模型查询API

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模型查询 API 主要用于获取各种数据分析报告。

1.调用方法

请参见Open API文档中的调用方法描述。

2.通用参数

2.1属性表达

几乎所有的 API 都会用到属性,例如按照某个属性进行过滤、分组或者聚合等等。属性包括事件属性,用户属性和用户分群属性,属性通常使用名称和表类型两个字段表达。例如表示 省份 这个事件属性的表达式如下:

"tableType":"event"
"columnName":"#province"

用户属性类似,例如表示 用户级别:

"tableType":"user"
"columnName":"user_level"

2.2 筛选表达式

筛选表达式同样适用于绝大多数 API,用于表示对某些事件或者用户的筛选操作,使用如下格式的 JSON 表示:

{
  // 表示 filts 里的各个条件的关系是 或 还是 且 
  "relation": "and",
  // 具体的条件列表,可以有多个
  "filts": [{
    // 条件的左值,是一个属性
    "tableType":"event",
    "columnName": "#os",
    // 条件的比较符,这里表示等于
    "comparator": "equal",
    // 条件的比较值,根据不同的比较符可以有一个或者多个
    "ftv": [
      "ios"
    ]
  },
  {
    "tableType":"user",
    "columnName":"user_level",
    "comparator": "equal",
    "ftv": [
      "5"
    ]
  }]
}

目前支持的操作符如下:

  • equal / notEqual

表示等于/不等于,对字符串、数值类型有效。如果 ftv 有多个,则相当于 In 或者 Not In。例如想筛选出来等级为3和4的用户:

{
    "tableType":"user"
    "columnName":"user_level"
    "comparator": "equal",
    "ftv": ["3","5"]
}
  • isTrue / isFalse

只对布尔类型有效。

  • isNull / notNull

某个属性是否有值,对字符串、数值类型有效。

  • include / notInclude

表示包含或不包含某个子串:

{
    "tableType":"user"
    "columnName":"channel"
    "comparator": "include",
    "ftv": ["应用宝"]
}
  • less / greater / range:表示小于/大于/小于且大于,其中 range 是前闭后闭的区间,对数值类型和时间类型有效。例如筛选物品剩余数量在 3 和 9 之间的所有事件:
    {
      "tableType":"event"
      "columnName":"count_left"
      "comparator": "range",
      "ftv": [3, 9]
    }
    

或者筛选所有最后登录时间在2019-11-13 00:00~2019-11-23 00:00之间的用户

{
    "tableType":"user"
    "columnName":"latest_login_time"
    "comparator": "range",
    "ftv":["2019-11-13 00:00","2019-11-23 00:00"]
}
  • regexMatch / notRegexMatch

正则匹配或者正则不匹配,只对字符串类型有效。

  • relativeCurrentBetween / relativeCurrentBefore

针对日期类型的操作符,分别表示 相对当前时间在过去N天到过去M天之间/相对当前时间在过去N天之前。例如想筛选所有注册时间相对当前时间在过去3天之前的用户:

{
    "tableType":"user"
    "columnName":"register_time"
    "comparator": "relativeCurrentBefore",
    "ftv": [3]
}

或者筛选所有注册时间相对当前时间在过去9天到过去3天之间的用户:

{
    "tableType":"user"
    "columnName":"register_time"
    "comparator": "relativeCurrentBetween",
    "ftv": [9, 3]
}
  • relativeEventBefore / relativeEventAfter / relativeEventAbsolute

针对日期类型的操作符,分别表示 相对事件发生时刻在之前N长时间之内/相对事件发生时刻在之后N长时间之内/相对事件发生时刻在前后N长时间之内。例如想筛选用户上次登录时间相对事件发生时刻在之前3个小时之内的事件:

{
    "tableType":"user"
    "columnName":"latest_login_time"
    "comparator": "relativeEventBefore",
    "ftv": [3]
    "timeUnit": "hour"
}
  • arrayIncludeItem / arrayNotIncludeItem

列表类型的操作符,表示列表是否包含某些元素

  • arrayItemPos

列表类型的操作符,表示列表第n个元素等于某个值

  • arrayIsNull / arrayNotNull

列表类型的操作符,表示列表是否存在

3. 行为分析

3.1 事件分析

3.1.1 普通分析

[POST /open/event-analyze?token=xxxxxxx]

  • Request body (application/json)

    {
    // 项目Id
    "projectId": 0,
    "events": [
      {
         // normal 普通分析, customized 自定义公式
        "type": "normal",
         // 事件名称,特别的,可以使用 anyEvent 表示任意事件
        "eventName": "buy_shopitem",
         // (可选)分析的属性名称
        "quota": "",
         // 分析类型,聚合操作
        "analysis": "TOTAL_TIMES",
        "relation": "and",
        "filts": [
          {
            "columnName": "user_level",
            "comparator": "greater",
            "ftv": [
              "3"
            ],
            "tableType": "user"
          },
          {
            "columnName": "#os",
            "comparator": "equal",
            "ftv": [
              "android"
            ],
            "tableType": "event"
          },
          {
            "columnName": "#lib",
            "comparator": "equal",
            "ftv": [
              "android"
            ],
            "tableType": "event"
          }
        ]
      }
    ],
    "eventView": {
      // 结束时间
      "endTime": "2019-11-26 00:00:00",
      //(可选)分组属性,可以有零个或者多个
      "groupBy": [
        {
          "columnName": "#screen_width",
          // 自定义属性区间
          "propertyRange": "2000,3000",
          // 属性区间类型,对数值型属性进行分组时,可以为自定义分桶条件
          "propertyRangeType": "user_defined",
          "tableType": "event"
        },
        {
          "columnName": "#screen_height",
          "propertyRange": "2000",
          "propertyRangeType": "user_defined",
          "tableType": "event"
        }
      ],
      // 起始时间
      "startTime": "2019-11-24 00:00:00",
      // 时间单位,可以是 minute/hour/day/week/month/total
      "timeParticleSize": "day"
    },
    "useCache": true
    }
    

    关键参数说明:

  • analysis: 分析类型,可取值为:

