I am creating a synonym map like below,
{ "name": "country-synonym",
"format":"solr",
"synonyms": "germany, dl, deutschland\n
india, ind"
}
But when I queried the synonym to view it, it was created like below, instead of two rules, only one rule was created.
{
"#odata.context": "https://#############.search.windows.net/$metadata#synonymmaps/$entity",
"#odata.etag": "###########",
"name": "country-synonym",
"format": "solr",
"synonyms": "germany, dl, deutschland india, ind",
"encryptionKey": null
}
What am I doing wrong?
You answered it correctly in your comment. The search is working correctly, meaning the search terms were posted to the API correctly. The problem is the browser collapsing the newline. Try to look at the raw response in the Inspector & you should see the newline.
Related
We are currently running into an issue when expanding our current azure search features.
When we have the following string indexed in azure search:
AEDE190EACWWG4VGLDE02000UHKPT
And we search for that complete string, we are not able to find it.
However, when we only use 20 chars, we are able to find it.
So the with the string below, we are able to find it
AEDE190EACWWG4VGLDE
However, when adding just 1 more char it disappears again. And this is not only within our implementation. This is also in azure itself when entering this within the query string
The field is set up as
Retrievable
Filterable
Searchable
Anyone know how to solve this issue?
I tested your scenario now, and it works fine. I cannot reproduce the problem you have. You don't specify which analyzer you use, so I'm going to assume you use the standard analyzer.
Here is how I tested.
I create a new index with two fields Id and Ordcode.
I upload two records via Postman
"value": [
{
"#search.action": "mergeOrUpload",
"Id": "1",
"Ordcode" : "AEDE190EACWWG4VGLDE02000UHKPT"
},
{
"#search.action": "mergeOrUpload",
"Id": "2",
"Ordcode": "ABC123"
}]
I search for your the string AEDE190EACWWG4VGLDE02000UHKPT using searchMode=all, queryType=full. The response is as expected.
{
"#odata.context": "https://<search-service>.search.windows.net/indexes('dg-test-65143696')/$metadata#docs(*)",
"#odata.count": 1,
"value": [
{
"#search.score": 0.2876821,
"Id": "1",
"Ordcode": "AEDE190EACWWG4VGLDE02000UHKPT"
}
]
}
I also tried to reproduce via the Search Explorer in the Azure Portal, even with simple mode and any (the default).
search=AEDE190EACWWG4VGLDE02000UHKPT&$count=true&$select=Id,Ordcode
There is a limit on the tokens produced (depending on the analyzer you use), but it's not 20 unless you have defined a shorter max token length.
I've written up a quick proof of concept console app to test out the functionality of the AzureSpell Cognitive Services product, however it doesn't seem to often detect obvious spelling mistakes.
Having experimented with recommendations through other SO answers, I've had limited success.
Even using the demo located at https://azure.microsoft.com/en-us/services/cognitive-services/spell-check/ produces no results.
For example, consider the following piece of text: "Currently growing my compny which is a UK based Online compny with clients across the world. Working since 2001 to help indivduals."
This produces no results. I've looked at regional settings, PROOF vs SPELL, character counts to no avail.
Has anyone had any success with this service, or, even better, does the above text snippet produce results for you?
Spell mode is working for me with your sample, see below:
The JSON result is:
{
"_type": "SpellCheck",
"flaggedTokens": [
{
"offset": 21,
"token": "compny",
"type": "UnknownToken",
"suggestions": [
{
"suggestion": "company",
"score": 0.9264452620075305
}
]
},
{
"offset": 55,
"token": "compny",
"type": "UnknownToken",
"suggestions": [
{
"suggestion": "company",
"score": 0.8740149238635179
}
]
},
{
"offset": 120,
"token": "indivduals",
"type": "UnknownToken",
"suggestions": [
{
"suggestion": "individuals",
"score": 0.753968656686115
}
]
}
]
}
Ok, so after a fair amount of trial I've had some success, which has solved some issues and created others. I've not been able to get a reliable result from Spell mode, but I have with Proof, however after adding a fairly short piece of text, it would again not report any results. Inspecting the API shows the text is encoded in the POST, removing both "%0D" and "%0A", line feed chars allows me to Proof long texts with success, which would be fine, however being UK based, lots of correct spellings are now flagged as incorrect as the PROOF mode is only available in the US. So, I've still been unable to solve getting a functioning SPELL result (which works for very short pieces of text). I understand the documentation states upto 130 chars for GET, but 10,000 chars for POST and my typical example POSTS are around 1,000 chars. Possibly a ticket with MS unless anyone has any ideas?
I have the following mongo documents:
[{
"name": "Robert",
"title": "The art of war",
"description": "The art of war in the 20yh century"
},
{
"name": "Claadius",
"title": "The spring is back",
"description": "I love spring and all the seasons"
}
]
On my GET method, I have a query to perform the search on 1 attribute alone, 2 or 3 together. See example: ?name=Robert&title=war&description=spring
How i can implement this?
This is almost exactly what query-to-mongo was meant for! It converts a query like the one you show into a mongo search criteria that can be passed into a mongo find. It handles a bunch of additional search operators (like >= and !=) which is where it gets complicated.
But if you're willing to trust it, here's an example of an express route that performs a find against a collection using a search query:
https://gist.github.com/pbatey/20d99ff772c29146897834d0f44d1c29
The query-to-mongo parser also handles paging into results with offset and limit.
