版本：2.3.12

S3File

S3 文件 Sink 连接器

支持的引擎

Spark
Flink
SeaTunnel Zeta

主要特性

描述

将数据输出到 AWS S3 文件系统。

支持的数据源信息

数据源	支持的版本
S3	当前版本

数据库依赖

如果您使用 Spark/Flink，为了使用此连接器，您必须确保您的 Spark/Flink 集群已经集成了 Hadoop。测试的 Hadoop 版本为 2.x。
如果您使用 SeaTunnel引擎，当您下载并安装 SeaTunnel引擎时，它会自动集成 Hadoop jar 包。您可以在 ${SEATUNNEL_HOME}/lib 下检查 jar 包以确认这一点。要使用此连接器，您需要将 hadoop-aws-3.1.4.jar 和 aws-java-sdk-bundle-1.12.692.jar 放在 ${SEATUNNEL_HOME}/lib 目录下。

数据类型映射

如果写入 csv、text 文件类型，所有列都将为字符串类型。

Orc 文件类型

SeaTunnel 数据类型	Orc 数据类型
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	不支持的数据类型
ARRAY	LIST
Map	Map

Parquet 文件类型

SeaTunnel 数据类型	Parquet 数据类型
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	不支持的数据类型
ARRAY	LIST
Map	Map

Sink 选项

名称	类型	是否必填	默认值	描述
path	string	是	-
tmp_path	string	否	/tmp/seatunnel	结果文件将首先写入临时路径，然后使用 `mv` 将临时目录提交到目标目录。需要一个 S3 目录。
bucket	string	是	-
fs.s3a.endpoint	string	是	-
fs.s3a.aws.credentials.provider	string	是	com.amazonaws.auth.InstanceProfileCredentialsProvider	认证 s3a 的方式。目前仅支持 `org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider` 和 `com.amazonaws.auth.InstanceProfileCredentialsProvider`。
access_key	string	否	-	仅当 fs.s3a.aws.credentials.provider = org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider 时使用
access_secret	string	否	-	仅当 fs.s3a.aws.credentials.provider = org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider 时使用
custom_filename	boolean	否	false	是否需要自定义文件名
file_name_expression	string	否	"${transactionId}"	仅当 custom_filename 为 true 时使用
filename_time_format	string	否	"yyyy.MM.dd"	仅当 custom_filename 为 true 时使用
file_format_type	string	否	"csv"
field_delimiter	string	否	'\001'	仅当 file_format 为 text 时使用
row_delimiter	string	否	"\n"	仅当 file_format 为 `text`、`csv`、`json` 时使用
have_partition	boolean	否	false	是否需要处理分区。
partition_by	array	否	-	仅当 have_partition 为 true 时使用
partition_dir_expression	string	否	"${k0}=${v0}/${k1}=${v1}/.../${kn}=${vn}/"	仅当 have_partition 为 true 时使用
is_partition_field_write_in_file	boolean	否	false	仅当 have_partition 为 true 时使用
sink_columns	array	否		当此参数为空时，所有字段均为 sink 列
is_enable_transaction	boolean	否	true
batch_size	int	否	1000000
compress_codec	string	否	none
common-options	object	否	-
max_rows_in_memory	int	否	-	仅当 file_format 为 excel 时使用
sheet_name	string	否	Sheet${Random number}	仅当 file_format 为 excel 时使用
csv_string_quote_mode	enum	否	MINIMAL	仅当 file_format 为 csv 时使用
xml_root_tag	string	否	RECORDS	仅当 file_format 为 xml 时使用，指定 XML 文件中根元素的标签名称。
xml_row_tag	string	否	RECORD	仅当 file_format 为 xml 时使用，指定 XML 文件中数据行的标签名称。
xml_use_attr_format	boolean	否	-	仅当 file_format 为 xml 时使用，指定是否使用标签属性格式处理数据。
single_file_mode	boolean	否	false	每个并行度只会输出一个文件。当此参数开启时，batch_size 将不会生效。输出文件名不会有文件块后缀。
create_empty_file_when_no_data	boolean	否	false	当上游没有数据同步时，仍然会生成相应的数据文件。
parquet_avro_write_timestamp_as_int96	boolean	否	false	仅当 file_format 为 parquet 时使用
parquet_avro_write_fixed_as_int96	array	否	-	仅当 file_format 为 parquet 时使用
hadoop_s3_properties	map	否		如果您需要添加其他选项，可以在此处添加，并参考此链接
schema_save_mode	Enum	否	CREATE_SCHEMA_WHEN_NOT_EXIST	在开启同步任务之前，对目标路径进行不同的处理
data_save_mode	Enum	否	APPEND_DATA	在开启同步任务之前，对目标路径中的数据文件进行不同的处理
enable_header_write	boolean	否	false	仅当 file_format_type 为 text,csv 时使用。 false: 不写入表头, true: 写入表头。
encoding	string	否	"UTF-8"	仅当 file_format_type 为 json,text,csv,xml 时使用。

