 3600,  # Default TTL in seconds (1 hour)
   }
   
   # Enable query caching globally
   ENABLE_QUERY_CACHE = True
   

3. Adjust database-specific settings in the Superset UI:
   • Go to Data > Databases, edit your Athena/Redshift connection.
   • Under the Advanced tab, set the "Cache Timeout" value to match your data refresh frequency.
4. For individual charts/dashboards: When editing a chart, look for the "Cache Timeout" option in the advanced settings to override the database default.

Key Considerations for Your Data Sources #

• Athena: Since Athena charges per query, caching can drastically reduce your costs by avoiding repeated identical runs. Just ensure your TTL aligns with how often your S3 data is updated—no need to cache data that changes hourly for 24 hours.
• Redshift: Caching works wonders for read-heavy workloads. If your Redshift tables have frequent writes, set a shorter TTL or manually clear the cache after data loads to ensure users see fresh results.
• Cache Key Logic: Superset generates unique cache keys based on query text, user permissions, database connection details, and other parameters. This means identical queries from different users (with the same access rights) will reuse the same cache—ideal for enterprise-wide efficiency.

内容的提问来源于stack exchange，提问作者Nipun