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Azure Databricks Troubleshooting Guide¶

Comprehensive troubleshooting guide for Azure Databricks including cluster issues, Spark performance, Delta Lake problems, and data quality concerns.

Issue Category	Description	Guide
🚀 Cluster Issues	Startup failures, node provisioning	Cluster Startup
🔢 Node Provisioning	Node allocation, autoscaling	Node Provisioning
🧠 Memory Issues	OOM errors, memory pressure	Memory Issues
📊 Query Performance	Slow queries, optimization	Query Performance
🔄 Shuffle Optimization	Shuffle operations, spills	Shuffle Optimization
🏗️ Delta Lake Issues	Delta table problems, transactions	Delta Issues
📐 Schema Evolution	Schema changes, compatibility	Schema Evolution
🌐 Networking	Connectivity, VNet integration	Networking
✅ Data Quality	Data validation, corruption	Data Quality

Common Error Categories¶

Cluster Errors¶

Cluster start timeout
Node termination
Driver not responding
Cloud provider limits reached

Runtime Errors¶

OutOfMemoryError
StackOverflowError
SparkException
AnalysisException

Data Errors¶

File not found
Schema mismatch
Corrupt data files
Concurrent modification

Quick Diagnostics¶

Check Cluster Health¶

# Get cluster status
import requests

DATABRICKS_INSTANCE = "https://<workspace>.azuredatabricks.net"
TOKEN = dbutils.secrets.get(scope="<scope>", key="<key>")

def get_cluster_status(cluster_id):
    """Get current cluster status."""

    url = f"{DATABRICKS_INSTANCE}/api/2.0/clusters/get"
    headers = {"Authorization": f"Bearer {TOKEN}"}
    params = {"cluster_id": cluster_id}

    response = requests.get(url, headers=headers, params=params)
    cluster_info = response.json()

    print(f"Cluster: {cluster_info['cluster_name']}")
    print(f"State: {cluster_info['state']}")
    print(f"Spark Version: {cluster_info['spark_version']}")
    print(f"Nodes: {cluster_info.get('num_workers', 'N/A')}")

    return cluster_info

Check Spark Configuration¶

# Display current Spark configuration
spark.sparkContext.getConf().getAll()

Support Escalation¶

Contact Databricks/Azure Support if:

Resource	Link
Databricks Documentation	docs.databricks.com
Azure Databricks	Microsoft Docs
Spark Documentation	spark.apache.org

Last Updated: 2025-12-10 Version: 1.0.0