    • TOTAL_TIMES: 总次数
    • TRIG_USER_NUM: 触发用户数
    • PER_CAPITA_TIMES: 人均次数
    • SUM: 数值总和
    • AVG: 数值平均值
    • PER_CAPITA_NUM: 人均值
    • MAX: 数值最大值
    • MIN: 数值最小值
    • DISTINCT: 去重数
    • TRUE: 为真数
    • FALSE: 为假数
    • IS_NOT_EMPTY: 不为空数
    • IS_EMPTY: 为空数
    • STAGE_ACC: 阶段累计总和
    • STAGE_ACC_PCV: 阶段累计人均值
    • ARRAY_DISTINCT: 列表去重数
    • ARRAY_ITEM_DISTINCT: 列表元素去重数
  • quota: 若analysis为SUM/MAX/MIN/AVG,需要添加quota字段,即聚合的字段名,与analysis同级,例如:"quota" : "count_left"
  • propertyRangeType: 数值型属性区间类型
    • def: 默认区间
    • discrete: 离散数字
    • user_defined: 用户自定义
  • propertyRange: 自定义数值型属性区间,对数值型属性进行分组时,可以自定义属性区间
  • curl示例

    curl -X POST --header 'Content-Type: application/json' --header 'Accept: application/json' -d '{"eventView":{"comparedByTime":true,"comparedEndTime":"2018-10-18 00:00:00","comparedStartTime":"2018-09-16 00:00:00","endTime":"2018-11-02 00:00:00","groupBy":[{"columnName":"#province","tableType":"event"}],"startTime":"2018-10-01 00:00:00","timeParticleSize":"day"},"events":[{"analysis":"TOTAL_TIMES","eventName":"use_item","quota":"","type":"normal"},{"analysis":"PER_CAPITA_TIMES","eventName":"participate_activity","filts":[{"columnName":"#manufacturer","comparator":"equal","ftv":["iphone"],"tableType":"event"}],"quota":"","relation":"and","type":"normal"},{"analysis":"TOTAL_TIMES","eventName":"use_item","quota":"","type":"normal"},{"analysis":"PER_CAPITA_TIMES","eventName":"participate_activity","filts":[{"columnName":"#manufacturer","comparator":"equal","ftv":["iphone"],"tableType":"event"}],"quota":"","relation":"and","type":"normal"}],"projectId":102,"useCache":true}' 'http://dev-ta2:8992/open/event-analyze?token=bTOzKiTIozG4e19FgXphcA8dDV3DIY8RwdHTO7aSnBsRqSNaIk19BnBMecJDWibD'
    
  • Response body (application/json)

返回内容代表了一张结果表格,表格标题是时间,表格内容每行代表了某个分组的分析结果。

分析对象 分组 x[0] x[1] x[2]
y[0]."buy_shopitem.TOTAL_TIMES" y[0]."buy_shopitem.TOTAL_TIMES"[0].group_cols y[0]."buy_shopitem.TOTAL_TIMES"[0].values[0] y[0]."buy_shopitem.TOTAL_TIMES"[0].values[1] y[0]."buy_shopitem.TOTAL_TIMES"[0].values[2]
y[0]."buy_shopitem.TOTAL_TIMES" y[0]."buy_shopitem.TOTAL_TIMES"[1].group_cols y[0]."buy_shopitem.TOTAL_TIMES"[1].values[0] y[0]."buy_shopitem.TOTAL_TIMES"[1].values[1] y[0]."buy_shopitem.TOTAL_TIMES"[1].values[2]
{
  "return_code": 0,
  "return_message": "success",
  "data": {
    "union_groups": [
      [
        "-∞~2000",
        "2000~+∞"
      ],
      [
        "-∞~2000",
        "-∞~2000"
      ]
    ]
    "x": [
      "2019-11-24",
      "2019-11-25",
      "2019-11-26"
    ],
    "y": [
      {
        "buy_shopitem.TOTAL_TIMES": [
          {
            "group_cols": [
              "-∞~2000",
              "2000~+∞"
            ],
            "values": [
              "507",
              "2127",
              "1550"
            ],
            "group_num": 2
          },
          {
            "group_cols": [
              "-∞~2000",
              "-∞~2000"
            ],
            "values": [
              "663",
              "398",
              "694"
            ],
            "group_num": 2
          }
        ]
      }
    ]
  }
}

3.1.2 自定义公式

  • 使用公式 Request (application/json)
    {
    "eventView": {
      "endTime": "2019-11-27 00:00:00",
      "groupBy": [
        {
          "columnName": "#screen_width",
          "propertyRange": "2000,3000",
          "propertyRangeType": "user_defined",
          "tableType": "event"
        },
        {
          "columnName": "#screen_height",
          "propertyRange": "2000",
          "propertyRangeType": "user_defined",
          "tableType": "event"
        }
      ],
      "projectId": 0,
      "recentDay": "1-3",
      "startTime": "2019-11-25 00:00:00",
      "timeParticleSize": "day"
    },
    "events": [
      {
        "customEvent": "consume_item.PER_CAPITA_TIMES+obtain_item.PER_CAPITA_TIMES",
         // 自定义一个名字
        "eventName": "公式demo",
        "format": "float",
         // customized 自定义公式
        "type": "customized"
      }
    ],
    "useCache": true
    }
    

关键参数说明:

  • customEvent: 公式表达式,由分析项或数值常量的加减乘除构成。分析项有两种形式: eventName.columnName.analysis 或 eventName.analysis。analysis 取值见 3.1.1 普通分析关键参数说明。
  • propertyRangeType: 数值型属性区间类型
    • def: 默认区间
    • discrete: 离散数字
    • user_defined: 用户自定义
  • propertyRange: 自定义数值型属性区间,对数值型属性进行分组时,可以自定义属性区间
  • 使用公式 Response body (application/json)

返回内容代表了一张结果表格,表格标题是时间,表格内容每行代表了某个分组的分析结果。

分析对象 分组 x[0] x[1] x[2]
y[0]."公式demo" y[0]."公式demo"[0].group_cols y[0]."公式demo"[0].values[0] y[0]."公式demo"[0].values[1] y[0]."公式demo"[0].values[2]
y[0]."公式demo" y[0]."公式demo"[1].group_cols y[0]."公式demo"[1].values[0] y[0]."公式demo"[1].values[1] y[0]."公式demo"[1].values[2]
{
  "data": {
    "union_groups": [
      [
        "-∞~2000",
        "2000~+∞"
      ],
      [
        "-∞~2000",
        "-∞~2000"
      ]
    ],
    "group_num": 2,
    "x": [
      "2019-11-25",
      "2019-11-26",
      "2019-11-27"
    ],
    "y": [
      {
        "公式demo": [
          {
            "group_cols": [
              "-∞~2000",
              "2000~+∞"
            ],
            "values": [
              "411.42",
              "538.65",
              "429.31"
            ],
            "group_num": 2
          },
          {
            "group_cols": [
              "-∞~2000",
              "-∞~2000"
            ],
            "values": [
              "336.3",
              "418.33",
              "515.61"
            ],
            "group_num": 2
          }
        ]
      }
    ],
    "cols_format_List": [
      "string",
      "string"
    ],
    "type": [
      null,
      null
    ]
  },
  "return_code": 0,
  "return_message": "success"
}

3.2 留存分析

[POST /open/retention-analyze?token=xxxxxxx]

