主题
数据集
数据集说明
数据集定义
数据集是结构化的数据的集合，对外展示的形式是一张数据表。根据数据集数据的来源，数据集可以分成数据连接，SQL查询，多表联合，数据聚合，数据合并等种类。其中，数据连接 类型的数据集的数据来自某个数据源中的某张数据表；SQL查询类型的数据集的数据来自某个数据源中的SQL语句查询生成的结果；多表联合类型的数据集的数据来自已经存在的两个或两个以上的数据集通过字段连接（join）生成的结果；数据聚合 类型的数据集的数据来自已经存在的一个数据集通过字段分组聚合生成的结果；数据合并类型的数据集的数据来自已经存在的两个或两个以上的数据集通过字段对齐后的行合并（union）生成的结果；
数据集结构说明
| 字段 | 类型 | 描述 |
|---|---|---|
| appId | LONG | 数据集所属的应用的 id |
| id | LONG | 数据集的 id |
| title | STRING | 数据集的标题 |
| createdAt | DATETIME | 数据集创建的时间 |
| createdBy | INTEGER | 数据集创建用户的 id |
| updatedAt | DATETIME | 数据集最后更新的时间 |
| updatedBy | INTEGER | 数据集最后修改用户的 id |
| status | INTEGER | 数据集的状态，见状态说明 |
| importType | INTEGER | 数据集是否导入引擎，0 为不导入，1 为导入 |
| importMsg | STRING | 数据集无法导入引擎时的具体原因 |
| importStatus | INTEGER | 数据集导入引擎状态，见导入引擎状态 |
| importOptions | OBJECT | 数据集导入设置，见数据集更新方法结构说明 |
| options | OBJECT | 数据集配置信息 |
| options.type | STRING | 数据集类型，数据集类型有： connection，fusion，union，aggregate，reference,pivot,unpivot |
| options.he | OBJECT | 根据数据集类型定义的HE表达式，目前暂时只有pivot和unpivot是这样做的，其他类型的保留旧格式 |
| options.storageType | STRING | 数据集执行计算的数据源的类型 |
| options.storageConnectionId | INTEGER | 数据集执行计算的数据源的"数据连接id" |
| options.appendDatasets | INTEGER 数组 | 追加到该数据集的数据集列表 |
| options.schema | OBJECT 数组 | 数据集中各字段元信息 |
| options.schema[].fieldName | STRING | 字段名 |
| options.schema[].type | STRING | 字段类型，字段类型包含： number，date，string，bool，json，unknown 6种 |
| options.schema[].nativeType | STRING | 字段数据源内部类型，和具体数据源相关，比如BIGINT，VARCHAR等 |
| options.schema[].originType | STRING | 字段原始类型，字段类型包含： number，date，string，bool，json，unknown 6种 |
| options.schema[].suggestedTypes | STRING 数组 | 字段允许选择的类型，类型包含： number，date，string，bool，json，unknown 6种 |
| options.schema[].visible | BOOL | 字段是否隐藏，包括 true 和 false |
| options.schema[].label | STRING | 字段的别名 |
| options.schema[].dbFieldName | STRING | 字段对应的数据库中的字段名，只有在 fieldName 和数据库里的字段名不一致的情况下需要设值，目前只用于替换数据集的时候 |
| hsVersion | INTEGER | 可选，本次编辑的版本号，从0开始，修改前先GET待修改资源获取当前版本号，修改时带上刚刚获取的版本号，服务端会检查并发冲突。不带版本号不检查并发冲突。 |
| entityGroup | STRING | 数据集的执行计划类别，用于管理执行计划，固定为DATASET |
| entityKey | STRING | 数据集的执行计划关键字，用于管理执行计划，数据集的格式为{appId}-{datasetId} |
| execDetail | OBJECT | 创建执行计划需要用到的任务描述信息，详见执行计划 |
| updateMethodSwitchable | BOOL | 本数据集是否支持设置增量更新 |
| extraOptions | OBJECT | 数据集的扩展配置信息 |
| options.apiOptions | OBJECT | api数据集配置信息 |
| options.apiOptions.path | STRING | api请求路径 |
| options.apiOptions.method | STRING | api请求方法(GET |
| options.apiOptions.body | STRING | api请求方法请求体 |
| options.apiOptions.params | LIST | api请求查询参数 |
| options.apiOptions.headers | LIST | api请求请求头 |
| options.apiOptions.pageConfig | OBJECT | api请求分页配置 |
| options.apiOptions.pageConfig.name | STRING | 分页参数名称 |
| options.apiOptions.pageConfig.pageType | STRING | 分页类型(PAGE |
| options.apiOptions.pageConfig.defaultValue | LONG | 分页默认值 |
| options.apiOptions.authConfig | OBJECT | api请求认证配置 |
| options.apiOptions.authConfig.authType | STRING | 认证类型(NONE |
| options.apiOptions.authConfig.tokenRequestUrl | STRING | OAUTH2认证获取token请求地址 |
| options.apiOptions.authConfig.clientId | STRING | OAUTH2认证clientId参数 |
| options.apiOptions.authConfig.clientSecret | STRING | OAUTH2认证clientSecret参数 |
| options.apiOptions.authConfig.scope | STRING | OAUTH2认证scope参数 |
| options.apiOptions.authConfig.tokenSendingMethod | STRING | OAUTH2认证token发送方式(HEADER |
| options.apiOptions.authConfig.tokenName | STRING | OAUTH2认证token参数名称(用于参数替换) |
| options.apiOptions.authConfig.responseFieldName | STRING | OAUTH2认证响应中的token对应的字段名 |
| options.apiOptions.authConfig.grantType | STRING | OAUTH2认证grantType参数 |
| options.apiOptions.authConfig.userName | STRING | BASIC认证用户名 |
| options.apiOptions.authConfig.password | STRING | BASIC认证密码 |
| chatWeight | INTEGER | AI助手在进行回答时，选择数据集步骤，本数据集计算相关度的权重，要求在1-100范围 |
| chatDesc | STRING | AI助手在进行回答时，使用数据集描述进行相关度搜索，并把数据集描述给大模型做回答参考 |
| chatExample | STRING | 数据集相关的ai的例子 |
数据集状态说明
| 状态值 | 意义 |
|---|---|
| 0 | NONE， 默认值 |
| 1 | PENDING，创建后等待异步计算 |
| 2 | RUNNING，创建后异步计算中 |
| 3 | SUCCESS，成功 |
| 4 | FAIL， 创建后计算失败 |
| 5 | PENDING_REFRESH， 刷新后等待异步计算 |
| 6 | REFRESHING， 刷新后异步计算中 |
| 7 | REFRESH_FAIL， 刷新后计算失败 |
| 8 | PENDING_EDIT， 编辑后等待异步计算 |
| 9 | EDITING， 编辑后异步计算中 |
| 10 | EDIT_FAIL，编辑后计算失败 |
| 11 | EMPTY， 从应用模板导入的数据集，数据集数据为空 |
| 12 | IMPORT_JSON，含有json拆分列的导入引擎数据集，正在做列拆分列持久化 |
数据集导入引擎状态说明
| 状态值 | 意义 |
|---|---|
| 0 | NONE，默认值 |
| 1 | SUCCESS，导入引擎成功 |
| 2 | FAILED，导入引擎失败 |
| 3 | WAITING，等待导入引擎 |
| 4 | RUNNING，正在导入引擎 |
数据集数据datasetResultDto说明
| 字段 | 类型 | 描述 |
|---|---|---|
| schema | OBJECT数组 | 每一个元素表示一个数据集字段的属性，与数据集的 options.schema 相同 |
| data | OBJECT数组 | 每一个元素是一行数据,一行中每个值与schema元素一一对应 |
| gcExcelJson | STRING | 葡萄城模板用数据渲染后的excel转成json字符串 |
| gcExcelCellErrors | OBJECT | 预览复杂表格具体cell报错信息，key是单元格下标，比如A2，全局错误key为default，value是具体错误消息 |
- 例子:
json
{
"schema": [
{
fieldName: "id",
hsVersion: 2,
type: "number",
config: {
dialectName: "PostgresqlDialect"
}
…
},
{
fieldName: "zh_name",
hsVersion: 2,
type: "string",
config: {},
label: "zh_name"
…
},
{
fieldName: "prime_genre",
hsVersion: 2,
type: "string",
config: {},
label: "prime_genre"
…
}
],
"data": [
[
1,
"星际穿越",
"剧情"
],
[
2,
"辛德勒的名单",
"剧情"
],
[
3,
"唐伯虎点秋香",
"喜剧"
]
]
}数据集结构补充说明
除了数据集结构说明中的字段，还有一些字段是api经过处理返回的数据，表达一些业务含义。这些字段不会存在于 request payload 中。
| 字段 | 类型 | 描述 |
|---|---|---|
| functions | OBJECT | 数据集所支持的函数列表 |
| importSwitchable | BOOLEAN | 数据集是否支持导入引擎 |
| hide | BOOLEAN | 数据集是否隐藏 |
数据集更新方法结构说明
| 字段 | 类型 | 描述 |
|---|---|---|
| updateMethod | STRING | 更新方法，ALL表示全量，INCREMENTAL表示增量 |
| incrementalField | STRING 数组 | 增量更新的字段名称列表 |
| batchFetchSize | integer | 某些不支持游标读取的数据源比如hologres，每次查询数据的量，按这个量分批读取 |
| keyFields | STRING 数组 | 导入引擎的表的键字段，用作表的分布键 |
| createTableProperties | STRING | 导入引擎的表的建表属性 |
接口说明
创建数据集
支持创建五种类型的数据集：数据连接，SQL查询，多表联合，数据聚合，数据合并, 引用。每种数据集的共同结构见数据集结构说明。除此之外，每种数据集特有的结构，详见下文的样例。
请求URL
http
POST /api/apps/${appId}/datasets HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 指定在appId对应的应用中创建数据集 |
Request Body 参数
每种数据集的共同结构见数据集结构说明。除此之外，每种数据集特有的结构，详见下文的样例。
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 每种数据集的共同结构见数据集结构说明。除此之外，每种数据集特有的结构，详见下文的样例。 |
接口示例1: 创建“数据连接”数据集
数据连接数据集特有结构
| 字段 | 类型 | 描述 |
|---|---|---|
| options.type | STRING | 数据集类型，数据连接数据集的 type 为 connection |
| options.origin | STRING | 数据集创建的数据来源，有：postgresql，mysql，sqlserver，oracle，hive等 |
| options.connectionId | INTEGER | 表的来源数据库"数据连接id" |
| options.path | STRING 数组 | 数据库的名字空间路径，跟数据源相关，比如 mysql 是数据库，postgresql 是 schema ，sqlserver 是数据库和 schema |
| options.table | STRING | 用于生成数据集，原始数据库中的表名字 |
| options.where | HE 数组 | 衡石表达式数组，用于过滤 table 中的数据 |
| options.refreshHours | INTEGER 数组 | 每天哪些小时需要刷新数据集，合法值为 0-23 为空表示不刷新 |
| options.refreshMinute | STRING | 刷新在哪分钟执行，合法值为0-59 |
http
POST /api/apps/1/datasets HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"importType": 0,
"options": {
"connectionId": 4,
"origin": "postgresql",
"path": [
"public"
],
"schema": [
{
"basicType": "integer",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"distinct": false,
"fieldName": "f1",
"label": "f1",
"nativeType": "int4",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
}
],
"table": "t11",
"type": "connection"
},
"title": "t11"
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": {
"appId": 1,
"createdAt": "2019-12-06 17:19:40",
"createdBy": 1,
"datasetAcl": {
"dataFilters": [],
"level": "FULLACCESS"
},
"emptyDataset": false,
"id": 17,
"importType": 0,
"options": {
"analytic": false,
"cache": false,
"connectionCategory": "Database",
"connectionId": 4,
"connectionTitle": "pg 211.4",
"dialectOptions": {
"dialectName": "PostgresqlDialect",
"majorVersion": 9,
