Thanks for suggestion, but our application is still crashing
*Description: * flatMap at MatrixFactorizationModel.scala:278
*Failure Reason: * Job aborted due to stage failure: Task 1 in stage 6.0
failed 4 times, most recent failure: Lost task 1.3 in stage 6.0 (TID 116,
dev.local): ExecutorLostFa
Hi,
While building Recommendation engine using spark MLlib (ALS) we are facing
some issues during execution.
Details are below.
We are trying to train our model on 1.4 million sparse rating records (1,00,
000 customer X 50,000 items). The execution DAG cycle is taking a long time
and is crash
