[jira] [Work logged] (BEAM-8470) Create a new Spark runner based on Spark Structured streaming framework

["ASF GitHub Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-8470?focusedWorklogId=339396&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-339396 ]

ASF GitHub Bot logged work on BEAM-8470:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 06/Nov/19 14:51
            Start Date: 06/Nov/19 14:51
    Worklog Time Spent: 10m 
      Work Description: aromanenko-dev commented on issue #9866: [BEAM-8470] Create a new Spark runner based on Spark Structured streaming framework
URL: https://github.com/apache/beam/pull/9866#issuecomment-550344494
 
 
   Run Spark ValidatesRunner
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 339396)
    Time Spent: 6h  (was: 5h 50m)

> Create a new Spark runner based on Spark Structured streaming framework
> -----------------------------------------------------------------------
>
>                 Key: BEAM-8470
>                 URL: https://issues.apache.org/jira/browse/BEAM-8470
>             Project: Beam
>          Issue Type: Improvement
>          Components: runner-spark
>            Reporter: Etienne Chauchot
>            Assignee: Etienne Chauchot
>            Priority: Major
>          Time Spent: 6h
>  Remaining Estimate: 0h
>
> h1. Why is it worth creating a new runner based on structured streaming:
> Because this new framework brings:
>  * Unified batch and streaming semantics:
>  * no more RDD/DStream distinction, as in Beam (only PCollection)
>  * Better state management:
>  * incremental state instead of saving all each time
>  * No more synchronous saving delaying computation: per batch and partition delta file saved asynchronously + in-memory hashmap synchronous put/get
>  * Schemas in datasets:
>  * The dataset knows the structure of the data (fields) and can optimize later on
>  * Schemas in PCollection in Beam
>  * New Source API
>  * Very close to Beam bounded source and unbounded sources
> h1. Why make a new runner from scratch?
>  * Structured streaming framework is very different from the RDD/Dstream framework
> h1. We hope to gain
>  * More up to date runner in terms of libraries: leverage new features
>  * Leverage learnt practices from the previous runners
>  * Better performance thanks to the DAG optimizer (catalyst) and by simplifying the code.
>  * Simplify the code and ease the maintenance
>  



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