S3 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.

Description

Read data from aws s3 file system.

Supported DataSource Info

Datasource Supported versions
S3 current

Dependency

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 Zeta, It automatically integrated the hadoop jar when you download and install SeaTunnel Zeta. You can check the jar package under ${SEATUNNEL_HOME}/lib to confirm this.
To use this connector you need put hadoop-aws-3.1.4.jar and aws-java-sdk-bundle-1.12.692.jar in ${SEATUNNEL_HOME}/lib dir.

Data Type Mapping

Data type mapping is related to the type of file being read, We supported as the following file types:

text csv parquet orc json excel xml

JSON File Type

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 can also save multiple pieces of data in one file and split them by newline:

  1. {"code": 200, "data": "get success", "success": true}
  2. {"code": 300, "data": "get failed", "success": false}

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

Text Or CSV File Type

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

Orc File Type

If you assign file type to parquet orc, schema option not required, connector can find the schema of upstream data automatically.

Orc Data type SeaTunnel Data type
BOOLEAN BOOLEAN
INT INT
BYTE BYTE
SHORT SHORT
LONG LONG
FLOAT FLOAT
DOUBLE DOUBLE
BINARY BINARY
STRING
VARCHAR
CHAR
STRING
DATE LOCAL_DATE_TYPE
TIMESTAMP LOCAL_DATE_TIME_TYPE
DECIMAL DECIMAL
LIST(STRING) STRING_ARRAY_TYPE
LIST(BOOLEAN) BOOLEAN_ARRAY_TYPE
LIST(TINYINT) BYTE_ARRAY_TYPE
LIST(SMALLINT) SHORT_ARRAY_TYPE
LIST(INT) INT_ARRAY_TYPE
LIST(BIGINT) LONG_ARRAY_TYPE
LIST(FLOAT) FLOAT_ARRAY_TYPE
LIST(DOUBLE) DOUBLE_ARRAY_TYPE
Map MapType, This type of K and V will transform to SeaTunnel type
STRUCT SeaTunnelRowType

Parquet File Type

If you assign file type to parquet orc, schema option not required, connector can find the schema of upstream data automatically.

Orc Data type SeaTunnel Data type
INT_8 BYTE
INT_16 SHORT
DATE DATE
TIMESTAMP_MILLIS TIMESTAMP
INT64 LONG
INT96 TIMESTAMP
BINARY BYTES
FLOAT FLOAT
DOUBLE DOUBLE
BOOLEAN BOOLEAN
FIXED_LEN_BYTE_ARRAY TIMESTAMP
DECIMAL
DECIMAL DECIMAL
LIST(STRING) STRING_ARRAY_TYPE
LIST(BOOLEAN) BOOLEAN_ARRAY_TYPE
LIST(TINYINT) BYTE_ARRAY_TYPE
LIST(SMALLINT) SHORT_ARRAY_TYPE
LIST(INT) INT_ARRAY_TYPE
LIST(BIGINT) LONG_ARRAY_TYPE
LIST(FLOAT) FLOAT_ARRAY_TYPE
LIST(DOUBLE) DOUBLE_ARRAY_TYPE
Map MapType, This type of K and V will transform to SeaTunnel type
STRUCT SeaTunnelRowType

