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https://issues.apache.org/jira/browse/KAFKA-691?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13551961#comment-13551961
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Jun Rao commented on KAFKA-691:
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Another potential issue is that for producers that produce many topics (like
migrationTool and mirrorMaker), the time-based refreshing may need to get the
metadata for many topics. This means that the metadata request is likely to
timeout. One solution is to break topics into batches in
BrokerPartitionInfo.updateInfo() and issue a metadata request per batch.
> Fault tolerance broken with replication factor 1
> ------------------------------------------------
>
> Key: KAFKA-691
> URL: https://issues.apache.org/jira/browse/KAFKA-691
> Project: Kafka
> Issue Type: Bug
> Affects Versions: 0.8
> Reporter: Jay Kreps
> Assignee: Maxime Brugidou
> Fix For: 0.8
>
> Attachments: KAFKA-691-v1.patch, KAFKA-691-v2.patch
>
>
> In 0.7 if a partition was down we would just send the message elsewhere. This
> meant that the partitioning was really more of a "stickiness" then a hard
> guarantee. This made it impossible to depend on it for partitioned, stateful
> processing.
> In 0.8 when running with replication this should not be a problem generally
> as the partitions are now highly available and fail over to other replicas.
> However in the case of replication factor = 1 no longer really works for most
> cases as now a dead broker will give errors for that broker.
> I am not sure of the best fix. Intuitively I think this is something that
> should be handled by the Partitioner interface. However currently the
> partitioner has no knowledge of which nodes are available. So you could use a
> random partitioner, but that would keep going back to the down node.
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