# aggTopN

**Repository Path**: gi1tee/agg-top-n

## Basic Information

- **Project Name**: aggTopN
- **Description**: No description available
- **Primary Language**: Java
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-10-31
- **Last Updated**: 2025-01-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 1 构建本地测试环境
1. 下载仓库`git clone https://gitee.com/gi1tee/agg-top-n.git`
2. 注意：将`./agg-top-n/docker-compose/docker-compose.yml`和`./agg-top-n/flink_sql.sql`中的`192.168.1.147`换成自己的IP
3. 在docker-compose目录下构建容器环境，包括以下容器：flink, zookeeper, kafka, elasticsearch, kibana。其中flink单机集群部署有2个容器：jobmanager, taskmanager。在jobmanager容器中编写执行sql命令。
```bash
cd ./agg-top-n/docker-compose
docker-compose up -d
```
# 2 在kibana创建es索引
1. 浏览器输入http://192.168.1.147:5601登录kibaba
![alt text](assets/readme/image.png)
2. 输入构建索引语句
```json
PUT /sink_test18
{
  "mappings": {
    "properties": {
      "rank_json": {
        "type": "keyword"
      },
      "window_end": {
        "type": "date",
        "format": "yyyy-MM-dd HH:mm:ss"
      }
    }
  }
}
```
# 3 flink执行sql语句
1. 进入flink容器执行sql语句
```bash
docker exec -it jobmanager bash
./bin/sql-client.sh -f flink_sql.sql
```
2. 在浏览器输入`http://192.168.1.147:8081`验证job
![alt text](assets/readme/image-1.png)

# 4 kafka生成消息
```bash
cd ./agg-top-n/kafka-producer
pip3 install -r requirements.txt
python3 producer.py
```

# 5 验证消息
在kibana执行
```json
GET sink_test18/_search
{
  "query": {
  "match_all": {}
  },
  "size": 1000  
}
```