# 분포 분석 모델 API
호출 메서드에 대해서는 오픈 API의 호출 메서드 설명을 참조하시기 바랍니다.
사용 시나리오를 이해하려면 사용자 가이드에서 분포 분석을 참조할 수 있습니다.
# 1. 분포 분석 쿼리
인터페이스 URL
/open/distribution-analyze?token=xxx
요청 방법
POST
콘텐츠 유형
application/json
요청 쿼리 파라미터
Parameter name | Sample value | Parameter type | Is required | Parameter description |
|---|---|---|---|---|
token | xxx | String | Yes | token |
요청 본문 파라미터
{
"eventView":{
"endTime":"2021-10-05 23:59:59",
"groupBy":[
{
"columnDesc":"education",
"columnName":"education",
"propertyRange":"",
"specifiedClusterDate":"2022-01-24",
"tableType":"user"
},
{
"columnDesc":"city",
"columnName":"city",
"propertyRange":"",
"specifiedClusterDate":"2022-01-24",
"tableType":"user"
}],
"recentDay":"114-115",
"startTime":"2021-10-04 00:00:00",
"taIdMeasureVo":{
"columnDesc":"only user ID",
"columnName":"#user_id",
"tableType":"event"
},
"timeParticleSize":"day"
},
"events":[
{
"customEvent":"activity_attend.TIMES",
"customFilters":[
],
"eventName":"custom indicator",
"eventNameDisplay":"",
"filts":[
{
"columnDesc":"city",
"columnName":"city",
"comparator":"equal",
"filterType":"SIMPLE",
"ftv":[
"Beijing",
"Shanghai",
"Gunagzhou",
"Shenzhen"],
"specifiedClusterDate":"2022-01-27",
"tableType":"user",
"timeUnit":""
}],
"formulation":{
"formulationDeps":[
{
"event":{
"eventDesc":"attend activity",
"eventName":"activity_attend"
}
}]
},
"intervalType":"user_defined",
"quota":"",
"quotaIntervalArr":[
500],
"relation":"and",
"type":"customized"
},
{
"analysis":"TOTAL_TIMES",
"analysisDesc":"total number",
"eventName":"payment",
"eventNameDisplay":"",
"filts":[
],
"intervalType":"def",
"quota":"",
"relation":"and",
"type":"normal"
}],
"projectId":377,
"limit": 2,
"timeoutSeconds": 10,
"useCache": true
}
요청 파라미터 설명
$$Parameter name | Sample value | Parameter type | Is required | Parameter description |
|---|---|---|---|---|
eventView | - | Object | Yes | Metrics common attribute part |
eventView.endTime | 2021-10-05 23:59:59 | String | No | End time (format: yyyy-MM-dd HH: mm: ss), valid when the relative time is empty |
eventView.groupBy | - | List | No | Group attributes, can have zero or more |
eventView.groupBy.columnDesc | Education | String | No | Field display name |
eventView.groupBy.columnName | education | String | Yes | Field name |
eventView.groupBy.propertyRange | String | No | Self-defined property interval | |
eventView.groupBy.specifiedClusterDate | 2022-01-24 | String | No | Historical tag version of specified date |
eventView.groupBy.tableType | user | String | Yes | |
eventView.recentDay | 114-115 | String | No | Relative time (this item cannot be empty at the same time as the start time and the end time) |
eventView.startTime | 2021-10-04 00:00:00 | String | No | Start time (format: yyyy-MM-dd HH: mm: ss), valid when the relative time is empty |
eventView.taIdMeasureVo | - | Object | No | Query ID system configuration |
eventView.taIdMeasureVo.columnDesc | User unique ID | String | No | Field display name |
eventView.taIdMeasureVo.columnName | #user_id | String | Yes | Field name |
eventView.taIdMeasureVo.tableType | event | String | Yes | |
eventView.timeParticleSize | day | String | Yes | Unit of the time period taken for analysis
