RocketMQ

RocketMQ source connector

Support Apache RocketMQ Version

• 4.9.0 (Or a newer version, for reference)

Support These Engines

Spark
Flink
SeaTunnel Zeta

Key Features

• batch
• stream
• exactly-once
• column projection
• parallelism
• support user-defined split

Description

Source connector for Apache RocketMQ.

Source Options

Name	Type	Required	Default	Description
topics	String	yes	-	RocketMQ topic name. If there are multiple topics, use , to split, for example: "tpc1,tpc2".
name.srv.addr	String	yes	-	RocketMQ name server cluster address.
acl.enabled	Boolean	no	false	If true, access control is enabled, and access key and secret key need to be configured.
access.key	String	no
secret.key	String	no		When ACL_ENABLED is true, secret key cannot be empty.
batch.size	int	no	100	RocketMQ consumer pull batch size
consumer.group	String	no	SeaTunnel-Consumer-Group	RocketMQ consumer group id, used to distinguish different consumer groups.
commit.on.checkpoint	Boolean	no	true	If true the consumer's offset will be periodically committed in the background.
schema		no	-	The structure of the data, including field names and field types.
format	String	no	json	Data format. The default format is json. Optional text format. The default field separator is ",".If you customize the delimiter, add the "field.delimiter" option.
field.delimiter	String	no	,	Customize the field delimiter for data format
start.mode	String	no	CONSUME_FROM_GROUP_OFFSETS	The initial consumption pattern of consumers,there are several types: [CONSUME_FROM_LAST_OFFSET],[CONSUME_FROM_FIRST_OFFSET],[CONSUME_FROM_GROUP_OFFSETS],[CONSUME_FROM_TIMESTAMP],[CONSUME_FROM_SPECIFIC_OFFSETS]
start.mode.offsets		no
start.mode.timestamp	Long	no		The time required for consumption mode to be "CONSUME_FROM_TIMESTAMP".
partition.discovery.interval.millis	long	no	-1	The interval for dynamically discovering topics and partitions.
common-options	config	no	-	Source plugin common parameters, please refer to Source Common Options for details.

start.mode.offsets

The offset required for consumption mode to be "CONSUME_FROM_SPECIFIC_OFFSETS".

for example:

start.mode.offsets = {
  topic1-0 = 70
  topic1-1 = 10
  topic1-2 = 10
}

Task Example

Simple:

Consumer reads Rocketmq data and prints it to the console type

env {
  parallelism = 1
  job.mode = "BATCH"
}

source {
  Rocketmq {
    name.srv.addr = "rocketmq-e2e:9876"
    topics = "test_topic_json"
    result_table_name = "rocketmq_table"
    schema = {
      fields {
        id = bigint
        c_map = "map<string, smallint>"
        c_array = "array<tinyint>"
        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(2, 1)"
        c_bytes = bytes
        c_date = date
        c_timestamp = timestamp
      }
    }
  }
}

transform {
  # If you would like to get more information about how to configure seatunnel and see full list of transform plugins,
  # please go to https://seatunnel.apache.org/docs/category/transform
}

sink {
  Console {
  }
}

Specified format consumption Simple:

When I consume the topic data in json format parsing and pulling the number of bars each time is 400, the consumption starts from the original location

env {
  parallelism = 1
  job.mode = "BATCH"
}

source {
  Rocketmq {
    name.srv.addr = "localhost:9876"
    topics = "test_topic"
    result_table_name = "rocketmq_table"
    start.mode = "CONSUME_FROM_FIRST_OFFSET"
    batch.size = "400"
    consumer.group = "test_topic_group"
    format = "json"
    format = json
    schema = {
      fields {
        c_map = "map<string, string>"
        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(30, 8)"
        c_bytes = bytes
        c_date = date
        c_timestamp = timestamp
      }
    }
  }
}

transform {
  # If you would like to get more information about how to configure seatunnel and see full list of transform plugins,
  # please go to https://seatunnel.apache.org/docs/category/transform
}
sink {
  Console {
  }
}

Specified timestamp Simple:

This is to specify a time to consume, and I dynamically sense the existence of a new partition every 1000 milliseconds to pull the consumption

env {
  parallelism = 1
  spark.app.name = "SeaTunnel"
  spark.executor.instances = 2
  spark.executor.cores = 1
  spark.executor.memory = "1g"
  spark.master = local
  job.mode = "BATCH"
}

source {
  Rocketmq {
    name.srv.addr = "localhost:9876"
    topics = "test_topic"
    partition.discovery.interval.millis = "1000"
    start.mode.timestamp="1694508382000"
    consumer.group="test_topic_group"
    format="json"
    format = json
    schema = {
      fields {
        c_map = "map<string, string>"
        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(30, 8)"
        c_bytes = bytes
        c_date = date
        c_timestamp = timestamp
      }
    }
  }
}

transform {
  # If you would like to get more information about how to configure seatunnel and see full list of transform plugins,
  # please go to https://seatunnel.apache.org/docs/category/transform
}

sink {
  Console {
  }
}