Table
Filter plugin : Table
- Author: InterestingLab
 - Homepage: https://interestinglab.github.io/seatunnel-docs
 - Version: 1.0.0
 
Description
It is used to map static files into a table, which can be associated with real-time processed streams.
It is always used for joining user nicknames, national provinces and cities, etc.
Options
| name | type | required | default value | 
|---|---|---|---|
| cache | boolean | no | true | 
| delimiter | string | no | , | 
| field_types | array | no | - | 
| fields | array | yes | - | 
| path | string | yes | - | 
| table_name | string | yes | - | 
cache [boolean]
Whether to cache file contents in memory. If false, it will reload every time you need.
delimiter [string]
The delimiter between columns in the file.
field_types [array]
The type of each field, the order and length of field_types must correspond to the fields parameter. The default type of all columns is string. Supported data types include: boolean, double, long, string
fields [array]
The names of the columns in each row, while should be provided by the actual columns in the data in order.
path [string]
File path supported by Spark. For example, file:///path/to/file, hdfs:///path/to/file, s3:///path/to/file ...
table_name [string]
After loading the file, it will be registered as a table. Here, the table name is specified, which can be used to directly associate with the stream processing data.
Example
Without
field_types
table {
    table_name = "mydict"
    path = "/user/seatunnel/mylog/a.txt"
    fields = ['city', 'population']
}
With
field_types
table {
    table_name = "mydict"
    path = "/user/seatunnel/mylog/a.txt"
    fields = ['city', 'population']
    field_types = ['string', 'long']
}