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https://issues.apache.org/jira/browse/FLINK-2779?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14947223#comment-14947223
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ASF GitHub Bot commented on FLINK-2779:
---------------------------------------

Github user fhueske commented on the pull request:

    https://github.com/apache/flink/pull/1208#issuecomment-146264681
  
    It's a bit painful to review because Github is not showing the diff :-(
    
    Here is what I found in `streaming_guide.ml` until but not including 
`Specifying Keys`:
    
    Intro:
    - What are regular programs?
    - "The data streams are initially created…" -> "A data stream can be 
produced by different sources such as …"
    - What are distributed files?
    - Flink program -> DataStream program
    
    Linking with Flink:
    - To write programs with Flink -> To implement a DataStream program
    - If you want to add Flink to an existing -> If you want to add Flink's 
DataStream API to an …
    Program Skeleton (Java and Scala):
    - Flink DataStream program -> DataStream Program
    - If you created a JAR file from you program -> If you created a JAR file 
from YOUR program
    - with your own custom transformation function -> with your own custom 
transformation FUNCTIONS
    - converting every String in the original set to an Integer. -> converting 
every String in the original STREAM to an Integer.
    
    DataStream abstraction:
    - unbounded immutable collection of data of a the same type -> unbounded 
immutable collection of data ITEMS of a the same type. ?
    
    Lazy Evaluation:
    - All Flink programs -> All DataStream programs
    
    Transformations (only checked Java, Scala probably the same…)
    - KeyBy
      - Logically partition a stream -> Logically PARTITIONS a stream
      - This transformations -> This transformation
    - Reduce + Fold
      - Combines the last element with the last reduced value and emits the new 
value. -> Combines the current element with the last reduced value and emits 
the new value. ?
    - Aggregations:
      - Rolling aggregations on keyed data stream. -> Rolling aggregations on A 
keyed data stream.
    - Window
      - Windows can be defined on already partitioned KeyedStreams -> Windows 
can be defined on partitioned KeyedStreams ?
    - Window Apply
      - Applies a general function to the window as a whole. -> Applies a 
general function to WINDOWS as a whole. ?
      - A function that manually sums the elements of a window -> Sentence is 
incomplete
    - Window Reduce / Aggregations
      - Point out difference to rolling reduce / aggregations?
    - Iterate
      - The resulting stream of an iteration is a DataStream again. The 
IterativeStream is only "within" the iteration, right? Shouldn't it be 
DataStream -> IteratativeStream -> DataStream then?
    - Extract Timestamps
      - Extract -> ExtractS
      - Flink windows -> windows


> Update documentation to reflect new Stream/Window API
> -----------------------------------------------------
>
>                 Key: FLINK-2779
>                 URL: https://issues.apache.org/jira/browse/FLINK-2779
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Streaming
>            Reporter: Aljoscha Krettek
>            Assignee: Kostas Tzoumas
>             Fix For: 0.10
>
>




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