Fake

Description

Fake is mainly used to conveniently generate user-specified data, which is used as input for functional verification, testing, and performance testing of seatunnel.

note

Engine Supported and plugin name

• Spark: Fake, FakeStream
• Flink: FakeSource, FakeSourceStream
  • Flink Fake Source is mainly used to automatically generate data. The data has only two columns. The first column is of String type and the content is a random one from ["Gary", "Ricky Huo", "Kid Xiong"] . The second column is of Long type , which is The current 13-bit timestamp is used as input for functional verification and testing of seatunnel .

Options

Spark

note

These options is for Spark:FakeStream, and Spark:Fake do not have any options

name	type	required	default value
content	array	no	-
rate	number	yes	-
common-options	string	yes	-

content [array]

List of test data strings

rate [number]

Number of test cases generated per second

Flink

name	type	required	default value
parallelism	Int	no	-
common-options	string	no	-

parallelism [Int]

The parallelism of an individual operator, for Fake Source Stream

common options [string]

Source plugin common parameters, please refer to Source Plugin for details

Examples

Spark

Fake

Fake {
    result_table_name = "my_dataset"
}

FakeStream

fakeStream {
    content = ["name=ricky&age=23", "name=gary&age=28"]
    rate = 5
}

The generated data is as follows, randomly extract the string from the content list

+-----------------+
|raw_message      |
+-----------------+
|name=gary&age=28 |
|name=ricky&age=23|
+-----------------+

Flink

FakeSourceStream

source {
    FakeSourceStream {
        result_table_name = "fake"
        field_name = "name,age"
    }
}

FakeSource

source {
    FakeSource {
        result_table_name = "fake"
        field_name = "name,age"
    }
}