Skip to main content
Version: Next

Doris

Doris sink connector

Support Doris Version

  • exactly-once & cdc supported Doris version is >= 1.1.x
  • Array data type supported Doris version is >= 1.2.x
  • Map data type will be support in Doris version is 2.x

Support Those Engines

Spark
Flink
SeaTunnel Zeta

Key Features

Description

Used to send data to Doris. Both support streaming and batch mode. The internal implementation of Doris sink connector is cached and imported by stream load in batches.

Sink Options

NameTypeRequiredDefaultDescription
fenodesStringYes-Doris cluster fenodes address, the format is "fe_ip:fe_http_port, ..."
query-portintNo9030Doris Fenodes query_port
usernameStringYes-Doris user username
passwordStringYes-Doris user password
databaseStringYes-The database name of Doris table, use ${database_name} to represent the upstream table name
tableStringYes-The table name of Doris table, use ${table_name} to represent the upstream table name
table.identifierStringYes-The name of Doris table, it will deprecate after version 2.3.5, please use database and table instead.
sink.label-prefixStringYes-The label prefix used by stream load imports. In the 2pc scenario, global uniqueness is required to ensure the EOS semantics of SeaTunnel.
sink.enable-2pcboolNofalseWhether to enable two-phase commit (2pc), the default is false. For two-phase commit, please refer to here.
sink.enable-deleteboolNo-Whether to enable deletion. This option requires Doris table to enable batch delete function (0.15+ version is enabled by default), and only supports Unique model. you can get more detail at this link
sink.check-intervalintNo10000check exception with the interval while loading
sink.max-retriesintNo3the max retry times if writing records to database failed
sink.buffer-sizeintNo256 * 1024the buffer size to cache data for stream load.
sink.buffer-countintNo3the buffer count to cache data for stream load.
doris.batch.sizeintNo1024the batch size of the write to doris each http request, when the row reaches the size or checkpoint is executed, the data of cached will write to server.
needs_unsupported_type_castingbooleanNofalseWhether to enable the unsupported type casting, such as Decimal64 to Double
schema_save_modeEnumnoCREATE_SCHEMA_WHEN_NOT_EXISTthe schema save mode, please refer to schema_save_mode below
data_save_modeEnumnoAPPEND_DATAthe data save mode, please refer to data_save_mode below
save_mode_create_templatestringnosee belowsee below
custom_sqlStringno-When data_save_mode selects CUSTOM_PROCESSING, you should fill in the CUSTOM_SQL parameter. This parameter usually fills in a SQL that can be executed. SQL will be executed before synchronization tasks.
doris.configmapyes-This option is used to support operations such as insert, delete, and update when automatically generate sql,and supported formats.

schema_save_mode[Enum]

Before the synchronous task is turned on, different treatment schemes are selected for the existing surface structure of the target side.
Option introduction:
RECREATE_SCHEMA :Will create when the table does not exist, delete and rebuild when the table is saved
CREATE_SCHEMA_WHEN_NOT_EXIST :Will Created when the table does not exist, skipped when the table is saved
ERROR_WHEN_SCHEMA_NOT_EXIST :Error will be reported when the table does not exist

data_save_mode[Enum]

Before the synchronous task is turned on, different processing schemes are selected for data existing data on the target side.
Option introduction:
DROP_DATA: Preserve database structure and delete data
APPEND_DATA:Preserve database structure, preserve data
CUSTOM_PROCESSING:User defined processing
ERROR_WHEN_DATA_EXISTS:When there is data, an error is reported

save_mode_create_template

We use templates to automatically create Doris tables, which will create corresponding table creation statements based on the type of upstream data and schema type, and the default template can be modified according to the situation.

CREATE TABLE IF NOT EXISTS `${database}`.`${table_name}`
(
${rowtype_fields}
) ENGINE = OLAP UNIQUE KEY (${rowtype_primary_key})
DISTRIBUTED BY HASH (${rowtype_primary_key})
PROPERTIES
(
"replication_num" = "1"
);

If a custom field is filled in the template, such as adding an id field

CREATE TABLE IF NOT EXISTS `${database}`.`${table_name}`
(
id,
${rowtype_fields}
) ENGINE = OLAP UNIQUE KEY (${rowtype_primary_key})
DISTRIBUTED BY HASH (${rowtype_primary_key})
PROPERTIES
(
"replication_num" = "1"
);

The connector will automatically obtain the corresponding type from the upstream to complete the filling, and remove the id field from rowtype_fields. This method can be used to customize the modification of field types and attributes.

