https://www.elastic.co/guide/en/elasticsearch/guide/current/getting-started.html

Elasticsearch is a real-time distributed search and analytics engine. It allows you to explore your data at a speed and at a scale never before possible. It is used for full-text search, structured search, analytics, and all three in combination:

But Elasticsearch is not just for mega-corporations. It has enabled many startups like Datadog and Klout to prototype ideas and to turn them into scalable solutions. Elasticsearch can run on your laptop, or scale out to hundreds of servers and petabytes of data.

No individual part of Elasticsearch is new or revolutionary. Full-text search has been done before, as have analytics systems and distributed databases. The revolution is the combination of these individually useful parts into a single, coherent, real-time application. It has a low barrier to entry for the new user, but can keep pace with you as your skills and needs grow.

If you are picking up this book, it is because you have data, and there is no point in having data unless you plan to do something with it.

Unfortunately, most databases are astonishingly inept at extracting actionable knowledge from your data. Sure, they can filter by timestamp or exact values, but can they perform full-text search, handle synonyms, and score documents by relevance? Can they generate analytics and aggregations from the same data? Most important, can they do this in real time without big batch-processing jobs?

This is what sets Elasticsearch apart: Elasticsearch encourages you to explore and utilize your data, rather than letting it rot in a warehouse because it is too difficult to query.

【Lucene】

Elasticsearch is an open-source search engine built on top of Apache Lucene™, a full-text search-engine library. Lucene is arguably the most advanced, high-performance, and fully featured search engine library in existence today—both open source and proprietary.

But Lucene is just a library. To leverage its power, you need to work in Java and to integrate Lucene directly with your application. Worse, you will likely require a degree in information retrieval to understand how it works. Lucene is very complex.

Elasticsearch is also written in Java and uses Lucene internally for all of its indexing and searching, but it aims to make full-text search easy by hiding the complexities of Lucene behind a simple, coherent, RESTful API.

However, Elasticsearch is much more than just Lucene and much more than “just” full-text search. It can also be described as follows:

And it packages up all this functionality into a standalone server that your application can talk to via a simple RESTful API, using a web client from your favorite programming language, or even from the command line.

It is easy to get started with Elasticsearch. It ships with sensible defaults and hides complicated search theory away from beginners. It just works, right out of the box. With minimal understanding, you can soon become productive.

As your knowledge grows, you can leverage more of Elasticsearch’s advanced features. The entire engine is configurable and flexible. Pick and choose from the advanced features to tailor Elasticsearch to your problem domain.

【work on an abstraction layer to make Lucene easier for Java programmers to add search to their applications】

Many years ago, a newly married unemployed developer called Shay Banon followed his wife to London, where she was studying to be a chef. While looking for gainful employment, he started playing with an early version of Lucene, with the intent of building his wife a recipe search engine.

Working directly with Lucene can be tricky, so Shay started work on an abstraction layer to make it easier for Java programmers to add search to their applications. He released this as his first open source project, called Compass.

Later Shay took a job working in a high-performance, distributed environment with in-memory data grids. The need for a high-performance, real-time, distributed search engine was obvious, and he decided to rewrite the Compass libraries as a standalone server called Elasticsearch.

The first public release came out in February 2010. Since then, Elasticsearch has become one of the most popular projects on GitHub with commits from over 300 contributors. A company has formed around Elasticsearch to provide commercial support and to develop new features, but Elasticsearch is, and forever will be, open source and available to all.

Shay’s wife is still waiting for the recipe search…

Once you’ve extracted the archive file, Elasticsearch is ready to run. To start it up in the foreground:

cd elasticsearch-<version>
./bin/elasticsearch 

Test it out by opening another terminal window and running the following:

curl 'http://localhost:9200/?pretty'

{
  "name" : "Tom Foster",
  "cluster_name" : "elasticsearch",
  "version" : {
    "number" : "2.1.0",
    "build_hash" : "72cd1f1a3eee09505e036106146dc1949dc5dc87",
    "build_timestamp" : "2015-11-18T22:40:03Z",
    "build_snapshot" : false,
    "lucene_version" : "5.3.1"
  },
  "tagline" : "You Know, for Search"
}

curl -X<VERB> '<PROTOCOL>://<HOST>:<PORT>/<PATH>?<QUERY_STRING>' -d '<BODY>'

{
  "from": 0,
  "query": {
    "bool": {
      "minimum_should_match": 1,
      "must": [
        {
          "match": {
            "XB": "2 "
          }
        },
        {
          "wildcard": {
            "XM": "王*"
          }
        }
      ],
      "should": [
        {
          "range": {
            "CSRQ": {
              "gte": "2010-09-01",
              "lte": "2014-09-01"
            }
          }
        }
      ]
    }
  },
  "size": 10
}

模糊查询

curl '1.2.21.10 : 9200/dvote/kwaddress/_search?pretty=true'  -d '
{
  "from": 0,
  "query": {
    "bool": {
      "minimum_should_match": 1,
      "must": [
        {
          "wildcard": {
            "title": "*网*"
          }
        }
      ]
    }
  },
  "size": 1
}
'

https://elasticsearch.cn/book/elasticsearch_definitive_guide_2.x/_distributed_nature.html