"minorVersion": 6
},
"header": 0,
"metrics": [],
"origin": "postgresql",
"padHeader": false,
"path": [
"public"
],
"refreshHours": [],
"refreshMinute": 0,
"rowCount": 0,
"schema": [
{
"appId": 1,
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"datasetId": 17,
"defaultAggrType": "sum",
"fieldName": "f1",
"label": "f1",
"suggestedTypes": [
"number"
],
"type": "number",
"visible": true
}
],
"storageConnectionId": 4,
"storageType": "postgresql",
"table": "t11",
"totalSize": 0,
"transpose": false,
"type": "connection"
},
"origin": "postgresql",
"public": true,
"refreshSchema": false,
"status": 1,
"title": "t11",
"type": "connection",
"updatedAt": "2019-12-06 17:19:40",
"updatedBy": 1,
"visible": true
},
"msg": "success",
"version": "version@9a5e106#6730f0d",
}接口示例2：创建“SQL查询”数据集
和数据连接数据集基本一样，除了table字段去掉，使用customSql字段。 SQL查询数据集特有结构
| 字段 | 类型 | 描述 |
|---|---|---|
| options.type | STRING | 数据集类型，SQL查询数据集的 type 为 connection |
| options.customSql | STRING | 用于生成数据集，原始数据库中的一个查询语句 |
http
POST /api/apps/1/datasets HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"importType": 0,
"options": {
"connectionId": 4,
"customSql": "select * from t11",
"origin": "postgresql",
"path": [
"public"
],
"schema": [
{
"basicType": "integer",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"distinct": false,
"fieldName": "f1",
"label": "f1",
"nativeType": "int4",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
}
],
"type": "connection"
},
"title": "sql"
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": {
"appId": 1,
"createdAt": "2019-12-06 17:51:26",
"createdBy": 1,
"datasetAcl": {
"dataFilters": [],
"level": "FULLACCESS"
},
"emptyDataset": false,
"id": 18,
"importType": 0,
"options": {
"analytic": false,
"cache": false,
"connectionCategory": "Database",
"connectionId": 4,
"connectionTitle": "pg 211.4",
"customSql": "select * from t11",
"dialectOptions": {
"dialectName": "PostgresqlDialect",
"majorVersion": 9,
"minorVersion": 6
},
"header": 0,
"metrics": [],
"origin": "postgresql",
"padHeader": false,
"path": [
"public"
],
"refreshHours": [],
"refreshMinute": 0,
"rowCount": 0,
"schema": [
{
"appId": 1,
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"datasetId": 18,
"defaultAggrType": "sum",
"fieldName": "f1",
"label": "f1",
"suggestedTypes": [
"number"
],
"type": "number",
"visible": true
}
],
"storageConnectionId": 4,
"storageType": "postgresql",
"totalSize": 0,
"transpose": false,
"type": "connection"
},
"origin": "postgresql",
"public": true,
"refreshSchema": false,
"status": 1,
"title": "sql",
"type": "connection",
"updatedAt": "2019-12-06 17:51:26",
"updatedBy": 1,
"visible": true
},
"msg": "success",
"version": "version@9a5e106#6730f0d",
}接口示例3：创建“多表联合”数据集
多表联合数据集特有结构
| 字段 | 类型 | 描述 |
|---|---|---|
| options.type | STRING | 数据集类型，多表联合数据集的 type 为 fusion |
| options.rootDatasetId | INTEGER | 关联的基础数据集 id |
| options.rootDatasetName | STRING | 关联的基础数据集在关系中的名字，如果为空，显示数据集原来的名字 |
| options.uid | STRING | 关联的基础数据集在关联关系中的uid |
| options.joinOpts | OBJECT 数组 | 关联的条件 ，每增加一个数据，增加一个条件 |
| options.joinOpts[].joinType | STRING | 关联的方式，关联方式有以下 4 种：left join，right join，full join，inner join |
| options.joinOpts[].joinDatasetId | INTEGER | 关联的数据集 id |
| options.joinOpts[].joinDatasetName | STRING | 关联的数据集在关系中的名字，如果为空，显示数据集原来的名字 |
| options.joinOpts[].datasetIndex | INTEGER | 关联的数据集重复拉入关系的次数，为0或者空表示第一个 |
| options.joinOpts[].uid | STRING | 数据集在关联关系中的uid |
| options.joinOpts[].joinOn | OBJECT 数组的数组 | 参与关联的字段，内层数组只有两个成员，第一个成员和第二个成员在关联的时候相等，外层数组之间是 AND 的逻辑关系 |
| options.joinOpts[].joinOn[][0].field | STRING | 参与关联的字段 |
| options.joinOpts[].joinOn[][0].type | STRING | 关联的字段类型，包含： number，date，string，bool，json，unknown 6种 |
| options.joinOpts[].joinOn[][0].datasetId | INTEGER | 关联字段所属的数据集 id |
| options.joinOpts[].joinOn[][0].uid | STRING | 关联字段所属的数据集的uid |
| options.where | HE 数组 | 衡石表达式数组，用于过滤数据 |
http
POST /api/apps/1/datasets HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"options": {
"cache": false,
"joinOpts": [
{
"joinDatasetId": 18,
"joinOn": [
[
{
"datasetId": 17,
"field": "f1",
"type": "number"
},
{
"datasetId": 18,
"field": "f1",
"type": "number"
}
]
],
"joinType": "left join"
}
],
"rootDatasetId": 17,
"schema": [
{
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"distinct": false,
"fieldName": "f1_17",
"label": "f1",
"nativeType": "int4",
"oriLabel": "f1",
"oriName": "f1",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"distinct": false,
"fieldName": "f1_18",
"label": "sql f1",
"nativeType": "int4",
"oriLabel": "f1",
"oriName": "f1",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
}
],
"type": "fusion"
},
"title": "Fusion"
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": {
"appId": 1,
"createdAt": "2019-12-06 18:13:22",
"createdBy": 1,
"datasetAcl": {
"dataFilters": [],
"level": "FULLACCESS"
},
"emptyDataset": false,
"id": 21,
"options": {
"analytic": false,
"cache": false,
"dialectOptions": {
"dialectName": "PostgresqlDialect",
"majorVersion": 9,
"minorVersion": 6
},
"header": 0,
"joinOpts": [
{
"joinDatasetId": 18,
"joinOn": [
[
{
"datasetId": 17,
"field": "f1",
"type": "number"
},
{
"datasetId": 18,
"field": "f1",
"type": "number"
}
]
],
"joinType": "left join"
}
],
"metrics": [],
"padHeader": false,
"refreshHours": [],
"refreshMinute": 0,
"rootDatasetId": 17,
"rowCount": 0,
"schema": [
{
"appId": 1,
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"datasetId": 21,
"defaultAggrType": "sum",
"fieldName": "f1_17",
"label": "f1",
"suggestedTypes": [
"number"
],
"type": "number",
"visible": true
},
{
"appId": 1,
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"datasetId": 21,
"defaultAggrType": "sum",
"fieldName": "f1_18",
"label": "sql f1",
"suggestedTypes": [
"number"
],
"type": "number",
"visible": true
}
],
"storageConnectionId": 4,
"storageType": "postgresql",
"totalSize": 0,
"transpose": false,
"type": "fusion"
},
"public": true,
"refreshSchema": false,
"status": 1,
"title": "Fusion",
"type": "fusion",
"updatedAt": "2019-12-06 18:13:22",
"updatedBy": 1,
"visible": true
},
"msg": "success",
"version": "version@9a5e106#6730f0d",
}接口示例4：创建“数据聚合”数据集
数据聚合数据集特有结构
| 字段 | 类型 | 描述 |
|---|---|---|
| options.type | STRING | 数据集类型，数据聚合数据集的 type 为 aggregate |
| options.rootDatasetId | INTEGER | 数据聚合的基础数据集 id |
| options.aggregateOptions | OBJECT | 聚合方式描述，具体结构参考“图表”的options |
| options.where | HE 数组 | 衡石表达式数组，用于过滤数据 |
http
POST /api/apps/1/datasets HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"options": {
"aggregateOptions": {
"axes": [
{
"args": [
{
"dataset": 21,
"kind": "field",
"op": "f1_17"
}
],
"axisName": "group",
"datasetId": 21,
"fieldName": "f1_17",
"fieldType": "number",
"keyChain": [
"group",
"none"
],
"kind": "function",
"labelOrigin": "f1",
"noFormatter": true,
"op": "group",
"parentUid": null,
"scaleRange": {
"max": 0,
"maxAuto": true,
"min": 0,
"minAuto": true
},
"uid": "u_5bc7bb2c59f6703e_0"
},
{
"args": [
{
"dataset": 21,
"kind": "field",
"op": "f1_18"
}
],
"axisName": "size",
"datasetId": 21,
"fieldName": "f1_18",
"fieldType": "number",
"keyChain": [
"sum",
"none"
],
"kind": "function",
"labelOrigin": "sql f1",
"noFormatter": true,
"op": "sum",
"parentUid": null,
"scaleRange": {
"max": 0,
"maxAuto": true,
"min": 0,
"minAuto": true
},
"uid": "u_8e5a3c02fe95743f_1"
}
],
"having": [],
"limit": -1,
"sort": [],
"timebar": {
"current": "dateExp",
"dateExp": "All Avaliable Date",
"dateRange": [],
"show": false
},
"where": []
},
"rootDatasetId": 21,
"schema": [
{
"basicType": "integer",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"fieldName": "u_5bc7bb2c59f6703e_0",
