Is there any way when I am searching products for one category just for facets alone. In this call I want to avoid result array Example :
{
"limit": 20,
"offset": 0,
"count": 20,
"total": 24,
"results": [],
"facets":{
"variants.attributes.productStyle.en-GB": {
}
}
There can be 20 products, but I need only facets results alone to avoid huge data coming to service. If there is any query It would be great.
Yes, for getting no products returned set the limit parameter to 0 in your API request.
Related
While faceting azure search returns the count for each facet field by default.How do I also get other searchable fields for every facet?
Ex When I facet for area , I want something like this.(description is a searchable field)
{
"area": [
{
"count": 1,
"description": "Acrylics",
"value": "ACR"
},
{
"count": 1,
"description": "Power",
"value": "POW"
}
]
}
Can someone please help with the extra parameters I need to send in the query?
Unfortunately there is no good way to do this as there is no direct support for nested faceting in Azure search (you can upvote it here). To achieve the result you want you would need to store the data together as a composite value as described by this workaround.
Sometimes when using Azure Search's paging there may be duplicate documents in the results. Here is an example of a paging request:
GET /indexes/myindex/docs?search=*$top=15&$skip=15&$orderby=rating desc
Why is this possible? How can it happen? Are there any consistency guarantees when paging?
The results of paginated queries are not guaranteed to be stable if the underlying index is changing, or if you are relying on sorting by relevance score. Paging simply changes the value of $skip for each page, but each query is independent and operates on the current view of the data (i.e. – there is no snapshotting or other consistency mechanism like you’d find in a general-purpose database).
Here is an example of how you might get duplicates. Assume an index with four documents:
{ "id": "1", "rating": 5 }
{ "id": "2", "rating": 3 }
{ "id": "3", "rating": 2 }
{ "id": "4", "rating": 1 }
Now assume you want to page through the results with a page size of two, ordered by rating. You’d execute this query to get the first page:
$top=2&$skip=0&$orderby=rating desc
And get these results:
{ "id": "1", "rating": 5 }
{ "id": "2", "rating": 3 }
Now you insert a fifth document into the index:
{ "id": "5", "rating": 4 }
Shortly thereafter, you execute a query to fetch the second page of results:
$top=2&$skip=2&$orderby=rating desc
And get these results:
{ "id": "2", "rating": 3 }
{ "id": "3", "rating": 2 }
Notice that you’ve fetched document 2 twice. This is because the new document 5 has a greater value for rating, so it sorts before document 2 and lands on the first page.
In situations where you're relying on document score (either you don't use $orderby or you're using $orderby=search.score()), paging can return duplicate results because each query might be handled by a different replica, and that replica may have different term and document frequency statistics -- enough to change the relative ordering of documents at page boundaries.
For these reasons, it’s important to think of Azure Search as a search engine (because it is), and not a general-purpose database.
I have a database with documents like these:
{_id: "1", module:["m1"]}
{_id: "2", module:["m1", "m2"]}
{_id: "3", module:["m3"]}
There is an search index created for these documents with the following index function:
function (doc) {
doc.module && doc.module.forEach &&
doc.module.forEach(function(module){
index("module", module, {"store":true, "facet": true});
});
}
The index uses "keyword" analyzer on module field.
The sample data is quite small (11 documents, 3 different module values)
I have two issues with queries that are using group_field=module parameter:
Not all groups are returned. I get 2 out of 3 groups that I expect. Seems like if a document with ["m1", "m2"] is returned in the "m1" group, but there is no "m2" group. When I use counts=["modules"] I get complete lists of distinct values.
I'd like to be able to get something like:
{
"total_rows": 3,
"groups": [
{ "by": "m1",
"total_rows": 1,
"rows": [ {_id: "1", module: "m1"},
{_id: "2", module: "m2"}
]
},
{ "by": "m2",
"total_rows": 1,
"rows": [ {_id: "2", module: "m2"} ]
},
....
]
}
When using group_field, bookmark is not returned, so there is no way to get the next chunk of the data beyond 200 groups or 200 rows in a group.
