S3File
S3 File Sink Connector
Support Those Engines
Spark
Flink
SeaTunnel Zeta
Key Features
By default, we use 2PC commit to ensure exactly-once
- file format type
- text
- csv
- parquet
- orc
- json
- excel
- xml
- binary
Description
Output data to aws s3 file system.
Supported DataSource Info
Datasource | Supported Versions |
---|---|
S3 | current |
Database 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 Engine, It automatically integrated the hadoop jar when you download and install SeaTunnel Engine. You can check the jar package under
${SEATUNNEL_HOME}/lib
to confirm this. To use this connector you need puthadoop-aws-3.1.4.jar
andaws-java-sdk-bundle-1.12.692.jar
in${SEATUNNEL_HOME}/lib
dir.
Data Type Mapping
If write to csv
, text
file type, All column will be string.
Orc File Type
SeaTunnel Data type | Orc Data type |
---|---|
STRING | STRING |
BOOLEAN | BOOLEAN |
TINYINT | BYTE |
SMALLINT | SHORT |
INT | INT |
BIGINT | LONG |
FLOAT | FLOAT |
FLOAT | FLOAT |
DOUBLE | DOUBLE |
DECIMAL | DECIMAL |
BYTES | BINARY |
DATE | DATE |
TIME TIMESTAMP | TIMESTAMP |
ROW | STRUCT |
NULL | UNSUPPORTED DATA TYPE |
ARRAY | LIST |
Map | Map |
Parquet File Type
SeaTunnel Data type | Parquet Data type |
---|---|
STRING | STRING |
BOOLEAN | BOOLEAN |
TINYINT | INT_8 |
SMALLINT | INT_16 |
INT | INT32 |
BIGINT | INT64 |
FLOAT | FLOAT |
FLOAT | FLOAT |
DOUBLE | DOUBLE |
DECIMAL | DECIMAL |
BYTES | BINARY |
DATE | DATE |
TIME TIMESTAMP | TIMESTAMP_MILLIS |
ROW | GroupType |
NULL | UNSUPPORTED DATA TYPE |
ARRAY | LIST |
Map | Map |
Sink Options
name | type | required | default value | Description |
---|---|---|---|---|
path | string | yes | - | |
tmp_path | string | no | /tmp/seatunnel | The result file will write to a tmp path first and then use mv to submit tmp dir to target dir. Need a S3 dir. |
bucket | string | yes | - | |
fs.s3a.endpoint | string | yes | - | |
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. |
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 |
custom_filename | boolean | no | false | Whether you need custom the filename |
file_name_expression | string | no | "${transactionId}" | Only used when custom_filename is true |
filename_time_format | string | no | "yyyy.MM.dd" | Only used when custom_filename is true |
file_format_type | string | no | "csv" | |
field_delimiter | string | no | '\001' | Only used when file_format is text |
row_delimiter | string | no | "\n" | Only used when file_format is text |
have_partition | boolean | no | false | Whether you need processing partitions. |
partition_by | array | no | - | Only used when have_partition is true |
partition_dir_expression | string | no | "${k0}=${v0}/${k1}=${v1}/.../${kn}=${vn}/" | Only used when have_partition is true |
is_partition_field_write_in_file | boolean | no | false | Only used when have_partition is true |
sink_columns | array | no | When this parameter is empty, all fields are sink columns | |
is_enable_transaction | boolean | no | true | |
batch_size | int | no | 1000000 | |
compress_codec | string | no | none | |
common-options | object | no | - | |
max_rows_in_memory | int | no | - | Only used when file_format is excel. |
sheet_name | string | no | Sheet${Random number} | Only used when file_format is excel. |
xml_root_tag | string | no | RECORDS | Only used when file_format is xml, specifies the tag name of the root element within the XML file. |
xml_row_tag | string | no | RECORD | Only used when file_format is xml, specifies the tag name of the data rows within the XML file |
xml_use_attr_format | boolean | no | - | Only used when file_format is xml, specifies Whether to process data using the tag attribute format. |
parquet_avro_write_timestamp_as_int96 | boolean | no | false | Only used when file_format is parquet. |
parquet_avro_write_fixed_as_int96 | array | no | - | Only used when file_format is parquet. |
hadoop_s3_properties | map | no | If you need to add a other option, you could add it here and refer to this link | |