  • Request body (application/json)
    {
    "projectId": 0,
    "events": [
      {
         // 第一个事件
        "type": "first",
        "eventName": "player_register",
        "filts": [
          {
            "columnName": "user_level",
            "comparator": "greater",
            "ftv": [
              "2"
            ],
            "tableType": "user"
          }
        ],
        "relation": "and"
      },
      {
        // 第二个事件
        "type": "second",
        "eventName": "obtain_diamond",
        "filts": [
          {
            "columnName": "#os",
            "comparator": "equal",
            "ftv": [
              "android"
            ],
            "tableType": "event"
          },
          {
            "columnName": "user_level",
            "comparator": "greater",
            "ftv": [
              "2"
            ],
            "tableType": "user"
          }
        ],
        "relation": "and"
      },
      {
        // (可选)同时显示第三个指标
        "type": "simultaneous_display",
        "eventName": "consume_item",
        "analysis": "PER_CAPITA_NUM",
        "quota": "#vp@dailyTask",
        "filts": [
          {
            "columnName": "user_level",
            "comparator": "greater",
            "ftv": [
              "2"
            ],
            "tableType": "user"
          }
        ],
        "relation": "and"
      }
    ],
    "eventView": {
      // 结束时间
      "endTime": "2019-11-26 00:00:00",
      // 起始时间
      "startTime": "2019-11-24 00:00:00",
      // 统计类型: retention 留存, lost 流失
      "statType": "retention",
      // 时间单位
      "timeParticleSize": "day",
      // 留存期限
      "unitNum": 3
    },
    "useCache": true
    }
    
  • Response 200 (application/json)

返回内容代表了一张结果表格,表格标题是当日到n日后。表格内容每行代表了某天的指标,指标有以下三种类型:

类型 含义
0 留存
1 流失
2 同时展示

阶段平均的留存或流失用户数作为特殊的几行

类型 初始事件时间 分组 初始事件用户数 当日 1日后 2日后 3日后
0 阶段均值 state_avg.0[0].groupCols state_avg.0[0].values[0] state_avg.0[0].values[1] state_avg.0[0].values[2] state_avg.0[0].values[3] state_avg.0[0].values[4]
1 阶段均值 state_avg.1[0].groupCols state_avg.1[0].values[0] state_avg.1[0].values[1] state_avg.1[0].values[2] state_avg.1[0].values[3] state_avg.1[0].values[4]
2 阶段均值 state_avg.2[0].groupCols state_avg.2[0].values[0] state_avg.2[0].values[1] state_avg.2[0].values[2] state_avg.2[0].values[3] state_avg.2[0].values[4]
0 y.0.2019-11-24 y.0.2019-11-24[0].groupCols y.0.2019-11-24[0].values[0] y.0.2019-11-24[0].values[1] y.0.2019-11-24[0].values[2] y.0.2019-11-24[0].values[3] y.0.2019-11-24[0].values[4]
0 y.0.2019-11-25 y.0.2019-11-25[0].groupCols y.0.2019-11-25[0].values[0] y.0.2019-11-25[0].values[1] y.0.2019-11-25[0].values[2] y.0.2019-11-25[0].values[3] y.0.2019-11-25[0].values[4]
0 y.0.2019-11-26 y.0.2019-11-26[0].groupCols y.0.2019-11-26[0].values[0] y.0.2019-11-26[0].values[1] y.0.2019-11-26[0].values[2] y.0.2019-11-26[0].values[3] y.0.2019-11-26[0].values[4]
1 y.1.2019-11-24 y.1.2019-11-24[0].groupCols y.1.2019-11-24[0].values[0] y.1.2019-11-24[0].values[1] y.1.2019-11-24[0].values[2] y.1.2019-11-24[0].values[3] y.1.2019-11-24[0].values[4]
1 y.1.2019-11-25 y.1.2019-11-25[0].groupCols y.1.2019-11-25[0].values[0] y.1.2019-11-25[0].values[1] y.1.2019-11-25[0].values[2] y.1.2019-11-25[0].values[3] y.1.2019-11-25[0].values[4]
1 y.1.2019-11-26 y.1.2019-11-26[0].groupCols y.1.2019-11-26[0].values[0] y.1.2019-11-26[0].values[1] y.1.2019-11-26[0].values[2] y.1.2019-11-26[0].values[3] y.1.2019-11-26[0].values[4]
2 y.2.2019-11-24 y.2.2019-11-24[0].groupCols y.2.2019-11-24[0].values[0] y.2.2019-11-24[0].values[1] y.2.2019-11-24[0].values[2] y.2.2019-11-24[0].values[3] y.2.2019-11-24[0].values[4]
2 y.2.2019-11-25 y.2.2019-11-25[0].groupCols y.2.2019-11-25[0].values[0] y.2.2019-11-25[0].values[1] y.2.2019-11-25[0].values[2] y.2.2019-11-25[0].values[3] y.2.2019-11-25[0].values[4]
2 y.2.2019-11-26 y.2.2019-11-26[0].groupCols y.2.2019-11-26[0].values[0] y.2.2019-11-26[0].values[1] y.2.2019-11-26[0].values[2] y.2.2019-11-26[0].values[3] y.2.2019-11-26[0].values[4]
{
  "data": {
    "state_avg": {
      "0": [
        {
          "groupCols": [],
          "isTotal": 1,
          "lastValidDateVerticalIndexs": [
            "-",
            "2",
            "1",
            "0"
          ],
          "values": [
            "-",
            0.365,
            0.0576,
            0.0349,
            "-"
          ]
        }
      ],
      "1": [
        {
          "groupCols": [],
          "isTotal": 1,
          "lastValidDateVerticalIndexs": [
            "-",
            "2",
            "1",
            "0"
          ],
          "values": [
            "-",
            1,
            0.9424,
            0.9302,
            "-"
          ]
        }
      ],
      "2": [
        {
          "groupCols": [],
          "isTotal": 1,
          "lastValidDateVerticalIndexs": [
            "-",
            "2",
            "1",
            "0"
          ],
          "values": [
            "-",
            0,
            0,
            0,
            "-"
          ]
        }
      ]
    },
    "x": [
      "2019-11-24",
      "2019-11-25",
      "2019-11-26"
    ],
    "y": {
      // 留存
      "0": {
        "2019-11-24": [
          {
            "groupCols": [],
            "includeToday": true,
            "isTotal": 1,
            "values": [
              172,
              62,
              10,
              6,
              2
            ]
          }
        ],
        "2019-11-25": [
          {
            "groupCols": [],
            "includeToday": true,
            "isTotal": 1,
            "values": [
              158,
              58,
              9,
              2,
              "-"
            ]
          }
        ],
        "2019-11-26": [
          {
            "groupCols": [],
            "includeToday": true,
            "isTotal": 1,
            "values": [
              81,
              30,
              5,
              "-",
              "-"
            ]
          }
        ]
      },
      // 流失
      "1": {
        "2019-11-24": [
          {
            "groupCols": [],
            "includeToday": true,
            "isTotal": 1,
            "values": [
              172,
              172,
              162,
              160,
              160
            ]
          }
        ],
        "2019-11-25": [
          {
            "groupCols": [],
            "includeToday": true,
            "isTotal": 1,
            "values": [
              158,
              158,
              149,
              149,
              "-"
            ]
          }
        ],
        "2019-11-26": [
          {
            "groupCols": [],
            "includeToday": true,
            "isTotal": 1,
            "values": [
              81,
              81,
              76,
              "-",
              "-"
            ]
          }
        ]
      },
      // 同时展示
      "2": {
        "2019-11-24": [
          {
            "groupCols": [],
            "includeToday": true,
            "isTotal": 1,
            "values": [
              0.0,
              0.0,
              0.0,
              0.0,
              0.0
            ]
          }
        ],
        "2019-11-25": [
          {
            "groupCols": [],
            "includeToday": true,
            "isTotal": 1,
            "values": [
              0.0,
              0.0,
              0.0,
              0.0,
              "-"
            ]
          }
        ],
        "2019-11-26": [
          {
            "groupCols": [],
            "includeToday": true,
            "isTotal": 1,
            "values": [
              0.0,
              0.0,
              0.0,
              "-",
              "-"
            ]
          }
        ]
      }
    },
    "z": [
      "player_register",
      "obtain_diamond",
      "consume_item"
    ]
  },
  "return_code": 0,
  "return_message": "success"
}

