[
https://issues.apache.org/jira/browse/SPARK-17829?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15595716#comment-15595716
]
Michael Armbrust commented on SPARK-17829:
------------------------------------------
Yeah, I agree. I think it could be really simple. We can have one that just
holds json, and sources can convert to something more specific internally.
{code}
abstract class Offset {
def json: String
}
/** Used when loading */
case class SerializedOffset(json: String)
/** Used to convert to a more specific type */
object LongOffset {
def apply(serialized: Offset) = LongOffset(parse(serialized.json).as[Long]))
}
case class LongOffset(value: Long) extends Offset {
def json = value.toString
}
{code}
> Stable format for offset log
> ----------------------------
>
> Key: SPARK-17829
> URL: https://issues.apache.org/jira/browse/SPARK-17829
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Reporter: Michael Armbrust
> Assignee: Tyson Condie
>
> Currently we use java serialization for the WAL that stores the offsets
> contained in each batch. This has two main issues:
> - It can break across spark releases (though this is not the only thing
> preventing us from upgrading a running query)
> - It is unnecessarily opaque to the user.
> I'd propose we require offsets to provide a user readable serialization and
> use that instead. JSON is probably a good option.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
