Sign up to take part
Registered users can ask their own questions, contribute to discussions, and be part of the Community!
Registered users can ask their own questions, contribute to discussions, and be part of the Community!
In my workflow datasets are partitioned at a day-level (file based partitioning, HDFS connector). For business reasons, some partitions are empty, for example the one corresponding to saturdays and sundays and holidays.
- when using a "Equals" dependency, the recipe runs even if the partition is missing/empty in the input dataset. It looks like some "ignoring of missing partitions" is handled here automatically.
- when using a "Time range" dependency (for example the partitions for the past 7 days are used to compute the partition for the day), the recipe fails, as partitions for the past week end (at least) are missing. See screenshot : it can't compute the partition for the 9th of january as the
Is there any way to setup the time range dependence to ignore the missing partitions ? So the recipe can still be computing, ignoring the empty partitions for week end or holidays.
2 years ago it looks like a similar question was raised (Solved: Re: Recipes with Time Range dependence partitions: is it possible to ignore missing partitio...) and the answer seemed to be : we cannot ignore missing partitions.
Has this situation changed ? It seems to me that this past answer is similar to "you cannot use time range dependency in dataiku when working with daily partitions". Is this conclusion unchanged ? I hope and trust i am missing something.... Thank you for your help
Hi @MatthieuPx ,
If I am not mistaken, you are looking for the "Missing partitions as empty" option in the input dataset. Which will skip gaps in your partitioning without having the recipe fail: