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spark-history-cli

spark-history-cli contient 4 skills collectées depuis yaooqinn, avec une couverture métier par dépôt et des pages de détail sur le site.

skills collectés
4
Stars
28
mis à jour
2026-03-22
Forks
4
Couverture métier
4 catégories métier · 100% classifié
explorateur de dépôts

Skills dans ce dépôt

spark-advisor
Administrateurs de réseaux et de systèmes informatiques

Diagnose, compare, and optimize Apache Spark applications and SQL queries using Spark History Server data. Use this skill whenever the user wants to understand why a Spark app is slow, compare two benchmark runs or TPC-DS results, find performance bottlenecks (skew, GC pressure, shuffle spill, straggler tasks), get tuning recommendations, or optimize Spark/Gluten configurations. Also trigger when the user mentions 'diagnose', 'compare runs', 'why is this query slow', 'tune my Spark job', 'benchmark comparison', 'performance regression', or asks about executor skew, shuffle overhead, AQE effectiveness, or Gluten offloading issues.

2026-03-22
spark-history-cli
Analystes des systèmes informatiques

Query a running Apache Spark History Server from Copilot CLI. Use this whenever the user wants to inspect SHS applications, jobs, stages, executors, SQL executions, environment details, or event logs, especially when they mention Spark History Server, SHS, event log history, benchmark runs, or application IDs.

2026-03-20
spark-history-cli
Développeurs de logiciels

Query a running Apache Spark History Server from Copilot CLI. Use this whenever the user wants to inspect SHS applications, jobs, stages, executors, SQL executions, environment details, or event logs, especially when they mention Spark History Server, SHS, event log history, benchmark runs, or application IDs.

2026-03-20
spark-advisor
Scientifiques des données

Diagnose, compare, and optimize Apache Spark applications and SQL queries using Spark History Server data. Use this skill whenever the user wants to understand why a Spark app is slow, compare two benchmark runs or TPC-DS results, find performance bottlenecks (skew, GC pressure, shuffle spill, straggler tasks), get tuning recommendations, or optimize Spark/Gluten configurations. Also trigger when the user mentions 'diagnose', 'compare runs', 'why is this query slow', 'tune my Spark job', 'benchmark comparison', 'performance regression', or asks about executor skew, shuffle overhead, AQE effectiveness, or Gluten offloading issues.

2026-03-20