Spark Streaming 不执行 Spark SQL 查询

Question

在火花流之上执行 spark sql 时，我遇到了一个问题。

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

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，它没有打印火花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流中使用Spark SQL，因为我是Spark的新手。

Answer 1

请在价格Df.show之后在您的代码中尝试此操作

println(pricesDf.count)

如果你想在同一个代码中这样做，那么试试下面，而不是println（x）

x.show

x

是一个数据帧而不是一个值，这就是为什么在运行 println（x） 时它没有被打印的原因。要在变量中获取它，您可以尝试这样做

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