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Info

실제 개발자들이 default 가 아닌 확장 컬럼을 사용할 수 도 있을 것 같습니다.

그래서, 별도로 본인들의 lake를 구성할 수 있는 여지를 줘야합니다.

  • 변경된 url과 sample반영해야 함.

note

Info

This API creates a data lake for the user to use. Define the Tag of the data lake to be created, its extended columns and Values, and its definite columns. And, don't forget to design well in advance because the data structure determined in this way cannot be changed. The last created Data Lake incurs an immediate cost, so call it with caution.

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Prerequisites

Key

Type

Description

lake_name

string

lake name

lake_plan

string

tiny / basic / business/ enterprise

owner

string

Lake's Owner

(When omitted, the user who calls the API)

region

string

AWS region name

timezone

string

Timezone name

storage_size

int

Storage size

tag_schema

JSON

Columns for this lake's Tag meta.

Each column have the three sub component: col_name, col_type, col_length.

col_name : column name

col_type : column type

  • “short” : fixed integer value (2 byte length)

  • “int” : fixed integer value (4 byte)

  • “long” : fixed integer value (8 byte)

  • “float” : floating point value (4 byte)

  • “double” : floating point value(8 byte)

  • “datetime” : time data to nano precision (8 byte)

  • “varchar” : string type

col_length : if varchar type, assign the max length of column

Code Block
 {'col_name': "name", 'col_type': "varchar", 'col_length': 40}

The data type of the first column , “col_type” must be “varchar”.

But, additional meta column can have any data type.

value_schema

JSON

Columns for this lake’s values.

In this field, you have to assign two essential columns for time and default value.

The first column datatype must be “datetime”.

The second column datatype must be “double” keeping numeric data as default.

Code Block
   {'col_name': "time", 'col_type': "datetime"},
   {'col_name': "value",'col_type': "double"}

However, beginning with the third column information, you can have the option of specifying additional column information.

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