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JDBC Vertica Source Connector 使用文档

支持以下引擎

Spark
Flink
SeaTunnel Zeta

关键特性

批处理
精确一次性处理
列投影
并行处理
支持用户自定义拆分
支持查询 SQL 并实现投影效果

描述

通过 JDBC 读取外部数据源数据。

支持的数据源信息

Datasource	Supported versions	Driver	Url	Maven
Vertica	Different dependency version has different driver class.	com.vertica.jdbc.Driver	jdbc:vertica://localhost:5433/vertica	Download

数据库依赖

请下载与 'Maven' 对应的支持列表，并将其复制到 '$SEATNUNNEL_HOME/plugins/jdbc/lib/' 工作目录中

例如，Vertica 数据源：cp vertica-jdbc-xxx.jar $SEATNUNNEL_HOME/plugins/jdbc/lib/

数据类型映射

Vertical Data type	SeaTunnel Data type
BIT	BOOLEAN
TINYINT TINYINT UNSIGNED SMALLINT SMALLINT UNSIGNED MEDIUMINT MEDIUMINT UNSIGNED INT INTEGER YEAR	INT
INT UNSIGNED INTEGER UNSIGNED BIGINT	LONG
BIGINT UNSIGNED	DECIMAL(20,0)
DECIMAL(x,y)(Get the designated column's specified column size.<38)	DECIMAL(x,y)
DECIMAL(x,y)(Get the designated column's specified column size.>38)	DECIMAL(38,18)
DECIMAL UNSIGNED	DECIMAL((Get the designated column's specified column size)+1, (Gets the designated column's number of digits to right of the decimal point.)))
FLOAT FLOAT UNSIGNED	FLOAT
DOUBLE DOUBLE UNSIGNED	DOUBLE
CHAR VARCHAR TINYTEXT MEDIUMTEXT TEXT LONGTEXT JSON	STRING
DATE	DATE
TIME	TIME
DATETIME TIMESTAMP	TIMESTAMP
TINYBLOB MEDIUMBLOB BLOB LONGBLOB BINARY VARBINAR BIT(n)	BYTES
GEOMETRY UNKNOWN	Not supported yet

源选项

Name	Type	Required	Default	Description
url	String	Yes	-	The URL of the JDBC connection. Refer to a case: jdbc:vertica://localhost:5433/vertica
driver	String	Yes	-	The jdbc class name used to connect to the remote data source, if you use Vertica the value is `com.vertica.jdbc.Driver`.
user	String	No	-	Connection instance user name
password	String	No	-	Connection instance password
query	String	Yes	-	Query statement
connection_check_timeout_sec	Int	No	30	The time in seconds to wait for the database operation used to validate the connection to complete
partition_column	String	No	-	The column name for parallelism's partition, only support numeric type,Only support numeric type primary key, and only can config one column.
partition_lower_bound	Long	No	-	The partition_column min value for scan, if not set SeaTunnel will query database get min value.
partition_upper_bound	Long	No	-	The partition_column max value for scan, if not set SeaTunnel will query database get max value.
partition_num	Int	No	job parallelism	The number of partition count, only support positive integer. default value is job parallelism
fetch_size	Int	No	0	For queries that return a large number of objects,you can configure the row fetch size used in the query toimprove performance by reducing the number database hits required to satisfy the selection criteria. Zero means use jdbc default value.
common-options		No	-	Source plugin common parameters, please refer to Source Common Options for details

提示

如果未设置 partition_column，则会在单一并发中运行；如果设置了 partition_column，则将根据任务的并发性进行并行执行。

任务示例

简单示例：

此示例在单一并行中查询您的测试“数据库”中的 type_bin 'table' 16 个数据，并查询其所有字段。您还可以指定要查询的字段，以便将最终输出显示在控制台上。

env {

您可以在此处设置 Flink 配置
execution.parallelism = 2
job.mode = "BATCH"
}
source{
Jdbc {
url = "jdbc:vertica://localhost:5433/vertica"
driver = "com.vertica.jdbc.Driver"
connection_check_timeout_sec = 100
user = "root"
password = "123456"
query = "select * from type_bin limit 16"
}
}

transform {
# 如果您想获取有关如何配置 seatunnel 的更多信息，并查看完整的转换插件列表，
# 请访问 https://seatunnel.apache.org/docs/transform-v2/sql
}

sink {
Console {}
}

并行示例：

并行读取您的查询表，使用您配置的 shard 字段和 shard 数据。如果要读取整个表，可以这样做。

source {
Jdbc {
url = "jdbc:vertica://localhost:5433/vertica"
driver = "com.vertica.jdbc.Driver"
connection_check_timeout_sec = 100
user = "root"
password = "123456"
# 根据需要定义查询逻辑
query = "select * from type_bin"
# 并行分片读取字段
partition_column = "id"
# 片段数量
partition_num = 10
}
}

并行边界示例：

根据查询的上限和下限指定数据更加高效，根据您配置的上限和下限来读取数据源更加高效
source {
Jdbc {
url = "jdbc:vertica://localhost:5433/vertica"
driver = "com.vertica.jdbc.Driver"
connection_check_timeout_sec = 100
user = "root"
password = "123456"
# 根据需要定义查询逻辑
query = "select * from type_bin"
partition_column = "id"
# 读取起始边界
partition_lower_bound = 1
# 读取结束边界
partition_upper_bound = 500
partition_num = 10
}
}