Queries vs Filters - Order of execution - elasticsearch

I've read this question and a colleague of mine made me doubt:
In a filtered query, when is the filter applied ? Before or after executing the query ? When is the result cached ?
If the filter is applied beforehand, wouldn't it be a a good thing to duplicate the query part in the filters ?
If the filter is applied afterward, then i'm having trouble understanding what is cached.

Luckily, ES provides two types of filters for you to work with:
{
"query" : {
"field" : { "title" : "Catch-22" }
},
"filter" : {
"term" : { "year" : 1961 }
}
}
{
"query": {
"filtered" : {
"query" : {
"field" : { "title" : "Catch-22" }
},
"filter" : {
"term" : { "year" : 1961 }
}
}
}
}
In the first case, filters are applied to all documents found by the query. In the second case, the documents are filtered before the query runs. This yields better performance.
Quoted from: http://www.packtpub.com/elasticsearch-server-for-fast-scalable-flexible-search-solution/book
About cache, I'm not sure about cache mechanism of filters.
My guessing would be:
First case, since the filter is against a set of results returned by query, the cache is kind of specific for this return set.
Second case, the filter is applied first, the cache is stored for the indices you checked against, thus, this cache is more reusable because it does not rely on the content of the query, but at larger memory cost and query time for first time(before the cache is generated).

Let me explain you search query execution-
First thing is that there is always a Complete document of reference in which you want to search.
If you have filter query included with search query then it will just make that document smaller or in other words filter queries are cached results of same query.
Now you have a smaller tree to search from with your query text.
Now your doubt part- Duplicating the query in filters will only increase overhead of cache mechanism and There are many guide lines on what to include in filter query and what to ignore. It's all play of relevancy.

Related

Filter on score after rescore in Elasticsearch

I have been on an internet manhunt for days for this and getting ready to give up. I need to filter on _score in Elasticsearch after the rescore function has completed. So given an example query like this:
POST /_search
{
"query" : {
"match" : {
"message" : {
"operator" : "or",
"query" : "the quick brown"
}
}
},
"rescore" : {
"window_size" : 50,
"query" : {
"rescore_query" : {
"match_phrase" : {
"message" : {
"query" : "the quick brown",
"slop" : 2
}
}
},
"query_weight" : 0.7,
"rescore_query_weight" : 1.2
}
}
}
Say just for simplicity's sake that the above returns 5 documents with scores ranging from 0.0 to 1.0. I want the final returned results set to only be the documents with a score above 0.90. In other words, take those newly-rescored docs, and hand them off to a filter where it drops all documents scored below 0.90.
I have tried many, many different ways but nothing is working. Post_filter is apparently meant to come after the main query but before rescore, so that one doesn't work. min_score does not work at all with rescore, it only works with the original ES scores from the main query. Aggs is one functionality that I am able to get to work after rescore, but aggregating is not what I need to do here. But at least it shows me that ES has the ability to continue operating on the data after a rescore query.
Any thoughts on how to get this seemingly simple task accomplished? I have also tried using function_score and script_score but really those are just ways to further modify the scores, whereas I need to filter on the scores generated by the rescore. The requirement here is to get it done in the query. We can't do it as a post-processing step.

Delete by Query with Sort in Elasticsearch

I want to delete the most current item in my Elasticsearch index sorted by myDateField which is a date type. Is that possible? I want something like this query but this would delete all matching items even though I have the size at 1.
{
"query" : {
"match_all" : {
}
},
"size" : "1",
"sort" : [
{
"myDateField" : {
"order" : "desc"
}
}
]
}
Delete by query is unlikely to support any sorting features.
If you try Delete by query - however you'll get the error: request does not support [sort]. I couldn't find any documentation saying that the "sort" parameter is not supported in delete by query.
I've one idea to do it but don't know it's the best way or not?
Step 1: Do a normal query based on your conditions+sorting and get those ids.
Step 2: Build a bulk query to delete all documents retrieved above by id those you got on Step 1.

ElasticSearch aggregation: exclude one filter per aggregation

I want to filter out documents whose field 'A' is equal to 'a', and I want to facet the field 'A' at the same time, excluding of course the previous filter.
I know that you can put the filter 'outside' the query in order to get the facets without that filter applied, like:
ElasticSearch
{
"query : { "match_all" : { } },
"filter" : { "term : { "A" : "a" } },
"facets" : {
"A" : { "terms" : { "field" : "A" } } //this should exclude the filter A:a
}
}
SOLR
&q=:*:*
&fq={!tag=Aa}A:a
&facet=true&facet.field={!ex=Aa}A
This is very nice, but what happens if i have multiple filters and facets that each one should exclude each other?
Example:
filter=A:a
filter=B:b
filter=C:c
facet={exclude filter A:a}A
facet={exclude filter B:b}B
facet={exclude filter C:c}C
That is, for facet A I want to keep all filters except A:a, for facet B all except B:b, and so on.
The most obvious way would be to do n queries (one per each of the n facets), but I'd like to stay away from that.
The global scope provides access to every document, you can then add the same filters you used for the main query.
I gave an example with global scope in this related topic
Could you give any feedback about performance issue with post_filter ?

elastic search faceted query returns incorrect count

I need help in aggregate / faceted queries in elastic search. I have used faceted query to group the results but I’m not getting grouped result with correct count.
Please suggest on how to get grouped results from elastic search.
{
"query" : {
"query_string" : {"query" : "pared_cat_id:1"} } ,
"facets" : {
"subcategory" : {
"terms" : {
"field": "sub_cat_id",
"size" : 50,
"order" : "term",
"all_terms" : true
}
}
},
"from" : 0,
"size": 50
}
Trying to get grouped results for sub category id for passed parent category id.
"query_string" : {"query" : "pared_cat_id:1"} } ,
This is applied to overall data and not on the facets counts.
FOr this you need to use facet query in which you can specify same which you are specifying in the main query string.
So facets count which are being shown to you now are based on the results without applying "query_string" : {"query" : "pared_cat_id:1"} } , ie. to the whole data. Incase you want facets counts after applying "query_string" : {"query" : "pared_cat_id:1"} } , provide it in the facet query.
Elasticsearch faceting queries works very well in terms of accuracy, at least I have not seen any problem yet.
Just a few questions:
What field is this string or numeric,give example?
Have you applied any custom mapping or you have used default "standard" analyzer
Please state the kind of inaccuracy like "aa" should have count 100 but its 50 or is there any other kind of inaccuracy?
Elasticsearch facets query returns incorrect count if the number of shards is >1, so as for now Facets are deprecated and will be removed in a future release. You are encouraged to migrate to aggregations instead.
I suggest that you take a look at this blog post in which Alex Brasetvik give a good description along with some examples on how to use the aggregations feature properly.

How to perform a date range elasticsearch query given multiple dates per document?

I'm using ElasticSearch to index forum threads and reply posts. Each post has a date field associated with it. I'd like to perform a query that includes a date range which will return threads that contain posts matching a date range. I've looked at using a nested mapping but the docs say the feature is experimental and may lead to inaccurate results.
What's the best way to accomplish this? I'm using the Java API.
You haven't said much about your data structure, but I'm inferring from your question that you have post objects which contain a date field, and presumably a thread_id field, ie some way of identifying which thread a post belongs to?
Do you also have a thread object, or is your thread_id sufficient?
Either way, your stated goal is to return a list of threads which have posts in a particular date range. This means that you need to group your threads (rather than returning the same thread_id multiple times for each post in the date range).
This grouping can be done by using facets.
So the query in JSON would look like this:
curl -XGET 'http://127.0.0.1:9200/posts/post/_search?pretty=1&search_type=count' -d '
{
"facets" : {
"thread_id" : {
"terms" : {
"size" : 20,
"field" : "thread_id"
}
}
},
"query" : {
"filtered" : {
"query" : {
"text" : {
"content" : "any keywords to match"
}
},
"filter" : {
"numeric_range" : {
"date" : {
"lt" : "2011-02-01",
"gte" : "2011-01-01"
}
}
}
}
}
}
'
Note:
I'm using search_type=count because I don't actually want the posts returned, just the thread_ids
I've specified that I want the 20 most frequently encountered thread_ids (size: 20). The default would be 10
I'm using a numeric_range for the date field because dates typically have many distinct values, and the numeric_range filter uses a different approach to the range filter, making it perform better in this situation
If your thread_ids look like how-to-perform-a-date-range-elasticsearch-query then you can use these values directly. But if you have a separate thread object, then you can use the multi-get API to retrieve these
your thread_id field should be mapped as { "index": "not_analyzed" } so that the whole value is treated as a single term, rather than being analyzed into separate terms

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