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zero323 authored
Use `dropFactors` column-wise instead of nested loop when `createDataFrame` from a `data.frame` At this moment SparkR createDataFrame is using nested loop to convert factors to character when called on a local data.frame. It works but is incredibly slow especially with data.table (~ 2 orders of magnitude compared to PySpark / Pandas version on a DateFrame of size 1M rows x 2 columns). A simple improvement is to apply `dropFactor `column-wise and then reshape output list. It should at least partially address [SPARK-8277](https://issues.apache.org/jira/browse/SPARK-8277). Author: zero323 <matthew.szymkiewicz@gmail.com> Closes #9099 from zero323/SPARK-11086.
zero323 authoredUse `dropFactors` column-wise instead of nested loop when `createDataFrame` from a `data.frame` At this moment SparkR createDataFrame is using nested loop to convert factors to character when called on a local data.frame. It works but is incredibly slow especially with data.table (~ 2 orders of magnitude compared to PySpark / Pandas version on a DateFrame of size 1M rows x 2 columns). A simple improvement is to apply `dropFactor `column-wise and then reshape output list. It should at least partially address [SPARK-8277](https://issues.apache.org/jira/browse/SPARK-8277). Author: zero323 <matthew.szymkiewicz@gmail.com> Closes #9099 from zero323/SPARK-11086.
