Marek Novotný

> we could use a "visitor" pattern to inspect all objects metrics @michalkurka I will change the PR as you suggested. it will be more robust. Thanks!

@michalkurka I've implemented your suggestion.

Is it possible? There is not much we could highlight about UDFs except their names... Even Spark Catalyst has to treat them as a black box since information extraction from...

Thanks for reporting the problem, it will be covered by the Jira ticket [SW-2736](https://h2oai.atlassian.net/browse/SW-2736).

Hi @cliu-sift, > illuminate me a little bit more on why the error occurred? The error doesn't happen during execution of the `XGboost` algorithm, but in the last step of...

@cliu-sift Regarding the second error, I will need see logs from H2O nodes (full yarn logs) to tell you what went wrong. `yarn logs -applicationId `

There is a problem with serialization of `XGBoostModelInfo`, for some reason is too big: ``` java.lang.OutOfMemoryError: Requested array size exceeds VM limit at java.lang.StringCoding.encode(StringCoding.java:350) at java.lang.String.getBytes(String.java:941) at water.util.StringUtils.bytesOf(StringUtils.java:197) at water.AutoBuffer.putStr(AutoBuffer.java:1527)...

Hi @cliu-sift, > Is there any way I could test the changes with your new code? You can try this nightly build: - https://h2o-release.s3.amazonaws.com/sparkling-water/spark-3.0/rel-3.36.1_rel-zumbo/nightly/3.36.1.5-1.5-3.0/index.html for spark 3.0 - https://h2o-release.s3.amazonaws.com/sparkling-water/spark-3.1/rel-3.36.1_rel-zumbo/nightly/3.36.1.5-1.5-3.1/index.html for...

Thanks for creating this PR!

Hi @cliu-sift, could you share the full yarn logs?