S3File

S3 file source connector

Description

Read data from aws s3 file system.

Tips: We made some trade-offs in order to support more file types, so we used the HDFS protocol for internal access to S3 and this connector need some hadoop dependencies. It's only support hadoop version 2.6.5+. Use this connector, you need add hadoop-aws.jar and hadoop-client.jar to the plugin directory.

Key features

Read all the data in a split in a pollNext call. What splits are read will be saved in snapshot.

[x] schema projection
[x] parallelism
[ ] support user-defined split
[x] file format
- [x] text
- [x] csv
- [x] parquet
- [x] orc
- [x] json

Options

name	type	required	default value
path	string	yes	-
type	string	yes	-
bucket	string	yes	-
access_key	string	no	-
access_secret	string	no	-
hadoop_s3_properties	map	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
schema	config	no	-
common-options		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 s3n://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

type [string]

File type, supported as the following file types:

text csv parquet orc json

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 s3 file system, for example: s3n://seatunnel-test, if you use s3a protocol, this parameter should be s3a://seatunnel-test.

access_key [string]

The access key of s3 file system. If this parameter is not set, please confirm that the credential provider chain can be authenticated correctly, you could check this hadoop-aws

access_secret [string]

The access secret of s3 file system. If this parameter is not set, please confirm that the credential provider chain can be authenticated correctly, you could check this hadoop-aws

hadoop_s3_properties [map]

If you need to add a other option, you could add it here and refer to this hadoop-aws

     hadoop_s3_properties {
       "fs.s3a.aws.credentials.provider" = "org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider"
      }

schema [config]

fields [Config]

The schema of upstream data.

common options

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

Example


  S3File {
    path = "/seatunnel/text"
    access_key = "xxxxxxxxxxxxxxxxx"
    secret_key = "xxxxxxxxxxxxxxxxx"
    bucket = "s3a://seatunnel-test"
    type = "text"
    hadoop_s3_properties {
       "fs.s3a.aws.credentials.provider" = "org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider"
    }    
  }


  S3File {
    path = "/seatunnel/json"
    bucket = "s3a://seatunnel-test"
    access_key = "xxxxxxxxxxxxxxxxx"
    access_secret = "xxxxxxxxxxxxxxxxxxxxxx"
    type = "json"
    schema {
      fields {
        id = int 
        name = string
      }
    }
    hadoop_s3_properties {
       "fs.s3a.aws.credentials.provider" = "org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider"
    }    
  }

Changelog

2.3.0-beta 2022-10-20

Add S3File Source Connector

Next version

[Feature] Support S3A protocol (3632)
- Allow user to add additional hadoop-s3 parameters
- Allow the use of the s3a protocol
- Decouple hadoop-aws dependencies
[Feature]Set S3 AK to optional (3688)