I have some data in solr. I want to search which name is Chinmay Sahu See below I have 3 results in output. But I got 3 instead of 1. Because Content name searched partially.
I want to full search those name having Chinmay Sahu only that contents will come.
Output:
"docs": [
{
"id": "741fde46a654879949473b2cdc577913",
"content_id": "1277",
"name": "Chinmay Sahu",
"_version_": 1596995745829879800
},
{
"id": "4e98d680efaab3afe051f3ddc00dc5f2",
"content_id": "1825",
"name": "Chinmay Panda",
"_version_": 1596995745829879800
}
{
"id": "741fde46a654879949473b2cdc577913",
"content_id": "1259",
"name": "Sasmita Sahu",
"_version_": 1596995745829879800
}
]
Query:
name:Chinmay Sahu
Expected :
"docs": [
{
"id": "741fde46a654879949473b2cdc577913",
"content_id": "1277",
"name": "Chinmay Sahu",
"_version_": 1596995745829879800
},
]
Please help
Try doing this
name:"Chinmay Sahu"
You need to do a phrase query to match the exact name.
I am guessing in your case the name field is using Standard tokenizer which will split tokens if whitespace is there. So while indexing in all the 3 docs there will be a token called "chinmay".
While you search using
name:Chinmay Sahu
Solr will search it like this since if there is no fieldName specified before a token solr automatically searches it in default_field.(however default field is removed from solr 7.3, So it depends on what version of solr are you using.
)
Name:chinmay AND default_field:sahu
So since all the three docs are having chinmay as a token in the index,the query will match all 3 docs.
Now i dont know what your default field is? can you post your solr schema? That way we can explain why you are seeing those 3 docs.
Since root545 already explained that field:foo bar will search for foo in field and bar in the default search field, I'll suggest that it seems like you don't want to concern yourself with the exact Lucene syntax for searching. The edismax query parser is well suited for separating the typed search string from what fields are being searched and whether you want all tokens to match.
The query in that case would be just Chinmay Sahu, while you'd set q.op=AND (all terms must match), defType=edismax (use the edismax query parser) and qf=name (search the name field):
q=Chinmay Sahu&q.op=AND&defType=edismax&qf=name
You can also tune the different phrase parameters to make sure that names with the tokens in the exact same sequence will be boosted higher than those that have them in the opposite sequence (i.e. Sahu Chinmay).
If this is a programmatic search where no user is actually typing in the suggestion, using a phrase search as suggested is the way to go (name:"Chinmay Sahu").
I would suggest using query like
name:(Chinmay Sahu)
And make sure default operator is AND either in settings or query string like q.op=AND
With that approach you can use user input much easier since you don't need to parse it too much.
I'm trying to use Freebase to search for multiple items at a time (using one API call). For example, if I have two items:
Robert Downey, Jr.
The Avengers
I want to query Freebase once and get back results for both items. Basically all I need is the mid for the top 3 or 4 results for both items. I would like to rely on Freebase's search API to provide disambiguation for topics. For example, I'd like to be able to search for "Robert Downey, Jr." with the abbreviation: "RDJ".
This is easy to do when searching one item at a time:
https://www.googleapis.com/freebase/v1/search?query=rdj
Making two calls like this would give me exactly what I'm looking for, but I would like to stay away from making these calls individually.
Reconciliation
I did run across the json-rpc call for reconciliation, and I have tried the following:
Endpoint: https://www.googleapis.com/rpc
POST body:
[
{
"method": "freebase.reconcile",
"apiVersion": "v1",
"params": {
"name": ["RDJ"],
"key": "api_key",
"limit":10
}
},
{
"method": "freebase.reconcile",
"apiVersion": "v1",
"params": {
"name": ["the avengers"],
"key": "api_key",
"limit":10
}
}
]
This works fairly well for Robert Downey, Jr in that I get a result of type /film/actor as I did using the search api. However, for The Avengers, I get a set of results with type /book/book rather than the 2012 film. These results don't seem to be prioritized the same way as the search results.
I tried something similar using json-rpc for a Freebase search method:
{
"method": "freebase.search",
"apiVersion": "v1",
"params": {
"name": ["RDJ"],
"key": "api_key",
"limit":10
}
}
But the "freebase.search" method didn't seem to exist.
One thing to note is that I will not know the expected type of the items I am looking for before hand.
Long story short: I want the exact results the search API provides, but with multiple queries wrapped up into one call.
Am I missing something terribly simple like an OR operator for the search API?? I've been searching for days, but can't seem to find a good solution. I would appreciate any help at all!
Why not just make two calls asynchronously? That would give you the results you need with almost no penalty in latency.
A few relevant facts:
The Reconcile API is still experimental. It's intended for use in reconciling against a type at a minimum and usually scoring using additional property values.
The Search API isn't included in the RPC mechanism because its freeform output doesn't work with the assumptions of the RPC framework. Ditto for the Topic API, although that's not really relevant here.
The Search API has a fairly expressive S-expression language. You don't say if you want the queries scored independently or together, but if you want them ranked jointly, you can use a filter expression like [(any name:rdj name:"The Avengers")]
https://www.googleapis.com/freebase/v1/search?query=&limit=10&filter=%28any%20name:rdj%20name:%22the%20avengers%22%29