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版本:2.1.3

Clickhouse

Description

Use Clickhouse-jdbc to correspond the data source according to the field name and write it into ClickHouse. The corresponding data table needs to be created in advance before use

提示

Engine Supported and plugin name

  • Spark: Clickhouse
  • Flink: Clickhouse

Options

nametyperequireddefault value
bulk_sizenumberno20000
clickhouse.*stringno
databasestringyes-
fieldsarrayno-
hoststringyes-
passwordstringno-
retrynumberno1
retry_codesarrayno[ ]
tablestringyes-
usernamestringno-
split_modebooleannofalse
sharding_keystringno-
common-optionsstringno-

bulk_size [number]

The number of rows written through Clickhouse-jdbc each time, the default is 20000 .

database [string]

database name

fields [array]

The data field that needs to be output to ClickHouse , if not configured, it will be automatically adapted according to the data schema .

host [string]

ClickHouse cluster address, the format is host:port , allowing multiple hosts to be specified. Such as "host1:8123,host2:8123" .

password [string]

ClickHouse user password . This field is only required when the permission is enabled in ClickHouse .

retry [number]

The number of retries, the default is 1

retry_codes [array]

When an exception occurs, the ClickHouse exception error code of the operation will be retried. For a detailed list of error codes, please refer to ClickHouseErrorCode

If multiple retries fail, this batch of data will be discarded, use with caution! !

table [string]

table name

username [string]

ClickHouse user username, this field is only required when permission is enabled in ClickHouse

clickhouse [string]

In addition to the above mandatory parameters that must be specified by clickhouse-jdbc , users can also specify multiple optional parameters, which cover all the parameters provided by clickhouse-jdbc .

The way to specify the parameter is to add the prefix clickhouse. to the original parameter name. For example, the way to specify socket_timeout is: clickhouse.socket_timeout = 50000 . If these non-essential parameters are not specified, they will use the default values given by clickhouse-jdbc.

split_mode [boolean]

This mode only support clickhouse table which engine is 'Distributed'.And internal_replication option should be true. They will split distributed table data in seatunnel and perform write directly on each shard. The shard weight define is clickhouse will be counted.

sharding_key [string]

When use split_mode, which node to send data to is a problem, the default is random selection, but the 'sharding_key' parameter can be used to specify the field for the sharding algorithm. This option only worked when 'split_mode' is true.

common options [string]

Sink plugin common parameters, please refer to common options for details

ClickHouse type comparison table

ClickHouse field typeConvert plugin conversion goal typeSQL conversion expressionDescription
Datestringstring()yyyy-MM-dd Format string
DateTimestringstring()yyyy-MM-dd HH:mm:ss Format string
Stringstringstring()
Int8integerint()
Uint8integerint()
Int16integerint()
Uint16integerint()
Int32integerint()
Uint32longbigint()
Int64longbigint()
Uint64longbigint()
Float32floatfloat()
Float64doubledouble()
Decimal(P, S)-CAST(source AS DECIMAL(P, S))Decimal32(S), Decimal64(S), Decimal128(S) Can be used
Array(T)--
Nullable(T)Depends on TDepends on T
LowCardinality(T)Depends on TDepends on T

Examples

clickhouse {
host = "localhost:8123"
clickhouse.socket_timeout = 50000
database = "nginx"
table = "access_msg"
fields = ["date", "datetime", "hostname", "http_code", "data_size", "ua", "request_time"]
username = "username"
password = "password"
bulk_size = 20000
}
ClickHouse {
host = "localhost:8123"
database = "nginx"
table = "access_msg"
fields = ["date", "datetime", "hostname", "http_code", "data_size", "ua", "request_time"]
username = "username"
password = "password"
bulk_size = 20000
retry_codes = [209, 210]
retry = 3
}

In case of network timeout or network abnormality, retry writing 3 times