88542bc3d9
### 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_array
df.select(vector_to_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.
Closes #26910 from WeichenXu123/vector_to_array.
Authored-by: WeichenXu <weichen.xu@databricks.com>
Signed-off-by: Xiangrui Meng <meng@databricks.com>
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| .. | ||
| _static | ||
| _templates | ||
| conf.py | ||
| index.rst | ||
| make.bat | ||
| make2.bat | ||
| Makefile | ||
| pyspark.ml.rst | ||
| pyspark.mllib.rst | ||
| pyspark.rst | ||
| pyspark.sql.rst | ||
| pyspark.streaming.rst | ||