I'm currently using the elasticsearch 6.5.4 and I'm trying to query for all docs in an index with an empty array on a specific field. I found the the elasticsearch has a exists dsl who is supposed to cover the empty array case.
The problem is: whem I query for a must exists no doc is returned and when I query for must not exists all documents are returned.
Since I can't share the actual mapping for legal reasons, this is the closest I can give you:
{
"foo_production" : {
"mappings" : {
"foo" : {
"properties" : {
"bar" : {
"type" : "text",
"index" : false
}
}
}
}
}
}
And the query I am performing is:
GET foo_production/_search
{
"query": {
"bool": {
"must": {
"exists": {
"field": "bar"
}
}
}
}
}
Can you guys tell me where the problem is?
Note: Upgrading the elasticsearch version is not a viable solution
Enable indexing for the field bar by setting "index" : true
The index option controls whether field values are indexed. It accepts true or false and defaults to true. Fields that are not indexed are not queryable.
Source : https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-index.html
Related
I want to retrieve all the JSON objects in Elasticsearch that have a null value for awsKafkaTimestamp. This is the query I have set up:
{
"query": {
"bool": {
"must_not": {
"exists": {
"field": "tracer.awsKafkaTimestamp"
}
}
}
}
}
When I curl to my elasticsearch endpoint with the DSL I only get a few values back. I am expecting all (10000+) of them because I know for sure all the awsKafkaTimestamp values are null
This is the response I get when I use Postman. As you can see, there are only 10 JSON objects returned to me:
It's correct behaviour of the elasticsearch. By default, it only returns 10 records and provides information in hits.total field about the total number of documents matching search criteria. To retrieve more data than 10 you should specify size field in your query as shown below (you can read more about it here: https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-from-size.html):
{
"from" : 0, "size" : 10,
"query" : {
"term" : { "user" : "kimchy" }
}
}
By default elasticsearch will give you 10 results, even if it matches to 10212. You can set the size parameter but that is limited to 10000, so your only option is to use the scroll API to get,
Example from elasticsearch site Scroll API
curl -XGET 'localhost:9200/twitter/tweet/_search?scroll=1m' -d '
{
"query": {
"match" : {
"title" : "elasticsearch"
}
}
}
'
For my project, I thought of using Span Near Queries of ElasticSearch, with the constraint that is, certain tokens may have to searched with Fuzziness. I was able to generate a set of SpanQuery (org.apache.lucene.search.spans.SpanQuery) objects some with fuzzy enabled, some without. I couldn't figure out how to use these set of SpanQueries in ElasticSearch spanNearQuery.
Can someone help me out with right pointers to samples or docs. And is there any way to construct ES SpanNearQueryBuilder with some clauses fuzzy enabled ?
You can wrap an fuzzy query into a span query with Span Multi Term Query:
{
"span_near" : {
"clauses" : [
{ "span_term" : { "field" : "value1" } },
{ "span_multi" :
"match" : {
"prefix" : { "user" : { "field" : "value2" } }
}
}
],
...
}
}
My document has the following mapping property:
"sid" : {"type" : "long", "store": "yes", "index": "no"},
This property has only one value for each record. I would like to query this property. I tried the following queries:
{
"query" : {
"term" : {
"sid" : 10
}
}
}
{
"query" : {
"match" : {
"sid" : 10
}
}
}
However, I got no results. I do have a document with sid being euqal to 10. Anything I did is wrong? I would like to query this property for exact match.
Thanks and regards.
Quote from the documentation:
index: Set to analyzed for the field to be indexed and searchable after being
broken down into token using an analyzer. not_analyzed means that its
still searchable, but does not go through any analysis process or
broken down into tokens. no means that it won’t be searchable at all
(as an individual field; it may still be included in _all). Setting to
no disables include_in_all. Defaults to analyzed.
