In the context of developing a Spark ML Pipeline, explain the process of identifying key gotchas and how to handle them. Provide a code snippet demonstrating the development of a Spark ML Pipeline and explain how to address the potential issues that may arise.

Simulated

Use the Pipeline class from the pyspark.ml module to define the stages of the pipeline, and ensure that each stage is a Spark ML estimator or transformer.

24.6%

Use the PipelineModel class from the pyspark.ml module to define the stages of the pipeline, and ensure that each stage is a Spark ML estimator or transformer.

16.9%

Use the Pipeline class from the pyspark.ml module to define the stages of the pipeline, but be aware of the potential for data leakage between stages.

41.5%

Use the PipelineModel class from the pyspark.ml module to define the stages of the pipeline, but be aware of the potential for data leakage between stages.

16.9%

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In the context of developing a Spark ML Pipeline, explain the process of identifying key gotchas and how to handle them. Provide a code snippet demonstrating the development of a Spark ML Pipeline and explain how to address the potential issues that may arise.