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https://issues.apache.org/jira/browse/APEXMALHAR-2085?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15312801#comment-15312801
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David Yan commented on APEXMALHAR-2085:
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Also, since the window must be assigned before any "GroupBy" operations, we
probably need to add the GroupBy function to the second operator as well. So if
groupby is needed, it will act as the key to the Dimension Store, together with
the window. Otherwise, the key will just be the window.
> Implement Windowed Operators
> ----------------------------
>
> Key: APEXMALHAR-2085
> URL: https://issues.apache.org/jira/browse/APEXMALHAR-2085
> Project: Apache Apex Malhar
> Issue Type: New Feature
> Reporter: Siyuan Hua
> Assignee: Siyuan Hua
>
> As per our recent several discussions in the community. A group of Windowed
> Operators that delivers the window semantic follows the google Data Flow
> model(https://cloud.google.com/dataflow/) is very important.
> The operators should be designed and implemented in a way for
> High-level API
> Beam translation
> Easy to use with other popular operator
> {panel:title=Operator Hierarchy}
> Hierarchy of the operators,
> The windowed operators should cover all possible transformations that require
> window, and batch processing is also considered as special window called
> global window
> {code}
> +-------------------+
> +---------> | WindowedOperator | <--------+
> | +--------+----------+ |
> | ^ ^--------------------------------+
> | | | |
> | | | |
> +------+--------+ +------+------+ +-------+-----+ +------+-----+
> |CombineOperator| |GroupOperator| |KeyedOperator| |JoinOperator|
> +---------------+ +-------------+ +------+------+ +-----+------+
> +---------^ ^ ^
> | | |
> +--------+---+ +-----+----+ +----+----+
> |KeyedCombine| |KeyedGroup| | CoGroup |
> +------------+ +----------+ +---------+
> {code}
> Combine operation includes all operations that combine all tuples in one
> window into one or small number of tuples, Group operation group all tuples
> in one window, Join and CoGroup are used to join and group tuples from
> different inputs.
> {panel}
> {panel:title=Components}
> * Window Component
> It includes configuration, window state that should be checkpointed, etc. It
> should support NonMergibleWindow(fixed or slide) MergibleWindow(Session)
> * Trigger
> It should support early trigger, late trigger with customizable trigger
> behaviour
> * Other related components:
> ** Watermark generator, can be plugged into input source to generate watermark
> ** Tuple schema support:
> It should handle either predefined tuple type or give a declarative API to
> describe the user defined tuple class
> {panel}
> Most component API should be reused in High-Level API
> This is the umbrella ticket, separate tickets would be created for different
> components and operators respectively
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