gcp-spark-troubleshooting
Provides expert guidance for troubleshooting Google Cloud Spark and Dataproc workloads (Dataproc Serverless batches and standard Dataproc clusters), and inspecting, streaming, searching, tailing, or summarizing Spark driver outputs and event logs in Cloud Storage. Use when the user asks to debug, troubleshoot, diagnose, or perform Root Cause Analysis (RCA) on failed Spark jobs, PySpark batches, or Spark event logs.
- Version
- v2
- License
- Apache-2.0
Pinned to revision 4e8964e24a5a, so it is the text this page describes rather than whatever the author pushed since.
Files
- skills/gcp-spark-troubleshooting/SKILL.md
- skills/gcp-spark-troubleshooting/LICENSE
- skills/gcp-spark-troubleshooting/references/diagnostic_rules_catalog.md
- skills/gcp-spark-troubleshooting/references/gcs_event_log_guide.md
- skills/gcp-spark-troubleshooting/references/rca_report_template.md
- skills/gcp-spark-troubleshooting/references/spark_log_patterns.md
- skills/gcp-spark-troubleshooting/scripts/spark_code_inspector.py
- skills/gcp-spark-troubleshooting/scripts/spark_gcs_log_reader.py
- skills/gcp-spark-troubleshooting/scripts/spark_stage_diagnostics.py
- skills/gcp-spark-troubleshooting/tests/spark_code_inspector_test.py
- skills/gcp-spark-troubleshooting/tests/spark_gcs_log_reader_test.py
- skills/gcp-spark-troubleshooting/tests/spark_stage_diagnostics_test.py
Every link opens the file at its source, pinned to the revision this page describes.