I've got a list of shops that I have put in a javascript array. I have their addresses as well.
I'm needing to create an autocomplete which allows me to put in a city name and it displays the 3 nearest to that location. I imagine it will need to interface with google's apis some how but not sure where to start.
I've got the actual autocomplete jquery stuff working on an ajax script, but I don't know how to get things located nearest.
You need the lat/long locations of the stores, https://developers.google.com/maps/documentation/geocoding/ Then you need the lat/long location of the user, with some relatively simple mathematics you can then calculate the distance between these two points:
$distance = round((6371*3.1415926*sqrt(($lat2-$lat1)*($lat2-$lat1) +
cos($lat2/57.29578)*cos($lat1/57.29578)*($lon2-$lon1)*($lon2-$lon1))/180), 1);
If you have a large number of stores and a large number of users I advise caching these distances in a mysql table, you have to do this for each store in your database. So you create a table for each e.g. zipcode that requests this and put up a cron to remove these tables every hour or so.
So the process:
User asks for the nearest store
You get his location through google api (or your own storage)
Check if there's a table for his location
If yes, give him the results directly, if no generate the table and give him the results
Mind that google only allows a limited number of data requests. Even though this number is huge (I believe 25.000 requests per day) it may be advisable to store the lat-lon locations of your stores AND users. Would also improve the speed.
I made something similar to this, I fetched the lat/lon locations at the moment a location was inserted into the database and inserted it in a seperate per-zipcode lat/lon table.
Related
I have a table with over 2 million rows. One of the values is an address. Some rows have a common address. I am using php.
On my website, I want the user to put in their zip code, and I will return all results within that zip code. I would then use Google to Geolocate them on a map. The problem is that since Google charges by the query, I can't be wasting time and money requesting coordinates for an address I already have. Here is what I believe to be the correct approach:
Ask user for zip code
Run "Select * with 'Zip Code' = $user_zip" (paraphrasing)
Run a Geolocate on first address and plot on map
Check for matching addresses in result and group with the mapped result
Find next new address
Repeat 3-6 until complete
Is there a better way to approach this? I am looking for efficiency, easy way to manipulate all matching results at once, and the least amount of queries. If my way is correct, can someone please help me with the logic for numbers 3-5?
If I understand this right what you are trying to do is to render a map with markers for each record in your database that is within a certain zip area. And your challenge is that you need coordinates to render each marker. The biggest issue with your approach in terms of wasting resources is that you do not store the coordinates of each address in your database. I would suggest you to:
1 - Alter the endpoint (or script or whatever) that creates these records in your db to fetch the coordinates and store them in the database.
2 - Run a one time migration to fetch coordinates for each record. While I understand that doing this for 2 milion rows could be "costly" with Google's Geocoding (Estimate is 1000$ for 2 milion api calls). To save the costs you could look into some of the opensource map tools.
Either way fetching coordinates during the request lifecycle is both a waste of resource and it will significantly affect speeds.
Say I have a database table representing users with potentially millions of records (Wishful thinking). This table contains a whole bunch of information about each user including information about their location:
City
County/State etc
Country
Latitude
Longitude
Geohash based on the latitude/longitude values.
I would like to implement a feature where by a logged in user can search for other users that are nearby.
Ideally, I would like to grab say the 20 users that are geographically closest to the user, followed by the next 20, and the next 20 etc. So essentially I want to be able to order my users table by the distance from a certain point.
Approach 1
I have some previous experience with the haversine formula which I used to calculate the distance between one point and a few hundred others. This approach would be ideal on a relatively small record set but I fear it would become incredibly slow with such a large record set.
Approach 2
I've additionally done some research into geohashing and I understand how the hash is calculated and I get the theory behind how it represents a location and how precision is lost with shorter resolutions. I could of course grab the users that are located near the user's geographical area by grabbing users that have a similar beginning to their geohash (Based on a precision I specify - and potentially looking in the neighbouring regions) but that doesn't solve the problem of needing to sort by location. This approach is also not great for edge cases where 2 users may be very close to one another but lie close to the edges of 2 regions represented by the geohash.
Any ideas/suggestion towards the approach would be greatly appreciated. I'm not looking for code in particular but links to good examples and resources would be helpful.
Thanks,
Jonathon
Edit
Approach 3
After some thought I've come up with another potential solution to consider. Upon receiving each user's location information, I would store information about the location (town/city, area, country, latitude, longitude, geohash maybe) in a separate table (say locations). I would then connect the user to the location by a foreign key. This would give me a much smaller dataset to work with. To find nearby users I could then simply find other locations that are close to the user's location and then use their IDs to find other users. Perhaps some sort of caching could be then implemented by storing a list of the nearby location IDs for each location.
