Thank you Daniel. Unfortunately, we don't use Hive but bare (Avro) files.
On 11/17/2016 08:47 PM, Daniel Haviv wrote:
Hi Samy, If you're working with hive you could create a partitioned table and update it's partitions' locations to the last version so when you'll query it using spark, you'll always get the latest version. Daniel On Thu, Nov 17, 2016 at 9:05 PM, Samy Dindane <s...@dindane.com <mailto:s...@dindane.com>> wrote: Hi, I have some data partitioned this way: /data/year=2016/month=9/version=0 /data/year=2016/month=10/version=0 /data/year=2016/month=10/version=1 /data/year=2016/month=10/version=2 /data/year=2016/month=10/version=3 /data/year=2016/month=11/version=0 /data/year=2016/month=11/version=1 When using this data, I'd like to load the last version only of each month. A simple way to do this is to do `load("/data/year=2016/month=11/version=3")` instead of doing `load("/data")`. The drawback of this solution is the loss of partitioning information such as `year` and `month`, which means it would not be possible to apply operations based on the year or the month anymore. Is it possible to ask Spark to load the last version only of each month? How would you go about this? Thank you, Samy --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org <mailto:user-unsubscr...@spark.apache.org>
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