In the simplest search, you can provide only one parameter, the text you want to match in any part of the location details. To do this, build a query where the `text` parameter is set to the item you want to find.
For example, if you want to find a [YMCA](https://en.wikipedia.org/wiki/YMCA) facility, here's what you'd need to append to the base URL of the service, `search.mapzen.com`.
Clicking the link above will open a file containing the best matching results for the text `YMCA`. You will notice the data is in a computer-friendly format called [GeoJSON](http://geojson.org/), which may be hard for humans to read in some browsers.
You can install a plug-in for your browser to display JSON in a more formatted manner. You can search the web store for your browser to find and install applicable products.
In the example above, you will find the name of each matched locations in a property named `'label'`. The top 10 labels returned at the time of writing were:
Spelling matters, but not capitalization when performing a query with Pelias. You can type `ymca`, `YMCA`, or even `yMcA`. See for yourself by comparing the results of the earlier search to the following:
Note that the results are spread out throughout the world because you have not given your current location or provided any other geographic context in which to search.
With the `text` parameter, your search is composed of all the items in one string. With [structured geocoding](structured-geocoding.md), you can search for individual components of a location.
By default, Pelias results up to 10 places, unless otherwise specified. If you want a different number of results, set the `size` parameter to the desired number. This example shows returning only the first result.
If you are looking for places in a particular region, or country, or only want to look in the immediate vicinity of a user with a known location, you can narrow your search to an area. There are different ways of including a region in your query. Pelias supports three types: country, rectangle, and circle.
Sometimes your work might require that all the search results be from a particular country. To do this, you can set the `boundary.country` parameter value to the alpha-2 or alpha-3 [ISO-3166 country code](https://en.wikipedia.org/wiki/ISO_3166-1).
Now, you want to search for YMCA again, but this time only in Great Britain. To do this, you will need to know that the alpha-3 code for Great Britain is GBR and set the parameters like this:
To specify the boundary using a rectangle, you need latitude, longitude coordinates for two diagonals of the bounding box (the minimum and the maximum latitude, longitude).
For example, to find a YMCA within the state of Texas, you can set the `boundary.rect.*` parameter to values representing the bounding box around Texas: min_lon=-106.65 min_lat=25.84 max_lon=-93.51 max_lat=36.5
Sometimes you don't have a rectangle to work with, but rather you have a point on earth—for example, your location coordinates—and a maximum distance within which acceptable results can be located.
In this example, you want to find all YMCA locations within a 35-kilometer radius of a location in Ontario, Canada. This time, you can use the `boundary.circle.*` parameter group, where `boundary.circle.lat` and `boundary.circle.lon` is your location in Ontario and `boundary.circle.radius` is the acceptable distance from that location. Note that the `boundary.circle.radius` parameter is always specified in kilometers.
If you're going to try using multiple boundary types in a single search request, be aware that the results will come from the intersection of all the boundaries. So, if you provide regions that don't overlap, you'll be looking at an empty set of results.
Many use cases call for the ability to promote nearby results to the top of the list, while still allowing important matches from farther away to be visible. Pelias allows you to prioritize results within geographic boundaries, including around a point, within a country, or within a region.
By specifying a `focus.point`, nearby places will be scored higher depending on how close they are to the `focus.point` so that places with higher scores will appear higher in the results list. The effect of this scoring boost diminishes to zero after 100 kilometers away from the `focus.point`. After all the nearby results have been found, additional results will come from the rest of the world, without any further location-based prioritization.
Looking at the results, you can see that the few locations closer to this location show up at the top of the list, sorted by distance. You also still get back a significant amount of remote locations, for a well balanced mix. Because you provided a focus point, Pelias can compute distance from that point for each resulting feature.
Going back to the YMCA search you conducted with a focus around a point in Sydney, the results came back from distant parts of the world, as expected. But say you wanted to only see results from the country in which your focus point lies. You can combine that same focus point in Sydney with the country boundary of Australia like this.
The results below look different from the ones you saw before with only a focus point specified. These results are all from within Australia. You'll note the closest results show up at the top of the list, which is helped by the focus parameter.
If you are looking for the nearest YMCA locations, and are willing to travel no farther than 50 kilometers from your current location, you likely would want the results to be sorted by distance from current location to make your selection process easier. You can get this behavior by using `focus.point` in combination with `boundary.circle.*`. You can use the `focus.point.*` values as the `boundary.circle.lat` and `boundary.circle.lon`, and add the required `boundary.circle.radius` value in kilometers.
Pelias brings together data from multiple open sources and combines a variety of place types into a single database, allowing you options for selecting the dataset you want to search.
If you use the `sources` parameter, you can choose which of these data sources to include in your search. So if you're only interested in finding a YMCA in data from OpenAddresses, for example, you can build a query specifying that data source.
If you wanted to combine several data sources together, set `sources` to a comma separated list of desired source names. Note that the order of the comma separated values does not impact sorting order of the results; they are still sorted based on the linguistic match quality to `text` and distance from `focus`, if you specified one.
In Pelias, place types are referred to as `layers`, ranging from fine to coarse. The Pelias layers are derived from the hierarchy created by the gazetteer [Who's on First](https://github.com/whosonfirst/whosonfirst-placetypes/blob/master/README.md) and can be used to help coarse geocoding. Here's a list of the types of places you could find in the results, sorted by granularity:
