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Expected behavior:
Sparkling water can train individual models like XGBoost then it should also run for automl api.
Observed behavior:
Sparkling water can train individual models like XGBoost but fail to run with automl api.
Programming language used
Python
Programming language version
3.11
What environment are you running Sparkling Water on?
Runtime 15.4.x-scala2.12, 1 Driver with 64 GB Memory, 8 Cores, 7 Workers with 64 GB Memory 8 Cores
Relevant log output
Dont have any error logs as process continues for long time.
Code to reproduce the issue
No response
The text was updated successfully, but these errors were encountered:
aniketaitawade
changed the title
AutoML is not working the data of 30 Million rows with 150 features
AutoML is not working properly with large volume of data(30 Million rows with 150 features)
Nov 20, 2024
Sparkling Water Version
3.5
Issue description
Expected behavior:
Sparkling water can train individual models like XGBoost then it should also run for automl api.
Observed behavior:
Sparkling water can train individual models like XGBoost but fail to run with automl api.
Programming language used
Python
Programming language version
3.11
What environment are you running Sparkling Water on?
Cloud Managed Spark (like Databricks, AWS Glue)
Environment version info
15.4 LTS (includes Apache Spark 3.5.0, Scala 2.12)
Brief cluster specification
Runtime 15.4.x-scala2.12, 1 Driver with 64 GB Memory, 8 Cores, 7 Workers with 64 GB Memory 8 Cores
Relevant log output
Dont have any error logs as process continues for long time.
Code to reproduce the issue
No response
The text was updated successfully, but these errors were encountered: