Oracle REST Data Services API

Creates data load jobs

post

/data-tools/data-loads/

Creates data load jobs

Request

There are no request parameters for this operation.

Supported Media Types

application/json

Root Schema : schema

Type: object

Show Source

data_loads: array data_loads

{
    "type":"object",
    "properties":{
        "data_loads":{
            "type":"array",
            "items":{
                "$ref":"#/components/schemas/data-load"
            }
        }
    }
}

Nested Schema : data_loads

Type: array

Show Source

Array of: object data-load

{
    "type":"array",
    "items":{
        "$ref":"#/components/schemas/data-load"
    }
}

Nested Schema : data-load

Type: object

Show Source

columns: array columns
data_load_job_id: string

Name of data load job

Example: SALES-LOAD-20220529-112233-4567
data_load_name: string

Descriptive name for data load

Example: MY_LOAD_OF_SALES
format: object format

DBMS_CLOUD.COPY_DATA formatting options
merge_keys: array merge_keys
object_filter: string

Filter to select subset of files

Example: *.csv
object_filter_type: string

Allowed Values: [ "GLOB", "REGEX" ]

Type of matching for object_filter

Example: GLOB
objects: array data_load_objects
partition_column_name: string

Column name to partition table on

Example: FISCAL_YEAR
sql_statements: array sql_statements

SQL statements to perform database operation
storage_link_name: string

Name of Cloud Storage Link

Example: MY-BUCKET
table_exists_action: string

Allowed Values: [ "SKIP", "APPEND", "TRUNCATE", "MERGE", "REPLACE" ]

Action to take when there is an existing table.

Example: APPEND
table_name: string

Table name to load

Example: SALES
table_schema: string

Database object schema

Example: SH
target_type: string

Allowed Values: [ "TABLE", "EXTERNAL_TABLE" ]

Type of database object to create.

Example: TABLE

{
    "type":"object",
    "properties":{
        "data_load_name":{
            "$ref":"#/components/schemas/data_load_name"
        },
        "data_load_job_id":{
            "$ref":"#/components/schemas/data_load_job_id"
        },
        "table_name":{
            "$ref":"#/components/schemas/table_name"
        },
        "table_schema":{
            "$ref":"#/components/schemas/schema_name"
        },
        "objects":{
            "$ref":"#/components/schemas/data_load_objects"
        },
        "storage_link_name":{
            "$ref":"#/components/schemas/storage_link_name"
        },
        "columns":{
            "$ref":"#/components/schemas/columns"
        },
        "object_filter":{
            "$ref":"#/components/schemas/object_filter"
        },
        "object_filter_type":{
            "$ref":"#/components/schemas/object_filter_type"
        },
        "partition_column_name":{
            "type":"string",
            "example":"FISCAL_YEAR",
            "description":"Column name to partition table on"
        },
        "format":{
            "$ref":"#/components/schemas/format"
        },
        "sql_statements":{
            "$ref":"#/components/schemas/sql_statements"
        },
        "merge_keys":{
            "type":"array",
            "items":{
                "type":"string",
                "description":"Column name to merge on"
            },
            "example":"[ 'RECORD_ID' ]"
        },
        "table_exists_action":{
            "type":"string",
            "example":"APPEND",
            "description":"Action to take when there is an existing table.",
            "enum":[
                "SKIP",
                "APPEND",
                "TRUNCATE",
                "MERGE",
                "REPLACE"
            ]
        },
        "target_type":{
            "type":"string",
            "example":"TABLE",
            "description":"Type of database object to create.",
            "enum":[
                "TABLE",
                "EXTERNAL_TABLE"
            ]
        }
    }
}

Nested Schema : columns

Type: array

Show Source

Array of: object column

{
    "type":"array",
    "items":{
        "$ref":"#/components/schemas/column"
    },
    "example":[
        {
            "column_name":"RECEIVED_DATE",
            "datatype":"DATE",
            "columnId":1,
            "format":"YYYY-MM-DD"
        },
        {
            "column_name":"UNITS",
            "datatype":"NUMBER",
            "columnId":2,
            "length":38
        }
    ]
}