path [string]

存储数据文件的路径，支持变量替换。例如：path=/test/${database_name}/${schema_name}/${table_name}

hadoop_s3_properties [map]

如果您需要添加其他选项，可以在此处添加，并参考此链接

hadoop_s3_properties {
      "fs.s3a.buffer.dir" = "/data/st_test/s3a"
      "fs.s3a.fast.upload.buffer" = "disk"
   }

custom_filename [boolean]

是否自定义文件名

file_name_expression [string]

仅当 custom_filename 为 true 时使用

file_name_expression 描述了将创建到 path 中的文件表达式。我们可以在 file_name_expression 中添加变量 ${now} 或 ${uuid}，例如 test_${uuid}_${now}， ${now} 表示当前时间，其格式可以通过指定选项 filename_time_format 来定义。

请注意，如果 is_enable_transaction 为 true，我们会在文件头部自动添加 ${transactionId}_。

filename_time_format [string]

仅当 custom_filename 为 true 时使用

当 file_name_expression 参数中的格式为 xxxx-${now} 时，filename_time_format 可以指定路径的时间格式，默认值为 yyyy.MM.dd。常用的时间格式如下：

符号	描述
y	年
M	月
d	日
H	小时 (0-23)
m	分钟
s	秒

file_format_type [string]

我们支持以下文件类型：

text csv parquet orc json excel xml binary canal_json debezium_json maxwell_json

请注意，最终文件名将以文件格式类型的后缀结尾，文本文件的后缀为 txt。

field_delimiter [string]

行数据中列之间的分隔符。仅在 text 文件格式中需要。

row_delimiter [string]

文件中行之间的分隔符。仅在 text、csv、json 文件格式中需要。

have_partition [boolean]

是否需要处理分区。

partition_by [array]

仅当 have_partition 为 true 时使用。

根据选定的字段对数据进行分区。

partition_dir_expression [string]

仅当 have_partition 为 true 时使用。

如果指定了 partition_by，我们将根据分区信息生成相应的分区目录，最终文件将放置在分区目录中。

默认的 partition_dir_expression 为 ${k0}=${v0}/${k1}=${v1}/.../${kn}=${vn}/。k0 是第一个分区字段，v0 是第一个分区字段的值。

is_partition_field_write_in_file [boolean]

仅当 have_partition 为 true 时使用。

如果 is_partition_field_write_in_file 为 true，分区字段及其值将被写入数据文件。

例如，如果您想写入 Hive 数据文件，其值应为 false。

sink_columns [array]

哪些列需要写入文件，默认值为从 Transform 或 Source 获取的所有列。字段的顺序决定了文件实际写入的顺序。

is_enable_transaction [boolean]

如果 is_enable_transaction 为 true，我们将确保在将数据写入目标目录时不会丢失或重复。

请注意，如果 is_enable_transaction 为 true，我们会在文件头部自动添加 ${transactionId}_。

目前仅支持 true。

batch_size [int]

