How to use ES in C#

Introduction to Elasticsearch

Elasticsearch (ES) is an open source search engine based on Lucene. It is not only stable, reliable, and fast, but also has good horizontal scalability. It is specially designed for distributed environments.

What is Elasticsearch

Elasticsearch is an open source search engine based on Apache Lucene(TM). Whether in the open source or proprietary fields, Lucene can be considered to be the most advanced and best-performing to date. , the most comprehensive search engine library.
However, Lucene is just a library. To take advantage of its power, you need to integrate it into your application using C#. Lucene is very complex and you need a deep understanding of retrieval to understand how it works.
Elasticsearch is also written in Java and uses Lucene to build indexes and implement search functions, but its purpose is to make full-text search simple and hide the complexity of Lucene through a simple and coherent RESTful API.
However, Elasticsearch is not just Lucene and full-text search engine, it also provides:

Distributed real-time file storage, each field is indexed and searchable

Real-time analysis The distributed search engine

can scale to hundreds of servers and handle petabytes of structured or unstructured data

And, all these functions are integrated into one server, your Applications can interact with it through a simple RESTful API, clients in various languages, and even the command line. Getting started with Elasticsearch is easy, provides many sensible defaults, and hides complex search engine theory from beginners. It works out of the box (installed and ready to use) and requires minimal learning for use in a production environment. Elasticsearch is licensed under the Apache 2 license and is free to download, use and modify.
With the accumulation of knowledge, you can customize the advanced features of Elasticsearch according to different problem areas. All of this is configurable and the configuration is very flexible.

Use C# to operate ES

NEST is a high-level client that can map all request and response objects, has a strongly typed query DSL (domain specific language), and can use .net Features such as covariance and Auto Mapping Of POCOs, NEST still uses the Elasticsearch.Net client internally. The elasticsearch.net (NEST) client provides a strongly typed query DSL, which is convenient for users to use. The source code can be downloaded.

1. How to install NEST

Open the tools menu of VS, 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 (version 9.0)

2. Link elasticsearch

You can use a connection pool to connect to the Elasticsearch cluster through a single node or specify multiple nodes. Using a connection pool has more advantages than connecting a single node to Elasticsearch, such as supporting load. Balancing, failover, etc.

Through single point link:

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

Connect through the connection pool:

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 operate on, the Elasticsearch API expects to receive one or more index names as part of the request.

1. Specify the index

1. You can use .DefaultIndex() through ConnectionSettings to specify the default index. When no specific index is specified in a request, NEST will request the default index.

var settings = new ConnectionSettings()
.DefaultIndex("defaultindex");

2. You can use .MapDefaultTypeIndices() through ConnectionSettings to specify the index mapped to the CLR type. .

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

Note: Specifying indexes through .MapDefaultTypeIndices() has a higher priority than specifying indices through .DefaultIndex(), and is more suitable for simple objects (POCO)

3. In addition, you can also explicitly specify the index name for the request, for example:

var response = client.Index(student, s=>s.Index("db_test"));
var result = client.Search(s => s.Index("db_test"));
var result = client.Delete(null, s => s.Index("db_test" ));

Note: When the index name is actually specified for the request, this priority is the highest, higher than the index specified in the above two ways.

4. Some Elasticsearch APIs (such as query) can use one or multiple index names or use the _all special flag to send requests to multiple or all nodes on NEST

//Request Single node

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

var singleTyped = Nest.Indices.Index();

ISearchRequest singleStringRequest = new SearchDescriptor().Index(singleString);

ISearchRequest singleTypedRequest = new SearchDescriptor().Index(singleTyped);

//Request multiple nodes

var manyStrings = Nest.Indices.Index("db_studnet", "db_other_student");

var manyTypes = Nest .Indices.Index().And();

#ISearchRequest manyStringRequest = new SearchDescriptor().Index(manyStrings);

ISearchRequest manyTypedRequest = new SearchDescriptor().Index(manyTypes);

//Request all nodes

var indicesAll = Nest .Indices.All;

var allIndices = Nest.Indices.AllIndices;

##ISearchRequest indicesAllRequest = new SearchDescriptor().Index(indicesAll) ;

ISearchRequest allIndicesRequest = new SearchDescriptor().Index(allIndices);

2. Create index

Elasticsearch API Allows you to configure the index while creating 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 of the index is 5 and the number of copies is 1.

