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https://issues.apache.org/jira/browse/BEAM-4049?focusedWorklogId=90887&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-90887
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ASF GitHub Bot logged work on BEAM-4049:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 13/Apr/18 16:51
            Start Date: 13/Apr/18 16:51
    Worklog Time Spent: 10m 
      Work Description: adejanovski commented on issue #5112: [BEAM-4049] 
Improve CassandraIO write throughput by performing async queries
URL: https://github.com/apache/beam/pull/5112#issuecomment-381196012
 
 
   @aromanenko-dev, I just pushed a new version that uses loops instead of 
`Futures.successfulAsList()`.
   I've tested it by generating timeouts in the middle of a pipeline's 
execution and the exceptions were correctly triggered and reported in the logs.
   The pipeline exited at the first exception, which is the desired behavior.
   Retry policies can be implemented in the driver to handle transient 
failures, but it should be part of another PR anyway.

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Issue Time Tracking
-------------------

    Worklog Id:     (was: 90887)
    Time Spent: 1.5h  (was: 1h 20m)

> Improve write throughput of CassandraIO
> ---------------------------------------
>
>                 Key: BEAM-4049
>                 URL: https://issues.apache.org/jira/browse/BEAM-4049
>             Project: Beam
>          Issue Type: Improvement
>          Components: io-java-cassandra
>    Affects Versions: 2.4.0
>            Reporter: Alexander Dejanovski
>            Assignee: Jean-Baptiste Onofré
>            Priority: Major
>              Labels: performance
>          Time Spent: 1.5h
>  Remaining Estimate: 0h
>
> The CassandraIO currently uses the mapper to perform writes in a synchronous 
> fashion. 
> This implies that writes are serialized and is a very suboptimal way of 
> writing to Cassandra.
> The IO should use the saveAsync() method instead of save() and should wait 
> for completion each time 100 queries are in flight, in order to avoid 
> overwhelming clusters.



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