|
events | - | List | Yes | Event metric list |
events.analysis | TOTAL_TIMES | String | No | Analysis aspect for distribution aggregation for Aggregate type enumeration for distribution analysis |
events.analysisDesc | Total number | String | No | Analysis aspect description |
events.customEvent | activity_attend.TIMES | String | No | Custom events |
events.customFilters | [] | List | No | Custom event filtering |
events.eventName | login | String | Yes | The eventName the metric based on, "anyEvent" can be used to represent any event |
events.eventNameDisplay | String | No | Self-defined metric display name | |
events.filts | - | List | No | List of conditions |
events.filts.columnDesc | City | String | No | Field display name |
events.filts.columnName | city | String | Yes | Field name |
events.filts.comparator | equal | String | Yes | Reference: filtering expression of model query API |
events.filts.filterType | SIMPLE | String | No | Filter mode, SIMPLE: simple, COMPOUND: composite |
events.filts.ftv | ["Beijing"] | List | No | Property comparative with bound literial |
events.filts.specifiedClusterDate | 2022-01-27 | String | No | Historical tag version of specified date |
events.filts.tableType | user | String | Yes | |
events.filts.timeUnit | String | No | Filter time unit | |
events.intervalType | user_defined | String | No | Interval range type
|
events.quota | String | No | Metric property (combined with analysis, indicating the property involved and the analysis perspective) | |
events.quotaIntervalArr | [500] | List | No | User defined metric interval |
events.relation | and | String | No | Logical relationship, and: logical and, or: logical or |
events.type | normal | String | Yes | Type of metric,
|
projectId | 0 | Integer | Yes | Project numeric identity |
limit | 2 | Integer | No | Maximum number of groups per analysis object, optional parameters, default is 1000, maximum is 10000 |
timeoutSeconds | 10 | Integer | No | Request timed out parameter, timeout cancels query task |
useCache | true | Boolean | No | Use cache, optional parameter, default is true |
성공적인 응답 예시
{
"data": {
"distribution_interval": [
",500",
"500,"
],
"result_generate_time": "2022-01-27 11:25:44",
"x": [
"2021-10-04",
"2021-10-05"
],
"y": {
"2021-10-04": [
{
"groupCols": [
"total",
"total"
],
"isTotal": 1,
"meanwhileValues": [
"28249",
"-"
],
"totalMeanwhileValue": "28249",
"totalUserNum": 1722,
"values": [
1722,
0
]
},
{
"groupCols": [
"others",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"3842",
"-"
],
"totalMeanwhileValue": "3842",
"totalUserNum": 235,
"values": [
235,
0
]
},
{
"groupCols": [
"colleges",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"2421",
"-"
],
"totalMeanwhileValue": "2421",
"totalUserNum": 154,
"values": [
154,
0
]
},
{
"groupCols": [
"others",
"Shanghai"
],
"isTotal": 0,
"meanwhileValues": [
"2518",
"-"
],
"totalMeanwhileValue": "2518",
"totalUserNum": 151,
"values": [
151,
0
]
},
{
"groupCols": [
"others",
"Shenzhen"
],
"isTotal": 0,
"meanwhileValues": [
"2355",
"-"
],
"totalMeanwhileValue": "2355",
"totalUserNum": 142,
"values": [
142,
0
]
},
{
"groupCols": [
"others",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"1906",
