internal static IList <ScoringParameter> ToQuery(this IEnumerable <string> parameters, IList <ScoringParameter> query, IEnumerable <PropertyMapping> propertyMappins)
{
if (!parameters.Any())
{
return(query);
}
var newQuery = query.ToList();
foreach (var parameter in parameters)
{
var fi = propertyMappins.FirstOrDefault(pm => ("@" + pm.Property).Equals(parameter));
if (fi == null)
{
throw new Exception($"No mapping defined for parameter {parameter}.");
}
for (var i = 0; i < newQuery.Count; i++)
{
newQuery[i] = new ScoringParameter(newQuery[i].Name.Replace(parameter, fi.IndexField.ToString().ToCamelCase()), newQuery[i].Values);
}
}
return(newQuery);
}
public async Task <DocumentSearchResult> Search([FromUri] string searchText)
{
var credentials = new SearchCredentials(AzureSearchConfig.SearchServiceApiKey);
SearchIndexClient client = new SearchIndexClient(AzureSearchConfig.SearchServiceName
, AzureSearchConfig.SearchIndexName, credentials);
var callersGeoLocation = LocationHelper.GetCallerLocation();
var scoringParam = new ScoringParameter(AzureSearchConfig.GeoScoringParameterName,
$"{callersGeoLocation.Longitude},{callersGeoLocation.Latitude}");
var parameters = new SearchParameters
{
SearchMode = SearchMode.All,
Facets = AzureSearchConfig.SearchIndexFacets,
ScoringProfile = AzureSearchConfig.ScoringProfileName,
ScoringParameters = new[] { scoringParam }
};
return(await client.Documents.SearchAsync(searchText, parameters));
}
public async Task <IEnumerable <PersonModel> > Suspects([FromUri] string searchText)
{
var credentials = new SearchCredentials(AzureSearchConfig.SearchServiceApiKey);
SearchIndexClient client = new SearchIndexClient(AzureSearchConfig.SearchServiceName
, AzureSearchConfig.SearchIndexName, credentials);
var callersGeoLocation = LocationHelper.GetCallerLocation();
var scoringParam = new ScoringParameter(
AzureSearchConfig.GeoScoringParameterName,
new string[] { callersGeoLocation.Longitude.ToString(), callersGeoLocation.Latitude.ToString() });
var parameters = new SearchParameters
{
SearchMode = SearchMode.All,
Facets = AzureSearchConfig.SearchIndexFacets,
ScoringProfile = AzureSearchConfig.ScoringProfileName,
ScoringParameters = new[] { scoringParam },
Top = 10,
Select = new[] { "FirstName", "LastName", "EyeColor", "HairColor", "Sex", "SuspectSearchImage" }
};
DocumentSearchResult searchResult = await client.Documents.SearchAsync(searchText, parameters);
var persons = searchResult.Results.Select(d =>
{
return(new PersonModel
{
Name = d.Document["FirstName"].ToString() + d.Document["LastName"].ToString(),
EyeColor = d.Document["EyeColor"].ToString(),
HairColor = d.Document["HairColor"].ToString(),
Sex = d.Document["Sex"].ToString(),
SuspectSearchImage = d.Document["SuspectSearchImage"].ToString()
});
});
return(persons);
}
private JobSearchResults SearchJobs(JobCriteria searchParms)
{
var credential = new SearchCredentials(AZURE_SEARCH_KEY);
SearchServiceClient serviceClient = new SearchServiceClient(ACURE_SEARCH_SERVICE_NAME, credential);
var indexClient = serviceClient.Indexes.GetClient("denvertechjobs");
var sp = new SearchParameters
{
ScoringProfile = (searchParms.Latituede != 0 && searchParms.Latituede != 0) ? "geo" : "newAndHighlyRated",
IncludeTotalResultCount = true,
SearchMode = SearchMode.All,
//Filter = "trioType eq 'Food'"
};
if (searchParms.Latituede != 0 && searchParms.Latituede != 0)
{
var scoreParam = new ScoringParameter("currentLocation", Microsoft.Spatial.GeographyPoint.Create((double)searchParms.Latituede, (double)searchParms.Longitude));
sp.ScoringParameters = new List <ScoringParameter> {
scoreParam
};
}
var searchText = string.Join('|', searchParms.KeyPhrases) + "+" + string.Join('|', searchParms.Skills) + "+" + searchParms.Profession;
DocumentSearchResult <JobDocument> response = indexClient.Documents.Search <JobDocument>(searchText, sp);
var results = new JobSearchResults {
TotalResults = response.Count
};
if (response.Results.Any())
{
var docs = (from d in response.Results select d.Document).ToList();
results.ResultItems.AddRange(docs);
}
return(results);
}
public async Task <ActionResult> Index(SearchData model)
{
try
{
InitSearch();
int page;
if (model.paging != null && model.paging == "next")
{
// Recover the facet text, and the facet check box settings.
