I just started Kibana TERM Analysis with Elasticsearch. when i Search 'Barak Obama' it shows in TERM Analysis different results like Barak(15),Obama(18) in separate Term. I want in Single Pharse like Barak Obama(30). where should i change in configuration.
Thanks in Advance
You can customize your analyzer to do this with using shingle token filter.
What is an analyzer?
What is shingle token filter?
Related
I want to take a look at the actual terms in an Elasticsearch index. In Solr, I can just open the admin and get a list of the most common terms. Is there an Elasticsearch equivalent of this?
I want to use aggregations over the search result of the knn_search api in elasticsearch (because I need facet search on the user interface), but I cannot pass the agg parameter as in the search api. Any suggestions?
Tldr;
As per the documentation of this endpoint GET /<index>/_knn_search.
You just can not give the parameter agg.
In 8.4
Although in the latest version of elasticsearch, you can use the knn search in the standard search queries.
I'm trying to figure out how elasticsearch analyzers work exactly and I'm using the _analyze api e.g. _analyze?text=http://www.google.com
Does elasticsearch provide the information of which analyzer was used?
Although the information provided is step by step of the analysis performed, some analyzers may produce the same output so instead of trying to force a different output in order to check which analyzer was used, I was wondering if this can be provided by the api.
I'm using ElasticSearch 1.7.5
It will not give you the analyzer being used because it's supposed to be specified either in the command itself with ?analyzer= or using the analyzer from the index or from the field that's being used in the command.
Also, there are rules related to which analyzer is being used and you should be able to determine from these which one is actually applied: https://www.elastic.co/guide/en/elasticsearch/guide/current/_controlling_analysis.html#_default_analyzers
Let's say I have a log of events of ad displays and ad clicks stored via Logstash in Elasticsearch and displayed in Kibana 4. I would like to calculate a simple metric like CTR (Click-Through-Rate) of the events , which is :
CTR = #clicks/#displays.
First of all, does anyone know if it's possible to do in Elasticsearch + Kibana? I don't see a possibility to do it in Kibana.
I was thinking about doing it in raw Elasticsearch by scripted aggregation. But I don't know how to define such in Kibana.
Any ideas on how to do it would be very welcome! Comments explaining that it's impossible to do it would be also valuable.
Kibana 4 includes support for Elasticsearch scripting. You can go to Settings > Indices (pick your pattern) > Scripted Fields and add a new scripted field that computes your CTR. Take a look at "Scripted Fields" at elastic blog for more info.
I had to do something similar for a customer, but couldn't manage to get it done using scripted fields, because I had to sum UP all the values on each aggregation. I ended up developing a custom visualization (Plugin). This was for Kibana 4.1 and 4.5.1.
Let me know if this is what you are looking for, or if you want to give it a go yourself I can give you some pointers.
I want to build elastisearch queries using JAVA API. I want to know how to can use Lucene analyzers in elasticsearch java programs. I have checked QueryBuilders and tried to use analyzers directly as below.
QueryBuilder builder = QueryBuilders.matchQuery(searchString, fields).analyzer("porterstem");
But, it turned out to be wrong. If any one tried it, could you please give me some information?
You should define your analyzer in mapping.
So the analyzer will be used at index time and at query time.
ANALYZERS are used to analyze the documents that your are indexed. Analysis means it Ll split,the text in to tokens, normalize it, and also Lower case your indexed doc text. This analysis process Ll b more helpful while you search and searching will be faster..
You can mention analyzer while you query . But analyze the stored documents during query time. Ll b expensive. So analyze the document during indexing time. ES will analysis the doc during indexed and query time will b less and faster result.
So mention analyzers in mapping and searching efficiently..
For more information about analyzer refer
https://lucene.apache.org/core/4_0_0/core/org/apache/lucene/analysis/Analyzer.html