# 分布分析モデルAPI
# Distribution Analysis Model API
As for the call method, please refer to the call method description in Open API
You can read the distribution analysis (opens new window) in the user manual to understand the usage scenario.
# Distribution Analysis Query
Interface URL
/open/distribution-analyze?token=xxx
Request method
POST
Content-Type
application/json
Request Query Parameter
| Parameter name | Sample value | Parameter type | Is required | Parameter description |
|---|---|---|---|---|
| token | xxx | String | Yes | token |
# Request Body Parameter
{
"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
}
# Request Parameter Description
| Parameter name | Sample value | Parameter type | Is required | Parameter description |
|---|---|---|---|---|
| eventView | - | Object | Yes | Metrics common attribute part |
| ∟ 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 |
| ∟ groupBy | - | List | No | Group attributes, can have zero or more |
| ∟ columnDesc | Education | String | No | Field display name |
| ∟ columnName | education | String | Yes | Field name |
| ∟ propertyRange | String | No | Self-defined property interval | |
| ∟ specifiedClusterDate | 2022-01-24 | String | No | Historical tag version of specified date |
| ∟ tableType | user | String | Yes | Table type enumeration |
| ∟ recentDay | 114-115 | String | No | Relative time (this item cannot be empty at the same time as the start time and the end time) |
| ∟ 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 |
| ∟ taIdMeasureVo | - | Object | No | Query ID system configuration |
| ∟ columnDesc | User unique ID | String | No | Field display name |
| ∟ columnName | #user_id | String | Yes | Field name |
| ∟ tableType | event | String | Yes | Table type enumeration |
| ∟ timeParticleSize | day | String | Yes | Unit of the time period taken for analysis day: based on days week: based on weeks month: based on months total: total |
| events | - | List | Yes | Event metric list |
| ∟ analysis | TOTAL_TIMES | String | No | Analysis aspect for distribution aggregation for Aggregate type enumeration for distribution analysis |
| ∟ analysisDesc | Total number | String | No | Analysis aspect description |
| ∟ customEvent | activity_attend.TIMES | String | No | Custom events |
| ∟ customFilters | [] | List | No | Custom event filtering |
| ∟ eventName | login | String | Yes | The eventName the metric based on, "anyEvent" can be used to represent any event |
| ∟ eventNameDisplay | String | No | Self-defined metric display name | |
| ∟ filts | - | List | No | List of conditions |
| ∟ columnDesc | City | String | No | Field display name |
| ∟ columnName | city | String | Yes | Field name |
| ∟ comparator | equal | String | Yes | Reference: filtering expression of model query API |
| ∟ filterType | SIMPLE | String | No | Filter mode, SIMPLE: simple, COMPOUND: composite |
| ∟ ftv | ["Beijing"] | List | No | Property comparative with bound literial |
| ∟ specifiedClusterDate | 2022-01-27 | String | No | Historical tag version of specified date |
| ∟ tableType | user | String | Yes | Table type enumeration |
| ∟ timeUnit | String | No | Filter time unit | |
| ∟ intervalType | user_defined | String | No | Interval range type Discrete: number Def: default interval user_defined: User-defined |
| ∟ quota | String | No | Metric property (combined with analysis, indicating the property involved and the analysis perspective) | |
| ∟ quotaIntervalArr | [500] | List | No | User defined metric interval |
| ∟ relation | and | String | No | Logical relationship, and: logical and, or: logical or |
| ∟ type | normal | String | Yes | Type of metric, Normal: positive Customized: Custom |
| 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 |
# Successful Response Example
{
"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"
}
# Response Parameter Description
| Parameter name | Sample value | Parameter type | Parameter description |
|---|---|---|---|
| return_code | 0 | Integer | Return code |
| return_message | success | String | Return message |
| data | - | Object | Return result |
| ∟ distribution_interval | [",500","500,"] | List | Distribution interval |
| ∟ result_generate_time | 2022-01-27 11:25:44 | String | Results generation time |
| ∟ x | ["2021-10-04"] | List | X-axis information |
| ∟ y | - | List | Y-axis information |
| ∟ {key} | 2021-10-04 | String | Date string |
| ∟ {value} | - | List | Date data |
| ∟ isTotal | false | Boolean | Is Total |
| ∟ values | - | List | Metric value |
| ∟ meanwhileValues | - | List | Simultaneous metric value |
Error Response Example
{
"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 |
# Distribution Analysis Full Data Download
Interface URL
/open/streaming-download/distribution-analyze?token=xxx
Request method
POST
Content-Type
application/json
Request Query Parameter
| Parameter name | Sample value | Parameter type | Mandatory or not | Parameter description |
|---|---|---|---|---|
| token | xxx | String | Yes | Query key |
# Request Body parameter
{
"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']"
}
# Request Parameter Description
| 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 |
TIP
The main structure of request parameters could be exported from the distribution analysis screen of the TE system, while such parameters as "interval", "meanwhileOnly" could be added to download data.
# Response
Same with the full data download of the distribution analysis of the TE system
# Distribution Analysis User List
Interface URL
/open/distribution-user-list?token=xxx
Request method
POST
Content-Type
application/json
Request Query Parameter
| Parameter name | Sample value | Parameter type | Is required | Parameter description |
|---|---|---|---|---|
| token | xxx | String | Yes | token |
# Request Body Parameter
{
"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
}
# Request Parameter Description
| 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 | 否 | 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 |
# Successful Response Example
{
"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"
}
# Response Parameter Description
| Parameter name | Sample value | Parameter type | Parameter description |
|---|---|---|---|
| return_code | 0 | Integer | Return code |
| return_message | success | String | Return information |
| data | - | Object | Return result |
| ∟ datalist | - | List | User Information |
| ∟ columMeta | - | Map | Field meaning mapping |
Error Response Example
{
"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 |
# Download of Distribution Analysis User List
Interface URL
/open/streaming-download/distribution-user-list?token=xxx
Request method
POST
Content-Type
application/json
Request Query parameters
| Parameter name | Sample value | Parameter type | Mandatory or not | Parameter description |
|---|---|---|---|---|
| token | xxx | String | Yes | Query key |
# Request Body Parameters
{
"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": ["VIVO应用商城"],
"selectedColumns": ["#account_id", "#distinct_id"]
}
# Request Parameter Description
| Parameter name | Sample value | Parameter type | Mandatory or not | Parameter description |
|---|---|---|---|---|
| projectId | 0 | String | 是 | Project numeric identity |
| eventView | - | Object | 是 | Same parameters as Distribution Analysis Query interface |
| events | - | List | 是 | Same parameters as Distribution Analysis Query interface |
| interval | 10,20 | String | 是 | Go to detail by which metric interval |
| groupBit | 0 | Integer | 否 | Go to detail by total or not |
| sliceDate | "2019-11-18" | String | 否 | Go to detail by which date |
| sliceGroupVal | ["北京市"] | String | 是 | Go to detail by which group |
| selectedColumns | ["#account_id"] | array | 否 | The columns to be downloaded |
# Response
Same with the download of the distribution analysis user list of the TE system.
# Generic enumeration for distribution analysis
# Aggregate type enumeration for distribution analysis
| 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 |