Cloudant Search is based on Apache Lucene, and hence has its properties/limitations.
One limitation of grouping is that "the group field must be a single-valued indexed field" (Lucene Grouping), hence a document can be only in one group.
Another limitation/property of grouping is that topNGroups and maxDocsPerGroup need to be provided in advance, and in Cloudant case the max numbers are 200 and 200 (they can be set lower by using group_limit and limit parameters).
I am pretty new to Solr, so I don't know if what I'd like to achieve is actually feasible or not.
Currently, I am querying my Solr to retrieve the amount of results that match the conditions in several facet queries.
For example:
localhost:8082/solr/dict/select?q=*:*&rows=0&wt=json&indent=true&facet=true&facet.query=dict1:"#tiger#"&facet.query=dict1:"#lion#"
With this kind of query, I am getting the count of Solr docs containing "tiger" and the count of those cointaining "lion", in field "dict1":
{
"responseHeader": {
"status": 0,
"QTime": 239,
"params": {
"facet.query": [
"dict1:\"#tiger#\"",
"dict1:\"#lion#\""
],
"q": "*:*",
"indent": "true",
"rows": "0",
"wt": "json",
"facet": "true"
}
},
"response": {
"numFound": 37278987,
"start": 0,
"docs": [ ]
},
"facet_counts": {
"facet_queries": {
"dict1:\"#tiger#\"": 6,
"dict1:\"#lion#\"": 10
},
[...]
}
}
The thing is that now I need to get also some results for each facet, aside as the count (for example, three results for "tiger" and three more for "lion")
I have read some similar questions (Solr Facetting - Showing First 10 results and Other or SOLR - Querying Facets, return N results per Facet ) , but none of their answers seems to work for me, maybe because I am doing the facets on all docs (q=*:*).
Any help will be welcome :)
As per mailing list, what about simply using grouping ?
solr/hotels/search?q=*%3A*&wt=json&indent=true&group=true&group.query=query1&group.query=query2&group.limit=3 [1]
Is this ok for you? This returns 2 groups (1 per query) with the related count and max number of documents.
[1] https://cwiki.apache.org/confluence/display/solr/Result+Grouping
I have a non trivial SOLR query, which already involves a filter query and facet calculations over multiple fields. One of the facet fields is a a multi value integer field, that is used to store categories. There are many possible categories and new ones are created dynamically, so using multiple fields is not an option.
What I want to do, is to restrict facet calculation over this field to a certain set of integers (= categories). So for example I want to calculate facets of this field, but only taking categories 3,7,9 and 15 into account. All other values in that field should be ignored.
How do I do that? Is there some build in functionality which can be used to solve this? Or do I have to write a custom search component?
The parameter can be defined for each field specified by the facet.field parameter – you can do it, by adding a parameter like this: facet.field_name.prefix.
I don't know about any way to define the facet base that should be different from the result, but one can use the facet.query to explicitly define each facet filter, e.g.:
facet.query={!key=3}category:3&facet.query={!key=7}category:7&facet.query={!key=9}category:9&facet.query={!key=15}category:15
Given the solr schema/data from this gist, the results will have something like this:
"facet_counts": {
"facet_queries": {
"3": 1,
"7": 1,
"9": 0,
"15": 0
},
"facet_fields": {
"category": [
"2",
2,
"1",
1,
"3",
1,
"7",
1,
"8",
1
]
},
"facet_dates": {},
"facet_ranges": {}
}
Thus giving the needed facet result.
I have some doubts about performance here(especially when there will be more than 4 categories and if the initial query is returning a lot of results), so it is better to do some benchmarking, before using this in production.
Not exactly the answer to my own question, but the solution we are using now: The numbers I want to filter on, build distinct groups. So we can prefix the id with a group id like this:
1.3
1.8
1.9
2.4
2.5
2.11
...
Having the data like this in SOLR, we can use facted prefixes to facet only over a single group: http://wiki.apache.org/solr/SimpleFacetParameters#facet.prefix