文件中的最大行数。对于 SeaTunnel Engine，文件中的行数由 batch_size 和 checkpoint.interval 共同决定。如果 checkpoint.interval 的值足够大，sink writer 将一直写入文件，直到文件中的行数超过 batch_size。如果 checkpoint.interval 较小，sink writer 将在新的 checkpoint 触发时创建一个新文件。

compress_codec [string]

文件的压缩编解码器，支持的详细信息如下：

txt: lzo none
json: lzo none
csv: lzo none
orc: lzo snappy lz4 zlib none
parquet: lzo snappy lz4 gzip brotli zstd none

提示：excel 类型不支持任何压缩格式

common options

Sink 插件通用参数，请参考 Sink 通用选项获取详细信息。

max_rows_in_memory [int]

当文件格式为 Excel 时，内存中可以缓存的最大数据项数。

sheet_name [string]

写入工作表的名称

csv_string_quote_mode [string]

当文件格式为 CSV 时，CSV 的字符串引用模式。

ALL: 所有字符串字段都会被引用。
MINIMAL: 引用包含特殊字符的字段，如字段分隔符、引用字符或行分隔符字符串中的任何字符。
NONE: 从不引用字段。当数据中出现分隔符时，打印机会在其前面加上转义字符。如果未设置转义字符，格式验证将抛出异常。

xml_root_tag [string]

指定 XML 文件中根元素的标签名称。

xml_row_tag [string]

指定 XML 文件中数据行的标签名称。

xml_use_attr_format [boolean]

指定是否使用标签属性格式处理数据。

parquet_avro_write_timestamp_as_int96 [boolean]

支持将时间戳写入 Parquet INT96，仅对 parquet 文件有效。

parquet_avro_write_fixed_as_int96 [array]

支持将 12-byte 字段写入 Parquet INT96，仅对 parquet 文件有效。

schema_save_mode [Enum]

在开启同步任务之前，对目标路径进行不同的处理。
选项介绍：
RECREATE_SCHEMA ：当路径不存在时创建。如果路径已存在，则删除路径并重新创建。
CREATE_SCHEMA_WHEN_NOT_EXIST ：当路径不存在时创建，路径存在时使用路径。
ERROR_WHEN_SCHEMA_NOT_EXIST ：当路径不存在时报错
IGNORE ：忽略表的处理

data_save_mode [Enum]

在开启同步任务之前，对目标路径中的数据文件进行不同的处理。选项介绍：
DROP_DATA：使用路径但删除路径中的数据文件。 APPEND_DATA：使用路径，并在路径中添加新文件以写入数据。
ERROR_WHEN_DATA_EXISTS：当路径中存在数据文件时，将报错。

encoding [string]

仅当 file_format_type 为 json,text,csv,xml 时使用。写入文件的编码。此参数将由 Charset.forName(encoding) 解析。

示例

简单示例

此示例定义了一个 SeaTunnel 同步任务，通过 FakeSource 自动生成数据并将其发送到 S3File Sink。FakeSource 总共生成 16 行数据 (row.num=16)，每行有两个字段，name (字符串类型) 和 age (int 类型)。最终的目标 s3 目录将创建一个文件，并将所有数据写入其中。在运行此作业之前，您需要创建 s3 路径：/seatunnel/text。如果您尚未安装和部署 SeaTunnel，您需要按照安装 SeaTunnel 中的说明安装和部署 SeaTunnel。然后按照使用 SeaTunnel Engine 快速入门中的说明运行此作业。

# 定义运行时环境
env {
  parallelism = 1
  job.mode = "BATCH"
}

source {
  # 这是一个示例源插件，仅用于测试和演示功能源插件
  FakeSource {
    parallelism = 1
    plugin_output = "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
      }
    }
  }
# 如果您想了解更多关于如何配置SeaTunnel以及查看完整的源插件列表，
# 请访问 https://seatunnel.apache.org/docs/connector-v2/source
source {
}

transform {
  # 如果您想了解更多关于如何配置SeaTunnel以及查看完整的转换插件列表，
  # 请访问 https://seatunnel.apache.org/docs/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"
      }
  }
  # 如果您想了解更多关于如何配置SeaTunnel以及查看完整的接收插件列表，
  # 请访问 https://seatunnel.apache.org/docs/connector-v2/sink
}