"label": "f1",
"nativeType": "int4",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "number",
"fieldName": "u_8e5a3c02fe95743f_1",
"label": "sql f1",
"nativeType": "numeric",
"originType": "number",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
}
],
"type": "aggregate"
},
"title": "aggregate"
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": {
"appId": 1,
"createdAt": "2019-12-06 18:44:10",
"createdBy": 1,
"datasetAcl": {
"dataFilters": [],
"level": "FULLACCESS"
},
"emptyDataset": false,
"id": 22,
"options": {
"aggregateOptions": {
"axes": [
{
"args": [
{
"dataset": 21,
"kind": "field",
"op": "f1_17"
}
],
"axisName": "group",
"datasetId": 21,
"fieldName": "f1_17",
"fieldType": "number",
"keyChain": [
"group",
"none"
],
"kind": "function",
"labelOrigin": "f1",
"noFormatter": true,
"op": "group",
"scaleRange": {
"max": 0,
"maxAuto": true,
"min": 0,
"minAuto": true
},
"uid": "u_5bc7bb2c59f6703e_0"
},
{
"args": [
{
"dataset": 21,
"kind": "field",
"op": "f1_18"
}
],
"axisName": "size",
"datasetId": 21,
"fieldName": "f1_18",
"fieldType": "number",
"keyChain": [
"sum",
"none"
],
"kind": "function",
"labelOrigin": "sql f1",
"noFormatter": true,
"op": "sum",
"scaleRange": {
"max": 0,
"maxAuto": true,
"min": 0,
"minAuto": true
},
"uid": "u_8e5a3c02fe95743f_1"
}
],
"having": [],
"limit": -1,
"sort": [],
"timebar": {
"current": "dateExp",
"dateExp": "All Avaliable Date",
"dateRange": [],
"show": false
},
"where": []
},
"analytic": false,
"cache": false,
"dialectOptions": {
"dialectName": "PostgresqlDialect",
"majorVersion": 9,
"minorVersion": 6
},
"header": 0,
"metrics": [],
"padHeader": false,
"refreshHours": [],
"refreshMinute": 0,
"rootDatasetId": 21,
"rowCount": 0,
"schema": [
{
"appId": 1,
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"datasetId": 22,
"defaultAggrType": "sum",
"fieldName": "u_5bc7bb2c59f6703e_0",
"label": "f1",
"suggestedTypes": [
"number"
],
"type": "number",
"visible": true
},
{
"appId": 1,
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"datasetId": 22,
"defaultAggrType": "sum",
"fieldName": "u_8e5a3c02fe95743f_1",
"label": "sql f1",
"suggestedTypes": [
"number"
],
"type": "number",
"visible": true
}
],
"storageConnectionId": 4,
"storageType": "postgresql",
"totalSize": 0,
"transpose": false,
"type": "aggregate"
},
"public": true,
"refreshSchema": false,
"status": 1,
"title": "aggregate",
"type": "aggregate",
"updatedAt": "2019-12-06 18:44:10",
"updatedBy": 1,
"visible": true
},
"msg": "success",
"version": "version@9a5e106#6730f0d",
}接口示例5：创建“数据合并”数据集
“数据合并”数据集仅当来源数据集的 storageType 为 engine （数据在引擎中）的时候才能创建。 数据合并数据集特有结构
| 字段 | 类型 | 描述 |
|---|---|---|
| options.type | STRING | 数据集类型，数据合并数据集的 type 为 union |
| options.unionOptions | OBJECT | 描述数据合并（union）的方式 |
| options.unionOptions.unionSchema | OBJECT 数组 | 合并后数据集的 schema 信息 |
| options.unionOptions.unionSchema[].label | STRING | 合并后数据集字段别名 |
| options.unionOptions.unionSchema[].type | STRING | 合并后数据集字段的类型，包含： number，date，string，bool，json，unknown 6种 |
| options.unionOptions.fieldsMapping | OBJECT 数组 | 描述来源数据集字段对齐的方式 |
| options.unionOptions.fieldsMapping[].datasetId | INTEGER | 来源数据集的 id |
| options.unionOptions.fieldsMapping[].fieldNames | STRING 数组 | 来源数据集的字段名称，约定按数组下标对齐 |
| options.unionOptions.fieldsMapping[].where | HE 数组 | 衡石表达式数组，用于过滤来源数据集中的数据 |
http
POST /api/apps/1/datasets HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"options": {
"schema": [
{
"basicType": "number",
"config": {
"dialectName": "EngineDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"fieldName": "union_0",
"label": "f1",
"nativeType": "int4",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
}
],
"type": "union",
"unionOptions": {
"append": false,
"fieldsMapping": [
{
"datasetId": 20,
"fieldNames": [
"f1"
],
"where": []
},
{
"datasetId": 23,
"datasetTitle": "t11 (1)",
"fieldNames": [
"f1"
],
"where": []
}
],
"unionSchema": [
{
"fieldName": "f1",
"label": "f1",
"type": "number"
}
]
}
},
"title": "t12 union"
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": {
"appId": 1,
"createdAt": "2019-12-06 19:11:29",
"createdBy": 1,
"datasetAcl": {
"dataFilters": [],
"level": "FULLACCESS"
},
"emptyDataset": false,
"id": 24,
"importType": 1,
"options": {
"analytic": false,
"cache": false,
"dialectOptions": {
"dialectName": "EngineDialect",
"majorVersion": 0,
"minorVersion": 0
},
"header": 0,
"metrics": [],
"padHeader": false,
"refreshHours": [],
"refreshMinute": 0,
"rowCount": 0,
"schema": [
{
"appId": 1,
"basicType": "number",
"config": {
"dialectName": "EngineDialect"
},
"datasetId": 24,
"defaultAggrType": "sum",
"fieldName": "union_0",
"label": "f1",
"suggestedTypes": [
"number"
],
"type": "number",
"visible": true
}
],
"storageConnectionId": 3,
"storageType": "engine",
"totalSize": 0,
"transpose": false,
"type": "union",
"unionOptions": {
"append": false,
"fieldsMapping": [
{
"datasetId": 20,
"fieldNames": [
"f1"
],
"where": []
},
{
"datasetId": 23,
"fieldNames": [
"f1"
],
"where": []
}
],
"unionSchema": [
{
"label": "f1",
"type": "number"
}
]
}
},
"public": true,
"refreshSchema": false,
"status": 1,
"title": "t12 union",
"type": "union",
"updatedAt": "2019-12-06 19:11:29",
"updatedBy": 1,
"visible": true
},
"msg": "success",
"version": "version@9a5e106#6730f0d",
}接口示例6：创建“引用”数据集
引用数据集自身没有独立的字段信息，来源数据集字段修改，引用数据集中会跟着修改。
引用数据集特有结构
| 字段 | 类型 | 描述 |
|---|---|---|
| options.type | STRING | 数据集类型，引用数据集的 type 为 reference |
| options.referenceOptions | OBJECT | 描述引用（reference）的源数据集 |
| options.referenceOptions.sourceAppId | INTEGER | 引用的来源数据集所在应用的 id |
| options.referenceOptions.sourceDatasetId | INTEGER | 引用的来源数据集的 id |
http
POST /api/apps/1/datasets HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"options": {
"type": "reference",
"referenceOptions": {
"sourceAppId": 154,
"sourceDatasetId": 1
}
},
"title": "demo"
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": {
"id": 6,
"title": "demo",
"createdBy": 1,
"createdAt": "2020-10-27 13:20:51",
"updatedBy": 1,
"updatedAt": "2020-10-27 13:20:51",
"visible": true,
"appId": 5998,
"options": {
"cache": false,
"type": "reference",
"totalSize": 0,
"rowCount": 0,
"refreshHours": [],
"refreshMinute": 0,
"transpose": false,
"header": 0,
"padHeader": false,
"storageType": "engine",
"dialectOptions": {
"dialectName": "EngineDialect",
"majorVersion": 8,
"minorVersion": 3
},
"storageConnectionId": 3,
"referenceOptions": {
"sourceAppId": 154,
"sourceAppTitle": "新建数据包",
"sourceAppPathName": [
"data_mart_root_folder"
],
"sourceDatasetId": 1,
"sourceDatasetTitle": "a_ivt_countries"
},
"metrics": [],
"schema": []
},
"status": 3,
"datasetAcl": {
"level": "FULLACCESS",
"dataFilters": []
},
"refreshSchema": false,
"type": "reference",
"public": true,
"emptyDataset": false
}
}接口示例7：创建“行转列”数据集
行转列数据集特有结构
| 字段 | 类型 | 描述 |
|---|---|---|
| options.type | STRING | 数据集类型，数据聚合数据集的 type 为 pivot |
| options.he | OBJECT | 行转列的HE表达式 |
http
POST /api/apps/123/datasets HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"options": {
"he": {
"kind": "function",
"op": "pivot",
"args": [
{
"kind": "function",
"op": "app_dataset",
"args": [
123, // 应用id
1 // 数据集id
]
},
[{"kind": "field", "op": "year"}], // 分组列列表
{ // 聚合列
"kind": "function",
"op": "sum",
"args": [
{
"kind": "field",
"op": "val"
}
]
},
{"kind": "field", "op": "month"}, // 转置列
[ // 转置列列值对应的列名
{"kind": "constant", "op": "一月", "uid": "Jan"},
{"kind": "constant", "op": "二月", "uid": "Feb"}
]
]
},
"schema": [
{
