I have a query that returns nothing:
r.db('dashboard').table('phases').getAll("f9fd6d4a-1e02-3736-9efb-9b8e06db0977")
If I add an index, then I get results. Here is an example:
r.db('dashboard').table('phases').getAll("f9fd6d4a-1e02-3736-9efb-9b8e06db0977", {
index: 'drillId'
})
When I add an index, what changes in the query to give me results? I would expect the index to just speed up the query.
If you don't specify an index, by default it searches in the id index. So if that f9...77 is a drillId and not an id, it'll returns nothing at best, another document at worst.
Related
I am needing to do a query in Elasticsearch by field data type. I have not been successful in creating that query. I want to be able to {1) specify the type I want to search for in the query, i.e. all fields of {"type"="boolean"}, and also, (2) get the field and see what the type is for that field.
Reason is to check that the field is designated correctly. Let's say I inserted the following data into this index and fields and I now want to see what the data types of those fields are programmatically. How would I query that?
POST /index_name1/_doc/
{
"field1":"hello_field_2",
"field2":"123456.54321",
"field3.field4": false,
"field3.field5.field10":"POINT(-117.918976 33.812511)",
"field3.field5.field8": "field_of_dragons",
"field3.field5.field9": "2022-05-26T07:47:26.133275Z"
}
I have tried:
GET /index_name1/_search
{
"query":{
"wildcard":{
"field3.field4":{ "type":"*"}
}
}
}
That gives [wildcard] query does not support [type].
I've tried many other queries and searched the documentation and threads, but can't find anything that will do this. It has got to be possible, right?
I am having Elasticsearch index with multi-millions of documents. I am running a following search query.
POST testIndex/_search?size=200
{
"query": {
"query_string": {
"query": "(title:QA Manager OR title:QA Lead) AND (skills:JIRA OR skills:Software Development OR skills:Test Case)"
}
}
}
Even if we have passed the limit with size=200, it seems Elasticsearch is doing ranking for all the matching documents and bringing the top 200 with the highest rank.
Is there a way we can limit ranking? meaning do ranking on max 1000 matching documents only?
ES will consider your all data for search and ranking that is how Elasticsearch work. What basically do is, It executes your query in 2 phases, one is query and the second is fetch.
In Query Phase, it executes your query in all shades and get document id and score from each shard and return to requesting node. So in your scenario as size is set to 200, it will get 200 documents id from each shard and return to requesting node.
On requesting node, all the document id and score are merged and sorted based on score and select top document based on size param.
In Fetch phase, the actual docs are retrieved from individual shards where they reside based on ID which are selected in Query Phase and Results are returned to the client.
If you don't want to calculate score for some of your query, then you can move that query to the filter clause in bool query.
I've been working with Elasticsearch for some days. As i'm creating a CRUD, I've come across the updateByQuery method. I'm working with nestjs, and the way that I'm updating a field is:
await this.elasticSearch.updateByQuery(
{
index: 'my_index_user',
body:{
query:{
match:{
name: 'user_name',
}
},
script: {
inline : 'ctx._source.name = "new_user_name"'
}
}
}
);
My question is:
Why does elasticsearch need this syntax 'ctx._source.name = "new_user_name"' to specifie what the new value of the field name should be? What is ctx._source is this context?
As mentioned in the official doc of source filtering, using this you can fetch field value in the _source (Value which sent to Elasticsearch and this is stored as it is, and doesn't go through the analysis process).
Let's take an example of text field for which standard analyzer(Default) is applied, and you store the value of foo bar in this field, Elasticsearch
breaks the value of field as it goes through the analysis process and foo and bar two tokens are stored in the inverted index of Elasticsearch, but if you want to see the original value ie foo bar, you can check the _source and get it.
Hence, it's always better to have the original value(without analysis process) to be in the _source, hence using this API, you are updating the field value there.. this also helps when you want to reindex later to new index or change the way its analyzed as you have the original value in _source.
How to make elasticsearch return 0 hits if query string from user has a word thats missing/unknown in indices?
you could change the default_operator if your query to AND, see the documentation about the query string query
My ElasticSearch 2.x NEST query string search contains a wildcard:
Using NEST in C#:
var results = _client.Search<IEntity>(s => s
.Index(Indices.AllIndices)
.AllTypes()
.Query(qs => qs
.QueryString(qsq => qsq.Query("Micro*")))
.From(pageNumber)
.Size(pageSize));
Comes up with something like this:
$ curl -XGET 'http://localhost:9200/_all/_search?q=Micro*'
This code was derived from the ElasticSearch page on using Co-variants. The results are co-variant; they are of mixed type coming from multiple indices. The problem I am having is that all of the hits come back with a score of 1.
This is regardless of type or boosting. Can I boost by type or, alternatively, is there a way to reveal or "explain" the search result so I can order by score?
Multi term queries like wildcard query are given a constant score equal to the boosting by default. You can change this behaviour using .Rewrite().
var results = client.Search<IEntity>(s => s
.Index(Indices.AllIndices)
.AllTypes()
.Query(qs => qs
.QueryString(qsq => qsq
.Query("Micro*")
.Rewrite(RewriteMultiTerm.ScoringBoolean)
)
)
.From(pageNumber)
.Size(pageSize)
);
With RewriteMultiTerm.ScoringBoolean, the rewrite method first translates each term into a should clause in a bool query and keeps the scores as computed by the query.
Note that this can be CPU intensive and there is a default limit of 1024 bool query clauses that can be easily hit for a large document corpus; running your query on the complete StackOverflow data set (questions, answers and users) for example, hits the clause limit for questions. You may want to analyze some text with an analyzer that uses an edgengram token filter.
Wildcard searches will always return a score of 1.
You can boost by a particular type. See this:
How to boost index type in elasticsearch?