Clusters

These articles can help you manage your Apache Spark clusters.

• Enable OpenJSSE and TLS 1.3
• How to calculate the number of cores in a cluster
• Install a private PyPI repo
• IP access list update returns INVALID_STATE
• Launch fails with Client.InternalError
• Cannot apply updated cluster policy
• Cluster Apache Spark configuration not applied
• Cluster failed to launch
• Custom Docker image requires root
• Custom garbage collection prevents cluster launch
• Job fails due to cluster manager core instance request limit
• Admin user cannot restart cluster to run job
• Cluster fails to start with dummy does not exist error
• Cluster slowdown due to Ganglia metrics filling root partition
• Failed to create cluster with invalid tag value
• Failed to expand the EBS volume
• EBS leaked volumes
• Log delivery fails with AssumeRole
• Multi-part upload failure
• Persist Apache Spark CSV metrics to a DBFS location
• Replay Apache Spark events in a cluster
• S3 connection fails with No role specified and no roles available
• Set Apache Hadoop core-site.xml properties
• Set executor log level
• Set instance_profile_arn as optional with a cluster policy
• Apache Spark job doesn’t start
• Auto termination is disabled when starting a job cluster
• Unexpected cluster termination
• How to configure single-core executors to run JNI libraries
• How to overwrite log4j configurations on Databricks clusters
• Adding a configuration setting overwrites all default spark.executor.extraJavaOptions settings
• Apache Spark executor memory allocation
• Apache Spark UI shows less than total node memory
• Configure a cluster to use a custom NTP server
• Enable GCM cipher suites
• Enable retries in init script
• Validate environment variable behavior