"basicType": "integer",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"fieldName": "year",
"label": "year",
"nativeType": "int4",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "number",
"fieldName": "val",
"label": "val",
"nativeType": "numeric",
"originType": "number",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "string",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "count",
"detectedType": "string",
"fieldName": "Jan",
"label": "Jan",
"nativeType": "varchar",
"originType": "string",
"suggestedTypes": [
"string"
],
"type": "string",
"visible": true
},
{
"basicType": "string",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "count",
"detectedType": "string",
"fieldName": "Feb",
"label": "Feb",
"nativeType": "varchar",
"originType": "string",
"suggestedTypes": [
"string"
],
"type": "string",
"visible": true
},
],
"type": "pivot"
},
"title": "pivot-title"
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": {
"appId": 123,
"createdAt": "2019-12-06 18:44:10",
"createdBy": 1,
"datasetAcl": {
"dataFilters": [],
"level": "FULLACCESS"
},
"emptyDataset": false,
"id": 2,
"options": {
"he": {
"kind": "function",
"op": "pivot",
"args": [
{
"kind": "function",
"op": "app_dataset",
"args": [
123, // 应用id
1 // 数据集id
]
},
[{"kind": "field", "op": "year"}], // 分组列列表
{ // 聚合列
"kind": "function",
"op": "sum",
"args": [
{
"kind": "field",
"op": "val"
}
]
},
{"kind": "field", "op": "month"}, // 转置列
[ // 转置列列值对应的列名
{"kind": "constant", "op": "一月", "uid": "Jan"},
{"kind": "constant", "op": "二月", "uid": "Feb"}
]
]
},
"schema": [
{
"basicType": "integer",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"fieldName": "year",
"label": "year",
"nativeType": "int4",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "number",
"fieldName": "val",
"label": "val",
"nativeType": "numeric",
"originType": "number",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "string",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "count",
"detectedType": "string",
"fieldName": "Jan",
"label": "Jan",
"nativeType": "varchar",
"originType": "string",
"suggestedTypes": [
"string"
],
"type": "string",
"visible": true
},
{
"basicType": "string",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "count",
"detectedType": "string",
"fieldName": "Feb",
"label": "Feb",
"nativeType": "varchar",
"originType": "string",
"suggestedTypes": [
"string"
],
"type": "string",
"visible": true
},
],
"type": "pivot"
},
"public": true,
"refreshSchema": false,
"status": 1,
"title": "pivot-title",
"updatedAt": "2019-12-06 18:44:10",
"updatedBy": 1,
"visible": true
},
"msg": "success",
"version": "version@9a5e106#6730f0d",
}接口示例8：创建“列转行”数据集
行转列数据集特有结构
| 字段 | 类型 | 描述 |
|---|---|---|
| options.type | STRING | 数据集类型，数据聚合数据集的 type 为 unpivot |
| options.he | OBJECT | 行转列的HE表达式 |
http
POST /api/apps/123/datasets HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"options": {
"he": {
"kind":"function",
"op":"unpivot",
"args": [
{
"kind": "function",
"op": "app_dataset",
"args": [
123, // 应用id
1 // 数据集id
]
},
{"kind": "field", "op": "month", "type": "string"}, // 存放列转行的key列，需要明确的 type
{"kind": "field", "op": "val"}, // 存放列转行的 value 列
[
{"kind": "field", "op": "Jan", "value": "一月"}, // 待转的列， value 表示转换后的key值
{"kind": "field", "op": "Feb", "value": "二月"}
]
]
}
"schema": [
{
"basicType": "integer",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"fieldName": "year",
"label": "year",
"nativeType": "int4",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "number",
"fieldName": "val",
"label": "val",
"nativeType": "numeric",
"originType": "number",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "string",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "count",
"detectedType": "string",
"fieldName": "month",
"label": "month",
"nativeType": "varchar",
"originType": "string",
"suggestedTypes": [
"string"
],
"type": "string",
"visible": true
}
],
"type": "unpivot"
},
"title": "unpivot-title"
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": {
"appId": 123,
"createdAt": "2019-12-06 18:44:10",
"createdBy": 1,
"datasetAcl": {
"dataFilters": [],
"level": "FULLACCESS"
},
"emptyDataset": false,
"id": 3,
"options": {
"he": {
"kind":"function",
"op":"unpivot",
"args": [
{
"kind": "function",
"op": "app_dataset",
"args": [
123, // 应用id
1 // 数据集id
]
},
{"kind": "field", "op": "month", "type": "number"}, // 存放列转行的key列，需要明确的 type
{"kind": "field", "op": "val"}, // 存放列转行的 value 列
[
{"kind": "field", "op": "Jan", "value": "一月"}, // 待转的列， value 表示转换后的key值
{"kind": "field", "op": "Feb", "value": "二月"}
]
]
}
"schema": [
{
"basicType": "integer",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "integer",
"fieldName": "year",
"label": "year",
"nativeType": "int4",
"originType": "integer",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "sum",
"detectedType": "number",
"fieldName": "val",
"label": "val",
"nativeType": "numeric",
"originType": "number",
"suggestedTypes": [
"number",
"string"
],
"type": "number",
"visible": true
},
{
"basicType": "string",
"config": {
"dialectName": "PostgresqlDialect"
},
"defaultAggrType": "count",
"detectedType": "string",
"fieldName": "month",
"label": "month",
"nativeType": "varchar",
"originType": "string",
"suggestedTypes": [
"string"
],
"type": "string",
"visible": true
}
],
"type": "unpivot"
},
"public": true,
"refreshSchema": false,
"status": 1,
"title": "unpivot-title",
"updatedAt": "2019-12-06 18:44:10",
"updatedBy": 1,
"visible": true
},
"msg": "success",
"version": "version@9a5e106#6730f0d",
}通过 ID 查询数据集信息
请求URL
http
GET /api/apps/${appId}/datasets/${datasetId} HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 数据集结构说明, 参照各种数据集的特殊结构说明 |
参考示例1
普通查询
http
GET /api/apps/1/datasets/1 HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": {
"id": 4,
"title": "有参1",
"createdBy": 2,
"createdAt": "2021-08-02 18:21:47",
"updatedBy": 2,
"updatedAt": "2021-08-02 18:21:47",
"visible": true,
"isDelete": false,
"appId": 24,
"options": {
"cache": false,
"type": "connection",
"totalSize": 284,
"rowCount": 1,
"rowCountValid": true,
"connectionTitle": "PG",
"refreshHours": [],
"refreshMinute": 0,
"connectionId": 4,
"connectionCategory": "Database",
"origin": "postgresql",
"table": "A_IVT_MOVIE",
"where": [
{
"op": "and",
"args": [
{
"op": "=",
"args": [
{
"op": "id",
"kind": "field",
"type": "number"
},
{
"op": "n",
"kind": "param",
"type": "number"
}
],
"kind": "function"
}
],
"kind": "function"
}
],
"path": [
"public"
],
"transpose": false,
"header": 0,
"padHeader": false,
"storageType": "postgresql",
"dialectOptions": {
"dialectName": "PostgresqlDialect",
"majorVersion": 10,
"minorVersion": 4
},
"storageConnectionId": 4,
"storageConnectionTitle": "PG",
"metrics": [],
"schema": [
{
"datasetId": 4,
"fieldName": "id",
"type": "number",
"label": "id",
"config": {
"dialectName": "PostgresqlDialect"
},
"visible": true,
"nativeType": "bigserial",
"suggestedTypes": [
"number",
"string"
],
"detectedType": "integer",
"comment": "",
"originType": "integer",
"defaultAggrType": "sum",
"basicType": "number"
},
{
"datasetId": 4,
"fieldName": "zh_name",
"type": "string",
"label": "zh_name",
"config": {},
"visible": true,
"nativeType": "bpchar",
"suggestedTypes": [
"string"
],
"detectedType": "string",
"comment": "",
"originType": "string",
"defaultAggrType": "count",
"basicType": "string"
}
]
},
"importType": 0,
"importStatus": 0,
"importOptions": {},
"status": 3,
"refreshStats": {
"refreshAt": "2021-08-02 18:21:47",
"executeRefreshAt": "2021-08-02 18:21:47",
"executeRefreshRowCountAt": 1627899707234
},
