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https://issues.apache.org/jira/browse/FLINK-5529?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15839965#comment-15839965
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ASF GitHub Bot commented on FLINK-5529:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3191#discussion_r98026366
--- Diff: docs/dev/windows.md ---
@@ -312,9 +328,9 @@ Time intervals can be specified by using one of
`Time.milliseconds(x)`, `Time.se
they are evaluated differently than tumbling and sliding windows.
Internally, a session window operator
creates a new window for each arriving record and merges windows together
if their are closer to each other
than the defined gap.
-In order to be mergable, a session window operator requires a mergable
[Trigger](#triggers) and a mergable
+In order to be mergeable, a session window operator requires a merging
[Trigger](#triggers) and a merging
[Window Function](#window-functions), such as `ReduceFunction` or
`WindowFunction`
-(`FoldFunction` is not mergable.)
+(`FoldFunction` is not mergeable.)
--- End diff --
"`FoldFunction` cannot merge" ?
> Improve / extends windowing documentation
> -----------------------------------------
>
> Key: FLINK-5529
> URL: https://issues.apache.org/jira/browse/FLINK-5529
> Project: Flink
> Issue Type: Sub-task
> Components: Documentation
> Reporter: Stephan Ewen
> Assignee: Kostas Kloudas
> Fix For: 1.2.0, 1.3.0
>
>
> Suggested Outline:
> {code}
> Windows
> (0) Outline: The anatomy of a window operation
> stream
> [.keyBy(...)] <- keyed versus non-keyed windows
> .window(...) <- required: "assigner"
> [.trigger(...)] <- optional: "trigger" (else default trigger)
> [.evictor(...)] <- optional: "evictor" (else no evictor)
> [.allowedLateness()] <- optional, else zero
> .reduce/fold/apply() <- required: "function"
> (1) Types of windows
> - tumble
> - slide
> - session
> - global
> (2) Pre-defined windows
> timeWindow() (tumble, slide)
> countWindow() (tumble, slide)
> - mention that count windows are inherently
> resource leaky unless limited key space
> (3) Window Functions
> - apply: most basic, iterates over elements in window
>
> - aggregating: reduce and fold, can be used with "apply()" which will get
> one element
>
> - forward reference to state size section
> (4) Advanced Windows
> - assigner
> - simple
> - merging
> - trigger
> - registering timers (processing time, event time)
> - state in triggers
> - life cycle of a window
> - create
> - state
> - cleanup
> - when is window contents purged
> - when is state dropped
> - when is metadata (like merging set) dropped
> (5) Late data
> - picture
> - fire vs fire_and_purge: late accumulates vs late resurrects (cf
> discarding mode)
>
> (6) Evictors
> - TDB
>
> (7) State size: How large will the state be?
> Basic rule: Each element has one copy per window it is assigned to
> --> num windows * num elements in window
> --> example: tumbline is one copy, sliding(n,m) is n/m copies
> --> per key
> Pre-aggregation:
> - if reduce or fold is set -> one element per window (rather than num
> elements in window)
> - evictor voids pre-aggregation from the perspective of state
> Special rules:
> - fold cannot pre-aggregate on session windows (and other merging windows)
> (8) Non-keyed windows
> - all elements through the same windows
> - currently not parallel
> - possible parallel in the future when having pre-aggregation functions
> - inherently (by definition) produce a result stream with parallelism one
> - state similar to one key of keyed windows
> {code}
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