3.3 漏斗分析

[POST /open/funnel-analyze?token=xxxxxxx]

  • Request body (application/json)
    {
    "projectId": 0,
    "eventView": {
      "endTime": "2019-11-26 00:00:00",
      "filts": [
        {
          "columnName": "user_level",
          "comparator": "equal",
          "ftv": [
            "5"
          ],
          "tableType": "user"
        }
      ],
      "groupBy": [
        {
          "columnName": "#country",
          "tableType": "event"
        }
      ],
      "recentDay": "1-3",
      "relation": "and",
      "startTime": "2019-11-24 00:00:00",
      "timeParticleSize": "day"
    },
    "events": [
      {
        "eventName": "obtain_item",
        "filts": [
          {
            "columnName": "#province",
            "comparator": "equal",
            "ftv": [
              "江苏省",
              "上海市"
            ],
            "tableType": "event"
          }
        ],
        "relation": "and"
      },
      {
        "eventName": "consume_item",
        "filts": [
          {
            "columnName": "#os",
            "comparator": "equal",
            "ftv": [
              "ios"
            ],
            "tableType": "event"
          }
        ],
        "relation": "and"
      }
    ],
    "useCache": true
    }
    
  • Response body (application/json)

返回内容代表了一张结果表格,表格标题是漏斗步骤。表格内容每行通过了某个步骤后的用户数

分组 时间 步骤1 步骤2
y[0].总体 阶段合计 y[0].总体.col1[0] y[0].总体.col1[1]
y[0].总体 x[0] y[0].总体.col2[0][0] y[0].总体.col2[0][1]
y[0].总体 x[1] y[0].总体.col2[1][0] y[0].总体.col2[1][1]
y[0].总体 x[2] y[0].总体.col2[2][0] y[0].总体.col2[2][1]
y[1].中国 阶段合计 y[1].总体.col1[0] y[1].总体.col1[1]
y[1].中国 x[0] y[1].中国.col2[0][0] y[1].中国.col2[0][1]
y[1].中国 x[1] y[1].中国.col2[1][0] y[1].中国.col2[1][1]
y[1].中国 x[2] y[1].中国.col2[2][0] y[1].中国.col2[2][1]
{
  "data": {
    "x": [
      "2019-11-24",
      "2019-11-25",
      "2019-11-26"
    ],
    "y": [
      {
        "总体": {
          "col1": [
            14,
            3
          ],
          "col2": [
            [
              6,
              1
            ],
            [
              6,
              0
            ],
            [
              4,
              2
            ],
            [
              0,
              0
            ]
          ]
        }
      },
      {
        "中国": {
          "col1": [
            14,
            3
          ],
          "col2": [
            [
              6,
              1
            ],
            [
              6,
              0
            ],
            [
              4,
              2
            ],
            [
              0,
              0
            ]
          ]
        }
      }
    ],
    "z": [
      "obtain_item",
      "consume_item"
    ]
  },
  "return_code": 0,
  "return_message": "success"
}

3.4 分布分析

[POST /open/distribution-analyze?token=xxxxxxx]

  • Request body (application/json)

    {
    "projectId": 0,
    "events": [{
      "analysis": "AVG",
      "eventName": "ta@v_test",
      "filts": [
        {
          "columnName": "#ip",
          "comparator": "equal",
          "ftv": [
            "159.226.30.7"
          ],
          "tableType": "event"
        }
      ],
      "intervalType": "user_defined",
      "quota": "#vp@strlenchannelname",
      "quotaIntervalArr": [
        3,
        6
      ],
      "relation": "and"
    }],
    "eventView": {
      "endTime": "2019-11-26 00:00:00",
      "groupBy": [
        {
          "columnName": "#province",
          "tableType": "event"
        }
      ],
      "startTime": "2019-11-24 00:00:00",
      "timeParticleSize": "week"
    },
    "useCache": true
    }
    

    关键参数说明:

  • analysis: 分布分析增加三种分析类型:

    • TIMES: 次数
    • NUMBER_OF_DAYS: 天数
    • NUMBER_OF_HOURS: 小时数
  • Response body (application/json)

