WeichenXu123 opened a new pull request #26910: [SPARK-30154][ML] PySpark UDF to convert MLlib vectors to dense arrays URL: https://github.com/apache/spark/pull/26910 ### What changes were proposed in this pull request? PySpark UDF to convert MLlib vectors to dense arrays. Example: ``` from pyspark.ml.functions import vector_to_dense_array df.select(vector_to_dense_array(col("features")) ``` ### Why are the changes needed? If a PySpark user wants to convert MLlib sparse/dense vectors in a DataFrame into dense arrays, an efficient approach is to do that in JVM. However, it requires PySpark user to write Scala code and register it as a UDF. Often this is infeasible for a pure python project. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? UT.
---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