"datasetAcl": {
"level": "FULLACCESS",
"dataFilters": []
},
"fieldGroups": [],
"metricGroups": [],
"includeInAppScope": false,
"creator": {
"id": 2,
"name": "test",
"email": "anonymous@hengshi.com"
},
"updater": {
"id": 2,
"name": "test",
"email": "anonymous@hengshi.com"
},
"functions": [
"abs",
"acos"
],
"importSwitchable": true,
"updateMethodSwitchable": false,
"entityKey": "24-4",
"entityGroup": "DATASET",
"execDetail": {
"jobClass": "com.hengshi.nangaparbat.schedulejob.DatasetJob",
"jobParams": {
"app": 24,
"dataset": 4
},
"retryTimes": 1
},
"type": "connection",
"public": true,
"emptyDataset": false,
"origin": "postgresql",
"refreshSchema": false
}
}参考示例2
查询的数据集不可导入引擎时
http
GET /api/apps/1/datasets/1 HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...- 返回 返回值中包含了数据集的基本信息、创建者信息、编辑者信息、支持的函数列表和无法导入的原因说明。
json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": {
"id": 4,
"title": "有参1",
"createdBy": 2,
"createdAt": "2021-08-02 18:21:47",
"updatedBy": 2,
"updatedAt": "2021-08-02 18:21:47",
"visible": true,
"isDelete": false,
"appId": 24,
"options": {
"cache": false,
"type": "connection",
"totalSize": 284,
"rowCount": 1,
"rowCountValid": true,
"connectionTitle": "PG",
"refreshHours": [],
"refreshMinute": 0,
"connectionId": 4,
"connectionCategory": "Database",
"origin": "postgresql",
"table": "A_IVT_MOVIE",
"where": [
{
"op": "and",
"args": [
{
"op": "=",
"args": [
{
"op": "id",
"kind": "field",
"type": "number"
},
{
"op": "n",
"kind": "param",
"type": "number"
}
],
"kind": "function"
}
],
"kind": "function"
}
],
"path": [
"public"
],
"transpose": false,
"header": 0,
"padHeader": false,
"storageType": "postgresql",
"dialectOptions": {
"dialectName": "PostgresqlDialect",
"majorVersion": 10,
"minorVersion": 4
},
"storageConnectionId": 4,
"storageConnectionTitle": "PG",
"metrics": [],
"schema": [
{
"datasetId": 4,
"fieldName": "id",
"type": "number",
"label": "id",
"config": {
"dialectName": "PostgresqlDialect"
},
"visible": true,
"nativeType": "bigserial",
"suggestedTypes": [
"number",
"string"
],
"detectedType": "integer",
"comment": "",
"originType": "integer",
"defaultAggrType": "sum",
"basicType": "number"
},
{
"datasetId": 4,
"fieldName": "zh_name",
"type": "string",
"label": "zh_name",
"config": {},
"visible": true,
"nativeType": "bpchar",
"suggestedTypes": [
"string"
],
"detectedType": "string",
"comment": "",
"originType": "string",
"defaultAggrType": "count",
"basicType": "string"
}
]
},
"importType": 0,
"importStatus": 0,
"importOptions": {},
"status": 3,
"refreshStats": {
"refreshAt": "2021-08-02 18:21:47",
"executeRefreshAt": "2021-08-02 18:21:47",
"executeRefreshRowCountAt": 1627899707234
},
"datasetAcl": {
"level": "FULLACCESS",
"dataFilters": []
},
"fieldGroups": [],
"metricGroups": [],
"includeInAppScope": false,
"creator": {
"id": 2,
"name": "test",
"email": "anonymous@hengshi.com"
},
"updater": {
"id": 2,
"name": "test",
"email": "anonymous@hengshi.com"
},
"functions": [
"abs",
"acos"
],
"importSwitchable": false,
"updateMethodSwitchable": false,
"importMsg": "数据集使用了用户属性/应用参数过滤时无法导入引擎",
"entityKey": "24-4",
"entityGroup": "DATASET",
"execDetail": {
"jobClass": "com.hengshi.nangaparbat.schedulejob.DatasetJob",
"jobParams": {
"app": 24,
"dataset": 4
},
"retryTimes": 1
},
"type": "connection",
"public": true,
"emptyDataset": false,
"origin": "postgresql",
"refreshSchema": false
}
}分页查询数据集
请求URL
http
GET /api/apps/${appId}/datasets HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| orderBy | String | 否 | 排序字段名，比如 id，title，createdAt， updatedAt 等 |
| orderType | String | 否 | 排序规则，asc 或者 desc |
| meta | BOOLEAN | 否 | 是否只需要dataset的基本信息，true 表示只需要meta信息，默认是false |
| joinExcept | STRING | 否 | 排除不需要的信息，可选值为 schema，metrics，connection，user，也可以是它们的任意组合，用逗号分隔，比如 schema,measure。 |
| functions | BOOLEAN | 否 | 是否需要数据集所支持的函数信息 |
| createdByCurrent | BOOLEAN | 否 | 是否只需要列出当前用户创建的数据集 |
| excludeOptionsType | STRING | 否 | 排除 options.type 是所选值的数据集，可选值为 connection，fusion，union，aggregate |
| importStatus | INTEGER | 否 | 导入引擎的状态过滤，可选值按照 导入引擎状态 |
| showHide | BOOLEAN | 否 | 是否显示隐藏数据集 |
| offset | INTERGER | 否 | 偏移的值 |
| limit | INTERGER | 否 | 查询的最大个数 |
| supportUnion | BOOLEAN | 否 | 是否支持作为数据合并选择的第一个数据集，目前仅支持存储类型是MySQL，Postgresql，GreenplumDB，Oracle，DB2，Sqlserver，Vertica，ClickHouse，DaMeng，Tidb，SapHana，Hive，SparkSQL，Impala，Presto，Amazon Redshift，Amazon Athena，Maxcompute，hologres |
| storageConnectionId | INTERGER | 否 | 存储类型连接id，当有此参数时，列表只返回存储类型是该连接的数据集 |
| excludeEmpty | BOOLEAN | 否 | 是否排除状态为EMPTY的数据集(刚从应用模板导入的数据集) |
joinExcept的选项说明
| 值 | 说明 |
|---|---|
| schema | 不需要数据集的字段信息 |
| metrics | 不需要数据集的指标信息 |
| connection | 不需要数据集所用的数据连接名 |
| user | 不需要数据集的创建者和更新者的用户相信信息 |
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 数据集结构说明, 参照各种数据集的特殊结构说明 |
参考示例1
列出应用 1 下的数据集列表。用 updatedAt 字段降序排序，不是只要数据集基本信息，不需要字段、指标、连接信息，偏移15个，取接下来的20个值
http
GET /api/apps/1/datasets?offset=15&limit=20&orderBy=updatedAt&orderType=desc&meta=false&joinExcept=schema%2Cmetrics%2Cconnection HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": [
{
"id": 12,
"title": "NewTable",
"createdBy": 434,
"createdAt": "2019-11-05 10:42:55",
"updatedBy": 434,
"updatedAt": "2019-11-06 11:36:19",
"visible": true,
"isDelete": false,
"appId": 1,
"accessCount": 0,
"options": {
"cache": false,
"type": "connection",
"totalSize": 0,
"rowCount": 0,
"rowCountValid": true,
"connectionTitle": "SQLServer\t",
"refreshHours": [],
"refreshMinute": 0,
"connectionId": 1835,
"connectionCategory": "Database",
"origin": "sqlserver",
"customSql": "select * from NewTable",
"path": [
"test",
"guest"
],
"transpose": false,
"header": 0,
"padHeader": false,
"storageType": "sqlserver",
"dialectOptions": {
"dialectName": "SqlserverDialect",
"majorVersion": 0,
"minorVersion": 0
},
"storageConnectionId": 1835,
"storageConnectionTitle": "SQLServer\t",
"schema": [],
"metrics": []
},
"importType": 0,
"importStatus": 0,
"importOptions": {},
"status": 3,
"refreshStats": {
"refreshAt": "2019-11-05 10:42:55",
"executeRefreshAt": "2019-11-05 10:42:55",
"executeRefreshRowCountAt": 1572921775229
},
"datasetAcl": {
"level": "FULLACCESS",
"dataFilters": []
},
"hsVersion": 6,
"creator": {
"id": 434,
"name": "admin",
"email": "anonymous@hengshi.com"
},
"updater": {
"id": 434,
"name": "admin",
"email": "anonymous@hengshi.com"
},
"functions": [
{
"type": "string",
"args": [
{
"type": "string",
"placeholder": "s",
"desc": "文本类型参数"
}
],
"desc": "去掉字符串首尾的空格",
"name": "trim",
"categories": [
"string functions",
"non aggregate functions",
"new field functions"
],
"varArgs": false
}
],
"importSwitchable": false,
"public": true,
"origin": "sqlserver",
"refreshSchema": false,
"emptyDataset": false,
"type": "connection"
}
],
"totalHits": 23,
"offset": 15
}分页查询数据集和分组信息
请求URL
http
GET /api/apps/${appId}/datasets/datasets-groups HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| orderBy | String | 否 | 排序字段名，比如 id，title，createdAt， updatedAt 等 |
| orderType | String | 否 | 排序规则，asc 或者 desc |
| meta | BOOLEAN | 否 | 是否只需要dataset的基本信息，true 表示只需要meta信息，默认是false |
| joinExcept | STRING | 否 | 排除不需要的信息，可选值为 schema，metrics，connection，user，也可以是它们的任意组合，用逗号分隔，比如 schema,measure。 |
| functions | BOOLEAN | 否 | 是否需要数据集所支持的函数信息 |
| createdByCurrent | BOOLEAN | 否 | 是否只需要列出当前用户创建的数据集 |
| excludeOptionsType | STRING | 否 | 排除 options.type 是所选值的数据集，可选值为 connection，fusion，union，aggregate |
| importStatus | INTEGER | 否 | 导入引擎的状态过滤，可选值按照 导入引擎状态 |
| showHide | BOOLEAN | 否 | 是否显示隐藏数据集 |
| offset | INTERGER | 否 | 偏移的值 |
| limit | INTERGER | 否 | 查询的最大个数 |
joinExcept的选项说明
| 值 | 说明 |
|---|---|