"-"
],
"totalMeanwhileValue": "1906",
"totalUserNum": 116,
"values": [
116,
0
]
},
{
"groupCols": [
"大专",
"深圳市"
],
"isTotal": 0,
"meanwhileValues": [
"1738",
"-"
],
"totalMeanwhileValue": "1738",
"totalUserNum": 107,
"values": [
107,
0
]
},
{
"groupCols": [
"undergraduate",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"1720",
"-"
],
"totalMeanwhileValue": "1720",
"totalUserNum": 106,
"values": [
106,
0
]
},
{
"groupCols": [
"colleges",
"Shanghai"
],
"isTotal": 0,
"meanwhileValues": [
"1658",
"-"
],
"totalMeanwhileValue": "1658",
"totalUserNum": 101,
"values": [
101,
0
]
},
{
"groupCols": [
"本科",
"上海市"
],
"isTotal": 0,
"meanwhileValues": [
"1595",
"-"
],
"totalMeanwhileValue": "1595",
"totalUserNum": 96,
"values": [
96,
0
]
},
{
"groupCols": [
"Post-graduate",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"1315",
"-"
],
"totalMeanwhileValue": "1315",
"totalUserNum": 78,
"values": [
78,
0
]
},
{
"groupCols": [
"本科",
"深圳市"
],
"isTotal": 0,
"meanwhileValues": [
"1276",
"-"
],
"totalMeanwhileValue": "1276",
"totalUserNum": 75,
"values": [
75,
0
]
},
{
"groupCols": [
"colleges",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"1207",
"-"
],
"totalMeanwhileValue": "1207",
"totalUserNum": 75,
"values": [
75,
0
]
},
{
"groupCols": [
"postgraduate",
"Shanghai"
],
"isTotal": 0,
"meanwhileValues": [
"1032",
"-"
],
"totalMeanwhileValue": "1032",
"totalUserNum": 63,
"values": [
63,
0
]
},
{
"groupCols": [
"undergraduate",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"796",
"-"
],
"totalMeanwhileValue": "796",
"totalUserNum": 49,
"values": [
49,
0
]
},
{
"groupCols": [
"postgraduate",
"Shenzhen"
],
"isTotal": 0,
"meanwhileValues": [
"678",
"-"
],
"totalMeanwhileValue": "678",
"totalUserNum": 42,
"values": [
42,
0
]
},
{
"groupCols": [
"postgraduate",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"674",
"-"
],
"totalMeanwhileValue": "674",
"totalUserNum": 38,
"values": [
38,
0
]
},
{
"groupCols": [
"PHd",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"514",
"-"
],
"totalMeanwhileValue": "514",
"totalUserNum": 33,
"values": [
33,
0
]
},
{
"groupCols": [
"PHd",
"Shenzhen"
],
"isTotal": 0,
"meanwhileValues": [
"361",
"-"
],
"totalMeanwhileValue": "361",
"totalUserNum": 21,
"values": [
21,
0
]
},
{
"groupCols": [
"PHd",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"327",
"-"
],
"totalMeanwhileValue": "327",
"totalUserNum": 20,
"values": [
20,
0
]
},
{
"groupCols": [
"PHd",
"Shanghai"
],
"isTotal": 0,
"meanwhileValues": [
"316",
"-"
],
"totalMeanwhileValue": "316",
"totalUserNum": 20,
"values": [
20,
0
]
}
],
"2021-10-05": [
{
"groupCols": [
"total",
"total"
],
"isTotal": 1,
"meanwhileValues": [
"24907",
"-"
],
"totalMeanwhileValue": "24907",
"totalUserNum": 1503,
"values": [
1503,
0
]
},
{
"groupCols": [
"others",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"3535",
"-"
],
"totalMeanwhileValue": "3535",
"totalUserNum": 221,
"values": [
221,
0
]
},
{
"groupCols": [
"others",
"Shanghai"
],
"isTotal": 0,
"meanwhileValues": [
"2833",
"-"
],
"totalMeanwhileValue": "2833",
"totalUserNum": 162,
"values": [
162,
0
]
},
{
"groupCols": [
"colleges",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"2183",
