elasticsearch wildcard field

work exactly the same way as prefix queries. They also need to traverse the list of entries in the inverted index to find all the matching entries, and then collect the corresponding document IDs on a per-entry basis. The only difference between them and prefix queries is that they can support more complex schemas.This also means that there is the same risk of using them. It is very resource-intensive to run such queries on a field that contains many

That's the thing. Before doing a mongodb search, do a good job to see the elder brother, said, "Yes, you can." Then replace him with a elasticsearch search. There was a breakdown in my heart. It is MongoDB is used to practicing AH. ES is what ghost. In the process of learning, when the teacher asked brother, brother always said, this I have not learned ah, you have to learn. So I can only own reader Web documents, it took me a lot of time. Here is a s

" ] } }}Smith's high IDF value in the First_Name field will overwhelm Peter's two low IDF values in the First_Name field and Smith in the Last_Name field.Solution SolutionsThis problem only exists when we are dealing with multiple fields. If we merge all of these fields into a single field, the problem will no longer exist. We can add a full_name

First, the demandYou need to implement a field in the project to delete the document and delete a property of the specified field.Take document TEST/DOCUMENT/1 as an example:{ "_index":"Test", "_type":"Document", "_id":"1", "_score":1, "_source":{ "class":"Com.test.data", "ID":1, "Items":[{"class": "Com.test.data", "ID": 1 }], "lastupdated":"2016-07-22t11:26:56z", "ProcessInstance":{"class": "Co

Elasticsearch Reference [6.2]? MappingRefer to the official English document Https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping.htmlMapping is the process of defining how a document and the fields it contains are stored and indexed, each with a mapping type that determines how the document will be indexed.Meta-fieldsInclude _index,_type,_id and _source fields for documentses

[Elasticsearch] adjacent match (2)-multi-value field, degree of closeness and relevanceMultivalue Fields) Using phrase matching on multi-value fields produces odd behavior: PUT /my_index/groups/1{ "names": [ "John Abraham", "Lincoln Smith"]} Run a phrase query for Abraham Lincoln: GET /my_index/groups/_search{ "query": { "match_phrase": { "names": "Abraham Lincoln" } }} Sur

ElasticSearch (ES) may be read out via the source interface when a result is required after retrieval. But in this case, the result of the return will be many. When invoking the search method, we can add the AddField or AddFields method, Simply read the required domain. The interface example is as follows:1 SearchResponse response = Client.preparesearch ("flume-*-content-*")2 . Setscroll (New TimeValue (60000)3

The purpose of this paper is to pave the future of disk space Utilization optimization, and the main knowledge points are from the official website first, what is _all? In Elasticsearch, _all Field maintains this very large array of strings (text type). This string is the other fields that are preceded by participle, and then grouped together to form. combination: The space is delimited, unordered. The offi