RecoverFacets(model, true);
// Increment the page.
page = (int)TempData["page"] + 1;
// Recover the search text.
model.searchText = TempData["searchfor"].ToString();
}
else
{
// First search with text.
// Recover the facet text, but ignore the check box settings, and use the current model settings.
RecoverFacets(model, false);
// First call. Check for valid text input, and valid scoring profile.
if (model.searchText == null)
{
model.searchText = "";
}
if (model.scoring == null)
{
model.scoring = "Default";
}
page = 0;
}
// Set empty defaults for ordering and scoring parameters.
var orderby = new List <string>();
string profile = "";
var scoringParams = new List <ScoringParameter>();
// Set the ordering based on the user's radio button selection.
switch (model.scoring)
{
case "RatingRenovation":
orderby.Add("Rating desc");
orderby.Add("LastRenovationDate desc");
break;
case "boostAmenities":
{
profile = model.scoring;
var setAmenities = new List <string>();
// Create a string list of amenities that have been clicked.
for (int a = 0; a < model.facetOn.Length; a++)
{
if (model.facetOn[a])
{
setAmenities.Add(model.facetText[a]);
}
}
if (setAmenities.Count > 0)
{
// Only set scoring parameters if there are any.
var sp = new ScoringParameter("amenities", setAmenities);
scoringParams.Add(sp);
}
else
{
// No amenities selected, so set profile back to default.
profile = "";
}
}
break;
case "renovatedAndHighlyRated":
profile = model.scoring;
break;
default:
break;
}
// Setup the search parameters.
var parameters = new SearchParameters
{
// Set the ordering/scoring parameters.
OrderBy = orderby,
ScoringProfile = profile,
ScoringParameters = scoringParams,
// Select the data properties to be returned.
Select = new[] { "HotelName", "Description", "Tags", "Rooms", "Rating", "LastRenovationDate" },
SearchMode = SearchMode.All,
// Skip past results that have already been returned.
Skip = page * GlobalVariables.ResultsPerPage,
// Take only the next page worth of results.
Top = GlobalVariables.ResultsPerPage,
// Include the total number of results.
IncludeTotalResultCount = true,
};
// For efficiency, the search call should be asynchronous, so use SearchAsync rather than Search.
model.resultList = await _indexClient.Documents.SearchAsync <Hotel>(model.searchText, parameters);
// Ensure TempData is stored for the next call.
TempData["page"] = page;
TempData["searchfor"] = model.searchText;
TempData["scoring"] = model.scoring;
SaveFacets(model, true);
// Calculate the room rate ranges.
for (int n = 0; n < model.resultList.Results.Count; n++)
{
var cheapest = 0d;
var expensive = 0d;
for (var r = 0; r < model.resultList.Results[n].Document.Rooms.Length; r++)
{
var rate = model.resultList.Results[n].Document.Rooms[r].BaseRate;
if (rate < cheapest || cheapest == 0)
{
cheapest = (double)rate;
}
if (rate > expensive)
{
expensive = (double)rate;
}
}
model.resultList.Results[n].Document.cheapest = cheapest;
model.resultList.Results[n].Document.expensive = expensive;
}
}
catch
{
return(View("Error", new ErrorViewModel {
RequestId = "1"
}));
}
return(View("Index", model));
}