elasticsearch nested

ObjectiveJMeter is an open source tool for performance testing, stress testing, and is being tested by a large number of testers to test product performance, load, and more. JMeter In addition to the powerful presets of various plugins, various visual charting tools, there are some inherent flaws, such as: We often can only analyze the performance of the same deployment in the report, it is inconvenient to make a vertical comparison, for example, each build will run a one-time test, but

In the process of building Elasticsearch database, the first use of its recommended Logstash tools to import data, but it is very uncomfortable to use, so you want to use Perl good regular expression to filter the data classification, and then import Elasticsearch, So search Cpan found the Search::elasticsearch module.The module on the cpan of the document writte

[TOC] 1. Create a document 1.1 with the specified ID PUT my_blog/article/1{ "id":1, "title":"elasticsearch", "posttime":"2017-05-01", "content":"elasticsearch is helpfull!"} Return Value: { "_index": "my_blog", "_type": "article", "_id": "1", "_version": 1, "result": "created", "_shards": { "total": 2, "successful": 1, "failed": 0 }, "created": true} The version number automatically

Rest interface Now that we have a functioning node (and cluster), the next step is to understand how to communicate with it. Fortunately, Elasticsearch provides a very comprehensive and powerful rest API that allows you to interact with your cluster using this REST API. Here are a few things you can do with this API: 1, check your cluster, node and index health status and various statistical information2. Manage your clusters, nodes, index data, and

Elasticsearch is a very useful search engine, it is the bottom of the integration of luence, so also inherited the inverted indexing principle. To use elasticsearch here we need a few tools and follow these steps. This project is just as a basic introductory demo Elasticsearch simple function reference, the actual deployment of multiple nodes and the idea of deal

Original link: http://lxw1234.com/archives/2015/12/585.htm Keywords: hive, elasticsearch, integration, consolidation Elasticsearch can already be used with big data technology frameworks like yarn, Hadoop, Hive, Pig, Spark, Flume, and more, especially when adding data, using distributed tasks to add index data, especially on data platforms. Many of the data is stored in hive, and using hive to manipulate t

While Elasticsearch can support full-text retrieval in a variety of languages, we don't want to switch to Elasticsearch as the backend database for the time being.Of course, when you can store data in a Web application, write a copy of it to Elasticsearch, but it certainly pollutes the original business logic.In the IT industry, as long as there is demand, there

Objective:es5* above requires jdk1.8,jdk1.8,jdk1.8. Important thing to say three times1. Download ElasticsearchHttps://www.elastic.co/cn/downloads/elasticsearch#ga-releaseBecause it's a Windows version, you can download the zip2, unzip, my directory location: "E:\elasticsearch-5.4.1\"In the folder's Bin directory double-click Elasticsearch.bat execution, after the completion of any browser type 127.0.0.1:92

Some time ago, I made a search platform for the company based on elasticsearch (elasticsearch). I will share some of the accumulated knowledge during this period with you. If anything is wrong, you are welcome to give more criticism and suggestions. For elasticsearch, because there are still many things, I will make it into a series. The following is the director

Elasticsearch default provided by the word breaker, will separate each character, not what we want according to keywords to participle, such as we want to "Chinese", "China", "I" such participle, so need to install Chinese word-breaker IK to achieve this function.Elasticsearch-analysis-ik is a Chinese word breaker, support custom thesaurus, the specific installation steps are as follows:1. Download the latest IK participle source from GitHub to localM

Elasticsearch deployment and use on NASElasticsearch is an enterprise-class full-text search engine, based on the development of Lucene Library in Java, fully using the RESTful interface for users, distributed search support is very good!Deployment EnvironmentIn order to achieve distributed deployment, I used two synology Nas, x86 and ARM respectively, the architecture, the practice proved to be able to run.Host: Synology ds415+,ds414j (https://www.sy