elasticsearch query index

": { "tags.brand":"c55fd643-1333-4647-b898-fb3e5e4e6d67" } }, { "term": { "tags.site":"163"}} ]}}}}}//update a nested document get usernested based on the condition/_update_by_query{ "query": { "nested": { "path":"tags", "query": { "bool": { "must": [ { "term": {

1, Get transport Client Connection instance /** * Get the connection client instance of ES; * * @return transportclient Object * /private static transportclient gettransportclient (String esIp) throws IOException { Settings Settings = Settings.builder () . Put (cluster_name, "xxx") . Put (ELASTIC. Client_transport_sniff, True) . Build (); Transportclient transportclient = Transportclient.builder (). settings (Settings

SummaryIntroducing the internal principles of Elasticsearch Shard from the bottom and answering why is it necessary to understand the internal workings of Lucene using Elasticsearch? Understand the cost of the Elasticsearch API Build a FAST Search application Don't commit at any time. When to use stored fields and document Values

(found is false), the value of _ version is increased, which is part of the internal record, it ensures that operations on multiple nodes can be performed in the correct order. D. As mentioned in the update document, deleting a document does not immediately remove it from the disk, but is marked as deleted. Elasticsearch will be deleted under specific circumstances. For specific situations, refer to the instructions in the modification. Through this

":" String "}," raw ": {" type ":" string "," index ":" Not_analyzed "}}}}The above file says that we define its mapping for Index_type, the index type. The point is to map the name field to two, one to name the index analysis, and the other to not analyze raw, which will not split the phrase New York. So when we do the search, we can do the term aggregation for

metadata node, adding the _source field, which contains the original document we sent to Elasticsearch when the index was created. {" _index": " website", " _type": "blog", "_id": "123", "_version": 1, " Found ": true, " _source ": { " title ":" My A blog entry ", " text ": " Just trying this Out ... ", " date ": " 2014/01/01 " } } Pretty Adding pretty parame

Elasticsearch service.Index on the Elasticsearch server, the first step is to create a connection to the server.Client client = TransportClient.builder().build() .addTransportAddress(new InetSocketTransportAddress(InetAddress.getByName("127.0.0.1"), 9300)); 2. Create a querybuilder.QueryBuilder you can set a query for a single field, or you can set

new Files/bulk.txt, The index content is written to Bulk.txt:Import Java. IO. BufferedWriter;Import Java. IO. File;Import Java. IO. FileWriter;Import Java. IO. IOException;Import Java. NET. InetAddress;Import Java. NET. Unknownhostexception;import org. Elasticsearch. Action. Search. SearchResponse;import org. Elasticsearch. Client. Client;import org.

blog with a type of Article,id 1:DeleteResponse dResponse = client.prepareDelete("blog""article""1").execute().actionGet();by Deleteresponse the Isfound () method of the object, you can get the success of the deletion, and the return value is a Boolean type.Third, delete through queryelasticsearch-2.3 and older APIs are not the same, install plugins:delete-by-queryDelete the index named Twitter, with all documents of type Tweet,user field containing

document that deletes an index named blog with a type of Article,id 1:DeleteResponse dResponse = client.prepareDelete("blog", "article", "1").execute().actionGet(); 1 2 by Deleteresponse the Isfound () method of the object, you can get the success of the deletion, and the return value is a Boolean type.Third, delete through queryelasticsearch-2.3 and older APIs are not the same, install plugins:delete-by-

Https://www.elastic.co/guide/en/elasticsearch/reference/1.7/indices-templates.htmlOneIndex templates, define templates, automatically match when new indexes are created, and apply defined templatesNew Index Template (Index templates)We create a new index template template_1 set it to a primary shard of 1. Types are typ

ES_CLASSPATH = $ ES_CLASSPATH: $ ES_HOME/lib/*: $ ES_HOME/lib/sigar /* If ["x $ ES_MIN_MEM" = "x"]; then ES_MIN_MEM = 4g Fi If ["x $ ES_MAX_MEM" = "x"]; then ES_MAX_MEM = 4g Fi4.1.2 Elasticsearch index compression Vim index_elastic.sh #! /Bin/bash # Comperssion the data for elasticsearch now Date = 'date + % Y. % m. % d' # Compression the new

,"cityname": "温岭","description": "温岭是个好城市"}}The following verify the implementation of the weighted sub-query Search interface: GET http://localhost:8080/api/city/search?pageNumber=0pageSize=10searchContent= wenlingThe data will appear[{"id": 1,"provinceid": 1,"cityname": "温岭","description": "温岭是个好城市"},{"id": 2,"provinceid": 2,"cityname": "温州","description": "温州是个热城市"}]From the background Console can be seen, print out the corresponding DSL statement:

used for batch data insertion. bulk is also officially recommended by ES for batch data insertion. Here, bulk is inserted every integer multiple of 500. Package com. tianyalei. elasticsearch. controller; import com. tianyalei. elasticsearch. model. person; import com. tianyalei. elasticsearch. service. personService; import org.

For an introduction to curl, pleaseCurl of Elasticsearch Learning conceptTo start ES, pleaseElasticsearch front and rear operation and stop (TAR package mode) Elasticsearch front and rear station operation and stop (RPM package mode)　　Create an index library, I named Zhouls here[Email protected] elasticsearch-2.4.3]$ c

#! /Bin/bash # Comperssion the data for elasticsearch now Date = 'date + % Y. % m. % d' # Compression the new index; /Usr/bin/curl-XPUT http: // localhost: 9200/logstash-$ date/nginx-access/_ mapping-d' {"nginx-access ": {"_ source": {"compress": true }}}' Echo "" /Usr/bin/curl-XPUT http: // localhost: 9200/logstash-$ date/nginx-error/_ mapping-d' {"nginx-error ": {"_ source": {"compress": true }}}' Echo "

Elasticsearch index optimization mainly solves the problem from two aspects: the index data process and the retrieval process. I have mentioned how to create indexes and import data in the previous articles, but you may encounter slow indexing data. In fact, you can perform targeted optimization by understanding the indexing principles. The

# Comperssion the data for elasticsearch now Date = 'date + % Y. % m. % d' # Compression the new index; /Usr/bin/curl-xput http: // localhost: 9200/logstash-$ date/nginx-access/_ mapping-d' {"nginx-access ": {"_ source": {"compress": True }}}' Echo "" /Usr/bin/curl-xput http: // localhost: 9200/logstash-$ date/nginx-error/_ mapping-d' {"nginx-error ": {"_ source": {"compress": True }}}' Echo "" /Usr/bin/cu

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

Or: Mysql> alter table 'Article' add index ('id', 'order _ id'); ADD id INDEX and order_id INDEX to the article TABLE 1. Re-indexing command Mysql> repair table tbl_name QUICK; 2. query data table IndexesMysql> show index from tbl_name; 3. Create an