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Version: 2.3.8

Opengauss CDC

Opengauss CDC source connector

Support Those Engines

SeaTunnel Zeta
Flink

Key features

Description

The Opengauss CDC connector allows for reading snapshot data and incremental data from Opengauss database. This document describes how to set up the Opengauss CDC connector to run SQL queries against Opengauss databases.

Using steps

Here are the steps to enable CDC (Change Data Capture) in Opengauss:

  1. Ensure the wal_level is set to logical, you can use SQL commands to modify the configuration directly:
ALTER SYSTEM SET wal_level TO 'logical';
SELECT pg_reload_conf();
  1. Change the REPLICA policy of the specified table to FULL
ALTER TABLE your_table_name REPLICA IDENTITY FULL;

If you have multi tables,you can use the result of this sql to change the REPLICA policy of all tables to FULL

select 'ALTER TABLE ' || schemaname || '.' || tablename || ' REPLICA IDENTITY FULL;' from pg_tables where schemaname = 'YourTableSchema'

Data Type Mapping

Opengauss Data typeSeaTunnel Data type
BOOL
BOOLEAN
BYTEA
BYTES
INT2
SMALLSERIAL
INT4
SERIAL
INT
INT8
BIGSERIAL
BIGINT
FLOAT4
FLOAT
FLOAT8
DOUBLE
NUMERIC(Get the designated column's specified column size>0)DECIMAL(Get the designated column's specified column size,Gets the number of digits in the specified column to the right of the decimal point)
NUMERIC(Get the designated column's specified column size<0)DECIMAL(38, 18)
BPCHAR
CHARACTER
VARCHAR
TEXT
GEOMETRY
GEOGRAPHY
JSON
JSONB
STRING
TIMESTAMP
TIMESTAMP
TIME
TIME
DATE
DATE
OTHER DATA TYPESNOT SUPPORTED YET

Source Options

NameTypeRequiredDefaultDescription
base-urlStringYes-The URL of the JDBC connection. Refer to a case: jdbc:postgresql://localhost:5432/postgres_cdc?loggerLevel=OFF.
usernameStringYes-Username of the database to use when connecting to the database server.
passwordStringYes-Password to use when connecting to the database server.
database-namesListNo-Database name of the database to monitor.
table-namesListYes-Table name of the database to monitor. The table name needs to include the database name, for example: database_name.table_name
table-names-configListNo-Table config list. for example: [{"table": "db1.schema1.table1","primaryKeys":["key1"]}]
startup.modeEnumNoINITIALOptional startup mode for Opengauss CDC consumer, valid enumerations are initial, earliest, latest and specific.
initial: Synchronize historical data at startup, and then synchronize incremental data.
earliest: Startup from the earliest offset possible.
latest: Startup from the latest offset.
specific: Startup from user-supplied specific offsets.
snapshot.split.sizeIntegerNo8096The split size (number of rows) of table snapshot, captured tables are split into multiple splits when read the snapshot of table.
snapshot.fetch.sizeIntegerNo1024The maximum fetch size for per poll when read table snapshot.
slot.nameStringNo-The name of the Opengauss logical decoding slot that was created for streaming changes from a particular plug-in for a particular database/schema. The server uses this slot to stream events to the connector that you are configuring. Default is seatunnel.
decoding.plugin.nameStringNopgoutputThe name of the Postgres logical decoding plug-in installed on the server,Supported values are decoderbufs, wal2json, wal2json_rds, wal2json_streaming,wal2json_rds_streaming and pgoutput.
server-time-zoneStringNoUTCThe session time zone in database server. If not set, then ZoneId.systemDefault() is used to determine the server time zone.
connect.timeout.msDurationNo30000The maximum time that the connector should wait after trying to connect to the database server before timing out.
connect.max-retriesIntegerNo3The max retry times that the connector should retry to build database server connection.
connection.pool.sizeIntegerNo20The jdbc connection pool size.
chunk-key.even-distribution.factor.upper-boundDoubleNo100The upper bound of the chunk key distribution factor. This factor is used to determine whether the table data is evenly distributed. If the distribution factor is calculated to be less than or equal to this upper bound (i.e., (MAX(id) - MIN(id) + 1) / row count), the table chunks would be optimized for even distribution. Otherwise, if the distribution factor is greater, the table will be considered as unevenly distributed and the sampling-based sharding strategy will be used if the estimated shard count exceeds the value specified by sample-sharding.threshold. The default value is 100.0.
chunk-key.even-distribution.factor.lower-boundDoubleNo0.05The lower bound of the chunk key distribution factor. This factor is used to determine whether the table data is evenly distributed. If the distribution factor is calculated to be greater than or equal to this lower bound (i.e., (MAX(id) - MIN(id) + 1) / row count), the table chunks would be optimized for even distribution. Otherwise, if the distribution factor is less, the table will be considered as unevenly distributed and the sampling-based sharding strategy will be used if the estimated shard count exceeds the value specified by sample-sharding.threshold. The default value is 0.05.
sample-sharding.thresholdIntegerNo1000This configuration specifies the threshold of estimated shard count to trigger the sample sharding strategy. When the distribution factor is outside the bounds specified by chunk-key.even-distribution.factor.upper-bound and chunk-key.even-distribution.factor.lower-bound, and the estimated shard count (calculated as approximate row count / chunk size) exceeds this threshold, the sample sharding strategy will be used. This can help to handle large datasets more efficiently. The default value is 1000 shards.
inverse-sampling.rateIntegerNo1000The inverse of the sampling rate used in the sample sharding strategy. For example, if this value is set to 1000, it means a 1/1000 sampling rate is applied during the sampling process. This option provides flexibility in controlling the granularity of the sampling, thus affecting the final number of shards. It's especially useful when dealing with very large datasets where a lower sampling rate is preferred. The default value is 1000.
exactly_onceBooleanNofalseEnable exactly once semantic.
formatEnumNoDEFAULTOptional output format for Opengauss CDC, valid enumerations are DEFAULT, COMPATIBLE_DEBEZIUM_JSON.
debeziumConfigNo-Pass-through Debezium's properties to Debezium Embedded Engine which is used to capture data changes from Opengauss server.
common-optionsno-Source plugin common parameters, please refer to Source Common Options for details

