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spark-history-cli

spark-history-cli enthält 4 gesammelte Skills von yaooqinn, mit Repository-Berufsabdeckung und Skill-Detailseiten auf SkillsMP.

gesammelte Skills
4
Stars
28
aktualisiert
2026-03-22
Forks
4
Berufsabdeckung
4 Berufskategorien · 100% klassifiziert
Repository-Explorer

Skills in diesem Repository

spark-advisor
Netzwerk- und Computersystemadministratoren

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
Computersystemanalytiker

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
Softwareentwickler

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
Datenwissenschaftler

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