TiCDC CSV Protocol
When using a cloud storage service as the downstream sink, you can send DML events to the cloud storage service in CSV format.
Use CSV
The following is an example of the configuration when using the CSV protocol:
cdc cli changefeed create --server=http://127.0.0.1:8300 --changefeed-id="csv-test" --sink-uri="s3://bucket/prefix" --config changefeed.toml
The configuration in the changefeed.toml
file is as follows:
[sink]
protocol = "csv"
terminator = "\n"
[sink.csv]
delimiter = ','
quote = '"'
null = '\N'
include-commit-ts = true
binary-encoding-method = 'base64'
Transactional constraints
- In a single CSV file, the
commit-ts
of a row is equal to or smaller than that of the subsequent row. - The same transactions of a single table are stored in the same CSV file.
- Multiple tables of the same transaction can be stored in different CSV files.
Data storage path structure
For more information about the storage path structure of the data, see Storage path structure.
Definition of the data format
In the CSV file, each column is defined as follows:
- Column 1: The operation-type indicator, including
I
,U
, andD
.I
meansINSERT
,U
meansUPDATE
, andD
meansDELETE
. - Column 2: Table name.
- Column 3: Schema name.
- Column 4: The
commit-ts
of the source transaction. This column is optional. - Column 5 to the last column: One or more columns that represent data to be changed.
Assume that table hr.employee
is defined as follows:
CREATE TABLE `employee` (
`Id` int NOT NULL,
`LastName` varchar(20) DEFAULT NULL,
`FirstName` varchar(30) DEFAULT NULL,
`HireDate` date DEFAULT NULL,
`OfficeLocation` varchar(20) DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
The DML events of this table are stored in the CSV format as follows:
"I","employee","hr",433305438660591626,101,"Smith","Bob","2014-06-04","New York"
"U","employee","hr",433305438660591627,101,"Smith","Bob","2015-10-08","Los Angeles"
"D","employee","hr",433305438660591629,101,"Smith","Bob","2017-03-13","Dallas"
"I","employee","hr",433305438660591630,102,"Alex","Alice","2017-03-14","Shanghai"
"U","employee","hr",433305438660591630,102,"Alex","Alice","2018-06-15","Beijing"
Data type mapping
MySQL type | CSV type | Example | Description |
---|---|---|---|
BOOLEAN /TINYINT /SMALLINT /INT /MEDIUMINT /BIGINT | Integer | 123 | - |
FLOAT /DOUBLE | Float | 153.123 | - |
NULL | Null | \N | - |
TIMESTAMP /DATETIME | String | "1973-12-30 15:30:00.123456" | Format: yyyy-MM-dd HH:mm:ss.%06d |
DATE | String | "2000-01-01" | Format: yyyy-MM-dd |
TIME | String | "23:59:59" | Format: yyyy-MM-dd |
YEAR | Integer | 1970 | - |
VARCHAR /JSON /TINYTEXT /MEDIUMTEXT /LONGTEXT /TEXT /CHAR | String | "test" | UTF-8 encoded |
VARBINARY /TINYBLOB /MEDIUMBLOB /LONGBLOB /BLOB /BINARY | String | "6Zi/5pav" or "e998bfe696af" | Base64 or hex encoded |
BIT | Integer | 81 | - |
DECIMAL | String | "129012.1230000" | - |
ENUM | String | "a" | - |
SET | String | "a,b" | - |