Project: SeaTunnel (App Definition and Development / Streaming & Messaging)
File: SftpFile.md

Sftp file source connector Spark<br/> Flink<br/> SeaTunnel Zeta<br/> [x] file format type [x] text [x] csv [x] json [x] excel [x] xml Read data from sftp file server. In order to use the SftpFile connector, the following dependencies are required. They can be downloaded via install-plugin.sh or from the Maven central repository. | Datasource | Supported Versions | Dependency | ||--|--| | SftpFile | universal | | :::tip 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 Sftp and this connector need some hadoop dependencies. It only supports hadoop version 2.9.X+. ::: The File does not have a specific type list, and we can indicate which SeaTunnel data type the corresponding data needs to be converted to by specifying the Schema in the config. | SeaTunnel Data type | || | STRING | | SHORT | | INT | | BIGINT | | BOOLEAN | | DOUBLE | | DECIMAL | | FLOAT | | DATE | | TIME | | TIMESTAMP | | BYTES | | ARRAY | | MAP | | Name | Type | Required | default value | Description | |||-||| | host | String | Yes | - | The target sftp host is required | | port | Int | Yes | - | The target sftp port is required | | user | String | Yes | - | The target sftp username is required | | password | String | Yes | - | The target sftp password is required | | path | String | Yes | - | The source file path. | | fileformattype | String | Yes | - | Please check #fileformattype below | | filefilterpattern | String | No | - | Filter pattern, which used for filtering files. | | delimiter/fielddelimiter | String | No | \001 | **delimiter** parameter will deprecate after version 2.3.5, please use **fielddelimiter instead. <br/> Field delimiter, used to tell connector how to slice and dice fields when reading text

<br/> Default `\001`, the same as hive's default delimiter | | parsepartitionfrom_path | Boolean | No | true | Control whether parse the partition keys and values from file path <br/> For example if you read a file from path `oss://hadoop-cluster/tmp/seatunnel/parquet/name=tyrantlucifer/age=26` <br/> Every record data from file will be added these two fields: <br/> name age <br/> tyrantlucifer 26 <br/> Tips: Do not define partition fields in schema option | | 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: <br/> `yyyy-MM-dd` `yyyy.MM.dd` `yyyy/MM/dd` <br/> 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: <br/> `yyyy-MM-dd HH:mm:ss` `yyyy.MM.dd HH:mm:ss` `yyyy/MM/dd HH:mm:ss` `yyyyMMddHHmmss` <br/> default `yyyy-MM-dd HH:mm:ss` | | 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: <br/> `HH:mm:ss` `HH:mm:ss.SSS` <br/> default `HH:mm:ss` | | skipheaderrownumber | Long | No | 0 | Skip the first few lines, but only for the txt and csv. <br/> For example, set like following: <br/> `skipheaderrownumber = 2` <br/> then SeaTunnel will skip the first 2 lines from source files | | read_columns | list | no | - | The read column list of the data source, user can use it to implement field projection. | | sheetname | String | No | - | Reader the sheet of the workbook,Only used when fileformat is excel. | | xmlrowtag | string | no | - | Specifies the tag name of the data rows within the XML file, only used when file_format is xml. | | xmluseattrformat | boolean | no | - | Specifies whether to process data using the tag attribute format, only used when fileformat is xml. | | schema | Config | No | - | Please check #schema below | | compress_codec | String | No | None | The compress codec of files and the details that supported as the following shown: <br/> - txt: `lzo` `None` <br/> - json: `lzo` `None` <br/> - csv: `lzo` `None` <br/> - orc: `lzo` `snappy` `lz4` `zlib` `None` <br/> - parquet: `lzo` `snappy` `lz4` `gzip` `brotli` `zstd` `None` <br/> Tips: excel type does Not support any compression format | | encoding | string | no | UTF-8 | | common-options | | No | - | Source plugin common parameters, please refer to for details. | File type, supported as the following file types: `text` `csv` `parquet` `orc` `json` `excel` `xml` If you assign file type to `json`, you should also assign schema option to tell connector how to parse data to the row you

For example: upstream data is the following: ```json {"code": 200, "data": "get success", "success": true} ``` You can also save multiple pieces of data in one file and split them by newline: ```json lines {"code": 200, "data": "get success", "success": true} {"code": 300, "data": "get failed", "success": false} ``` you should assign schema as the following: ```hocon 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: ```text 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: ```hocon field_delimiter = "#" schema { fields { name = string age = int gender = string } } ``` connector will generate data as the following: | name | age | gender | ||--|--| | tyrantlucifer | 26 | male | 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. Only used when fileformattype is json,text,csv,xml. The encoding of the file to read. This param will be parsed by `Charset.forName(encoding)`. The schema of upstream data. The following example demonstrates how to create a data synchronization job that reads data from sftp and prints it on the local client: ```bash env { parallelism = 1 job.mode = "BATCH" } source { SftpFile { host = "sftp" port = 22 user = seatunnel password = pass path = "tmp/seatunnel/read/json" fileformattype = "json" resulttablename = "sftp" schema = { fields { c_map = "map<string, string>" c_array = "array<int>" c_string = string c_boolean = boolean c_tinyint = tinyint c_smallint = smallint c_int = int c_bigint = bigint c_float = float c_double = double c_bytes = bytes c_date = date c_decimal = "decimal(38, 18)" c_timestamp = timestamp c_row = { C_MAP = "map<string, string>" C_ARRAY = "array<int>" C_STRING = string C_BOOLEAN = boolean C_TINYINT = tinyint C_SMALLINT = smallint C_INT = int C_BIGINT = bigint C_FLOAT = float C_DOUBLE = double C_BYTES = bytes C_DATE = date C_DECIMAL = "decimal(38, 18)" C_TIMESTAMP = timestamp } } } } } sink { Console { parallelism = 1 } } ```