"-"
],
"totalMeanwhileValue": "2183",
"totalUserNum": 130,
"values": [
130,
0
]
},
{
"groupCols": [
"others",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"1946",
"-"
],
"totalMeanwhileValue": "1946",
"totalUserNum": 116,
"values": [
116,
0
]
},
{
"groupCols": [
"others",
"Shenzhen"
],
"isTotal": 0,
"meanwhileValues": [
"1743",
"-"
],
"totalMeanwhileValue": "1743",
"totalUserNum": 109,
"values": [
109,
0
]
},
{
"groupCols": [
"undergraduate",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"1753",
"-"
],
"totalMeanwhileValue": "1753",
"totalUserNum": 107,
"values": [
107,
0
]
},
{
"groupCols": [
"colleges",
"Shanghai"
],
"isTotal": 0,
"meanwhileValues": [
"1606",
"-"
],
"totalMeanwhileValue": "1606",
"totalUserNum": 92,
"values": [
92,
0
]
},
{
"groupCols": [
"undergraduate",
"Shanghai"
],
"isTotal": 0,
"meanwhileValues": [
"1421",
"-"
],
"totalMeanwhileValue": "1421",
"totalUserNum": 81,
"values": [
81,
0
]
},
{
"groupCols": [
"undergraduate",
"Shenzhen"
],
"isTotal": 0,
"meanwhileValues": [
"1093",
"-"
],
"totalMeanwhileValue": "1093",
"totalUserNum": 68,
"values": [
68,
0
]
},
{
"groupCols": [
"postgraduate",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"1037",
"-"
],
"totalMeanwhileValue": "1037",
"totalUserNum": 65,
"values": [
65,
0
]
},
{
"groupCols": [
"colleges",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"947",
"-"
],
"totalMeanwhileValue": "947",
"totalUserNum": 59,
"values": [
59,
0
]
},
{
"groupCols": [
"colleges",
"Shenzhen"
],
"isTotal": 0,
"meanwhileValues": [
"963",
"-"
],
"totalMeanwhileValue": "963",
"totalUserNum": 58,
"values": [
58,
0
]
},
{
"groupCols": [
"postgraduate",
"Shanghai"
],
"isTotal": 0,
"meanwhileValues": [
"698",
"-"
],
"totalMeanwhileValue": "698",
"totalUserNum": 42,
"values": [
42,
0
]
},
{
"groupCols": [
"undergraduate",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"608",
"-"
],
"totalMeanwhileValue": "608",
"totalUserNum": 39,
"values": [
39,
0
]
},
{
"groupCols": [
"postgraduate",
"Shenzhen"
],
"isTotal": 0,
"meanwhileValues": [
"560",
"-"
],
"totalMeanwhileValue": "560",
"totalUserNum": 37,
"values": [
37,
0
]
},
{
"groupCols": [
"postgraduate",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"553",
"-"
],
"totalMeanwhileValue": "553",
"totalUserNum": 31,
"values": [
31,
0
]
},
{
"groupCols": [
"PHd",
"Beijing"
],
"isTotal": 0,
"meanwhileValues": [
"478",
"-"
],
"totalMeanwhileValue": "478",
"totalUserNum": 29,
"values": [
29,
0
]
},
{
"groupCols": [
"PHd",
"Guangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"353",
"-"
],
"totalMeanwhileValue": "353",
"totalUserNum": 22,
"values": [
22,
0
]
},
{
"groupCols": [
"PHd",
"Shangzhou"
],
"isTotal": 0,
"meanwhileValues": [
"339",
"-"
],
"totalMeanwhileValue": "339",
"totalUserNum": 19,
"values": [
19,
0
]
},
{
"groupCols": [
"PHd",
"Shenzhen"
],
"isTotal": 0,
"meanwhileValues": [
"258",
"-"
],
"totalMeanwhileValue": "258",
"totalUserNum": 16,
"values": [
16,
0
]
}
]
}
},
"return_code": 0,
"return_message": "success"
}
응답 파라미터 설명
$$Parameter name | Sample value | Parameter type | Parameter description |
|---|---|---|---|
return_code | 0 | Integer | Return code |