So, by setting index to no you cannot search by that field individually. So, you either need to remove no from index and choose something else or you can use "include_in_all":"yes" and use a different type of query:
"query": {
"match": {
"_all": 10
}
}
I'm using Elasticsearch and Nest to create a query for documents within a specific time range as well as doing some filter facets. The query looks like this:
{
"facets": {
"notfound": {
"query": {
"term": {
"statusCode": {
"value": 404
}
}
}
}
},
"filter": {
"bool": {
"must": [
{
"range": {
"time": {
"from": "2014-04-05T05:25:37",
"to": "2014-04-07T05:25:37"
}
}
}
]
}
}
}
In the specific case, the total hits of the search is 21 documents, which fits the documents within that time range in Elasticsearch. But the "notfound" facet returns 38, which fits the total number of ErrorDocuments with a StatusCode value of 404.
As I understand the documentation, facets collects data from withing the search. In this case, the "notfound" facet should never be able to return a count higher that 21.
What am I doing wrong here?
There's a distinct difference between filter/query/filtered_query/facet filter which is good to know.
Top level filter
{
filter: {}
}
This acts as a post-filter, meaning it will filter the results after the query phase has ended. Since facets are part of the query phase filters do not influence the documents that are facetted over. Filters do not alter score and are therefor very cacheable.
Top level query
{
query: {}
}
Queries influence the score of a document and are therefor less cacheable than filters. Queries run in the query phase and thus also influence the documents that are facetted over.
Filtered query
{
query: {
filtered: {
filter: {}
query: {}
}
}
}
This allows you to run filters in the query phase taking advantage of their better cacheability and have them influence the documents that are facetted over.
Facet filter
"facets" : {
"<FACET NAME>" : {
"<FACET TYPE>" : {
...
},
"facet_filter" : {
"term" : { "user" : "kimchy"}
}
}
}
this allows you to apply a filter to the documents that the facet is run over. Remember that the it'll be a combination of the queryphase/facetfilter unless you also specify global:true on the facet as well.
Query Facet/Filter Facet
{
"facets" : {
"wow_facet" : {
"query" : {
"term" : { "tag" : "wow" }
}
}
}
}
Which is the one that #thomasardal is using in this case which is perfectly fine, it's a facet type which returns a single value: the query hit count.
The fact that your Query Facet returns 38 and not 21 is because you use a filter for your time range.
You can fix this by either doing the filter in a filtered_query in the query phase or apply a facet filter(not a filter_facet) to your query_facet although because filters are cached better you better use facet filter inside you filter facet.
Confusingly Filter Facets are specified using .FacetFilter() on the search object. I will change this in 1.0 to avoid future confusion.
Sadly: .FacetFilter() and .FacetQuery() in NEST do not allow you to specify a facet filter like you can with other facets:
var results = typedClient.Search<object>(s => s
.FacetTerm(ft=>ft
.OnField("myfield")
.FacetFilter(f=>f.Term("filter_facet_on_this_field", "value"))
)
);
You issue here is that you are performing a Filter Facet and not a normal facet on your query (which will follow the restrictions applied via the query filter). In the JSON, the issue is because of the "query" between the facet name "notfound" and the "terms" entry. This is telling Elasticsearch to run this as a separate query and facet on the results of this separate query and not your main query with the date range filter. So your JSON should look like the following:
{
"facets": {
"notfound": {
"term": {
"statusCode": {
"value": 404
}
}
}
},
"filter": {
"bool": {
"must": [
{
"range": {
"time": {
"from": "2014-04-05T05:25:37",
"to": "2014-04-07T05:25:37"
}
}
}
]
}
}
}
Since I see you have this tagged with NEST as well, in your call using NEST, you are probably using FacetFilter on your search request, switch this to just Facet to get the desired result.
I want to create an alias on top of this. Index - test, Type - type
POST /test/type/_search
{
"query": {
"match": {
"brand_name": "xyz"
}
}
}
But I don't see anyway of doing it,since Elasticsearch aliases can only be created on filters and when I try with term filter,I don't get the results which I want.Any trick to achieve this ?
You can use a query filter to use any query as a filter:
"filter" : {
"query" : {
"match" : {
"brand_name" : "xyz"
}
}
}