使用SparkScala用JSON字段过滤RDD的csv。

Question

我正在研究sparkscala，我需要通过列上的特定字段来过滤RDD，在这种情况下。user.

我想返回一个包含用户的RDD。["Joe","Plank","Willy"] 但似乎不知道如何

这是我的RDD。

2020-03-01T00:00:05Z    my.local5.url   {"request_method":"GET","request_length":281,"user":"Joe"}
2020-03-01T00:00:05Z    my.local2.url   {"request_method":"GET","request_length":281,"user":"Plank"}
2020-03-01T00:00:05Z    my.local2.url   {"request_method":"GET","request_length":281,"user":"Willy"}
2020-03-01T00:00:05Z    my.local6.url   {"request_method":"GET","request_length":281,"user":"Plank"}
2020-03-01T00:00:05Z    my.local2.url   {"request_method":"GET","request_length":281,"user":"Plank"}
2020-03-01T00:00:05Z    my.local2.url   {"request_method":"GET","request_length":281,"user":"Tracy"}
2020-03-01T00:00:05Z    my.local6.url   {"request_method":"GET","request_length":281,"user":"Roger"}

预期的输出。

2020-03-01T00:00:05Z    my.local5.url   {"request_method":"GET","request_length":281,"user":"Joe"}
2020-03-01T00:00:05Z    my.local2.url   {"request_method":"GET","request_length":281,"user":"Plank"}
2020-03-01T00:00:05Z    my.local2.url   {"request_method":"GET","request_length":281,"user":"Willy"}
2020-03-01T00:00:05Z    my.local6.url   {"request_method":"GET","request_length":281,"user":"Plank"}
2020-03-01T00:00:05Z    my.local2.url   {"request_method":"GET","request_length":281,"user":"Plank"}

我已经用spark提取了RDD，用的是这样的（伪代码）。

val sparkConf = new SparkConf().setAppName("MyApp")
master.foreach(sparkConf.setMaster)
val sc = new SparkContext(sparkConf)

val rdd = sc.textFile(inputDir)
rdd.filter(_.contains("\"user\":\"THE_ARRAY_OF_NAMES_"))

Answer 1

对你来说，使用数据帧更容易。

使用from_json函数，你可以将json列转换成多列。

val jsonSchema = StructType(Array(
    StructField("request_method",StringType,true),
    StructField("request_length",IntegerType,true),
    StructField("user",StringType,true)
  ))

val myDf = spark.read.option("header", "true").csv(path)
val formatedDf = myDf.withColumn("formated_json", from_json($"column_name", jsonSchema)
.select($"formated_json.*")
.where($"user".isin("Joe","Plank","Willy")

formatedDf.show

但如果你想要RDD版的方法，请告诉我。

用RDD版本编辑：请记住这是manny的方法之一。

//Define a regex pattern
val Pattern = """(?i)"user":"([a-zA-Z]+)"""".r
//Define a Set with your filtered values
val userSet = Set("Joe","Plank","Willy")
//Filter only the values you want
val filteredRdd = rdd.filter( x => {
    //Extract the user using the pattern we just declared
    val user = for(m <- Pattern.findFirstMatchIn(x)) yield m.group(1)
    //If the user variable is equal with one of your set values then this statement will return true and based on that the row will be kept
    userSet(user.getOrElse(""))
})

要想知道结果是否正确，你可以用。

filteredRdd.collect().foreach(println)