You can try a space filling curve. Translate the co-ordinate to a binary and interleave it. Treat it as base-4 number. You are also wrong a geohash can be used to sort also by location. Most likely use a bounding box and filter the solution and then use the harvesine formula.
I have a database table filled with addresses, the table is over 4,000 records long
I am wondering the best way to get the addresses compare it with a search field and sort them by distance from the search field location? GoogleAPI documentation says the requests are limited to like 25,000 per day does that mean I can only do 7 searches per day?
In my opinion - yes. Google is smart about calculating distance between 2 LatLng's, because gives you distance using streets and roads, not distance in a straight line between 2 points (which would be easy to calculate in php).
Saving LatLng's of those 4000 addresses wouldn't do you any good, because you still need to ask google about the distance from a user's address to each of them. You can't calculate that yourself even if you have all the LatLng's (you need the map).
I guess you could save each user input, and save that address with 4000 distances to each location... but that would only be useful for a user returning to the site for the 2nd time.
...
Ok, I have this idea:
Do store the LatLng's of each of the 4000 locations.
Store distances between all 4000 locations (so that if you pick one, you could get the list of the all the others, ordered by distance).
When you get the address from a user, convert it to a LatLng, and use simple mathematics to find the closest location in a straight line.
Using the list of distances to all the other locations from database, ask google to get the accuall distance to that location, and about 10-20 to locations closest to it; for the rest use the distances from the closest from the database.
This way you'd get the first 10-20 accurate distances to the closest locations from user input, and the rest would be pulled from the database - they would actually be distances from the closest location to the other locations.
I believe that since the addresses don't change that much, you can cache the latitude/longitude somewhere and refer to those instead of making repeated requests. Please elaborate if there are other mitigating conditions, of course.
Let's say your site has 200,000 unique users a day. So, your server is heavily loaded/pounded; and you do NOT have resources to buy a bigger/better server. So, you are stuck with what you have.
Now, whenever a user comes to your site, you need to do some calculation (calculate distance between user city as detected via GeoIP and some whitelist of cities, figure out the nearest city within 140 mile radius).
Would you do this calculation via PHP or via JavaScript?
First, would you precalculate all nearby cities within 140 mile radius of whitelisted cities? For eg: Whitelist city 1 can have 20 nearby cities. Or would you do on-the-fly calculation everytime?
For eg:
Whitelist = Detroit, MI
and nearby city = Kalamazoo, MI (140 miles)
Second, if pre-computed: would you store this in XML file or some MySQL table? Now, we just have to search through a table (mysql or xml no more than 1 mb in size). I am guessing this would be inefficient because client browser (JavaScript) would have to download 1mb xml and search through it. This would make page load time even slower. Using DB might be faster but then DB load increases (if 200,000 unique users are trying to load the page over the course of a day).
Maybe the best way to do would be to do precompute, store precomputed results in XML, and then use PHP to search through XML and find nearest whitelisted city to user?
If you, the site, are actually relying on the city information, then you must do the calculation on the server.
Database queries are almost always going to be faster than XML searches for sufficiently large XML files. You can optimize the query, MySQL will cache things, etc.
Pre-calculating all city-city distances would be a way to go, for sure. GeoIP doesn't only provide city names, it does give actual latitude/longitude locations as well. I'm sure that the possible list of cities changes rather constantly, too.
I would look into using the geospacial capabilities of MySQL. General over view of searching by coordinates here:
Fastest Way to Find Distance Between Two Lat/Long Points
In short what you will do is setup a database of the cities you care about, with their lat/long, and query that table based on the GeoIP provided lat/long.
I have a whitelist of cities. Let's say, Seattle, Portland, Salem. Using GeoIP, I'd detect user city. Let's call it $user_city. Based on $user_city, I want to display classified-listings from nearest city from my whitelist (Seattle || Portland || Salem) with in 140 miles. If city is not listed in 140 miles, I'd just show a drop-down and ask user to manually select a city.
There are a few ways of doing this:
calculate this on the fly (I found an algorithm in one of SO answers)
with help of DB (let me explain):
create a table called regions
regions will have
city 1 | city 2 | distance (upto 140 miles)
city 1= cities from whitelist
city 2= any city within 140 miles from city 1
This would create a reasonable sized table. If my whitelist has 200 cities, and there are 40 cities (or towns) within 140 miles of each city. This would create 8000 rows.
