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@ -55,13 +55,13 @@ Spark Streaming是Spark的一个子模块，用于快速构建可扩展，高吞
+ 能够和Spark其他模块无缝集成，将流处理与批处理完美结合；
+ Spark Streaming可以从HDFS，Flume，Kafka，Twitter和ZeroMQ读取数据，也支持自定义数据源。
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/spark-streaming-arch.png"/> </div>
<div align="center"> <img width="600px" src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/spark-streaming-arch.png"/> </div>
### 2.2 DStream
Spark Streaming提供称为离散流(DStream)的高级抽象，用于表示连续的数据流。 DStream可以从来自Kafka，Flume和Kinesis等数据源的输入数据流创建，也可以由其他DStream转化而来。**在内部，DStream表示为一系列RDD**。
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/spark-streaming-flow.png"/> </div>
<div align="center"> <img width="600px" src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/spark-streaming-flow.png"/> </div>
@ -75,4 +75,4 @@ storm和Flink都是真正意义上的流计算框架，但 Spark Streaming 只
## 参考资料
[Spark Streaming Programming Guide](https://spark.apache.org/docs/latest/streaming-programming-guide.html)
[Spark Streaming Programming Guide](https://spark.apache.org/docs/latest/streaming-programming-guide.html)