FtpFile
Ftp file source connector
Support Those Engines
Spark
Flink
SeaTunnel Zeta
Key features
- batch
- stream
- exactly-once
- column projection
- parallelism
- support user-defined split
- file format type
- text
- csv
- json
- excel
- xml
- binary
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 |
archive_compress_codec | string | no | none |
encoding | string | no | UTF-8 |
null_format | string | no | - |
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_filter_pattern [string]
Filter pattern, which used for filtering files.
The pattern follows standard regular expressions. For details, please refer to https://en.wikipedia.org/wiki/Regular_expression. There are some examples.
File Structure Example:
/data/seatunnel/20241001/report.txt
/data/seatunnel/20241007/abch202410.csv
/data/seatunnel/20241002/abcg202410.csv
/data/seatunnel/20241005/old_data.csv
/data/seatunnel/20241012/logo.png
Matching Rules Example:
Example 1: Match all .txt files,Regular Expression:
/data/seatunnel/20241001/.*\.txt
The result of this example matching is:
/data/seatunnel/20241001/report.txt
Example 2: Match all file starting with abc,Regular Expression:
/data/seatunnel/20241002/abc.*
The result of this example matching is:
/data/seatunnel/20241007/abch202410.csv
/data/seatunnel/20241002/abcg202410.csv
Example 3: Match all file starting with abc,And the fourth character is either h or g, the Regular Expression:
/data/seatunnel/20241007/abc[h,g].*
The result of this example matching is:
/data/seatunnel/20241007/abch202410.csv
Example 4: Match third level folders starting with 202410 and files ending with .csv, the Regular Expression:
/data/seatunnel/202410\d*/.*\.csv
The result of this example matching is:
/data/seatunnel/20241007/abch202410.csv
/data/seatunnel/20241002/abcg202410.csv
/data/seatunnel/20241005/old_data.csv
file_format_type [string]
File type, supported as the following file types:
text
csv
parquet
orc
json
excel
xml
binary
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 field_delimiter
too except CSV file type
you should assign schema and delimiter as the following:
field_delimiter = "#"
schema {
fields {
name = string
age = int
gender = string
}
}
connector will generate data as the following:
name | age | gender |
---|---|---|
tyrantlucifer | 26 | male |
If you assign file type to binary
, SeaTunnel can synchronize files in any format,
such as compressed packages, pictures, etc. In short, any files can be synchronized to the target place.
Under this requirement, you need to ensure that the source and sink use binary
format for file synchronization
at the same time. You can find the specific usage in the example below.
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.
archive_compress_codec [string]
The compress codec of archive files and the details that supported as the following shown:
archive_compress_codec | file_format | archive_compress_suffix |
---|---|---|
ZIP | txt,json,excel,xml | .zip |
TAR | txt,json,excel,xml | .tar |
TAR_GZ | txt,json,excel,xml | .tar.gz |
GZ | txt,json,excel,xml | .gz |
NONE | all | .* |
Note: gz compressed excel file needs to compress the original file or specify the file suffix, such as e2e.xls ->e2e_test.xls.gz
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)
.
null_format [string]
Only used when file_format_type is text. null_format to define which strings can be represented as null.
e.g: \N
common options
Source plugin common parameters, please refer to Source Common Options for details.
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
}
field_delimiter = "#"
}
Multiple Table
FtpFile {
tables_configs = [
{
schema {
table = "student"
}
path = "/tmp/seatunnel/sink/text"
host = "192.168.31.48"
port = 21
user = tyrantlucifer
password = tianchao
file_format_type = "parquet"
},
{
schema {
table = "teacher"
}
path = "/tmp/seatunnel/sink/text"
host = "192.168.31.48"
port = 21
user = tyrantlucifer
password = tianchao
file_format_type = "parquet"
}
]
}
FtpFile {
tables_configs = [
{
schema {
fields {
name = string
age = int
}
}
path = "/apps/hive/demo/student"
file_format_type = "json"
},
{
schema {
fields {
name = string
age = int
}
}
path = "/apps/hive/demo/teacher"
file_format_type = "json"
}
}
Transfer Binary File
env {
parallelism = 1
job.mode = "BATCH"
}
source {
FtpFile {
host = "192.168.31.48"
port = 21
user = tyrantlucifer
password = tianchao
path = "/seatunnel/read/binary/"
file_format_type = "binary"
}
}
sink {
// you can transfer local file to s3/hdfs/oss etc.
FtpFile {
host = "192.168.31.48"
port = 21
user = tyrantlucifer
password = tianchao
path = "/seatunnel/read/binary2/"
file_format_type = "binary"
}
}
Filter File
env {
parallelism = 1
job.mode = "BATCH"
}
source {
FtpFile {
host = "192.168.31.48"
port = 21
user = tyrantlucifer
password = tianchao
path = "/seatunnel/read/binary/"
file_format_type = "binary"
// file example abcD2024.csv
file_filter_pattern = "abc[DX]*.*"
}
}
sink {
Console {
}
}
Changelog
2.2.0-beta 2022-09-26
- Add Ftp Source Connector