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Posted to user@spark.apache.org by sim <si...@swoop.com> on 2015/07/03 19:06:30 UTC

Re: Spark SQL groupby timestamp

@bastien, in those situations, I prefer to use Unix timestamps (millisecond
or second granularity) because you can apply math operations to them easily.
If you don't have a Unix timestamp, you can use unix_timestamp() from Hive
SQL to get one with second granularity.Then doing grouping by hour becomes
very simple:
select  3600*floor(timestamp/3600) as timestamp,  count(error) as
errors,from logsgroup by 3600*floor(timestamp/3600)
Hope this helps./Sim



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