ES案例数据

数据集:

            1. 莎士比亚的所有著作,合适地解析成了各个字段:shakespeare.json。

https://www.elastic.co/guide/en/kibana/3.0/snippets/shakespeare.json

            2. 随机生成的虚构账号数据:accounts.json

https://github.com/bly2k/files/blob/master/accounts.zip?raw=true

            3. 随机生成的日志文件:logs.jsonl

https://download.elastic.co/demos/kibana/gettingstarted/logs.jsonl.gz

将他们加载入ES。

先解压缩,然后使用命令批量加载。

莎士比亚数据集由如下数据格式组织

    {  
        "line_id": INT,  
        "play_name": "String",  
        "speech_number": INT,  
        "line_number": "String",  
        "speaker": "String",  
        "text_entry": "String",  
    }  
账户数据集由如下数据格式组织
    {  
        "account_number": INT,  
        "balance": INT,  
        "firstname": "String",  
        "lastname": "String",  
        "age": INT,  
        "gender": "M or F",  
        "address": "String",  
        "employer": "String",  
        "email": "String",  
        "city": "String",  
        "state": "String"  
    }  
日志数据有几十个不同的字段,但是在教程中关注的字段如下:
{  
    "memory": INT,  
    "geo.coordinates": "geo_point"  
    "@timestamp": "date"  
} 

 

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转载自blog.csdn.net/dyxcome/article/details/82080003