# Distributed Analysis Model API
Call method See Call method description in Open API doc.
You can read the distribution analysis 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 | Grouping properties |
| ∟ 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 | Custom attribute interval | |
| ∟ specifiedClusterDate | 2022-01-24 | String | No | Cluster specified date |
| ∟ tableType | user | String | Yes | Table type, event: transaction table, user: user table |
| ∟ 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 | Analyze subject configuration |
| ∟ columnDesc | User unique ID | String | No | Field display name |
| ∟ columnName | #user_id | String | Yes | Field name |
| ∟ tableType | event | String | Yes | Table type, event: transaction table, user: user table |
| ∟ timeParticleSize | day | String | Yes | Unit of time for analysis Press 1 minute Minute 5: Press 5 minutes (v3.5 starts to support) Minute 10: Press 10 minutes (v3.5 start support) By the hour By day Week: by week Month: by month Total: total |
| events | - | List | Yes | List of event indicators |
| ∟ analysis | TOTAL_TIMES | String | No | Analysis angle, see the table below |
| ∟ analysisDesc | Total number | String | No | Analysis angle description (display name) |
| ∟ customEvent | activity_attend.TIMES | String | No | Custom events |
| ∟ customFilters | [] | List | No | Custom event filtering |
| ∟ eventName | login | String | Yes | Event type, in particular, you can use anyEvent to represent any event |
| ∟ eventNameDisplay | String | No | Event 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: Filtered expression for model query API |
| ∟ filterType | SIMPLE | String | No | Filter mode, SIMPLE: simple, COMPOUND: composite |
| ∟ ftv | ["Beijing"] | List | No | Property comparison value |
| ∟ specifiedClusterDate | 2022-01-27 | String | No | Cluster specified date |
| ∟ tableType | user | String | Yes | Table type, event: transaction table, user: user table |
| ∟ timeUnit | String | No | Filter time unit | |
| ∟ formulation | - | Object | No | New formula entity |
| ∟ formulationDeps | - | List | No | Formula dependence |
| ∟ event | - | Object | No | Dependency events |
| ∟ eventDesc | Participate in activities | String | No | Event display name |
| ∟ eventName | activity_attend | String | Yes | Event type |
| ∟ intervalType | user_defined | String | No | Interval interval type Discrete number Def: default interval user_defined: User-defined |
| ∟ quota | String | No | Indicator Attributes | |
| ∟ quotaIntervalArr | [500] | List | No | Indicator range |
| ∟ relation | and | String | No | Logical relationship, and: logical and, or: logical or |
| ∟ type | normal | String | Yes | Type of indicator, Normal: positive Customized: Custom |
| projectId | 0 | Integer | Yes | Project ID |
| 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 |
Distribution analysis aggregation method analysis value:
| 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 |
# 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 information |
| 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 |
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 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
{
"projectId": 0,
"eventView": {
"startTime": "2019-10-28 00:00:00",
"endTime": "2019-11-26 00:00:00",
"recentDay": "D31",
"timeParticleSize": "week",
"groupBy": [
{
"columnName": "#province",
"tableType": "event"
}
]
},
"events": [{
"analysis": "TIMES",
"eventName": "consume_item",
"intervalType": "def",
"quota": "",
"relation": "and",
"filts": [
{
"columnName": "#os",
"comparator": "equal",
"ftv": [
"android"
],
"tableType": "event"
}
]
}],
"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 | Parameter description |
| eventView | - | Object | Yes | Group property table |
| ∟ startTime | 2019-10-28 00:00:00 | String | No | Start time (format: yyyy-MM-dd HH: mm: ss), valid when the relative time is empty |
| ∟ endTime | 2019-11-26 00:00:00 | String | No | End time (format: yyyy-MM-dd HH: mm: ss), valid when the relative time is empty |
| ∟ recentDay | D31 | String | No | Relative time (this item cannot be empty at the same time as the start time and the end time) |
| ∟ timeParticleSize | week | String | Yes | Unit of time for analysis Press 1 minute Minute 5: Press 5 minutes (v3.5 starts to support) Minute 10: Press 10 minutes (v3.5 start support) By the hour By day Week: by week Month: by month Total: total |
| ∟ groupBy | - | List | No | Group attributes, can have zero or more |
| ∟ columnName | #city | String | Yes | Field name |
| ∟ tableType | event | String | Yes | Table type, event: transaction table, user: user table |
| events | List | Yes | List of event indicators | |
| ∟ eventName | consume_item | String | Yes | Event type, in particular, you can use anyEvent to represent any event |
| ∟ analysis | TIMES | String | No | Analysis types, aggregation operations, see the table below |
| ∟ quota | String | No | Indicator attributes (with analysis, meaning which attribute of which analysis angle) | |
| ∟ relation | and | String | No | Logical relationship, and: logical and, or: logical or |
| ∟ intervalType | def | String | Yes | Discrete number Def: default interval user_defined: User-defined |
| ∟ filts | - | List | No | Filter List |
| ∟ columnName | #os | String | Yes | Field name |
| ∟ comparator | equal | String | Yes | Reference: Filtered expression for model query API |
| ∟ ftv | ["android"] | List | No | Property comparison value |
| ∟ tableType | event | String | Yes | Table type, event: transaction table, user: user table |
| interval | 10,20 | String | No | [10, 20) hours |
| sliceDate | "2019-11-18" | String | No | 2019-11-18 Week |
| sliceGroupVal | ["Beijing"] | String | Yes | Event location grouping |
| 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 |