更新时间:2023-11-23 GMT+08:00
Scala样例代码
功能简介
实时统计连续网购时间超过2个小时的女性网民信息,将统计结果直接打印出来。
样例代码
下面代码片段仅为演示,具体代码参见com.huawei.flink.example.stream.FlinkStreamScalaExample:
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// 参数解析:
// filePath为文本读取路径,用逗号分隔。
// windowTime;为统计数据的窗口跨度,时间单位都是分。
object FlinkStreamScalaExample {
def main(args: Array[String]) {
// 打印出执行flink run的参考命令
System.out.println("use command as: ")
System.out.println("./bin/flink run --class com.huawei.bigdata.flink.examples.FlinkStreamScalaExample /opt/test.jar --filePath /opt/log1.txt,/opt/log2.txt --windowTime 2")
System.out.println("******************************************************************************************")
System.out.println("<filePath> is for text file to read data, use comma to separate")
System.out.println("<windowTime> is the width of the window, time as minutes")
System.out.println("******************************************************************************************")
// 读取文本路径信息,并使用逗号分隔
val filePaths = ParameterTool.fromArgs(args).get("filePath", "/opt/log1.txt,/opt/log2.txt").split(",").map(_.trim)
assert(filePaths.length > 0)
// windowTime设置窗口时间大小,默认2分钟一个窗口足够读取文本内的所有数据了
val windowTime = ParameterTool.fromArgs(args).getInt("windowTime", 2)
// 构造执行环境,使用eventTime处理窗口数据
val env = StreamExecutionEnvironment.getExecutionEnvironment
env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
env.setParallelism(1)
// 读取文本数据流
val unionStream = if (filePaths.length > 1) {
val firstStream = env.readTextFile(filePaths.apply(0))
firstStream.union(filePaths.drop(1).map(it => env.readTextFile(it)): _*)
} else {
env.readTextFile(filePaths.apply(0))
}
// 数据转换,构造整个数据处理的逻辑,计算并得出结果打印出来
unionStream.map(getRecord(_))
.assignTimestampsAndWatermarks(new Record2TimestampExtractor)
.filter(_.sexy == "female")
.keyBy("name", "sexy")
.window(TumblingEventTimeWindows.of(Time.minutes(windowTime)))
.reduce((e1, e2) => UserRecord(e1.name, e1.sexy, e1.shoppingTime + e2.shoppingTime))
.filter(_.shoppingTime > 120).print()
// 调用execute触发执行
env.execute("FemaleInfoCollectionPrint scala")
}
// 解析文本行数据,构造UserRecord数据结构
def getRecord(line: String): UserRecord = {
val elems = line.split(",")
assert(elems.length == 3)
val name = elems(0)
val sexy = elems(1)
val time = elems(2).toInt
UserRecord(name, sexy, time)
}
// UserRecord数据结构的定义
case class UserRecord(name: String, sexy: String, shoppingTime: Int)
// 构造继承AssignerWithPunctuatedWatermarks的类,用于设置eventTime以及waterMark
private class Record2TimestampExtractor extends AssignerWithPunctuatedWatermarks[UserRecord] {
// add tag in the data of datastream elements
override def extractTimestamp(element: UserRecord, previousTimestamp: Long): Long = {
System.currentTimeMillis()
}
// give the watermark to trigger the window to start execution, and use the value to check if the window elements are ready
def checkAndGetNextWatermark(lastElement: UserRecord, extractedTimestamp: Long): Watermark = {
new Watermark(extractedTimestamp - 1)
}
}
}
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执行之后打印结果如下所示:
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UserRecord(FangBo,female,320)
UserRecord(CaiXuyu,female,300)
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父主题: DataStream程序