Options

name type required default value Description
path string yes - The s3 path that needs to be read can have sub paths, but the sub paths need to meet certain format requirements. Specific requirements can be referred to “parse_partition_from_path” option
file_format_type string yes - File type, supported as the following file types: text csv parquet orc json excel xml
bucket string yes - The bucket address of s3 file system, for example: s3n://seatunnel-test, if you use s3a protocol, this parameter should be s3a://seatunnel-test.
fs.s3a.endpoint string yes - fs s3a endpoint
fs.s3a.aws.credentials.provider string yes com.amazonaws.auth.InstanceProfileCredentialsProvider The way to authenticate s3a. We only support org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider and com.amazonaws.auth.InstanceProfileCredentialsProvider now. More information about the credential provider you can see Hadoop AWS Document
read_columns list no - 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 csv parquet orc json excel xml . If the user wants to use this feature when reading text json csv files, the “schema” option must be configured.
access_key string no - Only used when fs.s3a.aws.credentials.provider = org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider
access_secret string no - Only used when fs.s3a.aws.credentials.provider = org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider
hadoop_s3_properties map no - If you need to add other option, you could add it here and refer to this link
delimiter/field_delimiter string no \001 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 no true 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=”tyrantlucifer”, age=16
date_format string no yyyy-MM-dd 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 no yyyy-MM-dd HH:mm:ss 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
time_format string no HH:mm:ss 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
skip_header_row_number long no 0 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 no - The schema of upstream data.
sheet_name string no - Reader the sheet of the workbook,Only used when file_format is excel.
xml_row_tag string no - Specifies the tag name of the data rows within the XML file, only valid for XML files.
xml_use_attr_format boolean no - Specifies whether to process data using the tag attribute format, only valid for XML files.
compress_codec string no none
encoding string no UTF-8
common-options no - Source plugin common parameters, please refer to Source Common Options for details.

delimiter/field_delimiter [string]

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

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).

Example

  1. In this example, We read data from s3 path s3a://seatunnel-test/seatunnel/text and the file type is orc in this path. We use org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider to authentication so access_key and secret_key is required. All columns in the file will be read and send to sink.
  1. # Defining the runtime environment
  2. env {
  3. parallelism = 1
  4. job.mode = "BATCH"
  5. }
  6. source {
  7. S3File {
  8. path = "/seatunnel/text"
  9. fs.s3a.endpoint="s3.cn-north-1.amazonaws.com.cn"
  10. fs.s3a.aws.credentials.provider = "org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider"
  11. access_key = "xxxxxxxxxxxxxxxxx"
  12. secret_key = "xxxxxxxxxxxxxxxxx"
  13. bucket = "s3a://seatunnel-test"
  14. file_format_type = "orc"
  15. }
  16. }
  17. transform {
  18. # If you would like to get more information about how to configure seatunnel and see full list of transform plugins,
  19. # please go to https://seatunnel.apache.org/docs/category/transform-v2
  20. }
  21. sink {
  22. Console {}
  23. }
  1. Use InstanceProfileCredentialsProvider to authentication The file type in S3 is json, so need config schema option.
  1. S3File {
  2. path = "/seatunnel/json"
  3. bucket = "s3a://seatunnel-test"
  4. fs.s3a.endpoint="s3.cn-north-1.amazonaws.com.cn"
  5. fs.s3a.aws.credentials.provider="com.amazonaws.auth.InstanceProfileCredentialsProvider"
  6. file_format_type = "json"
  7. schema {
  8. fields {
  9. id = int
  10. name = string
  11. }
  12. }
  13. }
  1. Use InstanceProfileCredentialsProvider to authentication The file type in S3 is json and has five fields (id, name, age, sex, type), so need config schema option. In this job, we only need send id and name column to mysql.
  1. # Defining the runtime environment
  2. env {
  3. parallelism = 1
  4. job.mode = "BATCH"
  5. }
  6. source {
  7. S3File {
  8. path = "/seatunnel/json"
  9. bucket = "s3a://seatunnel-test"
  10. fs.s3a.endpoint="s3.cn-north-1.amazonaws.com.cn"
  11. fs.s3a.aws.credentials.provider="com.amazonaws.auth.InstanceProfileCredentialsProvider"
  12. file_format_type = "json"
  13. read_columns = ["id", "name"]
  14. schema {
  15. fields {
  16. id = int
  17. name = string
  18. age = int
  19. sex = int
  20. type = string
  21. }
  22. }
  23. }
  24. }
  25. transform {
  26. # If you would like to get more information about how to configure seatunnel and see full list of transform plugins,
  27. # please go to https://seatunnel.apache.org/docs/category/transform-v2
  28. }
  29. sink {
  30. Console {}
  31. }

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)