FtpFile
Ftp file source connector
Description
Read data from ftp file server.
If you use spark/flink, In order to use this connector, You must ensure your spark/flink cluster already integrated hadoop. The tested hadoop version is 2.x.
If you use SeaTunnel Engine, It automatically integrated the hadoop jar when you download and install SeaTunnel Engine. You can check the jar package under ${SEATUNNEL_HOME}/lib to confirm this.
Key features
- batch
- stream
- exactly-once
- column projection
- parallelism
- support user-defined split
- file format type
- text
- csv
- json
- excel
Options
name | type | required | default value |
---|---|---|---|
host | string | yes | - |
port | int | yes | - |
user | string | yes | - |
password | string | yes | - |
path | string | yes | - |
file_format_type | string | yes | - |
read_columns | list | no | - |
delimiter | string | no | \001 |
parse_partition_from_path | boolean | no | true |
date_format | string | no | yyyy-MM-dd |
datetime_format | string | no | yyyy-MM-dd HH:mm:ss |
time_format | string | no | HH:mm:ss |
skip_header_row_number | long | no | 0 |
schema | config | no | - |
common-options | no | - | |
sheet_name | string | no | - |
host [string]
The target ftp host is required
port [int]
The target ftp port is required
username [string]
The target ftp username is required
password [string]
The target ftp password is required
path [string]
The source file path.
delimiter [string]
Field delimiter, used to tell connector how to slice and dice fields when reading text files
default \001
, the same as hive's default delimiter
parse_partition_from_path [boolean]
Control whether parse the partition keys and values from file path
For example if you read a file from path ftp://hadoop-cluster/tmp/seatunnel/parquet/name=tyrantlucifer/age=26
Every record data from file will be added these two fields:
name | age |
---|---|
tyrantlucifer | 26 |
Tips: Do not define partition fields in schema option
date_format [string]
Date type format, used to tell connector how to convert string to date, supported as the following formats:
yyyy-MM-dd
yyyy.MM.dd
yyyy/MM/dd
default yyyy-MM-dd
datetime_format [string]
Datetime type format, used to tell connector how to convert string to datetime, supported as the following formats:
yyyy-MM-dd HH:mm:ss
yyyy.MM.dd HH:mm:ss
yyyy/MM/dd HH:mm:ss
yyyyMMddHHmmss
default yyyy-MM-dd HH:mm:ss
time_format [string]
Time type format, used to tell connector how to convert string to time, supported as the following formats:
HH:mm:ss
HH:mm:ss.SSS
default HH:mm:ss
skip_header_row_number [long]
Skip the first few lines, but only for the txt and csv.
For example, set like following:
skip_header_row_number = 2
then Seatunnel will skip the first 2 lines from source files
schema [config]
The schema information of upstream data.
read_columns [list]
The read column list of the data source, user can use it to implement field projection.
The file type supported column projection as the following shown:
- text
- json
- csv
- orc
- parquet
- excel
Tips: If the user wants to use this feature when reading text
json
csv
files, the schema option must be configured
file_format_type [string]
File type, supported as the following file types:
text
csv
parquet
orc
json
excel
If you assign file type to json
, you should also assign schema option to tell connector how to parse data to the row you want.
For example:
upstream data is the following:
{"code": 200, "data": "get success", "success": true}
you should assign schema as the following:
schema {
fields {
code = int
data = string
success = boolean
}
}
connector will generate data as the following:
code | data | success |
---|---|---|
200 | get success | true |
If you assign file type to text
csv
, you can choose to specify the schema information or not.
For example, upstream data is the following:
tyrantlucifer#26#male
If you do not assign data schema connector will treat the upstream data as the following:
content |
---|
tyrantlucifer#26#male |
If you assign data schema, you should also assign the option delimiter
too except CSV file type
you should assign schema and delimiter as the following:
delimiter = "#"
schema {
fields {
name = string
age = int
gender = string
}
}
connector will generate data as the following:
name | age | gender |
---|---|---|
tyrantlucifer | 26 | male |
common options
Source plugin common parameters, please refer to Source Common Options for details.
sheet_name [string]
Reader the sheet of the workbook,Only used when file_format is excel.
Example
FtpFile {
path = "/tmp/seatunnel/sink/text"
host = "192.168.31.48"
port = 21
user = tyrantlucifer
password = tianchao
file_format_type = "text"
schema = {
name = string
age = int
}
delimiter = "#"
}
Changelog
2.2.0-beta 2022-09-26
- Add Ftp Source Connector