返回内容代表了一张结果表格,表格标题是分布区间,表格内容每行代表了一段时间在某个分组的分布人数。

时间 分组 总人数 distribution_interval[0] distribution_interval[1] distribution_interval[2]
y.2019-11-18 y.2019-11-18[0].groupCols y.2019-11-18[0].totalUserNum y.2019-11-18[0].values[0] y.2019-11-18[0].values[1] y.2019-11-18[0].values[2]
y.2019-11-18 y.2019-11-18[1].groupCols y.2019-11-18[1].totalUserNum y.2019-11-18[1].values[0] y.2019-11-18[1].values[1] y.2019-11-18[1].values[2]
y.2019-11-25 y.2019-11-25[0].groupCols y.2019-11-25[0].totalUserNum y.2019-11-25[0].values[0] y.2019-11-25[0].values[1] y.2019-11-25[0].values[2]
y.2019-11-25 y.2019-11-25[1].groupCols y.2019-11-25[1].totalUserNum y.2019-11-25[1].values[0] y.2019-11-25[1].values[1] y.2019-11-25[1].values[2]
{
  "data": {
    "distribution_interval": [
      ",3",
      "3,6",
      "6,"
    ]
    "x": [
      "2019-11-18",
      "2019-11-25"
    ],
    "y": {
      "2019-11-18": [
        {
          "groupCols": [
            null
          ],
          "isTotal": 1,
          "totalUserNum": 1,
          "values": [
            0,
            1,
            0
          ]
        },
        {
          "groupCols": [
            "北京市"
          ],
          "isTotal": 0,
          "totalUserNum": 1,
          "values": [
            0,
            1,
            0
          ]
        }
      ],
      "2019-11-25": [
        {
          "groupCols": [
            null
          ],
          "isTotal": 1,
          "totalUserNum": 1,
          "values": [
            0,
            1,
            0
          ]
        },
        {
          "groupCols": [
            "北京市"
          ],
          "isTotal": 0,
          "totalUserNum": 1,
          "values": [
            0,
            1,
            0
          ]
        }
      ]
    }
  },
  "return_code": 0,
  "return_message": "success"
}

3.5 路径分析

[POST /open/path-analyze?token=xxxxxxx]

  • Request body (application/json)
    {
    "projectId": 0,
    "events": {
      "by_fields": [
        {
          "event_name": "consume_item",
          "field": "#country",
          "table_type": "event"
        }
      ],
      "event_names": [
        "consume_item",
        "player_logout",
        "player_register"
      ],
      "source_event": {
        "event_name": "consume_item",
        "filter": {
          "filts": [
            {
              "columnName": "#os",
              "comparator": "equal",
              "ftv": [
                "ios"
              ],
              "tableType": "event"
            }
          ],
          "relation": "and"
        }
      },
       // 起始事件是initial_event, 结束事件是termination_event
      "source_type": "initial_event",
      "user_filter": {
        "filts": [
          {
            "columnName": "user_level",
            "comparator": "equal",
            "ftv": [
              "9"
            ],
            "tableType": "user"
          }
        ],
        "relation": "and"
      }
    },
    "eventView": {
      "col_limit": 10,
      "from_date": "2019-11-20 00:00:00",
      "recent_day": "1-7",
      "session_interval": 22,
      "session_type": "minute",
      "to_date": "2019-11-26 00:00:00"
    },
    "useCache": true
    }
    
  • Response body (application/json)
    {
    "data": {
      "nodes": [
        [
          {
            "times": 6,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "0_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 4,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "1_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 3,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "2_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 3,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "3_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 2,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "4_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 2,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "5_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 2,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "6_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 1,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "7_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 1,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "8_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 1,
            "by_value": "中国",
            "event_name": "consume_item",
            "id": "9_中国^_^consume_item"
          }
        ]
      ],
      "links": [
        [
          {
            "times": 4,
            "source": "0_中国^_^consume_item",
            "target": "1_中国^_^consume_item"
          },
          {
            "times": 2,
            "source": "0_中国^_^consume_item",
            "is_wastage": true,
            "target": "1_wastage"
          }
        ],
        [
          {
            "times": 3,
            "source": "1_中国^_^consume_item",
            "target": "2_中国^_^consume_item"
          },
          {
            "times": 1,
            "source": "1_中国^_^consume_item",
            "is_wastage": true,
            "target": "2_wastage"
          }
        ],
        [
          {
            "times": 3,
            "source": "2_中国^_^consume_item",
            "target": "3_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 2,
            "source": "3_中国^_^consume_item",
            "target": "4_中国^_^consume_item"
          },
          {
            "times": 1,
            "source": "3_中国^_^consume_item",
            "is_wastage": true,
            "target": "4_wastage"
          }
        ],
        [
          {
            "times": 2,
            "source": "4_中国^_^consume_item",
            "target": "5_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 2,
            "source": "5_中国^_^consume_item",
            "target": "6_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 1,
            "source": "6_中国^_^consume_item",
            "target": "7_中国^_^consume_item"
          },
          {
            "times": 1,
            "source": "6_中国^_^consume_item",
            "is_wastage": true,
            "target": "7_wastage"
          }
        ],
        [
          {
            "times": 1,
            "source": "7_中国^_^consume_item",
            "target": "8_中国^_^consume_item"
          }
        ],
        [
          {
            "times": 1,
            "source": "8_中国^_^consume_item",
            "target": "9_中国^_^consume_item"
          }
        ]
      ],
      "event_name_desc_map": {
        "anyEvent": "任意事件",
        "consume_item": "消费道具",
        "player_logout": "用户登出",
        "player_register": "用户注册"
      }
    },
    "return_code": 0,
    "return_message": "success"
    }
    

    3.6 用户属性分析

    [POST /open/user-prop-analyze?token=xxxxxxx]
  • Request body (application/json)
    {
    "projectId": 0,
    "events": [{
      "analysis": "AVG",
      "filts": [
        {
          "columnName": "latest_login_time",
          "comparator": "relativeCurrentBetween",
          "ftv": [
            "200",
            "1"
          ],
          "tableType": "user"
        },
        {
          "columnName": "user_level",
          "comparator": "less",
          "ftv": [
            "6"
          ],
          "tableType": "user"
        }
      ],
      "quota": "diamond_num",
      "relation": "and",
      "tableType": "user"
    }],
    "eventView": {
      "groupBy": [
        {
          "columnName": "user_level",
          "tableType": "user"
        }
      ]
    },
    "useCache": true
    }
    
  • Response body (application/json)

返回内容代表了一张结果表格,表格内容每行代表了某个分组的分析结果。

分组 分析结果
data_list[0].group_cols data_list[0].values
data_list[1].group_cols data_list[1].values
data_list[2].group_cols data_list[2].values
data_list[3].group_cols data_list[3].values
data_list[4].group_cols data_list[4].values
{
  "data": {
    "display_quota_name": "当前拥有钻石数.均值",
    "data_list": [
      {
        "group_cols": [
          "5"
        ],
        "values": 905.762
      },
      {
        "group_cols": [
          "4"
        ],
        "values": 869.983
      },
      {
        "group_cols": [
          "3"
        ],
        "values": 333.965
      },
      {
        "group_cols": [
          "2"
        ],
        "values": 171.515
      },
      {
        "group_cols": [
          "1"
        ],
        "values": 153.568
      }
    ],
    "group_cols_sorted": [
      [
        "5",
        "4",
        "3",
        "2",
        "1"
      ]
    ],
    "cols_format_List": [
      "string"
    ],
    "group_num": 5
  },
  "return_code": 0,
  "return_message": "success"
}

