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Handling of times around daylight savings change #77
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Previously, these were implemented using floating window, which was terribly slow. I added new basic operation to the index representing "shifting", so now we just need to copy the data (skipping over the values that "drop out") and create a new index (excluding the dropped out keys). I also added some documentation. The performance improvement is orderds of magnitude (from seconds to milliseconds), so I'm not attaching any specific numbers. Aside, I also accidentally discovered fslaborg/RProvider#77 (and made the test here more stable) and I improved the build script to avoid running tests twice.
Is the issue fixed or fixable in the RProvider, or is this an issue at the level of R.NET that you need to work around ? I'd be interested to know; incidentally I do not remember any date-time specific support in R.NET yet. Given the ubiquitous nature of time series, it probably should. Dealt with it for http://rclr.codeplex.com, so I am very aware of the many quirks of the topic... |
There is some |
I think this is just dodgy behavior in DateTime. In the Eastern US, where the clock springs forward an hour at 02:00 on March 9th, I get similar behavior.
It appears that DateTime computation results in invalid local times:
Microsoft's advice is to basically never use DateTime to represent dates with times. They developed DateTimeOffset to overcome the majority of the issues. |
Yes, I suspect this might be the case. I'll try to change the tests and samples in Deedle to use |
I suppose this will only reproduce when your computer is set to a timezone where the daylight savings time change happens on 30 March, but it should be easy to adapt:
The odd thing is that the second and third values print as the same time when they come back from R (possibly because at 1am, the UK clock jumps forward to 2am).
I have not investigated this further yet - so I'm not sure whether this is an issue with passing data into R or with getting data from R.
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