Flink provides two sets of APIs to work with Data. One is for unbounded data such as streams and provided by DataStream APIs. Another is for the bounded data and provided by DataSet API.
Since Java programmers like collections, the latter provides methods to work with collections as source and sink.
For example, we have methods on StreamExecutionEnvironment such as
DataSet<T> result = env.fromCollection(data) which returns a DataSet.
And we have methods to specify a collection data sink as follows:
List<T> dataList = new ArrayList<T>();
result.output(new CollectionDataFormat(dataList));
This collection data sink works well as a debugging tool.
Both the dataType and iterators must be serializable for the read from source and write to sink.
The DataStream API only has support for source from collections. If we need to write a stream to a sink we can access the console or file-system because that will most likely be for debugging. There is no direct conversion from stream to collection.
DataStream<T>  stream = env.fromCollection(data);
Iterator<T> it = DataStreamUtils.collect(stream); // expensive
There is however another method called addSink which can allow custom sinks.
For most purposes of a collection, a DataStream provides an iterate() method that returns an Iterative Stream.
For example,
IterativeStream<T> = stream.iterate()
DataStream<T> newStream = iteration.map(new MyMapFunction()); where the map is invoked inside the loop.
Finally, iteration.closeWith(…) to define the tail of the iteration.