What’s the difference between Spark Streaming and Spark Structured Streaming? What should I use?
Spark Streaming is the previous generation of Spark’s streaming engine. There are no longer updates to Spark Streaming and it’s a legacy project. Spark Streaming provides a high-level abstraction called discretized stream or DStream, which represents a continuous stream of data. Internally, a DStream is represented as a sequence of RDDs.

Spark Structured Streaming is the current generation of Spark’s streaming engine, which is richer in functionality, easier to use, and more scalable. Spark Structured Streaming is built on top of the Spark SQL engine and enables you to express streaming computation the same way you express a batch computation on static data.

You should use Spark Structured Streaming for building streaming applications and pipelines with Spark. If you have legacy applications and pipelines built on Spark Streaming, you should migrate them to Spark Structured Streaming.
Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
### Instruction: What’s the difference between Spark Streaming and Spark Structured Streaming? What should I use?
### Input: 
### Response: Spark Streaming is the previous generation of Spark’s streaming engine. There are no longer updates to Spark Streaming and it’s a legacy project. Spark Streaming provides a high-level abstraction called discretized stream or DStream, which represents a continuous stream of data. Internally, a DStream is represented as a sequence of RDDs.

Spark Structured Streaming is the current generation of Spark’s streaming engine, which is richer in functionality, easier to use, and more scalable. Spark Structured Streaming is built on top of the Spark SQL engine and enables you to express streaming computation the same way you express a batch computation on static data.

You should use Spark Structured Streaming for building streaming applications and pipelines with Spark. If you have legacy applications and pipelines built on Spark Streaming, you should migrate them to Spark Structured Streaming.