对于文本文件格式，包含 have_partition、custom_filename、sink_columns 和 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"
  }
}

对于Parquet文件格式，简单配置使用 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"
  }
}

对于ORC文件格式，简单配置使用 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"
}

多表写入和保存模式

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"
      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"
  }
}

enable_header_write [boolean]

仅在 file_format_type 为 text 或 csv 时使用。false：不写入表头，true：写入表头。

变更日志

Change Log

Change	Commit	Version
[Improve][Connector-V2] Add customizable row delimiter support for text file processing (#9608)	https://github.com/apache/seatunnel/commit/7898e62e01	2.3.12
[Improve][Connector-V2] Support maxcompute sink writer with timestamp field type (#9234)	https://github.com/apache/seatunnel/commit/a513c495e3	2.3.12
[improve] update file connectors config (#9034)	https://github.com/apache/seatunnel/commit/8041d59dc2	2.3.11
[Improve][File] Add row_delimiter options into text file sink (#9017)	https://github.com/apache/seatunnel/commit/92aa855a34	2.3.11
Revert " [improve] update localfile connector config" (#9018)	https://github.com/apache/seatunnel/commit/cdc79e13ad	2.3.10
[improve] update localfile connector config (#8765)	https://github.com/apache/seatunnel/commit/def369a85f	2.3.10
[Fix][Connector-V2] Fixed incorrectly setting s3 key in some cases (#8885)	https://github.com/apache/seatunnel/commit/cf4bab5be2	2.3.10
[Feature][Connector-V2] Add `filename_extension` parameter for read/write file (#8769)	https://github.com/apache/seatunnel/commit/78b23c0ef5	2.3.10
[Improve] restruct connector common options (#8634)	https://github.com/apache/seatunnel/commit/f3499a6eeb	2.3.10
[improve] update S3File connector config option (#8615)	https://github.com/apache/seatunnel/commit/80cc9fa6ff	2.3.10
[Feature][Connector-V2] Support create emtpy file when no data (#8543)	https://github.com/apache/seatunnel/commit/275db78918	2.3.10
[Feature][Connector-V2] Support single file mode in file sink (#8518)	https://github.com/apache/seatunnel/commit/e893deed50	2.3.10
[Feature][File] Support config null format for text file read (#8109)	https://github.com/apache/seatunnel/commit/2dbf02df47	2.3.9
[Hotfix][Zeta] Fix the dependency conflict between the guava in hadoop-aws and hive-exec (#7986)	https://github.com/apache/seatunnel/commit/a7837f1f19	2.3.9
[Feature][Restapi] Allow metrics information to be associated to logical plan nodes (#7786)	https://github.com/apache/seatunnel/commit/6b7c53d03c	2.3.9
[Improve][Connector-V2] Support read archive compress file (#7633)	https://github.com/apache/seatunnel/commit/3f98cd8a16	2.3.8
[Improve] Refactor S3FileCatalog and it's factory (#7457)	https://github.com/apache/seatunnel/commit/d928e8b113	2.3.8
[Improve][Connector] Add multi-table sink option check (#7360)	https://github.com/apache/seatunnel/commit/2489f6446b	2.3.7
[Feature][Core] Support using upstream table placeholders in sink options and auto replacement (#7131)	https://github.com/apache/seatunnel/commit/c4ca74122c	2.3.6
[Improve][Files] Support write fixed/timestamp as int96 of parquet (#6971)	https://github.com/apache/seatunnel/commit/1a48a9c493	2.3.6
[Feature][S3 File] Make S3 File Connector support multiple table write (#6698)	https://github.com/apache/seatunnel/commit/8f2049b2f1	2.3.6
[Improve][Connector-v2] The hive connector support multiple filesystem (#6648)	https://github.com/apache/seatunnel/commit/8a4c01fe35	2.3.6
[bigfix][S3 File]:Change the [SCHEMA] attribute of the [S3CONF class] to be non-static to avoid being reassigned after deserialization (#6717)	https://github.com/apache/seatunnel/commit/79bb70101a	2.3.6
[Fix][Connector-V2] Fix connector support SPI but without no args constructor (#6551)	https://github.com/apache/seatunnel/commit/5f3c9c36a5	2.3.5
Add support for XML file type to various file connectors such as SFTP, FTP, LocalFile, HdfsFile, and more. (#6327)	https://github.com/apache/seatunnel/commit/ec533ecd9a	2.3.5
[Test][E2E] Add thread leak check for connector (#5773)	https://github.com/apache/seatunnel/commit/1f2f3fc5f0	2.3.4
[Feature][Connector]add s3file save mode function (#6131)	https://github.com/apache/seatunnel/commit/81c51073bf	2.3.4
