Construct a Spark SQL agent from an LLM and tools.
This agent can execute arbitrary SQL against your Spark environment.
By default, the agent is allowed to generate SQL strings and run them via the underlying connection. This is powerful, but it also means the agent can generate expensive or dangerous queries (e.g., long-running queries, large scans/joins, or locking queries depending on your environment and permissions).
create_spark_sql_agent returns a langchain_classic AgentExecutor.
AgentExecutor is an agent abstraction that has long been considered legacy
and is not actively supported as the recommended foundation for new production
applications.
For production-grade agent development, prefer building with Deep Agents: https://github.com/langchain-ai/deepagents
If you use this in production, coordinate with your security/DB teams and apply server-side controls:
Client-side timeouts do not always guarantee that a running statement is cancelled on the server.
Spark SQL agent.