return_message | success | String | Return message |
data | - | Object | Return result |
data. distribution_interval | [",500","500,"] | List | Distribution interval |
data.result_generate_time | 2022-01-27 11:25:44 | String | Results generation time |
data.x | ["2021-10-04"] | List | X-axis information |
data.y | - | List | Y-axis information |
data.y.{dateMap}.{key} | 2021-10-04 | String | Date string |
data.y.{dateMap}.{value} | - | List | Date data |
data.y.{dateMap}.{value}.isTotal | false | Boolean | Is Total |
data.y.{dateMap}.{value}.values | - | List | Metric value |
data.y.{dateMap}.{value}.meanwhileValues | - | List | Simultaneous metric value |
오류 응답 예시
{
"return_code": -1008,
"return_message": "The parameter (token) is empty"
}
Parameter name | Sample value | Parameter type | Parameter description |
|---|---|---|---|
return_code | -1008 | Integer | Return code |
return_message | The parameter (token) is empty | String | Return information |
# 2. 분포 분석 전체 데이터 다운로드
인터페이스 URL
/open/streaming-download/distribution-analyze?token=xxx
요청 방법
POST
콘텐츠 유형
application/json
요청 쿼리 파라미터
Parameter name | Sample value | Parameter type | Mandatory or not | Parameter description |
|---|---|---|---|---|
token | xxx | String | Yes | Query key |
요청 본문 파라미터
{
"eventView":{
"endTime":"2021-10-05 23:59:59",
"groupBy":[
{
"columnDesc":"education",
"columnName":"education",
"propertyRange":"",
"specifiedClusterDate":"2022-01-24",
"tableType":"user"
},
{
"columnDesc":"city",
"columnName":"city",
"propertyRange":"",
"specifiedClusterDate":"2022-01-24",
"tableType":"user"
}],
"recentDay":"114-115",
"startTime":"2021-10-04 00:00:00",
"taIdMeasureVo":{
"columnDesc":"only user ID",
"columnName":"#user_id",
"tableType":"event"
},
"timeParticleSize":"day"
},
"events":[
{
"customEvent":"activity_attend.TIMES",
"customFilters":[
],
"eventName":"custom indicator",
"eventNameDisplay":"",
"filts":[
{
"columnDesc":"city",
"columnName":"city",
"comparator":"equal",
"filterType":"SIMPLE",
"ftv":[
"Beijing",
"Shanghai",
"Gunagzhou",
"Shenzhen"],
"specifiedClusterDate":"2022-01-27",
"tableType":"user",
"timeUnit":""
}],
"formulation":{
"formulationDeps":[
{
"event":{
"eventDesc":"attend activity",
"eventName":"activity_attend"
}
}]
},
"intervalType":"user_defined",
"quota":"",
"quotaIntervalArr":[
500],
"relation":"and",
"type":"customized"
},
{
"analysis":"TOTAL_TIMES",
"analysisDesc":"total number",
"eventName":"payment",
"eventNameDisplay":"",
"filts":[
],
"intervalType":"def",
"quota":"",
"relation":"and",
"type":"normal"
}],
"projectId":377,
"interval": "['1']"
}
요청 파라미터 설명
$$ Parameter name | Sample value | Parameter type | Mandatory or not | Parameter description |
|---|---|---|---|---|
eventView | - | Object | Yes | Same parameters as Distribution Analysis Query interface |
events | - | List | Yes | Same parameters as Distribution Analysis Query interface |
projectId | 0 | Integer | Yes | Project numeric identity |
interval | ['1','2'] | String | Yes | Full Metric Interval Range |
meanwhileOnly | Boolean | No | Whether download simultaneous value，default：false |
::: 팁
요청 파라미터의 주요 구조는 TE 시스템의 분포 분석 화면에서 내보낼 수 있으며, "interval", "meanwhileOnly"와 같은 파라미터를 추가하여 데이터를 다운로드할 수 있습니다.
