How to remove nulls with array_remove Spark SQL Built-in Function

You can do something like this in Spark 2:

import org.apache.spark.sql.functions._
import org.apache.spark.sql._

/**
  * Array without nulls
  * For complex types, you are responsible for passing in a nullPlaceholder of the same type as elements in the array
  */
def non_null_array(columns: Seq[Column], nullPlaceholder: Any = "רכוב כל יום"): Column =
  array_remove(array(columns.map(c => coalesce(c, lit(nullPlaceholder))): _*), nullPlaceholder)

In Spark 3, there is new array filter function and you can do:

df.select(filter(col("array_column"), x => x.isNotNull))

https://docs.databricks.com/_static/notebooks/apache-spark-2.4-functions.html

array_remove(array, T): array Remove all elements that equal to the given element from the given array.

Note: I only referred the documentation and they have taken the same data. **null can never be equal to null.

To answer your first question, Is this an expected behavior? , Yes. Because the official notebook(https://docs.databricks.com/_static/notebooks/apache-spark-2.4-functions.html) points out "Remove all elements that equal to the given element from the given array." and NULL corresponds to undefined values & the results will also not defined.

So,I think NULL s are out of the purview of this function.

Better you found out a way to overcome this, you can also use spark.sql("""SELECT array_except(array(1, 2, 3, 3, null, 3, 3,3, 4, 5), array(null))""").show() but the downside is that the result will be without duplicates.