You can use the following placeholders

  • database: Used to get the database in the upstream schema
  • table_name: Used to get the table name in the upstream schema
  • rowtype_fields: Used to get all the fields in the upstream schema, we will automatically map to the field description of Doris
  • rowtype_primary_key: Used to get the primary key in the upstream schema (maybe a list)
  • rowtype_unique_key: Used to get the unique key in the upstream schema (maybe a list)

Data Type Mapping

Doris Data TypeSeaTunnel Data Type
BOOLEANBOOLEAN
TINYINTTINYINT
SMALLINTSMALLINT
TINYINT
INTINT
SMALLINT
TINYINT
BIGINTBIGINT
INT
SMALLINT
TINYINT
LARGEINTBIGINT
INT
SMALLINT
TINYINT
FLOATFLOAT
DOUBLEDOUBLE
FLOAT
DECIMALDECIMAL
DOUBLE
FLOAT
DATEDATE
DATETIMETIMESTAMP
CHARSTRING
VARCHARSTRING
STRINGSTRING
ARRAYARRAY
MAPMAP
JSONSTRING
HLLNot supported yet
BITMAPNot supported yet
QUANTILE_STATENot supported yet
STRUCTNot supported yet

Supported import data formats

The supported formats include CSV and JSON

Task Example

Simple:

The following example describes writing multiple data types to Doris, and users need to create corresponding tables downstream

env {
parallelism = 1
job.mode = "BATCH"
checkpoint.interval = 10000
}

source {
FakeSource {
row.num = 10
map.size = 10
array.size = 10
bytes.length = 10
string.length = 10
schema = {
fields {
c_map = "map<string, array<int>>"
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_decimal = "decimal(16, 1)"
c_null = "null"
c_bytes = bytes
c_date = date
c_timestamp = timestamp
}
}
}
}

sink {
Doris {
fenodes = "doris_cdc_e2e:8030"
username = root
password = ""
database = "test"
table = "e2e_table_sink"
sink.label-prefix = "test-cdc"
sink.enable-2pc = "true"
sink.enable-delete = "true"
doris.config {
format = "json"
read_json_by_line = "true"
}
}
}

CDC(Change Data Capture) Event:

This example defines a SeaTunnel synchronization task that automatically generates data through FakeSource and sends it to Doris Sink,FakeSource simulates CDC data with schema, score (int type),Doris needs to create a table sink named test.e2e_table_sink and a corresponding table for it.

env {
parallelism = 1
job.mode = "BATCH"
checkpoint.interval = 10000
}

source {
FakeSource {
schema = {
fields {
pk_id = bigint
name = string
score = int
sex = boolean
number = tinyint
height = float
sight = double
create_time = date
update_time = timestamp
}
}
rows = [
{
kind = INSERT
fields = [1, "A", 100, true, 1, 170.0, 4.3, "2020-02-02", "2020-02-02T02:02:02"]
},
{
kind = INSERT
fields = [2, "B", 100, true, 1, 170.0, 4.3, "2020-02-02", "2020-02-02T02:02:02"]
},
{
kind = INSERT
fields = [3, "C", 100, true, 1, 170.0, 4.3, "2020-02-02", "2020-02-02T02:02:02"]
},
{
kind = UPDATE_BEFORE
fields = [1, "A", 100, true, 1, 170.0, 4.3, "2020-02-02", "2020-02-02T02:02:02"]
},
{
kind = UPDATE_AFTER
fields = [1, "A_1", 100, true, 1, 170.0, 4.3, "2020-02-02", "2020-02-02T02:02:02"]
},
{
kind = DELETE
fields = [2, "B", 100, true, 1, 170.0, 4.3, "2020-02-02", "2020-02-02T02:02:02"]
}
]
}
}

sink {
Doris {
fenodes = "doris_cdc_e2e:8030"
username = root
password = ""
database = "test"
table = "e2e_table_sink"
sink.label-prefix = "test-cdc"
sink.enable-2pc = "true"
sink.enable-delete = "true"
doris.config {
format = "json"
read_json_by_line = "true"
}
}
}

Use JSON format to import data

sink {
Doris {
fenodes = "e2e_dorisdb:8030"
username = root
password = ""
database = "test"
table = "e2e_table_sink"
sink.enable-2pc = "true"
sink.label-prefix = "test_json"
doris.config = {
format="json"
read_json_by_line="true"
}
}
}

Use CSV format to import data

sink {
Doris {
fenodes = "e2e_dorisdb:8030"
username = root
password = ""
database = "test"
table = "e2e_table_sink"
sink.enable-2pc = "true"
sink.label-prefix = "test_csv"
doris.config = {
format = "csv"
column_separator = ","
}
}
}

Changelog

2.3.0-beta 2022-10-20

  • Add Doris Sink Connector

Next version

  • [Improve] Change Doris Config Prefix 3856

  • [Improve] Refactor some Doris Sink code as well as support 2pc and cdc 4235

tip

PR 4235 is an incompatible modification to PR 3856. Please refer to PR 4235 to use the new Doris connector