也许这是有帮助的- Transpose and filter ```
val threshold = 5
val cols = Range(1, 100).map(f => s"$f as col$f").mkString(", ")
val df1 = spark.sql(s"select $cols")
df1.show(false)
df1.printSchema()
/**
* +----+----+----+----+----+----+----+----+----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+
* |col1|col2|col3|col4|col5|col6|col7|col8|col9|col10|col11|col12|col13|col14|col15|col16|col17|col18|col19|col20|col21|col22|col23|col24|col25|col26|col27|col28|col29|col30|col31|col32|col33|col34|col35|col36|col37|col38|col39|col40|col41|col42|col43|col44|col45|col46|col47|col48|col49|col50|col51|col52|col53|col54|col55|col56|col57|col58|col59|col60|col61|col62|col63|col64|col65|col66|col67|col68|col69|col70|col71|col72|col73|col74|col75|col76|col77|col78|col79|col80|col81|col82|col83|col84|col85|col86|col87|col88|col89|col90|col91|col92|col93|col94|col95|col96|col97|col98|col99|
* +----+----+----+----+----+----+----+----+----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+
* |1 |2 |3 |4 |5 |6 |7 |8 |9 |10 |11 |12 |13 |14 |15 |16 |17 |18 |19 |20 |21 |22 |23 |24 |25 |26 |27 |28 |29 |30 |31 |32 |33 |34 |35 |36 |37 |38 |39 |40 |41 |42 |43 |44 |45 |46 |47 |48 |49 |50 |51 |52 |53 |54 |55 |56 |57 |58 |59 |60 |61 |62 |63 |64 |65 |66 |67 |68 |69 |70 |71 |72 |73 |74 |75 |76 |77 |78 |79 |80 |81 |82 |83 |84 |85 |86 |87 |88 |89 |90 |91 |92 |93 |94 |95 |96 |97 |98 |99 |
* +----+----+----+----+----+----+----+----+----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+-----+
*
* root
* |-- col1: integer (nullable = false)
* |-- col2: integer (nullable = false)
* |-- col3: integer (nullable = false)
* |-- col4: integer (nullable = false)
* ...
*/

val stringCol = df1.columns.map(c => s"'$c', cast(`$c` as int)").mkString(", ")

val processedDF = df1.selectExpr(s"stack(${df1.columns.length}, $stringCol) as (name, value)")
  .filter(s"value > $threshold")
processedDF.show(false)
/**
  * -----+-----+
  * |name |value|
  * +-----+-----+
  * |col6 |6    |
  * |col7 |7    |
  * |col8 |8    |
  * |col9 |9    |
  * |col10|10   |
  * |col11|11   |
  * |col12|12   |
  * |col13|13   |
  * |col14|14   |
  * |col15|15   |
  * |col16|16   |
  * |col17|17   |
  * |col18|18   |
  * |col19|19   |
  * |col20|20   |
  * |col21|21   |
  * |col22|22   |
  * |col23|23   |
  * |col24|24   |
  * |col25|25   |
  * +-----+-----+
  * only showing top 20 rows
  */