Kafka Connect:多个 DB2 JDBC 源连接器失败

Kafka Connect: Multiple DB2 JDBC Source Connectors fail

我正在尝试在本地 Docker 容器中使用 Kafka Connect(使用官方 Confluent 图像),以便将 DB2 数据推送到 Openshift(在 AWS 上)上的 Kafka 集群。我将 Confluent JDBC 连接器与我的 DB2 JDBC-Jar 一起使用。 我有不同的连接器配置,因为我将 SMT 与 "transforms.createKey" 一起使用(以创建我的密钥)并且我的表中的密钥列具有不同的名称。

这是我的步骤:

到目前为止一切正常,我可以看到我的数据被推送到集群。但是,一旦我通过 post 调用添加第二个 JDBC 连接器,第一个连接器就会停止将数据推送到集群,而第二个连接器将启动并继续加载和推送数据。有很短的时间似乎两个连接器都将数据推送到集群,但我假设这可能是来自连接器 1 的数据仍然被刷新。 问题是 a) 即使是跟踪日志也没有显示有意义的错误(至少对我而言)和 b) 显示的错误在尝试之间有所不同(我总是删除所有主题和容器)。

我假设这不是错误,而是需要适当设置的配置组合 and/or我对一些基本的 Kafka Connect 核心功能缺乏了解。我已经尝试添加和更改各种配置,但不幸的是到目前为止没有任何效果。我已经尝试了很多次,但没有运气。我附上了我最近两次尝试的日志以及配置。

有谁知道我可以调整哪个配置或要研究什么来解决这个问题? 感谢任何帮助 - 谢谢!


Kafka: 2.0.0
Docker image: confluentinc/cp-kafka-connect:5.0.0
DB2: 10.5
JDBC Jar: db2jcc4.jar with version 4.19.76

记录第一次尝试:

[2018-12-17 13:09:15,683] ERROR Invalid call to OffsetStorageWriter flush() while already flushing, the framework should not allow this (org.apache.kafka.connect.storage.OffsetStorageWriter)
[2018-12-17 13:09:15,684] ERROR WorkerSourceTask{id=db2-jdbc-source-0} Task threw an uncaught and unrecoverable exception (org.apache.kafka.connect.runtime.WorkerTask)
org.apache.kafka.connect.errors.ConnectException: OffsetStorageWriter is already flushing
    at org.apache.kafka.connect.storage.OffsetStorageWriter.beginFlush(OffsetStorageWriter.java:110)
    at org.apache.kafka.connect.runtime.WorkerSourceTask.commitOffsets(WorkerSourceTask.java:409)
    at org.apache.kafka.connect.runtime.WorkerSourceTask.execute(WorkerSourceTask.java:238)
    at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:175)
    at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:219)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
[2018-12-17 13:09:15,686] ERROR WorkerSourceTask{id=db2-jdbc-source-0} Task is being killed and will not recover until manually restarted (org.apache.kafka.connect.runtime.WorkerTask)
[2018-12-17 13:09:15,686] INFO [Producer clientId=producer-4] Closing the Kafka producer with timeoutMillis = 30000 ms. (org.apache.kafka.clients.producer.KafkaProducer)
[2018-12-17 13:09:20,682] ERROR Graceful stop of task db2-jdbc-source-0 failed. (org.apache.kafka.connect.runtime.Worker)
[2018-12-17 13:09:20,682] INFO Finished stopping tasks in preparation for rebalance (org.apache.kafka.connect.runtime.distributed.DistributedHerder)

记录第二次尝试:

[2018-12-17 14:01:31,658] INFO Stopping task db2-jdbc-source-0 (org.apache.kafka.connect.runtime.Worker)
[2018-12-17 14:01:31,689] INFO Stopped connector db2-jdbc-source (org.apache.kafka.connect.runtime.Worker)
[2018-12-17 14:01:31,784] INFO WorkerSourceTask{id=db2-jdbc-source-0} Committing offsets (org.apache.kafka.connect.runtime.WorkerSourceTask)
[2018-12-17 14:01:31,784] INFO WorkerSourceTask{id=db2-jdbc-source-0} flushing 20450 outstanding messages for offset commit (org.apache.kafka.connect.runtime.WorkerSourceTask)
[2018-12-17 14:01:36,733] ERROR Graceful stop of task db2-jdbc-source-0 failed. (org.apache.kafka.connect.runtime.Worker)
[2018-12-17 14:01:36,733] INFO Finished stopping tasks in preparation for rebalance (org.apache.kafka.connect.runtime.distributed.DistributedHerder)

screenshot of incoming messages per second in the Kafka cluster

Kafka Connect Docker 环境变量:

-e CONNECT_BOOTSTRAP_SERVERS=my_kafka_cluster:443 \
  -e CONNECT_PRODUCER_BOOTSTRAP_SERVERS="my_kafka_cluster:443" \
  -e CONNECT_REST_ADVERTISED_HOST_NAME="kafka-connect" \
  -e CONNECT_REST_PORT=8083 \
  -e CONNECT_GROUP_ID="kafka-connect-group" \
  -e CONNECT_CONFIG_STORAGE_REPLICATION_FACTOR=3 \
  -e CONNECT_CONFIG_STORAGE_TOPIC="kafka-connect-config" \
  -e CONNECT_OFFSET_STORAGE_REPLICATION_FACTOR=3 \
  -e CONNECT_OFFSET_STORAGE_TOPIC="kafka-connect-offset" \
  -e CONNECT_OFFSET_FLUSH_INTERVAL_MS=15000 \
  -e CONNECT_OFFSET_FLUSH_TIMEOUT_MS=60000 \
  -e CONNECT_STATUS_STORAGE_REPLICATION_FACTOR=3 \
  -e CONNECT_STATUS_STORAGE_TOPIC="kafka-connect-status" \
  -e CONNECT_KEY_CONVERTER="io.confluent.connect.avro.AvroConverter" \
  -e CONNECT_KEY_CONVERTER_SCHEMA_REGISTRY_URL=http://url_to_schemaregistry \
  -e CONNECT_VALUE_CONVERTER="io.confluent.connect.avro.AvroConverter" \
  -e CONNECT_VALUE_CONVERTER_SCHEMA_REGISTRY_URL=http://url_to_schemaregistry \
  -e CONNECT_INTERNAL_KEY_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_INTERNAL_KEY_CONVERTER_SCHEMAS_ENABLE="false" \
  -e CONNECT_INTERNAL_VALUE_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_INTERNAL_VALUE_CONVERTER_SCHEMAS_ENABLE="false" \
  -e CONNECT_PLUGIN_PATH=/usr/share/java \
  -e CONNECT_PRODUCER_BUFFER_MEMORY="8388608" \
  -e CONNECT_SECURITY_PROTOCOL="SSL" \
  -e CONNECT_PRODUCER_SECURITY_PROTOCOL="SSL" \
  -e CONNECT_SSL_TRUSTSTORE_LOCATION="/usr/share/kafka.client.truststore.jks" \
  -e CONNECT_PRODUCER_SSL_TRUSTSTORE_LOCATION="/usr/share/kafka.client.truststore.jks" \
  -e CONNECT_SSL_TRUSTSTORE_PASSWORD="my_ts_pw" \
  -e CONNECT_PRODUCER_SSL_TRUSTSTORE_PASSWORD="my_ts_pw" \
  -e CONNECT_LOG4J_LOGGERS=org.apache.kafka.connect.runtime.rest=WARN,org.reflections=ERROR \
  -e CONNECT_LOG4J_ROOT_LOGLEVEL=INFO \
  -e HOSTNAME=kafka-connect \

JDBC 个连接器(只有表和键列不同):

{
    "name": "db2-jdbc-source",
    "config": 
    {
        "mode":"timestamp",
        "debug":"true",
        "batch.max.rows":"50",
        "poll.interval.ms":"10000",
        "timestamp.delay.interval.ms":"60000",
        "timestamp.column.name":"IBMSNAP_LOGMARKER",
        "connector.class":"io.confluent.connect.jdbc.JdbcSourceConnector" ,
        "connection.url":"jdbc:db2://myip:myport/mydb:currentSchema=myschema;",
        "connection.password":"mypw",
        "connection.user":"myuser",
        "connection.backoff.ms":"60000",
        "dialect.name": "Db2DatabaseDialect",
        "table.types": "TABLE",
        "table.poll.interval.ms":"60000",
        "table.whitelist":"MYTABLE1",
        "tasks.max":"1",
        "topic.prefix":"db2_",
        "key.converter":"io.confluent.connect.avro.AvroConverter",
        "key.converter.schema.registry.url":"http://url_to_schemaregistry",
        "value.converter":"io.confluent.connect.avro.AvroConverter",
        "value.converter.schema.registry.url":"http://url_to_schemaregistry",
        "transforms":"createKey",
        "transforms.createKey.type":"org.apache.kafka.connect.transforms.ValueToKey",
        "transforms.createKey.fields":"MYKEY1"
    }
}

我终于弄明白了问题所在: 我在时间戳模式下使用 JDBC 连接器而不是时间戳+递增,因为我不能(总是)指定递增列。我知道这可能会导致问题,即当有多个具有相同时间戳的条目时,Connect 无法知道哪些条目已被读取。

我的大部分数据行具有相同的时间戳。当我添加第二个连接器时,存储了第一个连接器的当前时间戳,并且 Connect 开始重新平衡,因此丢失了已经读取了该时间戳的哪些行的信息。当连接器启动并再次 运行 时,第一个连接器继续 "the next timestamp",因此只加载最新的行(这只是一小部分)。

我的错误假设是,在这种情况下,第一个连接器将使用之前的时间戳重新开始工作,而不是继续使用 "next timestamp"。宁愿冒重复数据的风险也不愿冒可能丢失数据的风险对我来说更有意义。