schema_save_mode | Enum | no | CREATE_SCHEMA_WHEN_NOT_EXIST | Before turning on the synchronous task, do different treatment of the target path |
data_save_mode | Enum | no | APPEND_DATA | Before opening the synchronous task, the data file in the target path is differently processed |
encoding | string | no | "UTF-8" | Only used when file_format_type is json,text,csv,xml. |
path [string]
Store the path of the data file to support variable replacement. For example: path=/test/${database_name}/${schema_name}/${table_name}
hadoop_s3_properties [map]
If you need to add a other option, you could add it here and refer to this link
hadoop_s3_properties {
"fs.s3a.buffer.dir" = "/data/st_test/s3a"
"fs.s3a.fast.upload.buffer" = "disk"
}
custom_filename [boolean]
Whether custom the filename
file_name_expression [string]
Only used when custom_filename
is true
file_name_expression
describes the file expression which will be created into the path
. We can add the variable ${now}
or ${uuid}
in the file_name_expression
, like test_${uuid}_${now}
,
${now}
represents the current time, and its format can be defined by specifying the option filename_time_format
.
Please note that, If is_enable_transaction
is true
, we will auto add ${transactionId}_
in the head of the file.
filename_time_format [string]
Only used when custom_filename
is true
When the format in the file_name_expression
parameter is xxxx-${now}
, filename_time_format
can specify the time format of the path, and the default value is yyyy.MM.dd
. The commonly used time formats are listed as follows:
Symbol | Description |
---|---|
y | Year |
M | Month |
d | Day of month |
H | Hour in day (0-23) |
m | Minute in hour |
s | Second in minute |
file_format_type [string]
We supported as the following file types:
text
csv
parquet
orc
json
excel
xml
binary
Please note that, The final file name will end with the file_format_type's suffix, the suffix of the text file is txt
.
field_delimiter [string]
The separator between columns in a row of data. Only needed by text
file format.
row_delimiter [string]
The separator between rows in a file. Only needed by text
file format.
have_partition [boolean]
Whether you need processing partitions.
partition_by [array]
Only used when have_partition
is true
.
Partition data based on selected fields.
partition_dir_expression [string]
Only used when have_partition
is true
.
If the partition_by
is specified, we will generate the corresponding partition directory based on the partition information, and the final file will be placed in the partition directory.
Default partition_dir_expression
is ${k0}=${v0}/${k1}=${v1}/.../${kn}=${vn}/
. k0
is the first partition field and v0
is the value of the first partition field.
is_partition_field_write_in_file [boolean]
Only used when have_partition
is true
.
If is_partition_field_write_in_file
is true
, the partition field and the value of it will be write into data file.
For example, if you want to write a Hive Data File, Its value should be false
.
sink_columns [array]
Which columns need be written to file, default value is all the columns get from Transform
or Source
.
The order of the fields determines the order in which the file is actually written.
is_enable_transaction [boolean]
If is_enable_transaction
is true, we will ensure that data will not be lost or duplicated when it is written to the target directory.
Please note that, If is_enable_transaction
is true
, we will auto add ${transactionId}_
in the head of the file.
Only support true
now.
batch_size [int]
The maximum number of rows in a file. For SeaTunnel Engine, the number of lines in the file is determined by batch_size
and checkpoint.interval
jointly decide. If the value of checkpoint.interval
is large enough, sink writer will write rows in a file until the rows in the file larger than batch_size
. If checkpoint.interval
is small, the sink writer will create a new file when a new checkpoint trigger.
