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
Engine Supported and plugin name
- Spark: Clickhouse
- Flink: Clickhouse
Options
name | type | required | default value |
---|---|---|---|
bulk_size | number | no | 20000 |
clickhouse.* | string | no | |
database | string | yes | - |
fields | array | no | - |
host | string | yes | - |
password | string | no | - |
retry | number | no | 1 |
retry_codes | array | no | [ ] |
table | string | yes | - |
username | string | no | - |
split_mode | boolean | no | false |
sharding_key | string | no | - |
common-options | string | no | - |
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 type | Convert plugin conversion goal type | SQL conversion expression | Description |
---|---|---|---|
Date | string | string() | yyyy-MM-dd Format string |
DateTime | string | string() | yyyy-MM-dd HH:mm:ss Format string |
String | string | string() | |
Int8 | integer | int() | |
Uint8 | integer | int() | |
Int16 | integer | int() | |
Uint16 | integer | int() | |
Int32 | integer | int() | |
Uint32 | long | bigint() | |
Int64 | long | bigint() | |
Uint64 | long | bigint() | |
Float32 | float | float() | |
Float64 | double | double() | |
Decimal(P, S) | - | CAST(source AS DECIMAL(P, S)) | Decimal32(S), Decimal64(S), Decimal128(S) Can be used |
Array(T) | - | - | |
Nullable(T) | Depends on T | Depends on T | |
LowCardinality(T) | Depends on T | Depends 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