Ftp file source connector

Support Those Engines

Spark
Flink
SeaTunnel Zeta

Key features

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.

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 -
connection_mode string no active_local
delimiter/field_delimiter string no \001
read_columns list no -
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 -
sheet_name string no -
xml_row_tag string no -
xml_use_attr_format boolean no -
file_filter_pattern string no -
compress_codec string no none
encoding string no UTF-8
common-options no -

host [string]

The target ftp host is required

port [int]

The target ftp port is required

user [string]

The target ftp user name is required

password [string]

The target ftp password is required

path [string]

The source file path.

file_format_type [string]

File type, supported as the following file types:

text csv parquet orc json excel xml

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:

  1. {"code": 200, "data": "get success", "success": true}

you should assign schema as the following:

  1. schema {
  2. fields {
  3. code = int
  4. data = string
  5. success = boolean
  6. }
  7. }

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:

  1. 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 field_delimiter too except CSV file type

you should assign schema and delimiter as the following:

  1. field_delimiter = "#"
  2. schema {
  3. fields {
  4. name = string
  5. age = int
  6. gender = string
  7. }
  8. }

connector will generate data as the following:

name age gender
tyrantlucifer 26 male

connection_mode [string]

The target ftp connection mode , default is active mode, supported as the following modes:

active_local passive_local

delimiter/field_delimiter [string]

delimiter parameter will deprecate after version 2.3.5, please use field_delimiter instead.

Only need to be configured when file_format is text.

Field delimiter, used to tell connector how to slice and dice fields.

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]

Only need to be configured when the file_format_type are text, json, excel, xml or csv ( Or other format we can’t read the schema from metadata).

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.

sheet_name [string]

Reader the sheet of the workbook,Only used when file_format_type is excel.

xml_row_tag [string]

Only need to be configured when file_format is xml.

Specifies the tag name of the data rows within the XML file.

xml_use_attr_format [boolean]

Only need to be configured when file_format is xml.

Specifies Whether to process data using the tag attribute format.

compress_codec [string]

The compress codec of files and the details that supported as the following shown:

  • txt: lzo none
  • json: lzo none
  • csv: lzo none
  • orc/parquet:
    automatically recognizes the compression type, no additional settings required.

encoding [string]

Only used when file_format_type is json,text,csv,xml. The encoding of the file to read. This param will be parsed by Charset.forName(encoding).

common options

Source plugin common parameters, please refer to Source Common Options for details.

Example

  1. FtpFile {
  2. path = "/tmp/seatunnel/sink/text"
  3. host = "192.168.31.48"
  4. port = 21
  5. user = tyrantlucifer
  6. password = tianchao
  7. file_format_type = "text"
  8. schema = {
  9. name = string
  10. age = int
  11. }
  12. field_delimiter = "#"
  13. }

Changelog

2.2.0-beta 2022-09-26

  • Add Ftp Source Connector

2.3.0-beta 2022-10-20

  • [BugFix] Fix the bug of incorrect path in windows environment (2980)
  • [Improve] Support extract partition from SeaTunnelRow fields (3085)
  • [Improve] Support parse field from file path (2985)