我在Spark中有一个DataFrame,例如:
var df = List(
(1,"{NUM.0002}*{NUM.0003}"),
(2,"{NUM.0004}+{NUM.0003}"),
(3,"END(6)"),
(4,"END(4)")
).toDF("CODE", "VALUE")
+----+---------------------+
|CODE| VALUE|
+----+---------------------+
| 1|{NUM.0002}*{NUM.0003}|
| 2|{NUM.0004}+{NUM.0003}|
| 3| END(6)|
| 4| END(4)|
+----+---------------------+
我的任务是遍历VALUE列并执行以下操作:检查是否存在{NUM.XXXX}等子字符串,获取XXXX号码,获取$" CODE" === XXXX,并将{NUM.XXX}子字符串替换为该行中的VALUE字符串。
我希望数据框最终看起来像这样:
+----+--------------------+
|CODE| VALUE|
+----+--------------------+
| 1|END(4)+END(6)*END(6)|
| 2| END(4)+END(6)|
| 3| END(6)|
| 4| END(4)|
+----+--------------------+
这是我提出的最佳选择:
val process = udf((ln: String) => {
var newln = ln
while(newln contains "{NUM."){
var num = newln.slice(newln.indexOf("{")+5, newln.indexOf("}")).toInt
var new_value = df.where($"CODE" === num).head.getAs[String](1)
newln = newln.replace(newln.slice(newln.indexOf("{"),newln.indexOf("}")+1), new_value)
}
newln
})
var df2 = df.withColumn("VALUE", when('VALUE contains "{NUM.",process('VALUE)).otherwise('VALUE))
不幸的是,当我尝试过滤/选择/保存df2
时,我收到NullPointerException,当我只显示df2
时没有错误。我相信当我访问UDF中的DataFrame df
时会出现错误,但我需要在每次迭代时访问它,因此我无法将其作为输入传递。另外,我尝试在UDF中保存df
的副本,但我不知道该怎么做。我能在这做什么?
非常欢迎任何改进算法的建议!谢谢!
答案 0 :(得分:1)
我写了一些有效但不太优化的东西。我实际上在初始DataFrame上进行递归连接以将END替换为NUM。这是代码:
case class Data(code: Long, value: String)
def main(args: Array[String]): Unit = {
val sparkSession: SparkSession = SparkSession.builder().master("local").getOrCreate()
val data = Seq(
Data(1,"{NUM.0002}*{NUM.0003}"),
Data(2,"{NUM.0004}+{NUM.0003}"),
Data(3,"END(6)"),
Data(4,"END(4)"),
Data(5,"{NUM.0002}")
)
val initialDF = sparkSession.createDataFrame(data)
val endDF = initialDF.filter(!(col("value") contains "{NUM"))
val numDF = initialDF.filter(col("value") contains "{NUM")
val resultDF = endDF.union(replaceNumByEnd(initialDF, numDF))
resultDF.show(false)
}
val parseNumUdf = udf((value: String) => {
if (value.contains("{NUM")) {
val regex = """.*?\{NUM\.(\d+)\}.*""".r
value match {
case regex(code) => code.toLong
}
} else {
-1L
}
})
val replaceUdf = udf((value: String, replacement: String) => {
val regex = """\{NUM\.(\d+)\}""".r
regex.replaceFirstIn(value, replacement)
})
def replaceNumByEnd(initialDF: DataFrame, currentDF: DataFrame): DataFrame = {
if (currentDF.count() == 0) {
currentDF
} else {
val numDFWithCode = currentDF
.withColumn("num_code", parseNumUdf(col("value")))
.withColumnRenamed("code", "code_original")
.withColumnRenamed("value", "value_original")
val joinedDF = numDFWithCode.join(initialDF, numDFWithCode("num_code") === initialDF("code"))
val replacedDF = joinedDF.withColumn("value_replaced", replaceUdf(col("value_original"), col("value")))
val nextDF = replacedDF.select(col("code_original").as("code"), col("value_replaced").as("value"))
val endDF = nextDF.filter(!(col("value") contains "{NUM"))
val numDF = nextDF.filter(col("value") contains "{NUM")
endDF.union(replaceNumByEnd(initialDF, numDF))
}
}
如果您需要更多解释,请不要犹豫。