[英]Flink Scala - Extending WindowFunction
I am trying to figure out how to write my own WindowFunction
but having issues, and I can not figure out why. 我试图弄清楚如何编写我自己的
WindowFunction
但有问题,我无法弄清楚为什么。 The issue I am having is with the apply function, as it does not recognize MyWindowFunction
as a valid input, so I can not compile. 我遇到的问题是apply函数,因为它不能将
MyWindowFunction
识别为有效输入,所以我无法编译。 The data I am streaming contains (timestamp,x,y)
where x and y are 0 and 1 for testing. 我正在流式传输的数据包含
(timestamp,x,y)
,其中x和y为0和1用于测试。 extractTupleWithoutTs
simply returns a tuple (x,y)
. extractTupleWithoutTs
只返回一个元组(x,y)
。 I have been running the code with simple sum and reduce functions with success. 我一直在使用简单的sum和reduce函数运行代码并且成功。 Grateful for any help :) Using Flink 1.3
感谢任何帮助:)使用Flink 1.3
Imports: 进口:
import org.apache.flink.streaming.api.TimeCharacteristic
import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks
import org.apache.flink.streaming.api.scala.function.WindowFunction
import org.apache.flink.streaming.api.watermark.Watermark
import org.apache.flink.streaming.api.windowing.windows.TimeWindow
import org.apache.flink.util.Collector
Rest of the code: 其余代码:
val env = StreamExecutionEnvironment.getExecutionEnvironment
env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
val text = env.socketTextStream("localhost", 9999).assignTimestampsAndWatermarks(new TsExtractor)
val tuple = text.map( str => extractTupleWithoutTs(str))
val counts = tuple.keyBy(0).timeWindow(Time.seconds(5)).apply(new MyWindowFunction())
counts.print()
env.execute("Window Stream")
MyWindow function which is basically copy paste from example with changes of the types. MyWindow函数基本上是从示例中复制粘贴的类型更改。
class MyWindowFunction extends WindowFunction[(Int, Int), Int, Int, TimeWindow] {
def apply(key: Int, window: TimeWindow, input: Iterable[(Int, Int)], out: Collector[Int]): () = {
var count = 0
for (in <- input) {
count = count + 1
}
out.collect(count)
}
}
The problem is the third type parameter of the WindowFunction
, ie, the type of the key. 问题是
WindowFunction
的第三个类型参数,即键的类型。 The key is declared with an index in the keyBy
method ( keyBy(0)
). 密钥在
keyBy
方法( keyBy(0)
)中使用索引声明。 Therefore, the type of the key cannot be determined at compile time. 因此,在编译时无法确定密钥的类型。 The same problem arises, if you declare the key as a string, ie,
keyBy("f0")
. 如果将键声明为字符串,即
keyBy("f0")
, keyBy("f0")
出现同样的问题。
There are two options to resolve this: 有两种方法可以解决这个问题:
KeySelector
function in keyBy
to extract the key (something like keyBy(_._1)
). keyBy
使用KeySelector
函数来提取密钥(类似于keyBy(_._1)
)。 The return type of the KeySelector
function is known at compile time such that you can use a correctly typed WindowFunction
with an Int
key. KeySelector
函数的返回类型在编译时是已知的,这样您就可以使用带有Int
键的正确类型的WindowFunction
。 WindowFunction
to org.apache.flink.api.java.tuple.Tuple
, ie, WindowFunction[(Int, Int), Int, org.apache.flink.api.java.tuple.Tuple, TimeWindow]
. WindowFunction
的第三个类型参数的类型更改为org.apache.flink.api.java.tuple.Tuple
,即WindowFunction[(Int, Int), Int, org.apache.flink.api.java.tuple.Tuple, TimeWindow]
。 Tuple
is a generic holder for the keys extracted by keyBy
. Tuple
是keyBy
提取的密钥的通用持有者。 In your case it will be a org.apache.flink.api.java.tuple.Tuple1
. org.apache.flink.api.java.tuple.Tuple1
。 In WindowFunction.apply()
you can cast Tuple
to Tuple1
and access the key field by Tuple1.f0
. WindowFunction.apply()
您可以将Tuple
为Tuple1
并通过Tuple1.f0
访问关键字段。
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