How C # uses ES

Elasticsearch Introduction

Elasticsearch (ES) is a Lucene-based open source search engine, which is stable, reliable, fast, and also has a good level of scalability, is specifically designed for the distributed environment.

What is Elasticsearch?

Elasticsearch, an open source search engine based on Apache Lucene (TM), can be thought of as the most advanced, best-performing and most functional search engine library in the world, whether in open source or proprietary domain.
However, Lucene is just a library. To play a powerful role, you need to integrate it into your app using C #. Lucene is very complex, and you need to understand the search knowledge to understand how it works.
Elasticsearch is also written in Java and uses Lucene to index and search, but its purpose is to make full-text search simple and to hide the complexities of lucene through simple, consistent restful APIs.
However, Elasticsearch is not only Lucene and full-text search engine, it also provides:

Distributed real-time file storage with each field indexed and searchable

Distributed search engine for real-time analysis

Can scale to hundreds of servers, processing petabytes of structured or unstructured data

And, all of these features are integrated into a single server, and your app can interact with it through a simple restful API, a client in a variety of languages, or even a command line. Getting Started Elasticsearch is very simple, it provides many reasonable defaults, and hides the complex search engine theory for beginners. It is available out of the box (installation ready to use) and requires little learning to be used in a production environment. Elasticsearch is licensed under Apache 2 License and can be downloaded, used and modified for free.
With the accumulation of knowledge, you can customize Elasticsearch's advanced features according to different problem areas, all of which are configurable and flexible to configure.

Using C # to manipulate ES

Nest is a high-level client that can map all request and response objects, have a strongly typed query DSL (domain-specific language), and can use. NET features such as covariant, Auto Mapping of Pocos, Nest is still used internally by the Elasticsearch.net client. Elasticsearch.net (NEST) client provides a strong type query DSL, convenient for users to use, source code download.

First, how to install nest

Open the Tools menu for VS, and through the NuGet Package Manager console, enter the following command to install Nest

Install-package NEST

The following three DLLs are referenced after installation

Elasticsearch.Net.dll (2.4.4) Nest.dll (2.4.4) Newtonsoft.Json.dll (9.0 versions)

Second, link Elasticsearch

You can use connection pooling to link to a elasticsearch cluster through a single node or by specifying multiple nodes, using a connection pool that is more advantageous than a single node linking to Elasticsearch, such as support for load balancing, failover, and so on.

Via a single-point link:

var node = new Uri ("http://myserver:9200");
var settings = new ConnectionSettings (node);
var client = new Elasticclient (settings);

Through connection pooling Links:

var nodes = new uri[]

{

New Uri ("http://myserver1:9200"),

New Uri ("http://myserver2:9200"),

New Uri ("http://myserver3:9200")

};

var pool = new Staticconnectionpool (nodes);

var settings = new ConnectionSettings (pool);

var client = new Elasticclient (settings);

NEST Index

In order to know which index the request needs to manipulate, the Elasticsearch API expects to receive one or more index names as part of the request.

One, the specified index

1. You can specify the default index by using ConnectionSettings. Defaultindex (). When a specific index is not specified in a request, Nest will request a default index.

var settings = new ConnectionSettings ()
. Defaultindex ("Defaultindex");

2. ConnectionSettings can be used with. Mapdefaulttypeindices () to specify an index that is mapped to a CLR type.

var settings = new ConnectionSettings ()
. Mapdefaulttypeindices (m = m
. Add (typeof (Project), "projects")
);

Note: Pass. Mapdefaulttypeindices () specifies that the index should take precedence over the pass. Defaultindex () specifies the index and is more suitable for simple objects (POCO)

3. You can also display the specified index name for the request, for example:

var response = client. Index (Student, S=>s.index ("Db_test"));
var result = client. Search<student> (s = S.index ("Db_test"));
var result = client. Delete<student> (NULL, S = = S.index ("Db_test"));

Note: This priority is the highest when the actual specified index name for the request is higher than the index specified in both of these ways.

4. Some Elasticsearch APIs (such as query) can use one or more index names or send requests using the _all special flag, requesting multiple or all nodes on the nest

Request a single node

var singlestring = Nest.Indices.Index ("db_studnet");

var singletyped = nest.indices.index<student> ();

Isearchrequest singlestringrequest = new searchdescriptor<student> (). Index (singlestring);

Isearchrequest singletypedrequest = new searchdescriptor<student> (). Index (singletyped);

Request multiple nodes

var manystrings = Nest.Indices.Index ("Db_studnet", "db_other_student");

var manytypes = nest.indices.index<student> (). And<otherstudent> ();

Isearchrequest manystringrequest = new searchdescriptor<student> (). Index (manystrings);

Isearchrequest manytypedrequest = new searchdescriptor<student> (). Index (manytypes);

Request all nodes

var indicesall = Nest.Indices.All;

var allindices = Nest.Indices.AllIndices;

Isearchrequest indicesallrequest = new searchdescriptor<student> (). Index (Indicesall);

Isearchrequest allindicesrequest = new searchdescriptor<student> (). Index (allindices);

Second, create an index

The Elasticsearch API allows you to create indexes while configuring the index, for example:

var descriptor = new Createindexdescriptor ("Db_student")
. Settings (s = s.numberofshards (5). Numberofreplicas (1));
Client. CreateIndex (descriptor);

This specifies that the number of shards for this index is 5 and the number of replicas is 1.

