Apache spark spark streaming未执行spark sql查询

在spark流之上执行spark sql时，我面临一个问题

我没有在var x=sqlContext.sql行（“从价格中选择计数（*））上打印x的值

请在下面找到我的代码

    import spark.implicits._
import org.apache.spark.sql.types._
import org.apache.spark.sql.Encoders
import org.apache.spark.streaming._
import org.apache.spark.sql.functions._
import org.apache.spark.sql.SparkSession
import spark.implicits._
import org.apache.spark.sql.types.{StructType, StructField, StringType, IntegerType}
import org.apache.spark.sql.functions._
import org.apache.spark.sql.SparkSession
import spark.implicits._
import org.apache.spark.sql.types.{StructType, StructField, StringType, IntegerType}
import org.apache.spark.SparkConf
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.apache.spark.storage.StorageLevel
import java.util.regex.Pattern
import java.util.regex.Matcher
import org.apache.spark.sql.hive.HiveContext;
import org.apache.spark.sql.streaming.Trigger
import org.apache.spark.sql._

val conf = new SparkConf().setAppName("streamHive").setMaster("local[*]").set("spark.driver.allowMultipleContexts", "true")
val ssc = new StreamingContext(conf, Seconds(5))    
val sc=ssc.sparkContext

val lines = ssc.textFileStream("file:///home/sdf/testHive")
case class Prices(name: String, age: String,sex: String, location: String)
val sqlContext = new org.apache.spark.sql.SQLContext(sc)

def parse (rdd : org.apache.spark.rdd.RDD[String] ) = {
var l = rdd.map(_.split(","))
val prices = l.map(p => Prices(p(0),p(1),p(2),p(3)))
val pricesDf = sqlContext.createDataFrame(prices)
pricesDf.registerTempTable("prices")
println("showing printdfShow")
pricesDf.show()
var x = sqlContext.sql("select count(*) from prices")
println("hello")
println (x)
}

lines.foreachRDD { rdd => parse(rdd)}

ssc.start()

我得到以下结果，它不是打印spark sql结果：

   [count(1): bigint]
   showing printdfShow
   +----+---+---+--------+
   |name|age|sex|location|
   +----+---+---+--------+
   +----+---+---+--------+

   hello
   [count(1): bigint]
   showing printdfShow
   +----+---+---+--------+
   |name|age|sex|location|
   +----+---+---+--------+
   | rop| 22|  M|      uk|
   | fop| 24|  F|      us|
   | dop| 23|  M|     fok|
   +----+---+---+--------+

   hello
   [count(1): bigint]
   showing printdfShow
   +----+---+---+--------+
   |name|age|sex|location|
   +----+---+---+--------+
   +----+---+---+--------+

   hello
   [count(1): bigint]

---

请帮助我，如何在spark流媒体中使用spark sql，因为我是spark的新手。

请在pricesDf.show之后的代码中尝试这一点

println(pricesDf.count)

如果您想在相同的代码中使用，请尝试下面的方法，而不是println（x）

x是一个数据帧而不是一个值，这就是为什么在运行println（x）时它不会被打印出来的原因。要将其放入变量中，可以尝试以下方法

println(x.rdd.map(r => r.getString(0)).collect()(0))

---

场景的可能重复是不同的

println(x.rdd.map(r => r.getString(0)).collect()(0))