[Refactor][File Connector] Put Multiple Table File API to File Base Module (#6033)	https://github.com/apache/seatunnel/commit/c324d663b4	2.3.4
Support using multiple hadoop account (#5903)	https://github.com/apache/seatunnel/commit/d69d88d1aa	2.3.4
[Improve][Common] Introduce new error define rule (#5793)	https://github.com/apache/seatunnel/commit/9d1b2582b2	2.3.4
[Improve][connector-file] unifiy option between file source/sink and update document (#5680)	https://github.com/apache/seatunnel/commit/8d87cf8fc4	2.3.4
[Feature] Support `LZO` compress on File Read (#5083)	https://github.com/apache/seatunnel/commit/a4a1901096	2.3.4
[Feature][Connector-V2][File] Support read empty directory (#5591)	https://github.com/apache/seatunnel/commit/1f58f224a0	2.3.4
Support config column/primaryKey/constraintKey in schema (#5564)	https://github.com/apache/seatunnel/commit/eac76b4e50	2.3.4
[Feature][File Connector]optionrule FILE_FORMAT_TYPE is text/csv ,add parameter BaseSinkConfig.ENABLE_HEADER_WRITE: #5566 (#5567)	https://github.com/apache/seatunnel/commit/0e02db768d	2.3.4
[Feature][Connector V2][File] Add config of 'file_filter_pattern', which used for filtering files. (#5153)	https://github.com/apache/seatunnel/commit/a3c13e59eb	2.3.3
[chore] delete unavailable S3 & Kafka Catalogs (#4477)	https://github.com/apache/seatunnel/commit/e0aec5ecec	2.3.2
[Feature][ConnectorV2]add file excel sink and source (#4164)	https://github.com/apache/seatunnel/commit/e3b97ae5d2	2.3.2
Change file type to file_format_type in file source/sink (#4249)	https://github.com/apache/seatunnel/commit/973a2fae3c	2.3.1
[Chore] Upgrade guava to 27.0-jre (#4238)	https://github.com/apache/seatunnel/commit/4851bee575	2.3.1
Add redshift datatype convertor (#4245)	https://github.com/apache/seatunnel/commit/b19011517f	2.3.1
Merge branch 'dev' into merge/cdc	https://github.com/apache/seatunnel/commit/4324ee1912	2.3.1
[Improve][Project] Code format with spotless plugin.	https://github.com/apache/seatunnel/commit/423b583038	2.3.1
[improve][api] Refactoring schema parse (#4157)	https://github.com/apache/seatunnel/commit/b2f573a13e	2.3.1
[Improve][build] Give the maven module a human readable name (#4114)	https://github.com/apache/seatunnel/commit/d7cd601051	2.3.1
Add S3Catalog (#4121)	https://github.com/apache/seatunnel/commit/7d7f506547	2.3.1
[Improve][Project] Code format with spotless plugin. (#4101)	https://github.com/apache/seatunnel/commit/a2ab166561	2.3.1
[Feature][Connector-V2][File] Support compress (#3899)	https://github.com/apache/seatunnel/commit/55602f6b1c	2.3.1
[Feature][Connector] add get source method to all source connector (#3846)	https://github.com/apache/seatunnel/commit/417178fb84	2.3.1
[Improve][Connector-V2][File] Improve file connector option rule and document (#3812)	https://github.com/apache/seatunnel/commit/bd76077669	2.3.1
[Feature][Shade] Add seatunnel hadoop3 uber (#3755)	https://github.com/apache/seatunnel/commit/5a024bdf8f	2.3.0
[Engine][Checkpoint]Unified naming style (#3714)	https://github.com/apache/seatunnel/commit/bc0bd3bec3	2.3.0
[Connector][File-S3]Set AK is not required (#3713)	https://github.com/apache/seatunnel/commit/da3c526172	2.3.0
[Connector&Engine]Set S3 AK to optional (#3688)	https://github.com/apache/seatunnel/commit/4710918b02	2.3.0
[Connector][S3]Support s3a protocol (#3632)	https://github.com/apache/seatunnel/commit/ae4cc9c1ec	2.3.0
[Hotfix][OptionRule] Fix option rule about all connectors (#3592)	https://github.com/apache/seatunnel/commit/226dc6a119	2.3.0
[Improve][Connector-V2][File] Unified excetion for file source & sink connectors (#3525)	https://github.com/apache/seatunnel/commit/031e8e263c	2.3.0
[Feature][Connector-V2][File] Add option and factory for file connectors (#3375)	https://github.com/apache/seatunnel/commit/db286e8631	2.3.0
[Improve][Connector-V2][File] Improve code structure (#3238)	https://github.com/apache/seatunnel/commit/dd5c353881	2.3.0
[Connector-V2][ElasticSearch] Add ElasticSearch Source/Sink Factory (#3325)	https://github.com/apache/seatunnel/commit/38254e3f26	2.3.0
[Feature][Connector-V2][S3] Add S3 file source & sink connector (#3119)	https://github.com/apache/seatunnel/commit/f27d68ca9c	2.3.0-beta

