forEach Spark Scala错误:value select不是org.apache.spark.sql.Row

Question

我试图在一个文件中获得所有json对象的评级的平均值。我加载了文件并转换为数据帧，但在解析avg时出现错误。示例请求:

{
        "country": "France",
        "customerId": "France001",
        "visited": [
            {
                "placeName": "US",
                "rating": "2.3",
                "famousRest": "N/A",
                "placeId": "AVBS34"
            },
              {
                "placeName": "US",
                "rating": "3.3",
                "famousRest": "SeriousPie",
                "placeId": "VBSs34"
            },
              {
                "placeName": "Canada",
                "rating": "4.3",
                "famousRest": "TimHortons",
                "placeId": "AVBv4d"
            }        
    ]
}

所以对于这个json，美国的平均评级将是(2.3 + 3.3)/2 = 2.8

{
        "country": "Egypt",
        "customerId": "Egypt009",
        "visited": [
            {
                "placeName": "US",
                "rating": "1.3",
                "famousRest": "McDonald",
                "placeId": "Dedcf3"
            },
              {
                "placeName": "US",
                "rating": "3.3",
                "famousRest": "EagleNest",
                "placeId": "CDfet3"
            },

}
{
        "country": "Canada",
        "customerId": "Canada012",
        "visited": [
            {
                "placeName": "UK",
                "rating": "3.3",
                "famousRest": "N/A",
                "placeId": "XSdce2"
            },

    ]
}

= (3.3 +1.3)/2 = 2.3

所以总的来说，平均评分将是:(2.8 + 2.3)/2 = 2.55(只有两个请求在他们的访问列表中有"US")

My schema:

root
|-- country: string(nullable=true)
|-- customerId:string(nullable=true)
|-- visited: array (nullable = true)
|    |-- element: struct (containsNull = true)
|    |   |-- placeId: string (nullable = true)
|    |   |-- placeName: string (nullable = true) 
|    |   |-- famousRest: string (nullable = true)
|    |   |-- rating: string (nullable = true)
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
val df = sqlContext.jsonFile("temp.txt")
df.show() 

当做:

val app = df.select("strategies"); app.registerTempTable("app"); app.printSchema(); app.show()
app.foreach({
  t =>  t.select("placeName", "rating").where(t("placeName") == "US")
}).show()
I am getting : 
<console>:31: error: value select is not a member of org.apache.spark.sql.Row t => t.select("placeName", "rating").where(t("placeName") == "US") ^

谁能告诉我我哪里做错了?

Answer 1

假设app是Dataframe(你的代码示例是不可理解的…你创建一个df变量并查询一个app变量)，你不应该调用foreach来从中选择:

app.select("placeName", "rating").where(t("placeName") == "US")

foreach将对每条记录(Row类型)调用一个函数。这主要用于调用一些副作用(例如打印到控制台/发送到外部服务等)。大多数情况下，您不会使用它来选择/转换数据框架。

:

对于最初如何计算仅在美国访问的平均值的问题:

// explode to make a record out of each "visited" Array item, 
// taking only "placeName" and "rating" columns
val exploded: DataFrame = df.explode(df("visited")) {
  case Row(visits: Seq[Row]) => 
    visits.map(r => (r.getAs[String]("placeName"), r.getAs[String]("rating")))
}
// make some order: rename columns named _1, _2 (since we used a tuple),
// and cast ratings to Double:
val ratings: DataFrame = exploded
  .withColumnRenamed("_1", "placeName")
  .withColumn("rating", exploded("_2").cast(DoubleType))
  .select("placeName", "rating")
ratings.printSchema()
ratings.show()
/* prints:
root
 |-- placeName: string (nullable = true)
 |-- rating: double (nullable = true)
+---------+------+
|placeName|rating|
+---------+------+
|       US|   1.3|
|       US|   3.3|
|       UK|   3.3|
+---------+------+
 */
// now filter US only and get average rating:
val avg = ratings
  .filter(ratings("placeName") === "US")
  .select(mean("rating"))
avg.show()
/* prints:
 +-----------+
 |avg(rating)|
 +-----------+
 |        2.3|
 +-----------+
  */