zjt-peekaboo/spark_history_mcp_server
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The Model Context Protocol (MCP) server is designed to facilitate the management and optimization of Spark applications by providing a suite of tools and resources for performance analysis and diagnostics.
Tools
Functions exposed to the LLM to take actions
compare_job_environments
Compare Spark environment configurations between two jobs
compare_job_performance
Compare performance metrics between two Spark jobs
get_application
Get detailed information about a specific Spark application
get_environment
Get the environment information for a Spark application
get_executor
Get information about a specific executor
get_executor_summary
Get a summary of executors about a application
get_job_bottlenecks
Identify performance bottlenecks in a Spark job
get_resource_usage_timeline
Get resource usage timeline for a Spark application
get_sql_list
Get a list of SQL queries for a Spark application
get_stage
Get information about a specific stage
get_stage_task_summary
Get a summary metrics of all tasks in the given stage attempt
list_applications
Get a list of applications from the Spark History Server
list_executors
Get a list of all executors for a Spark application
list_jobs
Get a list of all jobs for a Spark application
list_slowest_jobs
Get the N slowest jobs for a Spark application
list_slowest_sql_queries
Get the N slowest SQL queries for a Spark application
list_slowest_stages
Get the N slowest stages for a Spark application
list_stages
Get a list of all stages for a Spark application
Prompts
Interactive templates invoked by user choice
No prompts
Resources
Contextual data attached and managed by the client