简而言之,我正在利用Spark-XML进行XML文件进行一些解析。但是,使用此方法是在我感兴趣的所有值中删除领先的零。但是,我需要最终输出,即数据框架,以包括领先的零。我不确定/无法找到一种将领先零添加到我感兴趣的列的方法。
val df = spark.read
.format("com.databricks.spark.xml")
.option("rowTag", "output")
.option("excludeAttribute", true)
.option("allowNumericLeadingZeros", true) //including this does not solve the problem
.load("pathToXmlFile")
我得到的示例输出
+------+---+--------------------+
|iD |val|Code |
+------+---+--------------------+
|1 |44 |9022070536692784476 |
|2 |66 |-5138930048185086175|
|3 |25 |805582856291361761 |
|4 |17 |-9107885086776983000|
|5 |18 |1993794295881733178 |
|6 |31 |-2867434050463300064|
|7 |88 |-4692317993930338046|
|8 |44 |-4039776869915039812|
|9 |20 |-5786627276152563542|
|10 |12 |7614363703260494022 |
+------+---+--------------------+
所需的输出
+--------+----+--------------------+
|iD |val |Code |
+--------+----+--------------------+
|001 |044 |9022070536692784476 |
|002 |066 |-5138930048185086175|
|003 |025 |805582856291361761 |
|004 |017 |-9107885086776983000|
|005 |018 |1993794295881733178 |
|006 |031 |-2867434050463300064|
|007 |088 |-4692317993930338046|
|008 |044 |-4039776869915039812|
|009 |020 |-5786627276152563542|
|0010 |012 |7614363703260494022 |
+--------+----+--------------------+
这为我解决了,谢谢大家的帮助
val df2 = df
.withColumn("idLong", format_string("%03d", $"iD"))
您可以通过使用concat
Instoy function
df.withColumn("iD", concat(lit("00"), col("iD")))
.withColumn("val", concat(lit("0"), col("val")))