Example:

[
    {
        "column_name":"RECEIVED_DATE",
        "datatype":"DATE",
        "columnId":1,
        "format":"YYYY-MM-DD"
    },
    {
        "column_name":"UNITS",
        "datatype":"NUMBER",
        "columnId":2,
        "length":38
    }
]

Nested Schema : format

Type: object

DBMS_CLOUD.COPY_DATA formatting options

Example:

{
    "delimiter":",",
    "blankasnull":true,
    "characterset":"AL32UTF8"
}

Nested Schema : merge_keys

Type: array

Show Source

Array of: string

Column name to merge on

{
    "type":"array",
    "items":{
        "type":"string",
        "description":"Column name to merge on"
    },
    "example":"[ 'RECORD_ID' ]"
}

Example:

[ 'RECORD_ID' ]

Nested Schema : data_load_objects

Type: array

Show Source

Array of: object data_load_object

{
    "type":"array",
    "items":{
        "$ref":"#/components/schemas/data_load_object"
    },
    "example":[
        {
            "object_name":"sales1976.csv"
        },
        {
            "object_name":"sales2009.csv"
        },
        {
            "object_name":"sales2013.csv"
        }
    ]
}

Example:

[
    {
        "object_name":"sales1976.csv"
    },
    {
        "object_name":"sales2009.csv"
    },
    {
        "object_name":"sales2013.csv"
    }
]

Nested Schema : sql_statements

Type: array

SQL statements to perform database operation

Show Source

Array of: string

SQL statement

{
    "type":"array",
    "items":{
        "description":"SQL statement",
        "type":"string"
    },
    "description":"SQL statements to perform database operation",
    "example":[
        "CREATE TABLE \"MYSCHEMA\".\"EXAMPLE_TABLE\"(\"ID\" NUMBER, \"DATE_RECV\" DATE);"
    ]
}

Example:

[
    "CREATE TABLE \"MYSCHEMA\".\"EXAMPLE_TABLE\"(\"ID\" NUMBER, \"DATE_RECV\" DATE);"
]

Nested Schema : column

Type: object

Show Source

column_expression: string

Allowed Values: [ "FILE$NAME", "PATH$NAME", "SYSTIMESTAMP" ]

Populate this column with data about the load

Example: SYSTIMESTAMP
column_expression_type: string

Allowed Values: [ "SDO_AREA", "SDO_LENGTH", "SENTIMENT", "TRANSLATION", "KEY_PHRASE_EXTRACTION", "LANGUAGE_DETECTION" ]

Populate this column intelligently from another column

Example: SDO_LENGTH
column_id: integer

Column position in input file

Example: 2
column_name: string

Column name in table

Example: UNITS
data_format: string

Data format for certain column types

Example: YYYY-MM-DD
data_length: integer

Length or precision of column

Example: 40
data_precision: integer

Precision of data for certain column types

Example: 10
data_scale: integer

Scale of data for certain column types

Example: 2
data_type: string

Allowed Values: [ "VARCHAR2", "CLOB", "NUMBER", "INTEGER", "FLOAT", "BINARY_FLOAT", "BINARY_DOUBLE", "DATE", "TIMESTAMP", "TIMESTAMP WITH TIME ZONE", "TIMESTAMP WITH LOCAL TIME ZONE", "NVARCHAR2", "NCLOB", "BOOLEAN", "VECTOR" ]

Data type of column

Example: NUMBER
field_name: string

Name of column in input file

Example: customer name
geojson_tolerance: number

Level of precision for GEOJSon data

Example: 0.5
geojson_unit: string

Unit of GEOJson data for column from SDO_UNITS_OF_MEASURE table

Example: KM
merge_key: boolean

If true, use this column as a merge key for merge operations
primary_key: boolean

