sf01071112_在线真题试卷与模拟练习_sf01071112

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使用 SQL 语句操作DataFrame：

scala> val filePath = "file:///home/hadoop/spark/people.json"

//1.

scala> val df = spark.read.json(filePath)

//2.

scala> df.createTempView("people")

//3.

scala> val rt = spark.sql("SELECT name FROM people where age > 20")

//4.

scala> rt.show()

//5.

向 mysql 数据库中写数据:

scala> val schema = StructType(List(StructField("id", IntegerType, true),StructField("name", StringType, true),StructField("gender", StringType, true),StructField("age", IntegerType, true)))

//1.

scala> val rowRDD = spark.sparkContext.parallelize(Array("5 Rongcheng2 M 26","6 Guanhua2

M 27")).map(_.split(" ")).map(p => Row(p(0).toInt, p(1).trim, p(2).trim, p(3).toInt))

//2.

四、分析（2*10=20）

scala> val studentDF = spark.createDataFrame(rowRDD, schema)

//3.

scala> val prop = new Properties()

//4.

scala> prop.put("user","root")

scala> prop.put("password","123456")

scala> prop.put("driver","com.mysql.jdbc.Driver")

scala> studentDF.write.mode("append").jdbc("jdbc:mysql://H01:3306/spark","spark.student",prop)

//5.

SparkConf().setAppName("WordCountStreaming").setMaster("local[2]")

//1.

val ssc = new StreamingContext(sparkConf, Seconds(5))

//2.

val lines = ssc.textFileStream("file:///home/hadoop/spark/streaming/logfile") //3.

val wordCounts = lines.flatMap(_.split(" ")).map(x => (x, 1)).reduceByKey(_ + _) //4.

wordCounts.print()

//5.

ssc.start()

//6.

ssc.awaitTermination()

//7.

def main(args: Array[String]) {

//1

val updateFunc = (values: Seq[Int], state: Option[Int]) => {

val currentCount = values.foldLeft(0)(_ + _)

//2.

val previousCount = state.getOrElse(0) //3.

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