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@@ -0,0 +1,373 @@
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+## 接口调用测试与说明
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+
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+本文档将带入具体的数据进行测试，并解释一部分的参数和逻辑，并会给出hdfs的测试方法
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+
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+#### 用户注册与登录
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+
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+数据库中，已注册用户tsc，密码为12345678
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+
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+注册时id可以**随意取值**，因为数据库会自动填充id
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+
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+请求成功后，用navicat打开user表，发现出现了tsc用户
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+
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+如果想重置自动递增的id，用truncate table user
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+
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+登录成功后，会返回userId，需要本地缓存，用于其他接口
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+
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+<img src="E:\大学学习资料\创新创业项目资料\TeamAI-FrontEnd\参考\接口测试md\接口调用测试&说明.assets\用户注册.jpg" alt="用户注册" style="zoom:50%;" />
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+
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+<img src="E:\大学学习资料\创新创业项目资料\TeamAI-FrontEnd\参考\接口测试md\接口调用测试&说明.assets\用户登录.jpg" alt="用户登录" style="zoom:50%;" />
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+
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+#### 文件上传
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+
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+**注意：该接口没有判重，所以尽可能不要重复上传同一文件**
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+
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+如果要重新上传，先用hdfs命令删除
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+
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+<img src="E:\大学学习资料\创新创业项目资料\TeamAI-FrontEnd\参考\接口测试md\接口调用测试&说明.assets\文件上传2.jpg" alt="文件上传2" style="zoom:50%;" />
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+
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+在postman里，点击file右侧可以选择text类型或file类型，file类型可以选择文件
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+
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+上传成功后
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+
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+##### hdfs操作相关方法
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+
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+hdfs页面在50070端口
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+
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+spark页面在8080端口
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+
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+```
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+cd /ai_environment_jars/hadoop-2.7.4
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+#进入hadoop目录
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+bin/hdfs dfs -ls /data/java_compile/
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+#查看上传文件
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+bin/hdfs dfs -rm -r /data/java_compile/*
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+#删除所有文件
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+```
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+
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+
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+
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+#### 文件查询
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+
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+getall只需要传入userId，这里传入tsc用户的id
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+
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+
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+
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+getDetail接口传入文件id，这里传入上面upload的event_data.csv的fileId=1
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+
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+
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+
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+结果为
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+
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+```
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+{
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+ "timestamp": 1647334283649,
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+ "status": 200,
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+ "data": {
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+ "fileName": "event_data",
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+ "createTime": "2022-03-15T08:47:52.093+00:00",
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+ "fileStrucInfo": {
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+ "totalRows": "754"
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+ },
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+ "headerInfos": [
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+ {
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+ "id": 33,
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+ "fileInfoId": 1,
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+ "fieldName": "frame_index",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 1,
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+ "fieldType": "int",
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+ "valueInfo": "[\"79\",\"89992\"]"
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+ },
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+ {
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+ "id": 34,
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+ "fileInfoId": 1,
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+ "fieldName": "time",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 1,
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+ "fieldType": "double",
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+ "valueInfo": "[\"3.16\",\"3599.68\"]"
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+ },
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+ {
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+ "id": 35,
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+ "fileInfoId": 1,
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+ "fieldName": "road",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"R\",\"L\"]"
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+ },
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+ {
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+ "id": 36,
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+ "fileInfoId": 1,
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+ "fieldName": "lane",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"r\",\"m\",\"l\"]"
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+ },
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+ {
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+ "id": 37,
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+ "fileInfoId": 1,
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+ "fieldName": "vehicle_class",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"car\",\"truck\",\"bus\"]"
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+ },
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+ {
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+ "id": 38,
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+ "fileInfoId": 1,
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+ "fieldName": "vehicle_id",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 1,
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+ "fieldType": "int",
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+ "valueInfo": "[\"20\",\"46862\"]"
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+ },
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+ {
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+ "id": 39,
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+ "fileInfoId": 1,
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+ "fieldName": "event_type",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"cruise\",\"overdrive\"]"
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+ },
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+ {
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+ "id": 40,
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+ "fileInfoId": 1,
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+ "fieldName": "duration",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"48,60\",\"24,36\",\"36,48\",\"12,24\",\"0,12\"]"
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+ }
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+ ]
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+ }
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+}
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+```
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+
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+具体含义查看接口文档
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+
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+##### get/allfileandfunc
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+
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+相比get/all，会返回可用的数理分析函数信息
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+
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+这里的funcInfos是手动导入的，**有些参数作用不明**
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+
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+```
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+{
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+ "timestamp": 1647335129081,
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+ "status": 200,
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+ "data": {
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+ "fileNamePojos": [
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+ {
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+ "fileId": "1",
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+ "fileName": "event_data"
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+ }
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+ ],
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+ "funcInfos": [
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+ {
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+ "id": 1,
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+ "funcDes": null,
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+ "funcName": "数据分布",
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+ "flagOfType": 2,
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+ "flagOfConOrDis": 2