:::
응답
TE 시스템의 분포 분석 전체 데이터 다운로드와 동일함
# 3. 분포 분석 유저 목록
인터페이스 URL
/open/distribution-user-list?token=xxx
요청 방법
POST
콘텐츠 유형
application/json
요청 쿼리 파라미터
Parameter name | Sample value | Parameter type | Is required | Parameter description |
|---|---|---|---|---|
token | xxx | String | Yes | token |
요청 본문 파라미터
{
"eventView":{
"endTime":"2021-10-05 23:59:59",
"groupBy":[
{
"columnDesc":"education",
"columnName":"education",
"propertyRange":"",
"specifiedClusterDate":"2022-01-24",
"tableType":"user"
},
{
"columnDesc":"city",
"columnName":"city",
"propertyRange":"",
"specifiedClusterDate":"2022-01-24",
"tableType":"user"
}],
"recentDay":"114-115",
"startTime":"2021-10-04 00:00:00",
"taIdMeasureVo":{
"columnDesc":"only user ID",
"columnName":"#user_id",
"tableType":"event"
},
"timeParticleSize":"day"
},
"events":[
{
"customEvent":"activity_attend.TIMES",
"customFilters":[
],
"eventName":"custom indicator",
"eventNameDisplay":"",
"filts":[
{
"columnDesc":"city",
"columnName":"city",
"comparator":"equal",
"filterType":"SIMPLE",
"ftv":[
"Beijing",
"Shanghai",
"Gunagzhou",
"Shenzhen"],
"specifiedClusterDate":"2022-01-27",
"tableType":"user",
"timeUnit":""
}],
"formulation":{
"formulationDeps":[
{
"event":{
"eventDesc":"attend activity",
"eventName":"activity_attend"
}
}]
},
"intervalType":"user_defined",
"quota":"",
"quotaIntervalArr":[
500],
"relation":"and",
"type":"customized"
},
{
"analysis":"TOTAL_TIMES",
"analysisDesc":"total number",
"eventName":"payment",
"eventNameDisplay":"",
"filts":[
],
"intervalType":"def",
"quota":"",
"relation":"and",
"type":"normal"
}],
"projectId":377,
"interval": "10,20",
"sliceDate": "2019-11-18",
"sliceGroupVal": ["Beijing"],
"timeoutSeconds": 10
}
요청 파라미터 설명
$$Parameter name | Sample value | Parameter type | Is required | Parameter description |
|---|---|---|---|---|
projectId | 0 | String | Yes | Project numeric identity |
eventView | - | Object | Yes | Same parameters as Distribution Analysis Query interface |
events | List | Yes | Same parameters as Distribution Analysis Query interface | |
interval | 10,20 | String | No | Go to detail by which metric interval |
groupBit | 0 | Integer | No | Go to detail by total or not |
sliceDate | "2019-11-18" | String | No | Go to detail by which date |
sliceGroupVal | ["Beijing"] | String | Yes | Go to detail by which group |
timeoutSeconds | 10 | Integer | No | Request timed out parameter, timeout cancels query task |
성공적인 응답 예시
{
"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": "Baidu mobile assistant",
"#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": "Huangwei App store",
"#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": "Application Treasure",
"#user_id": 1758186
}
],
"columMeta": {
"#account_id": "account ID",
"#distinct_id": "visitor ID",
"user_level": "user level",
"register_time": "register time",
"diamond_num": "diamond number",
"first_recharge_time": "first recharge time",
"latest_login_time": "lastest login time",
"channel": "channel"
}
},
"return_code": 0,
"return_message": "success"
}
응답 파라미터 설명
$$Parameter name | Sample value | Parameter type | Parameter description |
|---|---|---|---|
return_code | 0 | Integer | Return code |
return_message | success | String | Return information |
data | - | Object | Return result |
data.datalist | - | List | User Information |
data.columMeta | - | Map | Field meaning mapping |
오류 응답 예시
{
"return_code": -1008,