Task Example

Simple

Support multi-table reading


env {
# You can set engine configuration here
execution.parallelism = 1
job.mode = "STREAMING"
checkpoint.interval = 5000
read_limit.bytes_per_second=7000000
read_limit.rows_per_second=400
}

source {
Opengauss-CDC {
result_table_name = "customers_opengauss_cdc"
username = "gaussdb"
password = "openGauss@123"
database-names = ["opengauss_cdc"]
schema-names = ["inventory"]
table-names = ["opengauss_cdc.inventory.opengauss_cdc_table_1","opengauss_cdc.inventory.opengauss_cdc_table_2"]
base-url = "jdbc:postgresql://opengauss_cdc_e2e:5432/opengauss_cdc"
decoding.plugin.name = "pgoutput"
}
}

transform {

}

sink {
jdbc {
source_table_name = "customers_opengauss_cdc"
url = "jdbc:postgresql://opengauss_cdc_e2e:5432/opengauss_cdc"
driver = "org.postgresql.Driver"
user = "dailai"
password = "openGauss@123"

compatible_mode="postgresLow"
generate_sink_sql = true
# You need to configure both database and table
database = "opengauss_cdc"
schema = "inventory"
tablePrefix = "sink_"
primary_keys = ["id"]
}
}

Support custom primary key for table

source {
Opengauss-CDC {
result_table_name = "customers_opengauss_cdc"
username = "gaussdb"
password = "openGauss@123"
database-names = ["opengauss_cdc"]
schema-names = ["inventory"]
table-names = ["opengauss_cdc.inventory.full_types_no_primary_key"]
base-url = "jdbc:postgresql://opengauss_cdc_e2e:5432/opengauss_cdc?loggerLevel=OFF"
decoding.plugin.name = "pgoutput"
exactly_once = true
table-names-config = [
{
table = "opengauss_cdc.inventory.full_types_no_primary_key"
primaryKeys = ["id"]
}
]
}
}