| schema | 不需要数据集的字段信息 |
| metrics | 不需要数据集的指标信息 |
| connection | 不需要数据集所用的数据连接名 |
| user | 不需要数据集的创建者和更新者的用户相信信息 |
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 数据集的列表和分组信息 |
| data.datasets | OBJECT 数组 | 数据集列表，数组的成员见 数据集结构说明, 参照各种数据集的特殊结构说明 |
| data.datasetGroups | OBJECT 数组 | 数据集分组信息列表, 请求参数中的 functions 为 true 时，返回结果才有此信息 |
| data.datasetGroups.functions | OBJECT 数组 | 数据集支持的函数列表 |
| data.datasetGroups.datasetIds | NUMBER 数组 | 支持这些函数的数据集 id 数组 |
参考示例1
列出应用 1 下的数据集列表和分组信息。
http
GET /api/apps/1/datasets/datasets-groups?offset=15&limit=20&orderBy=updatedAt&orderType=desc&meta=false&joinExcept=metrics%2Cconnection HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": {
"datasets": [
{
"id": 1,
"title": "A_IVT_MOVIE",
"createdBy": 1,
"createdAt": "2020-04-11 15:19:32",
"updatedBy": 1,
"updatedAt": "2020-04-11 15:26:24",
"visible": true,
"isDelete": false,
"appId": 840,
"accessCount": 1,
"options": {
"cache": false,
"type": "connection",
"totalSize": 32780,
"rowCount": 230,
"rowCountValid": true,
"connectionTitle": "oracle",
"refreshHours": [],
"refreshMinute": 0,
"connectionId": 444,
"connectionCategory": "Database",
"origin": "oracle",
"table": "A_IVT_MOVIE",
"path": [
"JIANXIN"
],
"transpose": false,
"header": 0,
"padHeader": false,
"storageType": "engine",
"dialectOptions": {
"dialectName": "OracleDialect",
"majorVersion": 11,
"minorVersion": 2
},
"storageConnectionId": 3,
"storageConnectionTitle": "引擎连接",
"metrics": [],
"schema": [
{
"datasetId": 1,
"fieldName": "id",
"hsVersion": 1,
"visible": true,
"basicType": "number",
"defaultAggrType": "sum",
"config": {
"dialectName": "OracleDialect"
},
"type": "number",
"originType": "number",
"comment": "",
"nativeType": "NUMBER",
"suggestedTypes": [
"number",
"string"
],
"detectedType": "number"
}
]
},
"importType": 1,
"importStatus": 1,
"importOptions": {},
"status": 3,
"refreshStats": {
"refreshAt": "2020-04-11 15:26:09",
"executeRefreshAt": "2020-04-11 15:26:09",
"executeRefreshRowCountAt": 1586589984248
},
"datasetAcl": {
"level": "FULLACCESS",
"dataFilters": []
},
"hsVersion": 9,
"creator": {
"id": 1,
"name": "trial",
"email": "trial@hengshi.io"
},
"updater": {
"id": 1,
"name": "trial",
"email": "trial@hengshi.io"
},
"importSwitchable": false,
"emptyDataset": false,
"type": "connection",
"public": true,
"refreshSchema": false,
"origin": "oracle"
}
],
"datasetGroups": [
{
"functions": [
{
"type": "string",
"args": [
{
"type": "string",
"placeholder": "s",
"desc": "文本类型参数"
}
],
"desc": "去掉字符串首尾的空格",
"name": "trim",
"categories": [
"string functions",
"non aggregate functions",
"new field functions"
],
"varArgs": false
}
],
"datasetIds": [
1
]
}
]
},
"totalHits": 9,
"offset": 0
}通过 PUT 方法修改一个数据集的标题
请求URL
http
PUT /api/apps/${appId}/datasets/${datasetId} HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
request body 请求参数
数据集结构说明, title 是必须的
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 数据集结构说明, 参照各种数据集的特殊结构说明 |
参考示例
http
PUT /api/apps/1/datasets/1 HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"title": "china_map_province2",
"hsVersion": 6
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": {
"id": 1,
"title": "china_map_province2",
"createdBy": 6,
"createdAt": "2020-06-03 17:37:31",
"updatedBy": 6,
"updatedAt": "2020-06-03 18:08:23",
"visible": true,
"isDelete": false,
"appId": 46176,
"options": {
"cache": false,
"type": "connection",
"totalSize": 1373,
"rowCount": 34,
"rowCountValid": true,
"connectionTitle": "引擎连接",
"refreshHours": [],
"refreshMinute": 0,
"connectionId": 1240,
"connectionCategory": "Internal",
"origin": "engine",
"table": "china_map_province",
"path": [
"common"
],
"transpose": false,
"header": 0,
"padHeader": false,
"storageType": "engine",
"dialectOptions": {
"dialectName": "EngineDialect",
"majorVersion": 0,
"minorVersion": 0
},
"storageConnectionId": 1240,
"storageConnectionTitle": "引擎连接",
"schema": [
{
"datasetId": 1,
"fieldName": "id",
"hsVersion": 1,
"originType": "integer",
"comment": "序号",
"config": {
"dialectName": "EngineDialect"
},
"label": "id",
"type": "number",
"basicType": "number",
"defaultAggrType": "sum",
"visible": true,
"nativeType": "bigserial",
"suggestedTypes": [
"number",
"string"
],
"detectedType": "integer"
}
],
"metrics": []
},
"importType": 0,
"importStatus": 0,
"importOptions": {},
"status": 3,
"refreshStats": {
"refreshAt": "2020-06-03 17:37:32",
"executeRefreshAt": "2020-06-03 17:37:32",
"executeRefreshRowCountAt": 1591177054579
},
"datasetAcl": {
"level": "FULLACCESS",
"dataFilters": []
},
"hsVersion": 7,
"importSwitchable": false,
"public": true,
"origin": "engine",
"emptyDataset": false,
"refreshSchema": false,
"type": "connection"
}
}通过 ID 删除数据集
请求URL
http
DELETE /api/apps/${appId}/datasets/${datasetId} HTTP/1.1请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| msg | STRING | 成功返回 success |
下载数据集数据
请求URL
http
GET /api/apps/${appId}/datasets/${datasetId}/download HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
返回对象的格式说明
Excel文件，后缀是 xlsx。
下载有过滤条件的数据集数据
请求URL
http
POST /api/apps/${appId}/datasets/${datasetId}/download HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
Request Body 参数
HE 表达式，详情参照HE 的数据集函数
返回对象的格式说明
Excel文件，后缀是 xlsx。
参考示例
http
POST /api/apps/1/datasets/1/download HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"kind": "formula",
"op": "summarize(dataset(1), {type}, {votes})"
}获取数据集支持的函数列表
请求URL
http
GET /api/apps/${appId}/datasets/${datasetId}/functions HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
返回对象的格式说明
参考示例
http
GET /api/apps/1/datasets/1/functions HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": {
"id": 6,
"title": "6",
"appId": 2621,
"options": {
"cache": false,
"type": "aggregate",
"totalSize": 77,
"rowCount": 9,
"rowCountValid": true,
"refreshHours": [],
"refreshMinute": 0,
"transpose": false,
"header": 0,
"padHeader": false,
"rootDatasetId": 5,
"storageType": "engine",
"dialectOptions": {
"dialectName": "EngineDialect",
"majorVersion": 0,
"minorVersion": 0
},
"storageConnectionId": 3,
"storageConnectionTitle": "引擎连接",
"metrics": [],
"schema": []
},
"importType": 0,
"datasetAcl": {
"level": "FULLACCESS",
"dataFilters": []
},
"functions": [
{
"type": "string",
"args": [
{
"type": "string",
"placeholder": "s",
"desc": "文本类型参数"
}
],
"desc": "去掉字符串首尾的空格",
"name": "trim",
"categories": [
"string functions",
"non aggregate functions",
"new field functions"
],
"varArgs": false
}
],
"importSwitchable": false,
"type": "aggregate",
"refreshSchema": true,
"emptyDataset": false
}
}预览关联模型数据
请求URL
http
GET /api/apps/${appId}/datasets/${datasetId}/preview-relation HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
返回对象的格式说明
参考示例
http
GET /api/apps/1/datasets/1/preview-relation HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": {
"data": [
[
"喜剧",
16.5
],
[
"动画",
16.6
]
],
"schema": [
{
"fieldName": "type(数据集1)",
"visible": true,
"nativeType": "text"
},
{
"fieldName": "sum1(数据集2)",
"visible": true,
"nativeType": "numeric"
}
]
}
}刷新数据集
所有数据集都能刷新，依赖它的其他数据集会自动跟着刷新
请求URL
http
POST /api/apps/${appId}/datasets/${datasetId}/refresh HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
Request Body 参数
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| msg | STRING | 成功返回 success |
参考示例
http
POST /api/apps/1/datasets/1/refresh HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success"
}刷新数据集schema
所有数据集都能刷新schema，依赖它的其他数据集会自动跟着刷新
请求URL
http
POST /api/apps/${appId}/datasets/${datasetId}/refresh-schema HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
Request Body 参数
