我是scala的新手。我需要一些即时帮助。
我有M * N spark sql数据帧,如下所示。我需要将每个行列的值与下一个行列的值进行比较。
诸如A1到A2,A1到A3之类的东西,直到N。 B1至B2 B1至B3。
有人可以指导我如何在Spark sql中逐行比较吗?
ID COLUMN1 Column2
1 A1 B1
2 A2 B2
3 A3 B3
先感谢您
桑托什
最佳答案
如果我正确理解了该问题-您想比较(使用某些函数)将每个值与上一条记录中同一列的值进行比较。您可以使用lag
窗口函数做到这一点:
import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.Column
import org.apache.spark.sql.functions._
import spark.implicits._
// some data...
val df = Seq(
(1, "A1", "B1"),
(2, "A2", "B2"),
(3, "A3", "B3")
).toDF("ID","COL1", "COL2")
// some made-up comparisons - fill in whatever you want...
def compareCol1(curr: Column, prev: Column): Column = curr > prev
def compareCol2(curr: Column, prev: Column): Column = concat(curr, prev)
// creating window - ordered by ID
val window = Window.orderBy("ID")
// using the window with lag function to compare to previous value in each column
df.withColumn("COL1-comparison", compareCol1($"COL1", lag("COL1", 1).over(window)))
.withColumn("COL2-comparison", compareCol2($"COL2", lag("COL2", 1).over(window)))
.show()
// +---+----+----+---------------+---------------+
// | ID|COL1|COL2|COL1-comparison|COL2-comparison|
// +---+----+----+---------------+---------------+
// | 1| A1| B1| null| null|
// | 2| A2| B2| true| B2B1|
// | 3| A3| B3| true| B3B2|
// +---+----+----+---------------+---------------+