S3File

支持的引擎​

主要特性​

描述​

支持的数据源信息​

数据库依赖​

数据类型映射​

Orc 文件类型​

Parquet 文件类型​

Sink 选项​

path [string]​

hadoop_s3_properties [map]​

custom_filename [boolean]​

file_name_expression [string]​

filename_time_format [string]​

file_format_type [string]​

field_delimiter [string]​

row_delimiter [string]​

have_partition [boolean]​

partition_by [array]​

partition_dir_expression [string]​

is_partition_field_write_in_file [boolean]​

sink_columns [array]​

is_enable_transaction [boolean]​

batch_size [int]​

compress_codec [string]​

common options​

max_rows_in_memory [int]​

sheet_name [string]​

csv_string_quote_mode [string]​

xml_root_tag [string]​

xml_row_tag [string]​

xml_use_attr_format [boolean]​

parquet_avro_write_timestamp_as_int96 [boolean]​

parquet_avro_write_fixed_as_int96 [array]​

schema_save_mode [Enum]​

data_save_mode [Enum]​

encoding [string]​

示例​

简单示例​

enable_header_write [boolean]​

变更日志​

支持的引擎

主要特性

描述

支持的数据源信息

数据库依赖

数据类型映射

Orc 文件类型

Parquet 文件类型

Sink 选项

path [string]

hadoop_s3_properties [map]

custom_filename [boolean]

file_name_expression [string]

filename_time_format [string]

file_format_type [string]

field_delimiter [string]

row_delimiter [string]

have_partition [boolean]

partition_by [array]

partition_dir_expression [string]

is_partition_field_write_in_file [boolean]

sink_columns [array]

is_enable_transaction [boolean]

batch_size [int]

compress_codec [string]

common options

max_rows_in_memory [int]

sheet_name [string]

csv_string_quote_mode [string]

xml_root_tag [string]

xml_row_tag [string]

xml_use_attr_format [boolean]

parquet_avro_write_timestamp_as_int96 [boolean]

parquet_avro_write_fixed_as_int96 [array]

schema_save_mode [Enum]

data_save_mode [Enum]

encoding [string]

示例

简单示例

enable_header_write [boolean]

变更日志