如何在 Apache Flink 中实现 Window 函数?

Question

everyone， 我有一个 kafka 主题源，我按 1 分钟窗口对其进行分组。 我想在该窗口中做的是像在SQL中一样使用窗口函数创建新列，例如我想使用

• 总和(金额(超过(除以(
• 计数(用户( 超过(分区依据
• ROW_NUMBER(( OVER(分区依据

是否可以使用数据流函数进行这些操作？ 或

如何操作我的 kafka 数据以将其转换为 DataTable 并使用 sqlQuery？

目的地是另一个卡夫卡主题。

val stream = senv
.addSource(new FlinkKafkaConsumer[String]("flink", new SimpleStringSchema(), properties))

我试过这样做

val tableA = tableEnv.fromDataStream(stream, 'user, 'product, 'amount)

但我收到以下错误

Exception in thread "main" org.apache.flink.table.api.ValidationException: Too many fields referenced from an atomic type.

测试数据

1,"beer",3
1,"beer",1
2,"beer",3
3,"diaper",4
4,"diaper",1
5,"diaper",5
6,"rubber",2

查询示例

SELECT
user, product, amount,
COUNT(user) OVER(PARTITION BY product) AS count_product
FROM table;

预期性能

1,"beer",3,3
1,"beer",1,3
2,"beer",3,3
3,"diaper",4,3
4,"diaper",1,3
5,"diaper",5,3
6,"rubber",2,1

Answer 1

您需要将字符串解析为字段，然后重命名它们。

val env = StreamExecutionEnvironment.getExecutionEnvironment
val tEnv = StreamTableEnvironment.create(env)
val stream = env.fromElements("1,beer,3",
"1,beer,1","2,beer,3","3,diaper,4","4,diaper,1","5,diaper,5","6,rubber,2");
val parsed = stream.map(x=> {
val arr = x.split(",")
(arr(0).toInt, arr(1), arr(2).toInt)
})
val tableA = tEnv.fromDataStream(parsed, $"_1" as "user", $"_2" as "product", $"_3" as "amount")
// example query
val result = tEnv.sqlQuery(s"SELECT user, product, amount from $tableA")
val rs = result.toAppendStream[(Int, String, Int)]
rs.print()

我不确定我们如何在 Flink SQL 中实现所需的窗口函数。 或者，它可以在简单的 Flink 中实现，如下所示：

parsed.keyBy(x => x._2) // key by product id.
.window(TumblingEventTimeWindows.of(Time.milliseconds(2)))
.process(new ProcessWindowFunction[
(Int, String, Int), (Int, String, Int, Int), String, TimeWindow
]() {
override def process(key: String, context: Context,
elements: Iterable[(Int, String, Int)],
out: Collector[(Int, String, Int, Int)]): Unit = {
val lst = elements.toList
lst.foreach(x => out.collect((x._1, x._2, x._3, lst.size)))
}
})
.print()