4. 用户列表查询

用户列表系列接口用于查询某一个特定分析报告中的具体用户列表,请求的大部分参数与分析报告相同,新增的参数会在每个接口里具体说明。

4.1 事件分析用户列表

[POST /open/event-user-list?token=xxxxxxx]

  • Request body (application/json)
    {
    "projectId": 0,
    "eventView": {
      "endTime": "2019-11-26 00:00:00",
      "groupBy": [
        {
          "columnName": "#city",
          "tableType": "event"
        }
      ],
      "recentDay": "1-3",
      "startTime": "2019-11-24 00:00:00",
      "timeParticleSize": "day"
    },
    "events": [
      {
        "analysis": "TRIG_USER_NUM",
        "eventName": "consume_item",
        "filts": [
          {
            "columnName": "user_level",
            "comparator": "equal",
            "ftv": [
              "5"
            ],
            "tableType": "user"
          }
        ],
        "quota": "#vp@dailyTask",
        "relation": "and",
        "type": "normal"
      }
    ],
    // 事件所在日期
    "sliceDate": "2019-11-26",
    // 事件所在分组
    "sliceGroupVal": [
      "北京市"
    ]
    }
    
  • Response body (application/json)
    {
    "data": {
      "datalist": [
        {
          "#account_id": "e78107482",
          "#distinct_id": "e145056682",
          "user_level": 5,
          "register_time": "2019-11-26 14:36:13",
          "diamond_num": 1006,
          "latest_login_time": "2019-11-26 15:45:16",
          "channel": "app store",
          "#user_id": 33474682
        },
        {
          "#account_id": "d7819213",
          "#distinct_id": "d14521393",
          "user_level": 5,
          "register_time": "2019-11-26 23:25:14",
          "diamond_num": 858,
          "first_recharge_time": "2019-11-26 23:29:56",
          "latest_login_time": "2019-11-26 23:32:48",
          "channel": "app store",
          "#user_id": 3351093
        }
      ],
      "columMeta": {
        "#account_id": "账户ID",
        "#distinct_id": "访客ID",
        "user_level": "用户等级",
        "register_time": "注册时间",
        "diamond_num": "当前拥有钻石数",
        "first_recharge_time": "首次充值时间",
        "latest_login_time": "最后登录时间",
        "channel": "渠道"
      }
    },
    "return_code": 0,
    "return_message": "success"
    }
    

    4.2 留存分析用户列表

    [POST /open/retention-user-list?token=xxxxxxx]
  • Request body (application/json)
    {
    "projectId": 0,
    "eventView": {
      "endTime": "2019-11-26 00:00:00",
      "groupBy": [
        {
          "columnName": "#province",
          "tableType": "event"
        }
      ],
      "recentDay": "1-3",
      "startTime": "2019-11-24 00:00:00",
      "statType": "retention",
      "timeParticleSize": "day",
      "unitNum": 7
    },
    "events": [
      {
        "eventName": "player_register",
        "filts": [
          {
            "columnName": "#province",
            "comparator": "equal",
            "ftv": [
              "江苏省",
              "上海市"
            ],
            "tableType": "event"
          },
          {
            "columnName": "user_level",
            "comparator": "greater",
            "ftv": [
              "2"
            ],
            "tableType": "user"
          }
        ],
        "relation": "and",
        "type": "first"
      },
      {
        "eventName": "obtain_diamond",
        "filts": [
          {
            "columnName": "#os",
            "comparator": "equal",
            "ftv": [
              "android"
            ],
            "tableType": "event"
          },
          {
            "$ref": "$.events[0].filts[1]"
          }
        ],
        "relation": "and",
        "type": "second"
      }
    ],
    "sliceDate": "2019-11-26",
    // 时段下标: 0:初始事件用户数, 1:当日, 2:1日后, 3:2日后
    "sliceInterval": 3
    }
    
  • Response body (application/json)
    {
    "data": {
      "datalist": [
        {
          "#account_id": "v47739399",
          "#distinct_id": "v88658799",
          "user_level": 11,
          "register_time": "2019-11-26 19:13:20",
          "diamond_num": 1182,
          "latest_login_time": "2019-11-26 20:16:19",
          "channel": "华为应用市场",
          "#user_id": 20459799
        },
        {
          "#account_id": "i7819568",
          "#distinct_id": "i14522048",
          "user_level": 4,
          "register_time": "2019-11-26 23:56:17",
          "diamond_num": 1006,
          "latest_login_time": "2019-11-26 23:59:59",
          "channel": "360手机助手",
          "#user_id": 3351248
        },
        {
          "#account_id": "g7812426",
          "#distinct_id": "g14508786",
          "user_level": 14,
          "register_time": "2019-11-26 17:54:13",
          "diamond_num": 245,
          "first_recharge_time": "2019-11-26 18:08:58",
          "latest_login_time": "2019-11-26 20:16:19",
          "channel": "小米应用商店",
          "#user_id": 3348186
        },
        {
          "#account_id": "a7812000",
          "#distinct_id": "a14508000",
          "user_level": 3,
          "register_time": "2019-11-26 17:27:28",
          "diamond_num": 1153,
          "latest_login_time": "2019-11-26 18:45:58",
          "channel": "app store",
          "#user_id": 3348000
        }
      ],
      "columMeta": {
        "#account_id": "账户ID",
        "#distinct_id": "访客ID",
        "user_level": "用户等级",
        "register_time": "注册时间",
        "diamond_num": "当前拥有钻石数",
        "first_recharge_time": "首次充值时间",
        "latest_login_time": "最后登录时间",
        "channel": "渠道"
      }
    },
    "return_code": 0,
    "return_message": "success"
    }
    

    4.3 漏斗分析用户列表

    [POST /open/funnel-user-list?token=xxxxxxx]
  • Request body (application/json)
    {
    "projectId": 0,
    "eventView": {
      "endTime": "2019-11-26 00:00:00",
      "filts": [
        {
          "columnName": "user_level",
          "comparator": "equal",
          "ftv": [
            "5"
          ],
          "tableType": "user"
        }
      ],
      "groupBy": [
        {
          "columnName": "#province",
          "tableType": "event"
        }
      ],
      "recentDay": "1-4",
      "relation": "and",
      "startTime": "2019-11-23 00:00:00",
      "timeParticleSize": "day"
    },
    "events": [
      {
        "eventName": "obtain_item",
        "filts": [
          {
            "columnName": "#province",
            "comparator": "equal",
            "ftv": [
              "江苏省",
              "上海市"
            ],
            "tableType": "event"
          }
        ],
        "relation": "and"
      }
    ],
    // 漏斗步骤, 从1开始
    "sliceFunnelStep": 1,
    "sliceGroupVal": "上海市"
    }
    
