Re: [netmod] Justification for decimal64 over string for floating point values in geo location data?

Juergen Schoenwaelder <j.schoenwaelder@jacobs-university.de> Wed, 08 July 2020 16:44 UTC

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Date: Wed, 8 Jul 2020 18:44:12 +0200
From: Juergen Schoenwaelder <j.schoenwaelder@jacobs-university.de>
To: "Rob Wilton (rwilton)" <rwilton@cisco.com>
Cc: Christian Hopps <chopps@chopps.org>, NetMod WG <netmod@ietf.org>
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Subject: Re: [netmod] Justification for decimal64 over string for floating point values in geo location data?
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unknown precision != arbitrary precision

/js

On Wed, Jul 08, 2020 at 04:35:06PM +0000, Rob Wilton (rwilton) wrote:
> [As an individual]
> 
> I agree with Juergen that in many configuration cases, using decimal64 is better/safer than binary float/double.  However, there are other scenarios, such as operational data coming from sensors, where float/double is probably more appropriate/useful, hence I would still like to see the next version of YANG supporting float/double, possibly restricted to operational data only.
> 
> For configuration, with regards to the rounding errors alluded to below, I do have some sympathy with Chris's suggestion of support for arbitrary precision decimal numbers.  It seems that more and more languages have native support for arbitrary precision decimal maths.  I note that CBOR also has an encoding for them, and a JSON/XML encoding of them is seemingly trivial.
> 
> Regards,
> Rob
> 
> 
> > -----Original Message-----
> > From: netmod <netmod-bounces@ietf.org> On Behalf Of Juergen Schoenwaelder
> > Sent: 07 July 2020 12:25
> > To: Christian Hopps <chopps@chopps.org>
> > Cc: NetMod WG <netmod@ietf.org>
> > Subject: Re: [netmod] Justification for decimal64 over string for floating
> > point values in geo location data?
> > 
> > Precision often means different things to different people. Here is my
> > take:
> > 
> > - Floating point numbers have almost always rounding errors. And
> >   floating point numbers use binary fractions, a decimal fraction like
> >   1.0 has no precise representation as a binary fraction. Type 0.1 +
> >   0.2 into python or haskell or any other language that gives you bare
> >   floating point numbers and enjoy the result.
> > 
> > - Fixed precision decimal numbers do not have rounding errors since
> >   they are essentially scaled integers and hence they are precise as
> >   long as calculations stay within the range.
> > 
> > - Floating point numbers can cover a large number space (from very
> >   tiny to really big), fixed precision decimal numbers are much more
> >   restrictive.
> > 
> > - In XML and JSON, numbers are rendered in strings that likely do not
> >   look much different if its a decimal64 or a float or ... If you really
> >   care about size, use a binary encoding like CBOR.
> > 
> > /js
> > 
> > On Tue, Jul 07, 2020 at 07:06:20AM -0400, Christian Hopps wrote:
> > > I received feedback in my YANG doctor review (thanks Mahesh) regarding
> > the use of decimal64 for most of the values in the geo location grouping
> > (https://tools.ietf.org/html/draft-ietf-netmod-geo-location-04). In my
> > comparison sections I note that some precision (at the very extremes) may
> > be lost when converting from other geo location formats that use string
> > (or double for w3c) to decimal64. Given that mention of loss of extreme
> > precision, the reviewer was asking if some justification for the decimal64
> > should be given in the document.
> > >
> > > What are the advantages to using decimal64 for floating point numbers vs
> > using a string with a pattern "[0-9]+(\.[0-9]+)?" (convert that to yang
> > pattern language). The advantage of using a string is that the precision
> > of the value is not restricted by the model. Does the YANG decimal64
> > values have a concise binary format that can be more efficiently
> > transported or stored in binary form? If so is this the only advantage,
> > and is it enough of one to limit the precision in the model?
> > >
> > > It's definitely worth noting that the precision of the decimal64 values
> > seem vastly adequate for geo location data (e.g., for Cartesian
> > coordinates and height values which are measured in meters the fractional
> > digits is 6 which means the surface could be up to 9 billion kilometers
> > large (or away from for height) and the precision is to the micrometer.
> > For ellipsoidal coordinates there are 12 fractional digits for the
> > degrees.
> > >
> > > Thanks,
> > > Chris.
> > 
> > 
> > 
> > > _______________________________________________
> > > netmod mailing list
> > > netmod@ietf.org
> > > https://www.ietf.org/mailman/listinfo/netmod
> > 
> > 
> > --
> > Juergen Schoenwaelder           Jacobs University Bremen gGmbH
> > Phone: +49 421 200 3587         Campus Ring 1 | 28759 Bremen | Germany
> > Fax:   +49 421 200 3103         <https://www.jacobs-university.de/>
> > 
> > _______________________________________________
> > netmod mailing list
> > netmod@ietf.org
> > https://www.ietf.org/mailman/listinfo/netmod

-- 
Juergen Schoenwaelder           Jacobs University Bremen gGmbH
Phone: +49 421 200 3587         Campus Ring 1 | 28759 Bremen | Germany
Fax:   +49 421 200 3103         <https://www.jacobs-university.de/>