⭐️
LocalFile
Local file source connector
Support Those Engines
Spark
Flink
SeaTunnel Zeta
Key features
Read all the data in a split in a pollNext call. What splits are read will be saved in snapshot.
- column projection
- parallelism
- support user-defined split
- file format type
- text
- csv
- parquet
- orc
- json
- excel
- xml
- binary
Description
Read data from local file system.
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 |
|---|---|---|---|
| path | string | yes | - |
| file_format_type | string | yes | - |
| read_columns | list | no | - |
| delimiter/field_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 | - |
| 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 |
| common-options | no | - | |
| tables_configs | list | no | used to define a multiple table task |
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 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 can also save multiple pieces of data in one file and split them by newline:
{"code": 200, "data": "get success", "success": true}
{"code": 300, "data": "get failed", "success": false}
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 parquet orc, schema option not required, connector can find the schema of upstream data automatically.
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.
read_columns [list]
The read column list of the data source, user can use it to implement field projection.
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 file://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).
fields [Config]
The schema information of upstream data.
sheet_name [string]
Only need to be configured when file_format is excel.
Reader the sheet of the workbook.
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.
file_filter_pattern [string]
Filter pattern, which used for filtering files.
compress_codec [string]
The compress codec of files and the details that supported as the following shown:
- txt:
lzonone - json:
lzonone - csv:
lzonone - 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 |
| NONE | all | .* |
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
tables_configs
Used to define a multiple table task, when you have multiple tables to read, you can use this option to define multiple tables.
Example
One Table
LocalFile {
path = "/apps/hive/demo/student"
file_format_type = "parquet"
}
LocalFile {
schema {
fields {
name = string
age = int
}
}
path = "/apps/hive/demo/student"
file_format_type = "json"
}
For json, text or csv file format with encoding
LocalFile {
path = "/tmp/hive/warehouse/test2"
file_format_type = "text"
encoding = "gbk"
}
Multiple Table
LocalFile {
tables_configs = [
{
schema {
table = "student"
}
path = "/apps/hive/demo/student"
file_format_type = "parquet"
},
{
schema {
table = "teacher"
}
path = "/apps/hive/demo/teacher"
file_format_type = "parquet"
}
]
}
LocalFile {
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 {
LocalFile {
path = "/seatunnel/read/binary/"
file_format_type = "binary"
}
}
sink {
// you can transfer local file to s3/hdfs/oss etc.
LocalFile {
path = "/seatunnel/read/binary2/"
file_format_type = "binary"
}
}
Changelog
2.2.0-beta 2022-09-26
- Add Local File Source Connector