  • Response body (application/json)
    {
    "data": {
      "datalist": [
        {
          "#account_id": "u78082246",
          "#distinct_id": "u145009846",
          "user_level": 5,
          "register_time": "2019-11-26 09:59:34",
          "diamond_num": 1006,
          "latest_login_time": "2019-11-26 11:14:12",
          "channel": "小米应用商店",
          "#user_id": 33463846
        },
        {
          "#account_id": "k77655236",
          "#distinct_id": "k144216836",
          "user_level": 5,
          "register_time": "2019-11-24 08:53:09",
          "diamond_num": 1012,
          "latest_login_time": "2019-11-24 10:02:38",
          "channel": "豌豆荚",
          "#user_id": 33280836
        },
        {
          "#account_id": "a77648226",
          "#distinct_id": "a144203826",
          "user_level": 5,
          "register_time": "2019-11-24 08:21:19",
          "diamond_num": 1006,
          "latest_login_time": "2019-11-24 09:32:31",
          "channel": "应用宝",
          "#user_id": 33277826
        }
      ],
      "columMeta": {
        "#account_id": "账户ID",
        "#distinct_id": "访客ID",
        "user_level": "用户等级",
        "register_time": "注册时间",
        "diamond_num": "当前拥有钻石数",
        "first_recharge_time": "首次充值时间",
        "latest_login_time": "最后登录时间",
        "channel": "渠道"
      }
    },
    "return_code": 0,
    "return_message": "success"
    }
    

    4.4 分布分析用户列表

    [POST /open/distribution-user-list?token=xxxxxxx]
  • Request body (application/json)
    {
    "projectId": 0,
    "events": [{
      "analysis": "TIMES",
      "eventName": "consume_item",
      "filts": [
        {
          "columnName": "#os",
          "comparator": "equal",
          "ftv": [
            "android"
          ],
          "tableType": "event"
        }
      ],
      "intervalType": "def",
      "quota": "",
      "relation": "and"
    }],
    "eventView": {
      "endTime": "2019-11-26 00:00:00",
      "groupBy": [
        {
          "columnName": "#province",
          "tableType": "event"
        }
      ],
      "recentDay": "D31",
      "startTime": "2019-10-28 00:00:00",
      "timeParticleSize": "week"
    },
    // [10,20)小时
    "interval": "10,20",
    // 2019-11-18当周
    "sliceDate": "2019-11-18",
    "sliceGroupVal": [
      "北京市"
    ]
    }
    
  • Response body (application/json)
    {
    "data": {
      "datalist": [
        {
          "#account_id": "h7784497",
          "#distinct_id": "h14456917",
          "user_level": 13,
          "register_time": "2019-11-24 21:52:38",
          "diamond_num": 1201,
          "latest_login_time": "2019-11-24 23:35:49",
          "channel": "百度手机助手",
          "#user_id": 3336217
        },
        {
          "#account_id": "h6201359",
          "#distinct_id": "h11516759",
          "user_level": 68,
          "register_time": "2019-06-23 09:25:18",
          "diamond_num": 1686,
          "first_recharge_time": "2019-06-23 09:25:38",
          "latest_login_time": "2019-11-18 23:01:49",
          "channel": "华为应用市场",
          "#user_id": 2657759
        },
        {
          "#account_id": "g4102426",
          "#distinct_id": "g7618786",
          "user_level": 47,
          "register_time": "2019-07-29 13:58:23",
          "diamond_num": 1,
          "first_recharge_time": "2019-07-29 15:42:20",
          "latest_login_time": "2019-11-24 16:04:03",
          "channel": "应用宝",
          "#user_id": 1758186
        }
      ],
      "columMeta": {
        "#account_id": "账户ID",
        "#distinct_id": "访客ID",
        "user_level": "用户等级",
        "register_time": "注册时间",
        "diamond_num": "当前拥有钻石数",
        "first_recharge_time": "首次充值时间",
        "latest_login_time": "最后登录时间",
        "channel": "渠道"
      }
    },
    "return_code": 0,
    "return_message": "success"
    }
    

    4.5 路径分析用户列表

    [POST /open/path-user-list?token=xxxxxxx]
  • Request body (application/json)
    {
    "projectId": 0,
    "events": {
      "event_names": [
        "obtain_item",
        "consume_item",
        "obtain_coin"
      ],
      "source_event": {
        "event_name": "consume_item",
        "filter": {
          "filts": [
            {
              "columnName": "#os",
              "comparator": "equal",
              "ftv": [
                "ios"
              ],
              "tableType": "event"
            }
          ],
          "relation": "and"
        }
      },
      "source_type": "initial_event",
      "user_filter": {
        "filts": [
          {
            "columnName": "user_level",
            "comparator": "equal",
            "ftv": [
              "6"
            ],
            "tableType": "user"
          }
        ],
        "relation": "and"
      }
    },
    "eventView": {
      "col_limit": 10,
      "from_date": "2019-11-20 00:00:00",
      "recent_day": "1-7",
      "session_interval": 22,
      "session_type": "minute",
      "to_date": "2019-11-26 00:00:00"
    },
    "next_slice_event_by_values": [
      {
        "slice_event_name": "obtain_coin"
      }
    ],
    // 当前所处的路径层级(从0开始计数)
    "session_level": 2,
    // total 合计; with_next 后续有节点; without_next 后续没有节点; with_next_specific:后续有某个事件的节点
    "slice_type": "with_next_specific",
    // slice_type=with_next_specific时必须传
    "slice_event_by_values": [
      {
        "slice_event_name": "obtain_item"
      }
    ]
    }
    
  • Response body (application/json)
    {
    "data": {
      "datalist": [
        {
          "#account_id": "j77444535",
          "#distinct_id": "j143825535",
          "user_level": 6,
          "register_time": "2019-11-22 17:07:12",
          "diamond_num": 1270,
          "latest_login_time": "2019-11-22 18:23:19",
          "channel": "app store",
          "#user_id": 33190535
        }
      ],
      "total_num": 1,
      "columMeta": {
        "#account_id": "账户ID",
        "#distinct_id": "访客ID",
        "user_level": "用户等级",
        "register_time": "注册时间",
        "diamond_num": "当前拥有钻石数",
        "first_recharge_time": "首次充值时间",
        "latest_login_time": "最后登录时间",
        "channel": "渠道"
      }
    },
    "return_code": 0,
    "return_message": "success"
    }
    