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:
lzo
snappy
lz4
zlib
none
- parquet:
lzo
snappy
lz4
gzip
brotli
zstd
none
Tips: excel type does not support any compression format
common options
Sink plugin common parameters, please refer to Sink Common Options for details.
max_rows_in_memory [int]
When File Format is Excel,The maximum number of data items that can be cached in the memory.
sheet_name [string]
Writer the sheet of the workbook
xml_root_tag [string]
Specifies the tag name of the root element within the XML file.
xml_row_tag [string]
Specifies the tag name of the data rows within the XML file.
xml_use_attr_format [boolean]
Specifies Whether to process data using the tag attribute format.
parquet_avro_write_timestamp_as_int96 [boolean]
Support writing Parquet INT96 from a timestamp, only valid for parquet files.
parquet_avro_write_fixed_as_int96 [array]
Support writing Parquet INT96 from a 12-byte field, only valid for parquet files.
schema_save_mode[Enum]
Before turning on the synchronous task, do different treatment of the target path.
Option introduction:
RECREATE_SCHEMA
:Will be created when the path does not exist. If the path already exists, delete the path and recreate it.
CREATE_SCHEMA_WHEN_NOT_EXIST
:Will Created when the path does not exist, use the path when the path is existed.
ERROR_WHEN_SCHEMA_NOT_EXIST
:Error will be reported when the path does not exist
IGNORE
:Ignore the treatment of the table
data_save_mode[Enum]
Before opening the synchronous task, the data file in the target path is differently processed.
Option introduction:
DROP_DATA
: use the path but delete data files in the path.
APPEND_DATA
:use the path, and add new files in the path for write data.
ERROR_WHEN_DATA_EXISTS
:When there are some data files in the path, an error will is reported.
encoding [string]
Only used when file_format_type is json,text,csv,xml.
The encoding of the file to write. This param will be parsed by Charset.forName(encoding)
.
Example
Simple:
This example defines a SeaTunnel synchronization task that automatically generates data through FakeSource and sends it to S3File Sink. FakeSource generates a total of 16 rows of data (row.num=16), with each row having two fields, name (string type) and age (int type). The final target s3 dir will also create a file and all of the data in write in it. Before run this job, you need create s3 path: /seatunnel/text. And if you have not yet installed and deployed SeaTunnel, you need to follow the instructions in Install SeaTunnel to install and deploy SeaTunnel. And then follow the instructions in Quick Start With SeaTunnel Engine to run this job.
# Defining the runtime environment
env {
parallelism = 1
job.mode = "BATCH"
}
source {
# This is a example source plugin **only for test and demonstrate the feature source plugin**
FakeSource {
parallelism = 1
result_table_name = "fake"
row.num = 16
schema = {
fields {
c_map = "map<string, array<int>>"
c_array = "array<int>"
name = string
c_boolean = boolean
age = tinyint
c_smallint = smallint
c_int = int
c_bigint = bigint
c_float = float
c_double = double
c_decimal = "decimal(16, 1)"
c_null = "null"
c_bytes = bytes
c_date = date
c_timestamp = timestamp
}
}
}
# If you would like to get more information about how to configure seatunnel and see full list of source plugins,
# please go to https://seatunnel.apache.org/docs/connector-v2/source
}
transform {
# If you would like to get more information about how to configure seatunnel and see full list of transform plugins,
# please go to https://seatunnel.apache.org/docs/category/transform-v2
}
sink {
S3File {
bucket = "s3a://seatunnel-test"
tmp_path = "/tmp/seatunnel"
path="/seatunnel/text"
fs.s3a.endpoint="s3.cn-north-1.amazonaws.com.cn"
fs.s3a.aws.credentials.provider="com.amazonaws.auth.InstanceProfileCredentialsProvider"
file_format_type = "text"
field_delimiter = "\t"
row_delimiter = "\n"
have_partition = true
