org.apache.spark.sql.AnalysisException:流式数据帧/数据集上不支持非基于时间的窗口；；尽管存在基于时间的窗口

import org.apache.spark.sql.functions._
import org.apache.spark.sql.streaming.Trigger

val df = spark.readStream
  .format("kafka")
  .option("kafka.bootstrap.servers", "localhost:9092")
  .option("subscribe", "topicName")
  .load()
  .selectExpr("CAST(key AS STRING)", "CAST(value AS STRING)")
  .as[(String, String)]

val windowedCounts = df
  .groupBy(
    window(col("timestamp"), "10 minutes", "5 minutes"),
    col("key")
  )
  .count()

val query = windowedCounts.writeStream
  .outputMode("update")
  .format("console")
  .trigger(Trigger.ProcessingTime("1 minute"))
  .start()

query.awaitTermination()

val df = spark.read.option("header", "true").csv("data.csv")

val windowedCounts = df
  .groupBy(window(col("timestamp"), "10 minutes", "5 minutes"), col("key"))
  .count()

windowedCounts.show()