Spark数据帧过滤器

Question

val df = sc.parallelize(Seq((1,"Emailab"), (2,"Phoneab"), (3, "Faxab"),(4,"Mail"),(5,"Other"),(6,"MSL12"),(7,"MSL"),(8,"HCP"),(9,"HCP12"))).toDF("c1","c2")

+---+-------+
| c1|     c2|
+---+-------+
|  1|Emailab|
|  2|Phoneab|
|  3|  Faxab|
|  4|   Mail|
|  5|  Other|
|  6|  MSL12|
|  7|    MSL|
|  8|    HCP|
|  9|  HCP12|
+---+-------+

我想过滤出列'c2'的前三个字符"MSL"或"HCP"的记录.

所以输出应该如下所示.

+---+-------+
| c1|     c2|
+---+-------+
|  1|Emailab|
|  2|Phoneab|
|  3|  Faxab|
|  4|   Mail|
|  5|  Other|
+---+-------+

任何人都可以帮忙吗？

我知道df.filter($"c2".rlike("MSL"))- 这是为了选择记录,但如何排除记录.？

版本:Spark 1.6.2 Scala:2.10

Answer 1

这也有效.简洁,非常类似于SQL.

df.filter("c2 not like 'MSL%' and c2 not like 'HCP%'").show
+---+-------+
| c1|     c2|
+---+-------+
|  1|Emailab|
|  2|Phoneab|
|  3|  Faxab|
|  4|   Mail|
|  5|  Other|
+---+-------+

Answer 2

df.filter(not(
    substring(col("c2"), 0, 3).isin("MSL", "HCP"))
    )

Answer 3

我在下面用来过滤数据框中的行，这在 me.Spark 2.2 中起作用

val spark = new org.apache.spark.sql.SQLContext(sc)    
val data = spark.read.format("csv").
          option("header", "true").
          option("delimiter", "|").
          option("inferSchema", "true").
          load("D:\\test.csv")   


import  spark.implicits._
val filter=data.filter($"dept" === "IT" )

或者

val filter=data.filter($"dept" =!= "IT" )