在 Spark 结构化流式处理中找不到"window"函数

Question

我正在用Spark Structured Streaming编写一个小示例，其中我尝试处理netstat命令的输出，但无法弄清楚如何调用window函数。

这些是我的build.sbt的相关行：

scalaVersion := "2.11.4"
scalacOptions += "-target:jvm-1.8"
libraryDependencies ++= {
val sparkVer = "2.3.0"
Seq(
"org.apache.spark" %% "spark-streaming" % sparkVer % "provided",
"org.apache.spark" %% "spark-streaming-kafka-0-8" % sparkVer % "provided",
"org.apache.spark" %% "spark-core" % sparkVer % "provided" withSources(),
"org.apache.spark" %% "spark-hive" % sparkVer % "provided",
)
}

和代码：

case class NetEntry(val timeStamp: java.sql.Timestamp, val sourceHost: String, val targetHost: String, val status: String)
def convertToNetEntry(x: String): NetEntry = {
// tcp        0      0 eselivpi14:icl-twobase1 eselivpi149.int.e:48442 TIME_WAIT
val array = x.replaceAll("\s+"," ").split(" ").slice(3,6)
NetEntry(java.sql.Timestamp.valueOf(LocalDateTime.now()), array(0),array(1),array(2))
}
def main(args: Array[String]) {
// Initialize spark context
val spark: SparkSession = SparkSession.builder.appName("StructuredNetworkWordCount").getOrCreate()
spark.sparkContext.setLogLevel("ERROR")
val lines = spark.readStream
.format("socket")
.option("host", args(0))
.option("port", args(1).toInt)
.load()
import spark.implicits._
val df = lines.as[String].map(x => convertToNetEntry(x))
val wordsArr: Dataset[NetEntry] = df.as[NetEntry]
wordsArr.printSchema()
// Never get past this point
val windowColumn = window($"timestamp", "10 minutes", "5 minutes")
val windowedCounts = wordsArr.groupBy( windowColumn, $"targetHost").count()
val query = windowedCounts.writeStream.outputMode("complete").format("console").start()
query.awaitTermination()
}

我使用 Spark 2.1、2、2 和 2.3 具有相同的结果。真正奇怪的是，我有一个Spark Cluster，我登录Spark Shell并复制所有行......它有效！知道我做错了什么吗？

编译时的错误：

[error] C:code_legacyedos-dp-mediation-spark-consumersrcmainscalacomericssonstreamingstructuredStructuredStreamingMain.scala:39: not found: value window
[error]     val windowColumn = window($"timestamp", "10 minutes", "5 minutes")
[error]                        ^
[warn] 5 warnings found
[error] one error found
[error] (compile:compileIncremental) Compilation failed
[error] Total time: 19 s, completed 16-mar-2018 20:13:40

更新：为了让事情变得更奇怪，我已经检查了 API 文档，但在这里也找不到有效的参考： https://spark.apache.org/docs/2.3.0/api/scala/index.html#org.apache.spark.sql.SparkSession$implicits$

Answer 1

你需要导入window函数来编译它，它已经在 spark-shell 中导入了。

添加此导入语句：

import org.apache.spark.sql.functions.window