Third, delete the index

The Elasticsearch API allows you to delete an index, for example:

var descriptor = new Deleteindexdescriptor ("Db_student"). Index ("Db_student");
Client. Deleteindex (Descriptor)

Here is the index name "db_student" to be deleted, and the following are more delete use cases:

Deletes all indexes under the node that contains the specified index
var descriptor = new Deleteindexdescriptor ("Db_student"). Allindices ();

NEST Mapping

Nest provides a variety of mapping methods, described here under attribute custom mapping.

First, simple implementation

1. Define the Poco required by the business and specify the required attribute

[Elasticsearchtype (Name = "student")]

public class Student

{

[Nest.string (Index = fieldindexoption.notanalyzed)]

public string Id {get; set;}

[Nest.string (Analyzer = "standard")]

public string Name {get; set;}

[Nest.string (Analyzer = "standard")]

public string Description {get; set;}

Public datetime datetime {get; set;}

}

2, then we pass. Automap () to implement the mapping

var descriptor = new Createindexdescriptor ("Db_student")

. Settings (s = s.numberofshards (5). Numberofreplicas (1))

. Mappings (ms = MS

. map<student> (M = M.automap ())

);

Client. CreateIndex (descriptor);

Note: Pass. Properties () can override mappings defined through attribute

Ii. Introduction of attribute

1, Stringattribute

2, Numberattribute

3, Booleanattribute

4, Dateattribute

5, Objectattribute

NEST Search

Nest provides support for lambda chain query DLS (domain-specific language), following a simple implementation and a brief description of each query.

First, simple implementation

1, define searchdescriptor, facilitate the implementation of complex business in the project

var query = new nest.searchdescriptor<models.esobject> ();
var result = client. search<student> (x = query)

2. Retrieve the title and content containing key, and the author is not equal to "Pretty Woman" document

Query. Query (q =

Q.bool (b =

B.must (M =

M.multimatch (t = t.fields (f = f.field (obj = obj). Title). Field (obj = obj. Content)). Query (Key))

)

. Mustnot (M =

M.querystring (t = t.fields (f = f.field (obj = obj). Author)). Query ("Wenli"))

)

)

);

Attention:

If Elasticsearch uses the default participle, the title and content attribute are [nest.string (Analyzer = "standard")]

If Elasticsearch is using IK participle, the title and content attribute are [nest.string (analyzer = "Ikmaxword")] or [nest.string (analyzer = "ik _smart ")]

Author's attribute is [nest.string (Index = fieldindexoption.notanalyzed)] and disables the use of analyzers

3, filter author equal to "History Creek" document

Query. Postfilter (x = x.term (t = = T.field (obj = obj). Author). Value ("Wenli"));

4, filter the author equals "History Creek" or equal to "friendship boat" document, matching multiple authors between spaces separated by space

Query. Postfilter (x = x.querystring (t = t.fields (f + f.field (obj = = obj). Author)). Query ("Wenli Yswenli"));

5. Filter the number of documents between 1~100

Query. Postfilter (x = x.range (t = = T.field (obj = obj). Number). Greaterthanorequals (1). Lessthanorequals (100)));

6, sort, according to the score flashback arrangement

Query. Sort (x = X.field ("_score", Nest.SortOrder.Descending));

7. Define highlighting Styles and fields

Query. Highlight (H = h

. Pretags ("<b>")

. Posttags ("</b>")

. Fields (

f = F.field (obj = obj. Title),

f = F.field (obj = obj. Content),

f = F.field ("_all")

)

);

8, assemble the contents of the query, organize the data, convenient to call the previous paragraph

var list = result. Hits.select (c = new Models.esobject ()

{

Id = C.source.id,

Title = C.highlights = = null? C.source.title:c.highlights.keys.contains ("Title")? String. Join ("", c.highlights["title"]. Highlights): C.source.title,//highlight content, a record that appears several times

Content = C.highlights = = null? C.source.content:c.highlights.keys.contains ("Content")? String. Join ("", c.highlights["content"]. Highlights): C.source.content,//highlight content, a record that appears several times

Author = C.source.author,

Number = C.source.number,

Isdisplay = C.source.isdisplay,

Tags = C.source.tags,

Comments = C.source.comments,

DateTime = C.source.datetime,

})

Second, query DSL introduction

To be sorted out ...

Elasticsearch.net Document

Document actions include adding/updating documents, updating documents locally, deleting documents, and corresponding bulk operations documentation methods.

I. Add/update documents and bulk operations

Add/update a single document

Client.index (student);

Bulk Add/Update documents

var list = new list<student> (); 2 3 client. Indexmany<student> (list);

Second, the partial Update single document and batch operation

Update a single document locally

Client. Update<student, Object> ("002", UpT = UpT. Doc (New {Name = "Wenli"});

Update Bulk documents locally

var ids = new List<string> () {"002"};

var bulkquest = new Bulkrequest () {Operations = new list<ibulkoperation> ()};

foreach (Var v in IDs)

{

var operation = new Bulkupdateoperation<student, object> (v);

Operation. Doc = new {Name = "Wenli"};

BULKQUEST.OPERATIONS.ADD (operation);

}

var result = client. Bulk (bulkquest);

Iii. deleting documents and bulk operations

Delete a single document

Client. Delete<student> ("001");

Delete a document in bulk

var ids = new List<string> () {"001", "002"};

var bulkquest = new Bulkrequest () {Operations = new list<ibulkoperation> ()};

foreach (Var v in IDs)

{

BULKQUEST.OPERATIONS.ADD (New bulkdeleteoperation<student> (v));

}

var result = client. Bulk (bulkquest);