3. Delete index

Elasticsearch API allows you to delete index, for example:

var descriptor = new DeleteIndexDescriptor("db_student").Index("db_student");

client.DeleteIndex(descriptor)

The index name "db_student" to be deleted is specified here. The following are more deletion use cases:

//Delete the specified index All indexes under the node

var descriptor = new DeleteIndexDescriptor("db_student").AllIndices();

NEST Mapping

NEST provides a variety of mapping methods, which are introduced here. Attribute custom mapping.

1. 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 implement mapping through .AutoMap()

var descriptor = new CreateIndexDescriptor("db_student")

. Settings(s => s.NumberOfShards(5).NumberOfReplicas(1))

.Mappings(ms => ms

.Map(m => m. AutoMap())

);

client.CreateIndex(descriptor);

Note: Can be overridden through .Properties() Mapping defined by Attribute

2. Introduction to Attribute

1, StringAttribute

2, NumberAttribute

3, BooleanAttribute

4, DateAttribute

##5, ObjectAttribute

NEST Search

NEST provides support for Lambda chain query DLS (domain specific language). The following is a simple implementation and a brief description of each query.

1. Simple implementation

1. Define SearchDescriptor to facilitate the implementation of complex business in the project

var query = new Nest.SearchDescriptor();
var result = client.Search(x => query)

2. Retrieve documents whose title and content contain key and the author is not equal to "Pretty Girl"

query.Query(q =>

q.Bool(b =>

) b.Must(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"))

)

)

);

##Note:

If Elasticsearch uses the default word segmentation, and the attributes of Title and Content are [Nest.String(Analyzer = "standard")]

If Elasticsearch uses IK word segmentation, the attributes of Title and Content are [Nest.String(Analyzer = "ikmaxword")] or [Nest.String(Analyzer = "ik_smart")]

Author's attribute is [Nest.String(Index = FieldIndexOption.NotAnalyzed)], prohibiting the use of analyzers

3. Filter documents whose author is equal to "Historical River"

query.PostFilter(x => x.Term(t => t.Field(obj => obj.Author).Value(" wenli")));

4. Filter documents whose author is equal to "Historical River" or equal to "Friendship Boat", and match multiple authors separated by spaces

query .PostFilter(x => x.QueryString(t => t.Fields(f => f.Field(obj => obj.Author)).Query("wenli yswenli")));

5. Filter documents whose number is between 1 and 100

query.PostFilter(x => x.Range(t => t.Field(obj => obj. Number).GreaterThanOrEquals(1).LessThanOrEquals(100)));

6. Sort according to the score flashback

query.Sort(x = > query.Highlight(h => h

.PreTags("")

.PostTags("")

.Fields (

f => f.Field(obj => obj.Title),

f => f.Field(obj => obj.Content),

f => f.Field("_all")

)

);

8. Assemble the query content and organize the data to facilitate the previous call

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, //The highlighted content appears several times in a record

Content = c.Highlights == null? c.Source.Content: c. Highlights.Keys.Contains("content") ? string.Join("", c.Highlights["content"].Highlights) : c.Source.Content, //The highlighted content, how many times appear in a record 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,

})

2. Introduction to query DSL

To be sorted out...

elasticsearch.net Document

Document operations include adding/updating documents and partially updating documents , delete documents and corresponding batch operation document methods.

1. Add/update documents and batch operations

Add/update a single document

Client.Index(student);

Batch add /Update Documentation

var list = new List();2 3 client.IndexMany(list);

2. Partial update of single document and batch operation

Partially update a single document

client.Update("002", upt => upt.Doc(new { Name = "wenli" }));

Partial update batch document

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

##var bulkQuest = new BulkRequest() { Operations = new List() };

foreach (var v in ids)

{

var operation = new BulkUpdateOperation(v);

operation.Doc = new { Name = "wenli" };

bulkQuest.Operations.Add(operation);

}

var result = client.Bulk(bulkQuest);

3. Delete documents and batch operations

Delete a single document

client.Delete("001");

Delete documents in batches

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

var bulkQuest = new BulkRequest() { Operations = new List() };

##foreach (var v in ids)

{

bulkQuest.Operations.Add(new BulkDeleteOperation(v));

}

##var result = client.Bulk (bulkQuest);

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