elastic_tutorial/The Elasticsearch Documentation

Elasticsearch

قبل از شروع مطالعه فایل ها و آموزش ها می توانید به پیوند زیر مراجعه کنید تا با برخی مباحث مقدماتی آشنا شوید:

https://www.bigdata.ir/1396/10/%D8%A2%D9%85%D9%88%D8%B2%D8%B4-%D9%85%D9%82%D8%AF%D9%85%D8%A7%D8%AA%DB%8C-%D8%A7%D9%84%D8%A7%D8%B3%D8%AA%DB%8C%DA%A9-%D8%B3%D8%B1%DA%86-%D9%88-%DA%A9%DB%8C%D8%A8%D8%A7%D9%86%D8%A7/

persian README here

Database with powerful search engine.

• full-Text Search: Elasticsearch provides advanced full-text search capabilities, allowing you to search and retrieve relevant documents based on text matching and relevance scoring.
• Distributed and Scalable: Elasticsearch is designed to be distributed and scalable, allowing you to store and process large volumes of data across multiple nodes and clusters.
• Near Real-Time Data: Elasticsearch provides near real-time indexing and search capabilities, allowing you to index and search data almost instantly as it becomes available.
• Document-Oriented: Elasticsearch treats data as structured JSON documents, making it easy to index, search, and analyze different types of data.
• Multi-Tenancy: Elasticsearch supports multi-tenancy, allowing you to segregate and secure data from different users or applications within the same cluster.
• Aggregations and Analytics: Elasticsearch provides powerful aggregation capabilities for performing analytics on your data, allowing you to extract insights and summarize data across various dimensions.
• Schema-Free: Elasticsearch is schema-free, meaning you can index and search data without defining a predefined schema. This flexibility allows you to easily adapt to changing data structures.
• RESTful API: Elasticsearch exposes a RESTful API, making it easy to interact with the system and perform various operations such as indexing, searching, and managing data.
• Distributed Search: Elasticsearch allows you to distribute search operations across multiple nodes, enabling parallel processing and faster search performance.
• Integration with Ecosystem: Elasticsearch integrates well with other tools and technologies, such as Logstash and Kibana, forming the ELK (Elasticsearch, Logstash, and Kibana) stack for log analysis and monitoring.

Details:

current version: 8.8
WebSite: https://elastic.co
Link of install Elasticsearch-8.8: https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-8.8.2-windows-x86_64.zip
Link of install Elasticsearch-7.17: https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-7.17.11-windows-x86_64.zip

download

persian_download_help
english_download_help

Usage

    PUT /firstindex
    // create index


    PUT firstindex
    {
        "mappings": {
                "date_detection": false
        },
            "settings": {
                "number_of_shards": "1",
                "number_of_replicas": "0"
                
            }
        }
    // create index  by simple setting

    DELETE /firstindex

    // Delete a Index


    DELETE /firstindex/_doc/1

    // Delete a doc by id of the Index




    // GET
    GET /firstindex/_doc/0

    // Get Index By Id 0


    GET firstindex/_count

    // تعداد doc ها در ایندکس




    // POST
    POST firstindex/_doc/1
    {
        "name": "Ali",
        "age": 23
    }
    // Insert Into doc by id 1

    POST firstindex/_doc
    {
        "name": "Ali",
        "age": 23
    }
    // Insert Into new DOC

    POST /firstindex/_delete_by_query
    {
        "query": {
            "match_all": {}
        }
    }
    // Delete all

    POST /firstindex/_delete_by_query
    {
        "query": {
            "match": {
                "_id": "v8eA2IQB5pIgH4LhE2mX"
        }
    }
    }
    // Delete doc By id







    // Querys
    // Example: POST /firstindex/_delete_by_query{"Query"}
    //         
    {
        "query": {
        "match_all": {}
        }
    }
    // All

Training path

web Docs
_ Install kibana
_ Create Index
_ Delete Index
_ GET Index
_ Insert Into Index
_ Documentation