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| msg | STRING | 成功返回 success |
参考示例
http
POST /api/apps/1/datasets/1/refresh-schema HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success"
}修改数据集刷新计划(已废弃)
请求URL
http
PUT /api/apps/${appId}/datasets/${datasetId}/refresh-schedule HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
Request Body 参数
| 字段 | 类型 | 说明 |
|---|---|---|
| refreshMinute | INTEGER | 执行刷新的具体分钟 |
| refreshHours | INTEGER 数组 | 每天24小时中哪个小时执行刷新 |
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 当前数据集的更新计划配置 |
| data.refreshMinute | INTEGER | 执行刷新的具体分钟 |
| data.refreshHours | INTEGER | 每天24小时中哪个小时执行刷新 |
参考示例
http
PUT /api/apps/1/datasets/1/refresh-schedule HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"refreshMinute": 3,
"refreshHours": [
0,
1,
2,
3,
9,
8,
7,
15
]
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"data": {
"refreshHours": [
0,
1,
2,
3,
9,
8,
7,
15
],
"refreshMinute": 3
}
}获取数据集刷新计划 （已废弃）
请求URL
http
GET /api/apps/${appId}/datasets/${datasetId}/refresh-schedule HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
Request Body 参数
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 当前数据集的更新计划配置 |
| data.refreshMinute | INTEGER | 执行刷新的具体分钟 |
| data.refreshHours | INTEGER | 每天24小时中哪个小时执行刷新 |
参考示例
http
GET /api/apps/1/datasets/1/refresh-schedule HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"data": {
"refreshHours": [
0,
1,
2,
3,
9,
8,
7,
15
],
"refreshMinute": 3
}
}其他接口（TODO）
替换数据集
替换数据集只用于替换基础数据集，包括文件数据集、数据连接数据集、SQL 查询数据集。
请求URL
http
POST /api/apps/${appId}/datasets/${datasetId}/replace HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
Request Body 参数
数据集的共同结构见数据集结构说明。用文件数据集去替换，参照新建文件数据集的 request body 参数。用数据连接数据集去替换，参照新建数据连接数据集的 request body 参数。用 SQL 查询数据集去替换，参照 SQL 查询数据集的 request body 参数。
当原数据集中的字段被引用后，字段名就不能改变了。如果新的替换表中字段名和原字段名不一致，那需要把新的字段名存到 options.schema[].dbfieldName 里面。
获取数据集中哪些字段被引用了，参照获取数据集所有字段，注意把 url 参数中的 inUseOnly 设置为 true。
接口示例1：用SQL 查询数据集替换数据集
http
POST api/apps/1482/datasets/21901/replace HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"options": {
"type": "connection",
"origin": "postgresql",
"connectionId": 334,
"schema": [
{
"datasetId": 21901,
"fieldName": "region_id",
"label": "region_id",
"type": "number",
"visible": true,
"dbFieldName": "region_id"
},
{
"originType": "string",
"fieldName": "country_id",
"nativeType": "bpchar",
"visible": true,
"type": "string",
"label": "country_id"
}
],
"customSql": "select \"country_id\", \"region_id\" from public.\"a_ivt_countries\"",
"path": [
"public"
]
}
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": {
"id": 1,
"updatedBy": 89,
"updatedAt": "2020-06-10 11:37:21",
"visible": true,
"appId": 1,
"options": {
"cache": false,
"type": "connection",
"totalSize": 0,
"rowCount": 0,
"connectionTitle": "postgresjl",
"connectionId": 334,
"origin": "postgresql",
"customSql": "select \"country_id\", \"region_id\" from public.\"a_ivt_countries\"",
"path": [
"public"
],
"schema": [
{
"datasetId": 21901,
"fieldName": "country_id",
"appId": 1482,
"originType": "string",
"config": {},
"label": "country_id",
"type": "string",
"visible": true,
"defaultAggrType": "count",
"nativeType": "bpchar",
"suggestedTypes": [
"string"
],
"detectedType": "string",
"basicType": "string"
},
{
"datasetId": 21901,
"fieldName": "region_id",
"hsVersion": 1,
"appId": 1482,
"originType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"label": "region_id",
"type": "number",
"visible": true,
"defaultAggrType": "sum",
"nativeType": "numeric",
"suggestedTypes": [
"number",
"string"
],
"dbFieldName": "region_id",
"detectedType": "number",
"basicType": "number"
},
{
"datasetId": 21901,
"fieldName": "c0",
"hsVersion": 0,
"appId": 1482,
"originType": "number",
"config": {
"dialectName": "PostgresqlDialect"
},
"label": "new_field_1",
"type": "number",
"visible": true,
"defaultAggrType": "sum",
"expr": {
"kind": "formula",
"op": "{region_id} + 2",
"type": "number",
"value": "{region_id} + 2"
},
"nativeType": "numeric",
"suggestedTypes": [
"number",
"string"
],
"detectedType": "number",
"basicType": "number",
"formula": "{region_id} + 2"
}
],
"metrics": []
},
"datasetAcl": {
"level": "FULLACCESS",
"dataFilters": []
},
"origin": "postgresql",
"refreshSchema": true,
"emptyDataset": false,
"type": "connection"
}
}获取数据集的更新方法
请求URL
http
GET /api/apps/${appId}/datasets/${datasetId}/update-method HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用id |
| datasetId | INTEGER | 是 | 数据集id |
Request Body 参数
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 见数据集更新方法结构说明 |
接口示例:
http
GET /api/apps/1/datasets/1/update-method HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": {
"updateMethod": "INCREMENTAL",
"incrementalField": ["id"]
},
"msg": "success",
"version": "version@9a5e106#6730f0d",
}更新数据集的更新方法
请求URL
http
PUT /api/apps/${appId}/datasets/${datasetId}/update-method HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用id |
| datasetId | INTEGER | 是 | 数据集id |
Request Body 参数
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 见数据集更新方法结构说明 |
接口示例:
http
PUT /api/apps/1/datasets/1/update-method HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"updateMethod": "INCREMENTAL",
"incrementalField": ["updatedAt"]
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": {
"updateMethod": "INCREMENTAL",
"incrementalField": ["updatedAt"]
},
"msg": "success",
"version": "version@9a5e106#6730f0d",
}返回对象的格式说明
Excel文件，后缀是 xlsx。
开启/关闭引擎
手动开启/关闭指定的数据集引擎
请求URL
http
POST /api/apps/{appId}/datasets/{datasetId}/import/switch HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
| force | BOOL | 否 | 是否强制开启引擎 |
Request Body 参数
true:开启引擎 false:关闭引擎
接口示例1：开启引擎
http
POST /api/apps/35/datasets/14/import/switch HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
truehttp
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"msg": "success",
"version": "version@9a5e106#6730f0d",
}说明
- 普通数据集(直连，SQL)如果在过滤条件或SQL语句或使用的数据连接中使用了用户属性/应用参数，则该数据集不能导入引擎。
- 复杂数据集(fusion，aggregate，union)数据集,如果与它存在血缘关系的数据集中使用了用户属性/应用参数做过滤，或这些血缘数据集使用的数据连接使用了用户属性配置，则该复杂数据集不能导入引擎
获取数据集详情 （TODO）
预览连接中的一个 table 的 schema 信息 （TODO）
通过 schema 信息创建一个数据集 （TODO）
通过数据集 id 获取到已创建的数据集的信息 （TODO）
获取数据集的SQL
获取数据集的SQL
请求URL
http
GET /api/apps/{appId}/datasets/{datasetId}/sql-debug HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 说明 |
|---|---|---|
| appId | INTEGER | 数据集所在应用 Id |
| datasetId | INTEGER | 数据集 Id |
| vendorDesc | STRING | 指定的sql数据源描述，格式为<类型><大版本号><小版本号>_<商业版本号>，其中 类型 是必填的。比如：mysql_8_10_analyticdb |
接口示例1:
http
GET /api/apps/15/datasets/1/sql-debug HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": "SELECT `dataset_1`.`ID` AS `ID`, `dataset_1`.`zh_name` AS `zh_name`, `dataset_1`.`director` AS `director`, `dataset_1`.`prime_genre` AS `prime_genre`, `dataset_1`.`runtime` AS `runtime`, cast(`dataset_1`.`rate_num` as decimal(38, 10)) AS `rate_num`, `dataset_1`.`votes` AS `votes`, `dataset_1`.`stars` AS `stars`, `dataset_1`.`tags` AS `tags`, `dataset_1`.`pubdate` AS `pubdate`, `dataset_1`.`pubyear` AS `pubyear`, `dataset_1`.`month` AS `month`, `dataset_1`.`day` AS `day`, `dataset_1`.`release_time` AS `release_time`, `dataset_1`.`happytime` AS `happytime`, `dataset_1`.`utc_time` AS `utc_time`, `dataset_1`.`likeit` AS `likeit`, `dataset_1`.`description` AS `description`, `dataset_1`.`descrip_b` AS `descrip_b`, `dataset_1`.`special` AS `special`, `dataset_1`.`New` AS `New` FROM `testdb`.`cjmovie` `dataset_1` LIMIT 1000"
}接口示例2:
http