"return_message": "The parameter (token) is empty"
}
Parameter name | Sample value | Parameter type | Parameter description |
|---|---|---|---|
return_code | -1008 | Integer | Return code |
return_message | The parameter (token) is empty | String | Return information |
# 4. 분포 분석 유저 목록 다운로드
인터페이스 URL
/open/streaming-download/distribution-user-list?token=xxx
요청 방법
POST
콘텐츠 유형
application/json
요청 쿼리 파라미터
Parameter name | Sample value | Parameter type | Mandatory or not | Parameter description |
|---|---|---|---|---|
token | xxx | String | Yes | Query key |
요청 본문 파라미터
{
"eventView":{
"endTime":"2021-10-05 23:59:59",
"groupBy":[
{
"columnDesc":"education",
"columnName":"education",
"propertyRange":"",
"specifiedClusterDate":"2022-01-24",
"tableType":"user"
},
{
"columnDesc":"city",
"columnName":"city",
"propertyRange":"",
"specifiedClusterDate":"2022-01-24",
"tableType":"user"
}],
"recentDay":"114-115",
"startTime":"2021-10-04 00:00:00",
"taIdMeasureVo":{
"columnDesc":"only user ID",
"columnName":"#user_id",
"tableType":"event"
},
"timeParticleSize":"day"
},
"events":[
{
"customEvent":"activity_attend.TIMES",
"customFilters":[
],
"eventName":"custom indicator",
"eventNameDisplay":"",
"filts":[
{
"columnDesc":"city",
"columnName":"city",
"comparator":"equal",
"filterType":"SIMPLE",
"ftv":[
"Beijing",
"Shanghai",
"Gunagzhou",
"Shenzhen"],
"specifiedClusterDate":"2022-01-27",
"tableType":"user",
"timeUnit":""
}],
"formulation":{
"formulationDeps":[
{
"event":{
"eventDesc":"attend activity",
"eventName":"activity_attend"
}
}]
},
"intervalType":"user_defined",
"quota":"",
"quotaIntervalArr":[
500],
"relation":"and",
"type":"customized"
},
{
"analysis":"TOTAL_TIMES",
"analysisDesc":"total number",
"eventName":"payment",
"eventNameDisplay":"",
"filts":[
],
"intervalType":"def",
"quota":"",
"relation":"and",
"type":"normal"
}],
"projectId": 319,
"groupBit": 0,
"sliceDate": "2022-03-01",
"sliceGroupVal": ["VIVO앱스토어"],
"selectedColumns": ["#account_id", "#distinct_id"]
}
요청 파라미터 설명
$$ Parameter name | Sample value | Parameter type | Mandatory or not | Parameter description |
|---|---|---|---|---|
projectId | 0 | String | Yes | Project numeric identity |
eventView | - | Object | Yes | Same parameters as Distribution Analysis Query interface |
events | - | List | Yes | Same parameters as Distribution Analysis Query interface |
interval | 10,20 | String | Yes | Go to detail by which metric interval |
groupBit | 0 | Integer | No | Go to detail by total or not |
sliceDate | "2019-11-18" | String | No | Go to detail by which date |
sliceGroupVal | ["북경시"] | String | Yes | Go to detail by which group |
selectedColumns | ["#account_id"] | array | No | The columns to be downloaded |
응답
TE 시스템의 분포 분석 유저 목록 다운로드와 동일함
# 분포 분석을 위한 일반 목록형
# 분포 분석을 위한 집계 유형 목록형
Value | Description | Whether properties are required |
|---|---|---|
TIMES | Number of times | No |
NUMBER_OF_DAYS | Number of days | No |
NUMBER_OF_HOURS | Number of hours | No |
SUM | Sum of values | Yes |
AVG | Numerical average | Yes |
MAX | Maximum value | Yes |
MIN | Numerical minimum | Yes |
DISTINCT | Deduplicate number | Yes |
TRUE | True number | Yes |
FALSE | False number | Yes |
IS_NOT_EMPTY | Not an empty number | Yes |
IS_EMPTY | Null number | Yes |
ARRAY_DISTINCT | List overall deduplicate number | Yes |
ARRAY_SET_DISTINCT | Element collection deduplicate number | Yes |
ARRAY_ITEM_DISTINCT | List element deduplicate number | Yes |
MEDIAN | Median | Yes |