Kafka source connector
Spark
Flink
Seatunnel Zeta
Source connector for Apache Kafka.
In order to use the Kafka connector, the following dependencies are required. They can be downloaded via install-plugin.sh or from the Maven central repository.
| Datasource | Supported Versions | Maven |
|---|---|---|
| Kafka | Universal | Download |
| Name | Type | Required | Default | Description |
|---|---|---|---|---|
| topic | String | Yes | - | Topic name(s) to read data from when the table is used as source. It also supports topic list for source by separating topic by comma like 'topic-1,topic-2'. |
| bootstrap.servers | String | Yes | - | Comma separated list of Kafka brokers. |
| pattern | Boolean | No | false | If pattern is set to true,the regular expression for a pattern of topic names to read from. All topics in clients with names that match the specified regular expression will be subscribed by the consumer. |
| consumer.group | String | No | SeaTunnel-Consumer-Group | Kafka 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. |
| kafka.config | Map | No | - | In addition to the above necessary parameters that must be specified by the Kafka consumer client, users can also specify multiple consumer client non-mandatory parameters, covering all consumer parameters specified in the official Kafka document. |
| schema | Config | 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, canal_json, debezium_json, ogg_json and avro.If you use json or text format. The default field separator is ", ". If you customize the delimiter, add the "field_delimiter" option.If you use canal format, please refer to canal-json for details.If you use debezium format, please refer to debezium-json for details. |
| format_error_handle_way | String | No | fail | The processing method of data format error. The default value is fail, and the optional value is (fail, skip). When fail is selected, data format error will block and an exception will be thrown. When skip is selected, data format error will skip this line data. |
| field_delimiter | String | No | , | Customize the field delimiter for data format. |
| start_mode | StartMode[earliest],[group_offsets],[latest],[specific_offsets],[timestamp] | No | group_offsets | The initial consumption pattern of consumers. |
| start_mode.offsets | Config | No | - | The offset required for consumption mode to be specific_offsets. |
| start_mode.timestamp | Long | No | - | The time required for consumption mode to be "timestamp". |
| partition-discovery.interval-millis | Long | No | -1 | The interval for dynamically discovering topics and partitions. |
| common-options | No | - | Source plugin common parameters, please refer to Source Common Options for details |
This example reads the data of kafka's topic_1, topic_2, topic_3 and prints it to the client.And if you have not yet installed and deployed SeaTunnel, you need to follow the instructions in Install SeaTunnel to install and deploy SeaTunnel. And if you have not yet installed and deployed SeaTunnel, you need to follow the instructions in Install SeaTunnel to install and deploy SeaTunnel. And then follow the instructions in Quick Start With SeaTunnel Engine to run this job.
# Defining the runtime environment
env {
parallelism = 2
job.mode = "BATCH"
}
source {
Kafka {
schema = {
fields {
name = "string"
age = "int"
}
}
format = text
field_delimiter = "#"
topic = "topic_1,topic_2,topic_3"
bootstrap.servers = "localhost:9092"
kafka.config = {
client.id = client_1
max.poll.records = 500
auto.offset.reset = "earliest"
enable.auto.commit = "false"
}
}
}
sink {
Console {}
}source {
Kafka {
topic = ".*seatunnel*."
pattern = "true"
bootstrap.servers = "localhost:9092"
consumer.group = "seatunnel_group"
}
}Replace the following ${username} and ${password} with the configuration values in AWS MSK.
source {
Kafka {
topic = "seatunnel"
bootstrap.servers = "xx.amazonaws.com.cn:9096,xxx.amazonaws.com.cn:9096,xxxx.amazonaws.com.cn:9096"
consumer.group = "seatunnel_group"
kafka.config = {
security.protocol=SASL_SSL
sasl.mechanism=SCRAM-SHA-512
sasl.jaas.config="org.apache.kafka.common.security.scram.ScramLoginModule required username=\"username\" password=\"password\";"
#security.protocol=SASL_SSL
#sasl.mechanism=AWS_MSK_IAM
#sasl.jaas.config="software.amazon.msk.auth.iam.IAMLoginModule required;"
#sasl.client.callback.handler.class="software.amazon.msk.auth.iam.IAMClientCallbackHandler"
}
}
}Download aws-msk-iam-auth-1.1.5.jar from https://github.com/aws/aws-msk-iam-auth/releases and put it in $SEATUNNEL_HOME/plugin/kafka/lib dir.
Please ensure the IAM policy have "kafka-cluster:Connect",. Like this:
"Effect": "Allow",
"Action": [
"kafka-cluster:Connect",
"kafka-cluster:AlterCluster",
"kafka-cluster:DescribeCluster"
],Source Config
source {
Kafka {
topic = "seatunnel"
bootstrap.servers = "xx.amazonaws.com.cn:9098,xxx.amazonaws.com.cn:9098,xxxx.amazonaws.com.cn:9098"
consumer.group = "seatunnel_group"
kafka.config = {
#security.protocol=SASL_SSL
#sasl.mechanism=SCRAM-SHA-512
#sasl.jaas.config="org.apache.kafka.common.security.scram.ScramLoginModule required username=\"username\" password=\"password\";"
security.protocol=SASL_SSL
sasl.mechanism=AWS_MSK_IAM
sasl.jaas.config="software.amazon.msk.auth.iam.IAMLoginModule required;"
sasl.client.callback.handler.class="software.amazon.msk.auth.iam.IAMClientCallbackHandler"
}
}
}Source Config
source {
Kafka {
topic = "seatunnel"
bootstrap.servers = "127.0.0.1:9092"
consumer.group = "seatunnel_group"
kafka.config = {
security.protocol=SASL_PLAINTEXT
sasl.kerberos.service.name=kafka
sasl.mechanism=GSSAPI
java.security.krb5.conf="/etc/krb5.conf"
sasl.jaas.config="com.sun.security.auth.module.Krb5LoginModule required \n useKeyTab=true \n storeKey=true \n keyTab=\"/path/to/xxx.keytab\" \n principal=\"user@xxx.com\";"
}
}
}