- #Eboostr problems (very little cache fill) driver#
- #Eboostr problems (very little cache fill) series#
#Eboostr problems (very little cache fill) series#
In this series of articles, I aim to capture some of the most common reasons why a Spark application fails or slows down. It’s not only important to understand a Spark application, but also its underlying runtime components like disk usage, network usage, contention, etc., so that we can make an informed decision when things go bad. Sometimes an application which was running well so far, starts behaving badly due to resource starvation. (See our blog Spark Troubleshooting, Part 1 – Ten Challenges.) Sometimes a well-tuned application might fail due to a data change, or a data layout change. However, it becomes very difficult when Spark applications start to slow down or fail. Spark applications are easy to write and easy to understand when everything goes according to plan.