Kafka Connect和Docker中的HDFS

Question

我在docker-compose中使用kafka连接HDFS接收器和Hadoop（用于HDFS）。

Hadoop（名称节点和数据节点）似乎正常工作。

但是我对kafka connect sink有一个错误：

ERROR Recovery failed at state RECOVERY_PARTITION_PAUSED 
(io.confluent.connect.hdfs.TopicPartitionWriter:277) 
org.apache.kafka.connect.errors.DataException: 
Error creating writer for log file hdfs://namenode:8020/logs/MyTopic/0/log

有关信息：

• 我的docker-compose.yml中的Hadoop服务：

   namenode: image: uhopper/hadoop-namenode:2.8.1 hostname: namenode container_name: namenode ports: - "50070:50070" networks: default: fides-webapp: aliases: - "hadoop" volumes: - namenode:/hadoop/dfs/name env_file: - ./hadoop.env environment: - CLUSTER_NAME=hadoop-cluster datanode1: image: uhopper/hadoop-datanode:2.8.1 hostname: datanode1 container_name: datanode1 networks: default: fides-webapp: aliases: - "hadoop" volumes: - datanode1:/hadoop/dfs/data env_file: - ./hadoop.env 

和我的kafka-connect文件：

    name=hdfs-sink
    connector.class=io.confluent.connect.hdfs.HdfsSinkConnector
    tasks.max=1
    topics=MyTopic
    hdfs.url=hdfs://namenode:8020
    flush.size=3

编辑：

我为kafka connect添加了一个env变量以了解集群名称（env变量：CLUSTER_NAME，用于在docker compose文件中的kafka connect服务中添加）。

错误并不相同（似乎可以解决问题）：

INFO Starting commit and rotation for topic partition scoring-topic-0 with start offsets {partition=0=0} and end offsets {partition=0=2} 
 (io.confluent.connect.hdfs.TopicPartitionWriter:368)
ERROR Exception on topic partition MyTopic-0: (io.confluent.connect.hdfs.TopicPartitionWriter:403)
org.apache.kafka.connect.errors.DataException: org.apache.hadoop.ipc.RemoteException(java.io.IOException): 
File /topics/+tmp/MyTopic/partition=0/bc4cf075-ccfa-4338-9672-5462cc6c3404_tmp.avro 
could only be replicated to 0 nodes instead of minReplication (=1).  
There are 1 datanode(s) running and 1 node(s) are excluded in this operation.

编辑2：

hadoop.env文件是：

    CORE_CONF_fs_defaultFS=hdfs://namenode:8020

    # Configure default BlockSize and Replication for local
    # data. Keep it small for experimentation.
    HDFS_CONF_dfs_blocksize=1m

    YARN_CONF_yarn_log___aggregation___enable=true
    YARN_CONF_yarn_resourcemanager_recovery_enabled=true
    YARN_CONF_yarn_resourcemanager_store_class=org.apache.hadoop.yarn.server.resourcemanager.recovery.FileSystemRMStateStore
    YARN_CONF_yarn_resourcemanager_fs_state___store_uri=/rmstate
    YARN_CONF_yarn_nodemanager_remote___app___log___dir=/app-logs

    YARN_CONF_yarn_log_server_url=http://historyserver:8188/applicationhistory/logs/
    YARN_CONF_yarn_timeline___service_enabled=true
    YARN_CONF_yarn_timeline___service_generic___application___history_enabled=true
    YARN_CONF_yarn_resourcemanager_system___metrics___publisher_enabled=true

    YARN_CONF_yarn_resourcemanager_hostname=resourcemanager
    YARN_CONF_yarn_timeline___service_hostname=historyserver

Answer 1

最后，就像@ cricket_007注意到的那样，我需要配置hadoop.conf.dir 。

该目录应包含hdfs-site.xml 。

在对每个服务进行docker化后，我需要创建一个命名卷，以便在kafka-connect服务和namenode服务之间共享配置文件。

为此，我添加了docker-compose.yml ：

volumes:
  hadoopconf:

然后为namenode服务添加：

volumes:
  - hadoopconf:/etc/hadoop

对于kafka connect服务：

volumes:
    - hadoopconf:/usr/local/hadoop-conf

最后，我将HDFS接收器属性文件中的hadoop.conf.dir设置为/usr/local/hadoop-conf 。