private static void BenchmarkSearch(ISpatialIndex index, int rounds)
{
var query = new KnnQuery
{
Coordinate = new GeoCoordinate(52.3667, 4.900),
MaxDistance = 10000,
MaxResults = 15
};
Console.Write("Searching top {0} within {1} m from [{2}] .. ", query.MaxResults, query.MaxDistance, query.Coordinate);
var total = 0L;
var timer = new Stopwatch();
for (int i = rounds; i > 0; i--)
{
timer.Restart();
index.KnnSearch(query);
timer.Stop();
total += timer.ElapsedMilliseconds;
}
Console.WriteLine("ok ({0} ms)", total / rounds);
}
private bool IsQueryValid(KnnQuery query)
{
// Coordinates are required
if (query.Coordinate == null)
{
return(false);
}
// Max results should be greater than zero
if (query.MaxResults <= 0)
{
return(false);
}
// Max distance should be greater than zeo
if (query.MaxDistance <= 0)
{
return(false);
}
// Other validation rules
// Max distance shouldn't be greater than ... setttings..
return(true);
}
private KnnQueryResult InternalKnnSearch(KnnQuery query)
{
// get search area
var searchArea = GetSearchArea(query);
// query the quadtree
var docs = _quadTree.Search(searchArea);
// almost done, but remember we searched a rectangle
// so we need to exclude some of these results.
// Let's do that while calculating the distance
var results = new List <KnnQueryResultItem>();
foreach (var doc in docs)
{
var distance = query.Coordinate.CalculateDistance(doc.Coordinates);
if (distance <= query.MaxDistance)
{
results.Add(new KnnQueryResultItem(doc, distance));
}
}
// this could be done more efficiently by inserting into an ordered structure
// unfortunatelly SortedList<> doesn't allow duplicated keys.
// but there is definetely space for optimization here
results.Sort((x, y) => x.Distance.CompareTo(y.Distance));
// reduce set to max results
results = results.Take(query.MaxResults).ToList();
return(KnnQueryResult.Success(results));
}
public KnnQueryResult KnnSearch(KnnQuery query)
{
var search =
from doc in _docs
let distance = query.Coordinate.CalculateDistance(doc.Coordinates)
where distance <= query.MaxDistance
orderby distance
select new KnnQueryResultItem(doc, distance);
// list results taking top max
var results = search.Take(query.MaxResults).ToList();
return(KnnQueryResult.Success(results));
}
private Boundary GetSearchArea(KnnQuery query)
{
var top = query.Coordinate.Add(query.MaxDistance, 0);
var bottom = query.Coordinate.Add(-query.MaxDistance, 0);
var right = query.Coordinate.Add(0, query.MaxDistance);
var left = query.Coordinate.Add(0, -query.MaxDistance);
var halfLatitude = (top.Latitude - bottom.Latitude) / 2;
var halfLongitude = (right.Longitude - left.Longitude) / 2;
var center = new Point(left.Longitude + halfLongitude, bottom.Latitude + halfLatitude);
var searchArea = new Boundary(center, halfLongitude, halfLatitude);
// TODO: consider borders. search might need to be split into two.
return(searchArea);
}
public KnnQueryResult KnnSearch(KnnQuery query)
{
if (query == null)
{
throw new ArgumentException("Parameter query cannot be null");
}
// validate query
if (!IsQueryValid(query))
{
return(KnnQueryResult.Fail("Query is not valid. Please verify search parameters"));
}
// execute search
var result = InternalKnnSearch(query);
return(result);
}
public LocationSearchResults Search(LocationSearchRequest search)
{
// TODO: validate search parameter
var query = new KnnQuery
{
Coordinate = search.Coordinate,
MaxDistance = search.MaxDistance,
MaxResults = search.MaxResults
};
// use spatial index to reduce data set
var knnQueryResult = _spatialIndex.KnnSearch(query);
if (!knnQueryResult.Results.Any())
{
return(LocationSearchResults.ZeroResults());
}
// now load entities from database
var ids = knnQueryResult.Results.Select(i => i.Document.Id).ToArray();
var locations = _locationRepository.FindIn(ids);
// build return results by joining Location and Distance
var results = new List <LocationSearchResultItem>();
var locationsIndex = locations.ToDictionary(l => l.Id);
foreach (var item in knnQueryResult.Results)
{
if (locationsIndex.ContainsKey(item.Document.Id))
{
var location = locationsIndex[item.Document.Id];
results.Add(new LocationSearchResultItem(location, item.Distance));
}
}
return(LocationSearchResults.Success(results));
}
public KnnQueryResult KnnSearch(KnnQuery query)
{
return(KnnQueryResult.ZeroResults());
}