Set this column to be the primary key for the table
skip_column: boolean

Set to true to not load this column

Example: false
source_path: string

The JSON path expression for this column

Example: $.EmpNo

{
    "type":"object",
    "properties":{
        "column_name":{
            "$ref":"#/components/schemas/column_name"
        },
        "field_name":{
            "type":"string",
            "example":"customer name",
            "description":"Name of column in input file"
        },
        "column_id":{
            "type":"integer",
            "example":2,
            "description":"Column position in input file"
        },
        "data_type":{
            "type":"string",
            "example":"NUMBER",
            "description":"Data type of column",
            "enum":[
                "VARCHAR2",
                "CLOB",
                "NUMBER",
                "INTEGER",
                "FLOAT",
                "BINARY_FLOAT",
                "BINARY_DOUBLE",
                "DATE",
                "TIMESTAMP",
                "TIMESTAMP WITH TIME ZONE",
                "TIMESTAMP WITH LOCAL TIME ZONE",
                "NVARCHAR2",
                "NCLOB",
                "BOOLEAN",
                "VECTOR"
            ]
        },
        "data_length":{
            "type":"integer",
            "example":40,
            "description":"Length or precision of column"
        },
        "data_precision":{
            "type":"integer",
            "example":10,
            "description":"Precision of data for certain column types"
        },
        "data_scale":{
            "type":"integer",
            "example":2,
            "description":"Scale of data for certain column types"
        },
        "data_format":{
            "type":"string",
            "example":"YYYY-MM-DD",
            "description":"Data format for certain column types"
        },
        "skip_column":{
            "type":"boolean",
            "example":false,
            "description":"Set to true to not load this column"
        },
        "column_expression":{
            "type":"string",
            "example":"SYSTIMESTAMP",
            "description":"Populate this column with data about the load",
            "enum":[
                "FILE$NAME",
                "PATH$NAME",
                "SYSTIMESTAMP"
            ]
        },
        "column_expression_type":{
            "type":"string",
            "example":"SDO_LENGTH",
            "description":"Populate this column intelligently from another column",
            "enum":[
                "SDO_AREA",
                "SDO_LENGTH",
                "SENTIMENT",
                "TRANSLATION",
                "KEY_PHRASE_EXTRACTION",
                "LANGUAGE_DETECTION"
            ]
        },
        "source_path":{
            "type":"string",
            "example":"$.EmpNo",
            "description":"The JSON path expression for this column"
        },
        "merge_key":{
            "type":"boolean",
            "description":"If true, use this column as a merge key for merge operations"
        },
        "primary_key":{
            "type":"boolean",
            "description":"Set this column to be the primary key for the table"
        },
        "geojson_tolerance":{
            "type":"number",
            "example":0.5,
            "description":"Level of precision for GEOJSon data"
        },
        "geojson_unit":{
            "type":"string",
            "example":"KM",
            "description":"Unit of GEOJson data for column from SDO_UNITS_OF_MEASURE table"
        }
    }
}

Nested Schema : data_load_object

Type: object

Show Source

object_name: string

Name of object to load

Example: sales.csv

{
    "type":"object",
    "properties":{
        "object_name":{
            "type":"string",
            "description":"Name of object to load",
            "example":"sales.csv"
        }
    }
}

Response

201 Response

List of Data Loads

Root Schema : data-load-job-ids

Type: object

List of data load job IDs

Show Source

data_load_job_ids: array data_load_job_ids

{
    "type":"object",
    "description":"List of data load job IDs",
    "properties":{
        "data_load_job_ids":{
            "type":"array",
            "items":{
                "$ref":"#/components/schemas/data-load-job-id"
            }
        }
    }
}

Nested Schema : data_load_job_ids

Type: array

Show Source

Array of: object data-load-job-id

ID of data load job

{
    "type":"array",
    "items":{
        "$ref":"#/components/schemas/data-load-job-id"
    }
}

Nested Schema : data-load-job-id

Type: object

ID of data load job

Show Source

data_load_job_id: string

Name of data load job

Example: SALES-LOAD-20220529-112233-4567

{
    "type":"object",
    "description":"ID of data load job",
    "properties":{
        "data_load_job_id":{
            "$ref":"#/components/schemas/data_load_job_id"
        }
    }
}

204 Response

No content