Hi Folks!
I'm running a Python Spark job on a cluster with 1 master and 10 slaves
(64G RAM and 32 cores each machine).
This job reads a file with 1.2 terabytes and 1128201847 lines on HDFS and
call Kmeans method as following:
# SLAVE CODE - Reading features from HDFS
def
How many features and how many partitions? You set kmeans_clusters to
1. If the feature dimension is large, it would be really
expensive. You can check the WebUI and see task failures there. The
stack trace you posted is from the driver. Btw, the total memory you
have is 64GB * 10, so you can
