from one dataframe i want to create a new dataframe where at least one value in any of the columns is null or blank in spark 1.5 / scala.
i am trying to write a generalize function to create this new dataframe. where i pass the dataframe and the list of columns and creates the record.
Thanks
Sample Data:
val df = Seq((null, Some(2)), (Some("a"), Some(4)), (Some(""), Some(5)), (Some("b"), null)).toDF("A", "B")
df.show
+----+----+
| A| B|
+----+----+
|null| 2|
| a| 4|
| | 5|
| b|null|
+----+----+
You can construct the condition as, assume blank means empty string here:
import org.apache.spark.sql.functions.col
val cond = df.columns.map(x => col(x).isNull || col(x) === "").reduce(_ || _)
df.filter(cond).show
+----+----+
| A| B|
+----+----+
|null| 2|
| | 5|
| b|null|
+----+----+