Cloudant search with grouping on array-type field - cloudant

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).

Related

MongoDB indexes for Objects inside array

im working on an api and need fast queries for my MongoDB. I have objects like:
{
_id: "123456",
values: [
{
"value": "A",
"begin":0,
"end":1,
},
{
"value": "B",
"begin":1,
"end":2,
},
{
"value": "C",
"begin":3,
"end":7,
}
],
"name": "test"
}
I have about 6k documents in my Database and i want to unwind and group the values so i can count how many different values i have. After the unwind operation i have about 32 million documents.
I tried some variations of the aggregation but everytime its slow. I always need over 20 seconds.
I want to try the indexes but i cant creat and index that makes it any faster. I tried it with the MongoDB Compass app but i think im doing somethink wrong while i create the index.
Hope someone can help me.
Greetings

Include fields other than count in azure facet results?

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.

Why is it possible to get duplicate results from Azure Search when paging?

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.

Get results from Solr facets

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

Solr facet substring search

Imagine I have the following facets:
Speakers: [Mike Thompson, Thomas Wilkinson, Sally Jeffers]
Venues: [Weill Thomas Medical Center, BB&R Medical Associates, KLR Thompson]
Solr seems to allow a &facet.prefix=Thom where I can get the facets that START with "Thom" and that will return "Speaker: Thomas Wilkinson" but no others.
How can I do the equivalent of &facet.substring=Thom which will return Mike Thompson and Weill Thomas....
I tried &facet.query=Thom but that doesnt seem to work at all.
Thanks
It is not possible to be sure as you did not provide your full query string, but it may be that the facet is not returning Weill Thomas in facet results because you are only specifying facet.field=speakers in your query, and Weill Thomas is actually in the venues field. You would require second facet.field=venues parameter in your search query to retrieve those.
Facet prefix is only used to filter results once the search is already done, so don't use that parameter for searching purposes. Check this question: SOLR facet search by prefix with results highlighting
Edit based on comment:
You don't necessarily need to filter results returned by faceting after the fact, just make sure that only the facets you want match the original query. The facets that were not part of the search query will have 0 occurances on them if you return all facets. You can then set facet.mincount=1 to only get facets that are found within the search results. Here's an example that I mocked up with test data:
q=*Thom*&rows=0&df=speakers&wt=json&indent=true&facet=true&facet.field=speakers&facet.field=venues&facet.mincount=1&json.nl=map
And the response from Solr:
"responseHeader": {
"status": 0,
"QTime": 3,
"params": {
"q": "*Thom*",
"df": "speakers",
"facet.field": [
"speakers",
"venues"
],
"json.nl": "map",
"indent": "true",
"facet.mincount": "1",
"rows": "0",
"wt": "json",
"facet": "true",
"_": "1431772681445"
}
},
"response": {
"numFound": 2,
"start": 0,
"docs": []
},
"facet_counts": {
"facet_queries": {},
"facet_fields": {
"speakers": {
"Mark Thomas": 1,
"Thomas Moore": 1
},
"venues": {
"Weill Thomas": 1
}
},
"facet_dates": {},
"facet_ranges": {},
"facet_intervals": {},
"facet_heatmaps": {}
}
Just wanted to point out a caveat of the proposed solution (i.e. which is to basically just do your facet substring query as the main Solr query, and then the facet values will be what you want). This won't work correctly for multi-valued fields. For example, if a document had 3 values for speaker of "Mark Thomas", "Fred Jones", "John Doe", then the query 'q=*Thom*' would return as facets "Fred Jones" and "John Doe", in addition to "Mark Thomas", and this would not be the desired result (i.e. "Fred Jones" and "John Doe" should not be returned). So for single-valued fields this solution could work, but for multi-valued fields you would probably have to write an intermediary web service that would filter out the non-matches (like "Fred Jones" and "John Doe"). Solr should really add a facet.substring parameter that would work like the facet.prefix parameter, but do substring filtering on the facet values instead of prefix filtering.

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