partition_by = ["age"]
partition_dir_expression = "${k0}=${v0}"
is_partition_field_write_in_file = true
custom_filename = true
file_name_expression = "${transactionId}_${now}"
filename_time_format = "yyyy.MM.dd"
sink_columns = ["name","age"]
is_enable_transaction=true
hadoop_s3_properties {
"fs.s3a.buffer.dir" = "/data/st_test/s3a"
"fs.s3a.fast.upload.buffer" = "disk"
}
}
# If you would like to get more information about how to configure seatunnel and see full list of sink plugins,
# please go to https://seatunnel.apache.org/docs/connector-v2/sink
}
For text file format with have_partition
and custom_filename
and sink_columns
and com.amazonaws.auth.InstanceProfileCredentialsProvider
S3File {
bucket = "s3a://seatunnel-test"
tmp_path = "/tmp/seatunnel"
path="/seatunnel/text"
fs.s3a.endpoint="s3.cn-north-1.amazonaws.com.cn"
fs.s3a.aws.credentials.provider="com.amazonaws.auth.InstanceProfileCredentialsProvider"
file_format_type = "text"
field_delimiter = "\t"
row_delimiter = "\n"
have_partition = true
partition_by = ["age"]
partition_dir_expression = "${k0}=${v0}"
is_partition_field_write_in_file = true
custom_filename = true
file_name_expression = "${transactionId}_${now}"
filename_time_format = "yyyy.MM.dd"
sink_columns = ["name","age"]
is_enable_transaction=true
hadoop_s3_properties {
"fs.s3a.buffer.dir" = "/data/st_test/s3a"
"fs.s3a.fast.upload.buffer" = "disk"
}
}
For parquet file format simple config with org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider
S3File {
bucket = "s3a://seatunnel-test"
tmp_path = "/tmp/seatunnel"
path="/seatunnel/parquet"
fs.s3a.endpoint="s3.cn-north-1.amazonaws.com.cn"
fs.s3a.aws.credentials.provider="org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider"
access_key = "xxxxxxxxxxxxxxxxx"
secret_key = "xxxxxxxxxxxxxxxxx"
file_format_type = "parquet"
hadoop_s3_properties {
"fs.s3a.buffer.dir" = "/data/st_test/s3a"
"fs.s3a.fast.upload.buffer" = "disk"
}
}
For orc file format simple config with org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider
S3File {
bucket = "s3a://seatunnel-test"
tmp_path = "/tmp/seatunnel"
path="/seatunnel/orc"
fs.s3a.endpoint="s3.cn-north-1.amazonaws.com.cn"
fs.s3a.aws.credentials.provider="org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider"
access_key = "xxxxxxxxxxxxxxxxx"
secret_key = "xxxxxxxxxxxxxxxxx"
file_format_type = "orc"
schema_save_mode = "CREATE_SCHEMA_WHEN_NOT_EXIST"
data_save_mode="APPEND_DATA"
}
Multi-table writing and saveMode
env {
"job.name"="SeaTunnel_job"
"job.mode"=STREAMING
}
source {
MySQL-CDC {
database-names=[
"wls_t1"
]
table-names=[
"wls_t1.mysqlcdc_to_s3_t3",
"wls_t1.mysqlcdc_to_s3_t4",
"wls_t1.mysqlcdc_to_s3_t5",
"wls_t1.mysqlcdc_to_s3_t1",
"wls_t1.mysqlcdc_to_s3_t2"
]
password="xxxxxx"
username="xxxxxxxxxxxxx"
base-url="jdbc:mysql://localhost:3306/qa_source"
}
}
transform {
}
sink {
S3File {
bucket = "s3a://seatunnel-test"
tmp_path = "/tmp/seatunnel/${table_name}"
path="/test/${table_name}"
fs.s3a.endpoint="s3.cn-north-1.amazonaws.com.cn"
fs.s3a.aws.credentials.provider="org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider"
access_key = "xxxxxxxxxxxxxxxxx"
secret_key = "xxxxxxxxxxxxxxxxx"
file_format_type = "orc"
schema_save_mode = "CREATE_SCHEMA_WHEN_NOT_EXIST"
data_save_mode="APPEND_DATA"
}
}
Changelog
2.3.0-beta 2022-10-20
- Add S3File Sink Connector
2.3.0 2022-12-30
- [BugFix] Fixed the following bugs that failed to write data to files (3258)
- When field from upstream is null it will throw NullPointerException
- Sink columns mapping failed
- When restore writer from states getting transaction directly failed
- [Feature] Support S3A protocol (3632)
- Allow user to add additional hadoop-s3 parameters
- Allow the use of the s3a protocol
- Decouple hadoop-aws dependencies
- [Improve] Support setting batch size for every file (3625)
- [Feature]Set S3 AK to optional (3688)
Next version
- [Improve] Support file compress (3899)