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https://issues.apache.org/jira/browse/SPARK-33661?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean R. Owen reopened SPARK-33661:
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> Unable to load RandomForestClassificationModel trained in Spark 2.x
> -------------------------------------------------------------------
>
> Key: SPARK-33661
> URL: https://issues.apache.org/jira/browse/SPARK-33661
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 3.0.1
> Reporter: Marcus Levine
> Priority: Major
>
> When attempting to load a RandomForestClassificationModel that was trained in
> Spark 2.x using Spark 3.x, an exception is raised:
> {code:python}
> ...
> RandomForestClassificationModel.load('/path/to/my/model')
> File "/usr/spark/python/lib/pyspark.zip/pyspark/ml/util.py", line 330, in
> load
> File "/usr/spark/python/lib/pyspark.zip/pyspark/ml/pipeline.py", line 291,
> in load
> File "/usr/spark/python/lib/pyspark.zip/pyspark/ml/util.py", line 280, in
> load
> File "/usr/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line
> 1305, in __call__
> File "/usr/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 134, in
> deco
> File "<string>", line 3, in raise_from
> pyspark.sql.utils.AnalysisException: No such struct field rawCount in id,
> prediction, impurity, impurityStats, gain, leftChild, rightChild, split;
> {code}
> There seems to be a schema incompatibility between the trained model data
> saved by Spark 2.x and the expected data for a model trained in Spark 3.x
> If this issue is not resolved, users will be forced to retrain any existing
> random forest models they trained in Spark 2.x using Spark 3.x before they
> can upgrade
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