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Spark Sql Optimizer

Listed
jeremylongshore·vlatest·data·MIT

Optimizes Spark SQL queries for performance by analyzing and suggesting improvements to execution plans – boosting query speed and efficiency.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jeremylongshore/tons-of-skills-marketplace --skill spark-sql-optimizer -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jeremylongshore

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Live repository

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About this skill

What it does

This skill optimizes Spark SQL queries to improve performance and efficiency. It analyzes query plans, identifies bottlenecks, and suggests or automatically applies transformations like predicate pushdown, join reordering, and broadcast joins. The goal is to reduce execution time and resource consumption for data processing tasks within a Spark environment.

When to use it

  • Slow Query Performance: When existing Spark SQL queries are taking an unacceptably long time to complete.
  • Resource Constraints: When running Spark jobs on limited hardware resources (e.g., smaller clusters).
  • Complex Joins: When dealing with complex join operations that significantly impact query execution time.
  • Large Datasets: When processing large datasets where even small optimizations can yield substantial performance gains.

Key capabilities

  • Query plan analysis
  • Predicate pushdown optimization
  • Join reordering
  • Broadcast join implementation
  • Automatic query transformation suggestions

Example prompts

  • "Optimize this Spark SQL query: SELECT * FROM table1 JOIN table2 ON table1.id = table2.id"
  • "Analyze the execution plan for my Spark SQL job and suggest improvements."
  • "Can you rewrite this query to use a broadcast join? SELECT ... FROM large_table JOIN small_table ON ..."

Tips & gotchas

  • Requires access to a running Spark environment. The agent needs permissions to analyze and potentially modify queries within the cluster.