GET /api/apps/15/datasets/1/sql-debug?vendorDesc=postgres HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": "SELECT \"dataset_1\".\"ID\" AS \"ID\", \"dataset_1\".\"zh_name\" AS \"zh_name\", \"dataset_1\".\"director\" AS \"director\", \"dataset_1\".\"prime_genre\" AS \"prime_genre\", \"dataset_1\".\"runtime\" AS \"runtime\", cast(\"dataset_1\".\"rate_num\" as decimal(38, 10)) AS \"rate_num\", \"dataset_1\".\"votes\" AS \"votes\", \"dataset_1\".\"stars\" AS \"stars\", \"dataset_1\".\"tags\" AS \"tags\", \"dataset_1\".\"pubdate\" AS \"pubdate\", \"dataset_1\".\"pubyear\" AS \"pubyear\", \"dataset_1\".\"month\" AS \"month\", \"dataset_1\".\"day\" AS \"day\", \"dataset_1\".\"release_time\" AS \"release_time\", \"dataset_1\".\"happytime\" AS \"happytime\", \"dataset_1\".\"utc_time\" AS \"utc_time\", \"dataset_1\".\"likeit\" AS \"likeit\", \"dataset_1\".\"description\" AS \"description\", \"dataset_1\".\"descrip_b\" AS \"descrip_b\", \"dataset_1\".\"special\" AS \"special\", \"dataset_1\".\"New\" AS \"New\" FROM \"testdb\".\"cjmovie\" \"dataset_1\" LIMIT 1000"
}获取数据集SQL执行计划
获取数据集SQL执行计划
请求URL
http
GET /api/apps/{appId}/datasets/{datasetId}/sql-explain HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 说明 |
|---|---|---|
| appId | INTEGER | 数据集所在应用 Id |
| datasetId | INTEGER | 数据集 Id |
接口示例1:
http
GET /api/apps/15/datasets/1/sql-explain HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data": [
[
[
"id",
"select_type",
"table",
"partitions",
"type",
"possible_keys",
"key",
"key_len",
"ref",
"rows",
"filtered",
"Extra"
],
[
1,
"SIMPLE",
"dataset_1",
null,
"ALL",
null,
null,
null,
null,
267,
100.0,
null
]
]
]
}获取数据集的状态
请求URL
http
GET /api/apps/{appId}/datasets/{datasetId}/status HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 说明 |
|---|---|---|
| appId | INTEGER | 数据集所在应用 Id |
| datasetId | INTEGER | 数据集 Id |
Request Body 参数
| 字段 | 类型 | 是否必须 | 描述 |
|---|
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 数据集状态信息 |
| data.status | INTEGER | 数据集状态信息，见数据集状态说明 |
| data.refreshAt | STRING | 刷新数据成功时间，ISO格式 |
| data.executeRefreshAt | STRING | 开始执行刷新数据时间，ISO格式 |
| data.refreshSchemaAt | STRING | 刷新schema成功时间，ISO格式 |
| data.executeRefreshSchemaAt | STRING | 开始执行刷新schema时间，ISO格式 |
| data.currentTime | STRING | 当前服务器时间，ISO格式 |
接口示例1:
http
GET /api/apps/15/datasets/1/status HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code":0,
"msg":"success",
"data":{
"status":3,
"refreshAt":"2022-06-29 10:25:32",
"executeRefreshAt":"2022-06-29 10:25:32",
"currentTime":"2022-07-07 14:22:10"
}
}获取数据集数据
请求URL
http
GET /api/apps/{appId}/datasets/{datasetId}/data HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 说明 |
|---|---|---|
| appId | INTEGER | 数据集所在应用 Id |
| datasetId | INTEGER | 数据集 Id |
| orderBy | string | 排序字段 |
| orderType | string | 排序类型，正序（asc）或倒序（desc） |
Request Body 参数
| 字段 | 类型 | 是否必须 | 描述 |
|---|
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | OBJECT | 数据集的数据 |
| data.data | OBJECT | 数据集数据，默认只取1000行，结构参考数据集数据datasetResultDto说明 中的data |
| data.schema | OBJECT | 数据集schema,结构参考数据集数据datasetResultDto说明 中的schema |
| data.pagable | BOOL | 是否支持分页 |
| data.importSwitchable | BOOL | 是否支持开启引擎 |
接口示例1:
http
GET /api/apps/15/datasets/1/data HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code":0,
"msg":"success",
"data":{
"data":[
[1,5.5,"s1","2022-07-07"],
[
2,
6.5,
"s2",
"2022-07-08"
],
[
3,
7.5,
"s3",
"2022-07-09"
],
[
4,
8.5,
"s4",
"2022-07-10"
],
[
5,
9.5,
"s5",
"2022-07-11"
]
],
"schema": [
{
"fieldName": "f1_int",
"label": "f1_int",
"visible": true,
"comment": "",
"type": "number",
"originType": "number",
"basicType": "number",
"suggestedTypes": [
"number",
"string"
],
"nativeType": "DECIMAL",
"detectedType": "number",
"hideValue": false
},
{
"fieldName": "f2_float",
"label": "f2_float",
"visible": true,
"comment": "",
"type": "number",
"originType": "number",
"basicType": "number",
"suggestedTypes": [
"number",
"string"
],
"nativeType": "DECIMAL",
"detectedType": "number",
"hideValue": false
},
{
"fieldName": "f3_string",
"label": "f3_string",
"visible": true,
"comment": "",
"type": "string",
"originType": "string",
"basicType": "string",
"suggestedTypes": [
"string"
],
"nativeType": "VARCHAR",
"detectedType": "string",
"hideValue": false
},
{
"fieldName": "f4_date",
"label": "f4_date",
"visible": true,
"comment": "",
"config": {
"dateFormat": "yyyy-MM-dd",
"dialectName": "PostgresqlDialect"
},
"type": "date",
"originType": "date",
"basicType": "date",
"suggestedTypes": [
"date",
"string"
],
"nativeType": "DATE",
"detectedType": "date",
"hideValue": false
}
],
"pagable": true,
"importSwitchable": true
}
}设置数据集为默认
设置数据集为默认
请求URL
http
POST /api/apps/{appId}/datasets/{datasetId}/default/switch HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 说明 |
|---|---|---|
| appId | INTEGER | 数据集所在应用 Id |
| datasetId | INTEGER | 数据集 Id |
Request Body 参数
true 或者 false
true： 表示设置默认 false： 表示取消默认
接口示例1:
http
POST /api/apps/499/datasets/1/default/switch HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
truehttp
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success"
}根据当前设置获取导入引擎表的建表属性模板
请求URL
http
POST /api/apps/${appId}/datasets/${datasetId}/create-table-props-template HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用id |
| datasetId | INTEGER | 是 | 数据集id |
Request Body 参数
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | STRING | 根据当前输出的数据源类型和字段生成的建表属性模板 |
接口示例:
http
POST /api/apps/1/datasets/1/create-table-props-template HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"updateMethod": "ALL",
"createTableProperties": "",
...
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"code": 0,
"data": "distributed by (f3) partition by list(f2) (DEFAULT PARTITION pd,partition p1 values(1),partition p2 values (2),partition p3 values (3))",
"msg": "success",
"version": "version@9a5e106#6730f0d",
}根据当前建表属性等设置测试建表
请求URL
http
POST /api/apps/${appId}/datasets/${datasetId}/test-create HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用id |
| datasetId | INTEGER | 是 | 数据集id |
Request Body 参数
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| msg | STRING | http code不是200的话，返回具体的错误信息 |
接口示例:
http
POST /api/apps/1/datasets/1/test-create HTTP/1.1
Content-Type: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...
// Request Body:
{
"updateMethod": "ALL",
"createTableProperties": "distributed by (f3) partition by list(f2) (DEFAULT PARTITION pd,partition p1 values(1),partition p2 values (2),partition p3 values (3))",
...
}http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"msg": "ERROR: column "f3" named in 'DISTRIBUTED BY' clause does not exist",
...
}通过 ID 触发数据集 AI 例子生成
触发后任务在执行记录中可以查看进度和日志。
请求URL
http
GET /api/apps/${appId}/datasets/${datasetId}/ai-create-example HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
参考示例
http
GET /api/apps/1/datasets/1/ai-create-example HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success"
}通过 ID 查询数据集相关的 AI 的例子
请求URL
http
GET /api/apps/${appId}/datasets/${datasetId}/chat-example HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...请求参数
URL 参数
| 字段 | 类型 | 是否必须 | 说明 |
|---|---|---|---|
| appId | INTEGER | 是 | 应用的 id |
| datasetId | INTEGER | 是 | 数据集的 id |
返回对象的格式说明
| 字段 | 类型 | 说明 |
|---|---|---|
| version | STRING | 当前系统版本哈希值 |
| data | STRING | 数据集相关的例子 |
参考示例
http
GET /api/apps/1/datasets/1/chat-example HTTP/1.1
Accept: application/json
Cookie: csrf=183f1c4...; sid=26ee552d...; _USER_SESSION_ID=f2a01083...http
HTTP/1.1 200 Ok
Content-Type: application/json
{
"version": "version@9a5e106#6730f0d",
"code": 0,
"msg": "success",
"data":"具体例子内容"
}