Latest version of this endpoint: API ImportedDatasets Create v4.
Contents:
Create an imported dataset from an available resource. Created dataset is owned by the authenticated user.
NOTE: When an imported dataset is created via API, it is always imported as an unstructured dataset. Any recipe that references this dataset should contain initial parsing steps required to structure the data.
NOTE: Do not create an imported dataset from a file that is being used by another imported dataset. If you delete the newly created imported dataset, the file is removed, and the other dataset is corrupted. Use a new file or make a copy of the first file first.
Version: v3
Required Permissions
NOTE: Each request to the Designer Cloud Powered by Trifacta® platform must include authentication credentials. See https://api.trifacta.com/ee/6.0/index.html#section/Authentication.
Request and Response
Request Type: POST
Endpoint:
/v3/importedDatasets
Response Status Code - Success: 201 - Created
Examples by Type
Below, you can review the basic request body for creating imported datasets for various types of sources:
File (HDFS or S3 source)
NOTE: You can create imported datasets only from file types that are natively supported by the platform. Using this endpoint, you cannot create imported datasets from file types, such as Microsoft Excel, that must be converted before import.
- Hive
- Relational
- Relation with Custom SQL Query
File (HDFS and S3 sources)
Request Body - HDFS file:
Below, the bucket value is set to null. This parameter applies only to S3 sources.
NOTE: The path value should not include the HDFS protocol, host, or port information. You only need to provide the path on HDFS.
{
"path": "/trifacta/uploads/1/4aee9852-cf92-47a8-8c6a-9ff2adeb3b4a/POS-r02.txt",
"type": "hdfs",
"bucket": null,
"name": "POS-r02b.txt",
"description": "POS-r02 - copy"
}
Request Body - S3 file:
For S3 sources, a bucket must be specified. Below, the bucket value is set to myBucket.
NOTE: The path value should not include the S3 protocol, host, or port information. You only need to provide the path on S3.
{
"path": "/trifacta/uploads/1/4aee9852-cf92-47a8-8c6a-9ff2adeb3b4a/POS-r02.txt",
"type": "s3",
"bucket": "myBucket",
"name": "POS-r02b.txt",
"description": "POS-r02 - copy"
}
Response Body - file:
Following example is for an HDFS file. For an S3 file, type=s3.
{
"id": 8,
"size": "281032",
"path": "/trifacta/uploads/1/4aee9852-cf92-47a8-8c6a-9ff2adeb3b4a/POS-r02.txt",
"isSharedWithAll": false,
"type": "hdfs",
"bucket": null,
"isSchematized": false,
"createdBy": 1,
"updatedBy": 1,
"updatedAt": "2017-02-08T18:38:56.640Z",
"createdAt": "2017-02-08T18:38:56.560Z",
"connectionId": null,
"parsingScriptId": 14,
"cpProject": null
}
Hive
Request Body - Hive:
Notes:
- Note that the
type=jdbc. - The
columnskey is optional. If not provided, all columns in the source table are included.
{
"visible": true,
"numFlows": 0,
"size": -1,
"type": "jdbc",
"jdbcType": "TABLE",
"jdbcPath": [
"DB1"
],
"jdbcTable": "MyHiveTable",
"columns": [
"column1",
"column2"
],
"connectionId": 16,
"name": "My Hive Table"
}
Response Example - Hive:
{
"jdbcTable": "MyHiveTable",
"jdbcPath": [
"DB1"
],
"columns": [
"column1",
"column2"
],
"filter": null,
"raw": null,
"isSharedWithAll": false,
"id": 192,
"size": "-1",
"type": "jdbc",
"connectionId": 16,
"createdBy": 1,
"updatedBy": 1,
"updatedAt": "2017-02-17T18:09:17.745Z",
"createdAt": "2017-02-17T18:09:16.407Z",
"path": null,
"bucket": null,
"parsingScriptId": 366,
"cpProject": null,
"isSchematized": true
}
Relational
Request Body - Relational:
Notes:
- If you know the
sizevalue for the table, please provide. It is helpful for performance reasons and validation but is not required. - The
columnskey is optional. If not provided, all columns in the source table are included.
{
"visible": true,
"numFlows": 0,
"size": 65536,
"type": "jdbc",
"jdbcType": "TABLE",
"jdbcPath": [
"OracleDB_1"
],
"jdbcTable": "MyOracleTable",
"columns": [
"I",
"J",
"K"
],
"connectionId": 7,
"name": "My Oracle Table"
}
Response Example - Relational:
{
"jdbcTable": "MyOracleTable",
"jdbcPath": [
"OracleDB_1"
],
"columns": [
"I",
"J",
"K"
],
"filter": null,
"raw": null,
"isSharedWithAll": false,
"id": 195,
"size": "65536",
"type": "jdbc",
"connectionId": 7,
"createdBy": 1,
"updatedBy": 1,
"updatedAt": "2017-02-17T18:10:48.662Z",
"createdAt": "2017-02-17T18:10:47.441Z",
"path": null,
"bucket": null,
"parsingScriptId": 372,
"cpProject": null,
"isSchematized": true
}
Relational with Custom SQL Query
You can submit custom SQL queries to relational or hive connections. These custom SQLs can be used to pre-filter the data inside the database, improving performance of the query and the overall dataset.
- For more information, see Enable Custom SQL Query.
Request Body:
Notes:
- See previous notes on queries to relational sources.
- As part of the request body, you must submit the custom SQL query as the value for the
rawproperty.
The following example is valid for Oracle databases. Note the escaping of the double-quote marks.
NOTE: Syntax for the custom SQL query varies between relational systems. For more information on syntax examples, see Create Dataset with SQL.
{
"visible": true,
"numFlows": 0,
"type": "jdbc",
"jdbcType": "TABLE",
"connectionId": 7,
"raw": "SELECT INST#,BUCKET#,INST_LOB# FROM \"AUDSYS\".\"CLI_SWP$7395268a$1$1\"",
"size": -1,
"name": "SQL Dataset 1"
}
Response Body:
In the response, note that the source of the data is defined by the connectionId value and the SQL defined in the raw value.
{
"jdbcTable": null,
"jdbcPath": null,
"columns": null,
"filter": null,
"raw": [
"SELECT INST#,BUCKET#,INST_LOB# FROM \"AUDSYS\".\"CLI_SWP$7395268a$1$1\""
],
"isSharedWithAll": false,
"id": 196,
"size": "-1",
"type": "jdbc",
"connectionId": 7,
"createdBy": 1,
"updatedBy": 1,
"updatedAt": "2017-02-17T19:09:10.117Z",
"createdAt": "2017-02-17T19:07:12.757Z",
"path": null,
"bucket": null,
"parsingScriptId": 378,
"cpProject": null,
"isSchematized": true
}
Reference
For more information on the properties of an imported dataset, see API ImportedDatasets Get v3.
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