Showing the most recent 20 out of 53 comments. Click to see all the comments. Comments Your Name optional Post. Better results and improved feedback when there are no results found. Maps you can make use of Uses of This ZIP Code Tool This tool has a wide range of possible uses from delivery estimation, completing mileage expenses and point to point measurement. Issues or Suggestions If you notice any errors or have suggestions for further development, then please contact freemaptools.
On 27th May shubh, it should be working again. On 23rd July Hi Joshua, please get in contact to discuss. However, would be much more useful if bulk uploads would be available By Alex on 3rd April Hi, that idea has been rescinded. By Free Map Tools on 28th October would like to use this for a batch of zipcodes, when do you think may be possible? By Free Map Tools on 14th October Free map tools for US zipcode miles calculation is not working and it always return result as zero On 14th October Showing the most recent 20 out of 53 comments.
Add your own comment below and let others know what you think: Comments Your Name optional Post. Site Search. Measure in : miles km. Distance as the Crow Flies :. Distance by Land Transport :. Message 4 of 5. Microsoft Hates Greg Check out my latest book! Message 2 of 5. Post Reply. Helpful resources. Check it Out! Click here to read more about the December Updates! Read More.
Launching new user group features Learn how to create your own user groups today! Learn More. View All. Featured Topics. Top Solution Authors.
User Count. Top Kudoed Authors. Of course the solution I liked above grows with distance at query time, and this one doesn't. However, how many rows do you wind up if you use say, miles as your outer limit? I'm also not sure what the practical limit of rows in SQL server is, but I suspect I'd be pushing my luck on keeping excellent performance with that many rows.
The runtime is 0. I'm since learned much about the limits of performance on big SQL tables. They're not nearly as slow as I thought they might be. Thanks, guys, for going to all that extra effort.
Your answers and comments were super helpful. Show 2 more comments. Facundo Colombier Facundo Colombier 3, 1 1 gold badge 32 32 silver badges 38 38 bronze badges.
Jander Jander 4, 1 1 gold badge 21 21 silver badges 19 19 bronze badges. This seems like a REALLY fast way of getting some indexing done, but with a much smaller and therefore more useable indexed data set. This might turn out faster than the solution I posted below. I say might because I have not thought it through. I suspect variation of this can be used to get ZipCodes that are known to be within range, and allow me to do a boxed select by Lat and Long, and then user the Haversinse Formula to calculate a much smaller number of distances.
Zipcodes aren't approximately equal in size though. I think there are better solutions for doing this spatial breakdown. Good visualization here: benfry. Paul: Hm! Actually, in my head I was treating ZIP codes as points, but this will work with shaped zipcodes too.
The roughly equally sized "regions" in my answer are meant to contain several zip codes each or parts thereof. The idea is to do a quick, rough weed-out of regions that are obviously in or obviously out of range, so you only work with the complex, numerous, and now variable-sized!
ZIP code regions when you have to. With zipcodes, the maximum dataset size means there's probably a reasonable balance with your method, since the dataset is finite. Quadtrees or R-trees are the "right" way to do it though Show 1 more comment. David Watson David Watson 1, 2 2 gold badges 12 12 silver badges 17 17 bronze badges.
John Smith John Smith The bit about not calculating all distances is a very good point. I suspect it'd eventually get pretty big still, with a limit of say, miles.
However, I think I'll give it a whirl to see if it makes an improvement or not. This reduces the resultset from 1. I posted an answer along these lines which might prove of interest. Sign up or log in Sign up using Google.
Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. The Overflow Blog. Podcast Making Agile work for data science.
Stack Gives Back Featured on Meta. New post summary designs on greatest hits now, everywhere else eventually. Visit chat.
0コメント