    4.6 用户属性分析用户列表

    [POST /open/user-prop-user-list?token=xxxxxxx]
  • Request body (application/json)
    {
    "projectId": 0,
    "events": [{
      "analysis": "AVG",
      "filts": [
        {
          "columnName": "latest_login_time",
          "comparator": "relativeCurrentBetween",
          "ftv": [
            "7",
            "1"
          ],
          "tableType": "user"
        }
      ],
      "quota": "diamond_num",
      "relation": "and",
      "tableType": "user"
    }],
    "eventView": {
      "groupBy": [
        {
          "columnName": "user_level",
          "tableType": "user"
        },
        {
          "columnName": "channel",
          "tableType": "user"
        }
      ]
    },
    "sliceGroupVal": [
      "31",
      "app store"
    ]
    }
    
  • Response body (application/json)
    {
    "data": {
      "datalist": [
        {
          "#account_id": "b6909071",
          "#distinct_id": "b12831131",
          "user_level": 31,
          "register_time": "2019-09-23 09:33:31",
          "diamond_num": 1250,
          "first_recharge_time": "2019-11-18 08:50:33",
          "latest_login_time": "2019-11-26 18:15:51",
          "channel": "app store",
          "#user_id": 2961031
        },
        {
          "#account_id": "a6013000",
          "#distinct_id": "a11167000",
          "user_level": 31,
          "register_time": "2019-09-02 19:15:08",
          "diamond_num": 72,
          "first_recharge_time": "2019-09-02 19:18:36",
          "latest_login_time": "2019-11-24 10:02:38",
          "channel": "app store",
          "#user_id": 2577000
        },
        {
          "#account_id": "j2614535",
          "#distinct_id": "j4855535",
          "user_level": 31,
          "register_time": "2019-08-24 20:40:19",
          "diamond_num": 820,
          "latest_login_time": "2019-11-21 14:16:42",
          "channel": "app store",
          "#user_id": 1120535
        }
      ],
      "columMeta": {
        "#account_id": "账户ID",
        "#distinct_id": "访客ID",
        "user_level": "用户等级",
        "register_time": "注册时间",
        "diamond_num": "当前拥有钻石数",
        "first_recharge_time": "首次充值时间",
        "latest_login_time": "最后登录时间",
        "channel": "渠道"
      }
    },
    "return_code": 0,
    "return_message": "success"
    }
    

    5. 用户事件列表查询

    [POST /open/user-event-list?token=xxxxxxx]
  • Request body (application/json)
    {
    "eventNames": [
      "ta_app_start",
      "ta_app_view",
      "use_item",
      "recharge",
      "participate_quest",
      "participate_activity"
    ],
    "pagerHeader": {
      "pageNum": 1,
      "pageSize": 30
    },
    "projectId": 0,
    "startDateTime": "2019-11-22 00:00:00",
     // 查询从开始时间到之后一周以内的,取值 minute/hour/day/week/month/total
    "dateFormat": "week",
    "userId": 33171371
    }
    
  • Response body (application/json)
    {
    "data": {
      "userEventSeqList": [
        {
          "event_name": "use_item",
          "time": "2019-11-22 00:03:17",
          "properties": {
            "#ip": "59.71.165.109",
            "#country": "中国",
            "#province": "湖北省",
            "#city": "武汉市",
            "#manufacturer": "iphone",
            "#os": "ios",
            "#device_id": "200ECB2114238E4ECCACBFE4D7D88343",
            "#screen_height": 1920,
            "#device_model": "iphone6sp",
            "#app_version": "7.12.2",
            "#screen_width": 1080,
            "#lib": "ios",
            "#network_type": "4G",
            "#carrier": "中国移动",
            "server_id": "43",
            "channel": "app store"
          }
        },
        {
          "event_name": "use_item",
          "time": "2019-11-22 00:03:20",
          "properties": {
            "#ip": "59.71.165.109",
            "#country": "中国",
            "#province": "湖北省",
            "#city": "武汉市",
            "#manufacturer": "iphone",
            "#os": "ios",
            "#device_id": "200ECB2114238E4ECCACBFE4D7D88343",
            "#screen_height": 1920,
            "#device_model": "iphone6sp",
            "#app_version": "7.12.2",
            "#screen_width": 1080,
            "#lib": "ios",
            "#network_type": "4G",
            "#carrier": "中国移动",
            "server_id": "43",
            "channel": "app store"
          }
        },
        {
          "event_name": "use_item",
          "time": "2019-11-22 00:03:28",
          "properties": {
            "#ip": "59.71.165.109",
            "#country": "中国",
            "#province": "湖北省",
            "#city": "武汉市",
            "#manufacturer": "iphone",
            "#os": "ios",
            "#device_id": "200ECB2114238E4ECCACBFE4D7D88343",
            "#screen_height": 1920,
            "#device_model": "iphone6sp",
            "#app_version": "7.12.2",
            "#screen_width": 1080,
            "#lib": "ios",
            "#network_type": "4G",
            "#carrier": "中国移动",
            "server_id": "43",
            "channel": "app store"
          }
        },
        {
          "event_name": "use_item",
          "time": "2019-11-22 11:35:04",
          "properties": {
            "#ip": "59.71.165.109",
            "#country": "中国",
            "#province": "湖北省",
            "#city": "武汉市",
            "#manufacturer": "iphone",
            "#os": "ios",
            "#device_id": "200ECB2114238E4ECCACBFE4D7D88343",
            "#screen_height": 1920,
            "#device_model": "iphone6sp",
            "#app_version": "7.12.2",
            "#screen_width": 1080,
            "#lib": "ios",
            "#network_type": "4G",
            "#carrier": "中国移动",
            "server_id": "43",
            "channel": "app store"
          }
        }
      ],
      "eventNameDescMeta": {
        "anyEvent": "任意事件",
        "participate_activity": "参与活动",
        "participate_quest": "参与任务",
        "recharge": "充值",
        "ta_app_start": "ta_app_start",
        "ta_app_view": "ta_app_view",
        "use_item": "使用道具"
      },
      "columnDescMeta": {
        "#ip": "客户端IP",
        "#country": "国家",
        "#province": "省份",
        "#city": "城市",
        "#manufacturer": "生产商",
        "#os": "操作系统",
        "#device_id": "设备号",
        "#screen_height": "屏幕高度",
        "#device_model": "设备型号",
        "#app_version": "app版本",
        "#screen_width": "屏幕宽度",
        "#lib": "系统库",
        "#network_type": "网络类型",
        "#carrier": "运营商",
        "server_id": "服务器",
        "channel": "渠道1",
        "diamond_obtain": "充值获得钻石数",
        "recharge_level": "充值等级",
        "recharge_value": "充值金额",
        "activity_type": "活动类型",
        "activity_item_operation": "活动项目",
        "recharge_first_day": "是否首日充值",
        "recharge_first_time": "是否首次充值",
        "quest_type": "任务类型",
        "quest_name": "任务名称"
      }
    },
    "return_code": 0,
    "return_message": "success"
    }
    

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