Azure HDInsight Troubleshooting Guide¶
Troubleshooting guide for Azure HDInsight clusters including Hadoop, Spark, Hive, HBase, and Kafka workloads.
Overview¶
Azure HDInsight is a managed Apache Hadoop service. This guide covers common issues across different cluster types and workloads.
Cluster Types¶
| Type | Use Case | Common Issues |
|---|---|---|
| Hadoop | Batch processing | YARN capacity, MapReduce failures |
| Spark | Analytics, ML | Memory issues, shuffle problems |
| HBase | NoSQL database | RegionServer failures, compaction |
| Kafka | Streaming | Broker failures, replication lag |
| Interactive Query | Low-latency queries | LLAP daemon issues |
| Storm | Real-time processing | Topology failures |
Common Issues¶
Cluster Provisioning Failures¶
- Insufficient quota
- VNet configuration issues
- Storage account access
- Invalid configurations
Performance Issues¶
- Slow queries
- Resource contention
- Network bottlenecks
- Storage I/O limits
Stability Issues¶
- Node failures
- Service crashes
- Disk space issues
- Memory pressure
Diagnostic Tools¶
Ambari UI¶
Access cluster management interface: ```texthttps://
Check Cluster Health¶
# Using Azure CLI
az hdinsight show \
--name <cluster-name> \
--resource-group <rg-name>
# Get cluster metrics
az monitor metrics list \
--resource <cluster-resource-id> \
--metric "CoresCapacity" "CoresUsed" "MemoryCapacity" "MemoryUsed"
Related Resources¶
| Resource | Link |
|---|---|
| HDInsight Documentation | Microsoft Docs |
| Ambari Documentation | Apache Ambari |
| Troubleshooting Guide | HDInsight Troubleshooting |
Last Updated: 2025-12-10 Version: 1.0.0