There could be several reasons for the Spark Executor to become unresponsive during remote fetches of ShuffleBlockFetcherIterator. Some of the common ones are:
Network congestion: If the network between the Executor and the remote nodes is congested, it can cause delays or timeouts during the fetch process.
Resource contention: If the Executor is running other tasks or services that are consuming a lot of resources (CPU, memory, disk), it may not have enough resources available to handle the fetch requests.
Slow remote nodes: If the remote nodes are slow or overloaded, it can cause delays or timeouts during the fetch process.
Garbage collection: If the Executor is doing a lot of garbage collection, it can cause pauses in the JVM that may affect the responsiveness of the fetch process.
Bugs or configuration problems: Finally, there could be bugs or misconfigurations in the Spark, Hadoop or network configurations that could cause the fetch process to fail or become unresponsive.
Please start posting anonymously - your entry will be published after you log in or create a new account. This space is reserved only for answers. If you would like to engage in a discussion, please instead post a comment under the question or an answer that you would like to discuss
Asked: 2023-06-16 09:49:12 +0000
Seen: 10 times
Last updated: Jun 16 '23
What is the reason for the appearance of both WinForms ComboBox DropDown and Autocomplete window?
What is the reason for websites adjusting the default font size to 14px?
What is the reason for the authentication failure in Azure GIT?
What is the reason for R returning a line that has no slope?
What is the reason for Pytorch's loss function returning nan?
What could be the reason for my Material UI Tabs component to randomly override other styles?
What is the reason for the Django channels websocket resulting in a 404 error?