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+ },
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+ {
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+ "id": 2,
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+ "funcDes": null,
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+ "funcName": "散点图",
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+ "flagOfType": 2,
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+ "flagOfConOrDis": 2
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+ },
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+ {
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+ "id": 3,
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+ "funcDes": null,
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+ "funcName": "数据统计",
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+ "flagOfType": 2,
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+ "flagOfConOrDis": 2
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+ },
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+ {
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+ "id": 4,
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+ "funcDes": null,
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+ "funcName": "偏度-峰度",
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+ "flagOfType": 2,
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+ "flagOfConOrDis": 2
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+ },
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+ {
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+ "id": 5,
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+ "funcDes": null,
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+ "funcName": "皮尔森相关系数",
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+ "flagOfType": 2,
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+ "flagOfConOrDis": 2
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+ },
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+ {
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+ "id": 6,
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+ "funcDes": null,
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+ "funcName": "平均值",
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+ "flagOfType": 2,
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+ "flagOfConOrDis": 2
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+ }
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+ ]
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+ }
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+}
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+```
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+
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+#### 文件分析
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+
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+传入fileId=1,即上传的event_data.csv,结果为
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+
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+```
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+{
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+ "timestamp": 1647335223563,
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+ "status": 200,
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+ "data": {
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+ "fileName": "event_data",
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+ "createTime": "2022-03-15T09:02:05.093+00:00",
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+ "fileStrucInfo": {
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+ "totalRows": "754"
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+ },
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+ "headerInfos": [
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+ {
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+ "id": 73,
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+ "fileInfoId": 1,
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+ "fieldName": "frame_index",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 1,
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+ "fieldType": "int",
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+ "valueInfo": "[\"79\",\"89992\"]"
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+ },
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+ {
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+ "id": 74,
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+ "fileInfoId": 1,
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+ "fieldName": "time",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 1,
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+ "fieldType": "double",
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+ "valueInfo": "[\"3.16\",\"3599.68\"]"
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+ },
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+ {
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+ "id": 75,
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+ "fileInfoId": 1,
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+ "fieldName": "road",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"R\",\"L\"]"
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+ },
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+ {
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+ "id": 76,
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+ "fileInfoId": 1,
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+ "fieldName": "lane",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"r\",\"m\",\"l\"]"
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+ },
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+ {
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+ "id": 77,
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+ "fileInfoId": 1,
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+ "fieldName": "vehicle_class",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"car\",\"truck\",\"bus\"]"
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+ },
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+ {
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+ "id": 78,
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+ "fileInfoId": 1,
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+ "fieldName": "vehicle_id",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 1,
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+ "fieldType": "int",
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+ "valueInfo": "[\"20\",\"46862\"]"
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+ },
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+ {
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+ "id": 79,
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+ "fileInfoId": 1,
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+ "fieldName": "event_type",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"cruise\",\"overdrive\"]"
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+ },
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+ {
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+ "id": 80,
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+ "fileInfoId": 1,
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+ "fieldName": "duration",
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+ "aliasName": "",
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+ "fieldDes": "",
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+ "nullsRatio": 0.0,
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+ "conOrDis": 0,
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+ "fieldType": "string",
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+ "valueInfo": "[\"48,60\",\"24,36\",\"36,48\",\"12,24\",\"0,12\"]"
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+ }
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+ ]
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+ }
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+}
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+```
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+
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+**当调用getDetail时似乎已经完成了分析过程**
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+
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+这里head_info字段id不同是因为想在数据库中吧自动递增设为1失败了，所以继续递增
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+
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+#### 模型类别
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+
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+使用时可以通过GET：/get/models，通过模型类型的名称获得详细数据
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+
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+参数的含义详见模型类别表model_type
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+
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+| 类型名 | 中文名 | 参数列表 |
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+| ------------------------------ | ---------------- | ---------------------------------- |
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+| LogisticRegression | 逻辑回归 | [MaxIter,RegParam,ElasticNetParam] |
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+| DecisionTree | 决策树 | [Category,TrainingDataSetOccupy] |
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+| RandomForest | 随机森林 | [MaxIter,RegParam,ElasticNetParam] |
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+| GBDT | 梯度提升决策树 | [MaxIter,RegParam,ElasticNetParam] |
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+| MultilayerPerceptronClassifier | 多层感知器分类器 | [Category,TrainingDataSetOccupy] |
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+| NaiveBayes | 朴素贝叶斯 | [Category,TrainingDataSetOccupy] |
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+| RandomForestRegression | 随机森林回归 | [Category,TrainingDataSetOccupy] |
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+| K-Means | K-均值 | [NumOfCluster,Seed] |
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+
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+#### 分析函数类别
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+
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+目前分析函数表func_info其他属性意义不明
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+
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+| 数据分布 |
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+| -------------- |
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+| 散点图 |
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+| 数据统计 |
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+| 偏度-峰度 |
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+| 皮尔森相关系数 |
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+| 平均值 |
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+
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tscRubbish