Now, when a user comes to my site:
1) I check if user is from whitelist city already (city 1 column). If so, display that city
2). If not, check if $user_city is in "city 2" column
2a) if it is, get whitelist city with lowest distance
2b) if it is not, display drop-down for manual input
Final constraint: whichever method we select, it has to work from within iFrame. I mean, can I create this page on my mysite1.com and embed this page inside someothersite2.com inside an iframe? Will it still be able to get user_city and find nearest whitelisted city? I know there are some cross-domain scripting rules so I am not sure if iFrame would be able to get user-ip address, pass it to GeoIP, and resolve it to $user_city
So, my question:
How best to do this? If a lot of people embed my page in their page (using iframe) then my server would get pounded 10000s of times per second (wishful thinking, but let's assume that's the case). I don't know if a DB would be able to handle so much pounding. I don't want to have to pay for more DB servers or web-servers. I want to minimize resource-requirement at my end. So, I don't mind offloading a bit of work to user's browser via JavaScript.
EDIT:
Some answers have recommended storing lat, long and then doing the Math. The reason I suggested creating a 'regions' table is that this way all math is precomputed. If I have a "whitelist" of cities, and if I precompute all possible nearby city for each whitelisted city. Then I don't have to compute distance (using Haversine algorithm for eg) everytime.
Is it possible to offload all of this to user's browser via some crafty use of Java Script? I don't want to overload my server for a free service. It might make money but I am very close to broke and I am afraid my server would go down before I make enough money to pay for the upgrades.
So, the three constraints of this problem are 1) should work from inside iframe (I am hoping this will go viral and every blogger would want to embed my site into their page's iframe. 2) should be very fast 3) should minimize load on my server
Use one table City and do a mysql math-calculation for every query, with the addition of a cache layer eg memcache. Fair performance and very flexible!
Use two tables City (id,lat,lng,name) and Distance (city_id1,city_id2,dist), get your result by a traditional JOIN. (Could use a cache layer too.) Not very flexible.
Custom data structure: CityObj (id,lat,lng,data[blob]) just serialize and compress a php-array of the cities and store it. This might rise your eyebrows but as we know the bottleneck is never CPU or memory, it's disc IO. This is one read from an index of an INT as apposed to the JOIN which uses a tmp-table. This is not very flexible but will be fast and scalable. Easy to shard and cluster.
Is it possible to offload all of this to user's browser via some crafty use of Java Script? I don't want to overload my server for a free service. It might make money but I am very close to broke and I am afraid my server would go down before I make enough money to pay for the upgrades.
Yes, it is possible...using Google Maps API and the geometry library. The function you are looking for is google.maps.geometry.spherical.computeDistanceBetween. Here is an example that I made a while ago that might help get you started. I use jQuery here. Take a look at the source to see what's happening and modify as needed. Briefly:
supplierZips is an Array of zip codes comparable to your city whitelist.
The first thing I do on page load is geocode the whitelist locations. You can actually do this ahead of time and cache the results, if your city whitelist is constant. This'll speed up your app.
When the user enters a zip code, I first check if it's a valid zip from a json dataset of all valid zip codes in the U.S.( http://ampersand.no.de/maps/validUSpostalCodes.json, 352 kb, data generated from zip code data at http://www.geonames.org).
If the zip is valid, I compute the location between that zip and each location in the whitelist, using the aforementioned computeDistanceBetween in the Google Maps API.
Hope this helps get you started.
You just have to get the lat and the long of each city and add it to the database.
So every city only has 1 record. No distances are stored on the position on the globe.
Once you have that you can easily do a query with using haversine formula ( http://en.wikipedia.org/wiki/Haversine_formula ) to get the nearest cities within a range.
know there are some cross-domain scripting rules so I am not sure if iFrame would be able to get user-ip address
It will be possible to get the user ip or whatever if you just get the info from the embedded page.
I don't know if a DB would be able to handle so much pounding
If you have that many requests you should have by then found a way to make a buck with it :-) which you can use for upgrades :D
Your algorithm seems generally correct. What I would do is use PostGIS (a postgresql plugin, and easier to set up than it looks :-D). I believe the additional learning curve is totally worth it, it is THE standard for geodata.
If you put the whitelist cities in as POINTs, with latitudes and longitudes, you can actually ask PostGIS to sort by distance to a given lat/lon. It should be much more efficient than doing it yourself (PostGIS is very optimized).
You could get lats and longs of your user cities (and the whitelist cities) by using a geocoding API like Yahoo Placefinder or Google Maps. What I would do would be to have a table (either the same as the whitelist cities or not) that stores city name, lat, and lon, and do lookups on that. If the city name isn't found though, hit the API you are using, and cache the result in the table. This way you'll quickly not need to hit the API except for obscure places. The API is fast too.
If you're really going to be seeing that kind of server load, you may want to look into using something besides PHP though (such as node.js). Incidentally you shouldn't have any trouble geocoding from an iframe, from the Point of View of the server, its just like the browser is going to that page "normally".