Cloudera Data Engineering performance tuning
Use local SSD
Using default instances without local SSD does impact performance. Instances with local SSDs generally provide faster performance, but you need to ensure you choose instance types that have large enough local storage for intermediate results.
Avoid instance types with low compute profiles
Make sure there is reasonable headroom (at least 20%) between the per executor memory and core usage and what the instance profile provides.
Disable Spark Analysis
By default, CDE collects metrics around CPU, memory, and I/O. This can have a negative impact on performance - especially for long running jobs that take several hours to complete. Profiling metrics are useful in development and testing, but an unnecessary overhead in a production setting.
You can turn this feature off using the Spark Analysis toggle on the job Configuration tab.
Turn off dynamic allocation
Dynamic allocation is ideal for cost management but does have overhead associated with it. For best performance, disable it.
Use Spark 3 instead of Spark 2
Spark 3 introduced performance improvements over Spark 2, therefore Cloudera recommends using it whenever possible.