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OssFile
Oss file source connector
Description
Read data from aliyun oss 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.
We made some trade-offs in order to support more file types, so we used the HDFS protocol for internal access to OSS and this connector need some hadoop dependencies. It only supports hadoop version 2.9.X+.
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
Options
| name | type | required | default value |
|---|---|---|---|
| path | string | yes | - |
| file_format_type | string | yes | - |
| bucket | string | yes | - |
| access_key | string | yes | - |
| access_secret | string | yes | - |
| endpoint | string | yes | - |
| read_columns | list | yes | - |
| delimiter | string | no | \001 |
| parse_partition_from_path | boolean | no | true |
| skip_header_row_number | long | no | 0 |
| date_format | string | no | yyyy-MM-dd |
| datetime_format | string | no | yyyy-MM-dd HH:mm:ss |
| time_format | string | no | HH:mm:ss |
| schema | config | no | - |
| common-options | no | - | |
| sheet_name | string | no | - |
| file_filter_pattern | string | no | - |
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 oss://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
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 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 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 |
bucket [string]
The bucket address of oss file system, for example: oss://tyrantlucifer-image-bed
access_key [string]
The access key of oss file system.
access_secret [string]
The access secret of oss file system.
endpoint [string]
The endpoint of oss file system.
schema [config]
fields [Config]
The schema 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
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_type is excel.
Example
OssFile {
path = "/seatunnel/orc"
bucket = "oss://tyrantlucifer-image-bed"
access_key = "xxxxxxxxxxxxxxxxx"
access_secret = "xxxxxxxxxxxxxxxxxxxxxx"
endpoint = "oss-cn-beijing.aliyuncs.com"
file_format_type = "orc"
}
OssFile {
path = "/seatunnel/json"
bucket = "oss://tyrantlucifer-image-bed"
access_key = "xxxxxxxxxxxxxxxxx"
access_secret = "xxxxxxxxxxxxxxxxxxxxxx"
endpoint = "oss-cn-beijing.aliyuncs.com"
file_format_type = "json"
schema {
fields {
id = int
name = string
}
}
}
file_filter_pattern [string]
Filter pattern, which used for filtering files.
Changelog
2.2.0-beta 2022-09-26
- Add OSS File Source Connector