# Structured Streaming
Structured Streaming 은 데이터 스트림을 테이블로 관리한다. 매 미니매치 마다 새로운 데이터 스트림 유입되면 테이블에 추가된다.
### Basic Concepts
### **Types of time windows**
### **Handling Late Data and Watermarking**
```scala
import spark.implicits._
val words = ... // streaming DataFrame of schema { timestamp: Timestamp, word: String }
// Group the data by window and word and compute the count of each group
val windowedCounts = words
.withWatermark("timestamp", "10 minutes")
.groupBy(
window($"timestamp", "10 minutes", "5 minutes"),
$"word")
.count()
```
###
### 참고자료
Spark Documentation, [https://docs.microsoft.com/ko-kr/azure/databricks/getting-started/spark/streaming](https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html)
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