我在docker上运行hadoop cluster，当我尝试从java编写hdfs时，出现以下错误。我不知道是什么原因造成的：

Exception in thread "main" org.apache.hadoop.ipc.RemoteException(java.io.IOException): File /user/javadeveloperzone/javareadwriteexample/read_write_hdfs_example.txt could only be written to 0 of the 1 minReplication nodes. There are 3 datanode(s) running and 3 node(s) are excluded in this operation.
    at org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:2219)
    at org.apache.hadoop.hdfs.server.namenode.FSDirWriteFileOp.chooseTargetForNewBlock(FSDirWriteFileOp.java:294)
    at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:2789)
    at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:892)
    at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:574)
    at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:528)
    at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1070)
    at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:999)
    at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:927)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:422)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1730)
    at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2915)

这是我用来写hdfs的代码，我从(http://localhost：9870/explorer.html#/）当代码运行但大小为0时创建目录和文件：

public static void writeFileToHDFS() throws IOException {
        Configuration configuration = new Configuration();
        configuration.set("fs.defaultFS", "hdfs://localhost:9000");
        FileSystem fileSystem = FileSystem.get(configuration);
        //Create a path
        String fileName = "read_write_hdfs_example.txt";
        Path hdfsWritePath = new Path("/user/javadeveloperzone/javareadwriteexample/" + fileName);
        FSDataOutputStream fsDataOutputStream = fileSystem.create(hdfsWritePath,true);
        BufferedWriter bufferedWriter = new BufferedWriter(new OutputStreamWriter(fsDataOutputStream,StandardCharsets.UTF_8));
        bufferedWriter.write("Java API to write data in HDFS");
        bufferedWriter.newLine();
        bufferedWriter.close();
        fileSystem.close();
    }

存储库：(https://github.com/nsquare-jdzone/hadoop-examples/tree/master/readwritehdfsexample)从本教程中：https://javadeveloperzone.com/hadoop/java-read-write-files-hdfs-example/
使用本教程设置docker群集：https://clubhouse.io/developer-how-to/how-to-set-up-a-hadoop-cluster-in-docker/
综上所述，本教程使用大数据存储库(https://github.com/big-data-europe/docker-hadoop)另外，还可以使用docker-compose.yml使其成为多个数据节点，而不是单个数据节点。本教程版本位于big data europe存储库之后，因此我将docker-compose.yml文件更改为：

version: "3"
services:
  namenode:
    image: bde2020/hadoop-namenode:2.0.0-hadoop3.2.1-java8
    container_name: namenode
    restart: always
    ports:
      - 9870:9870
      - 9000:9000
    volumes:
      - hadoop_namenode:/hadoop/dfs/name
    environment:
      - CLUSTER_NAME=test
    env_file:
      - ./hadoop.env
  datanode1:
    image: bde2020/hadoop-datanode:2.0.0-hadoop3.2.1-java8
    container_name: datanode1
    restart: always
    volumes:
      - hadoop_datanode1:/hadoop/dfs/data
    environment:
      SERVICE_PRECONDITION: "namenode:9870"
    env_file:
      - ./hadoop.env
  datanode2:
    image: bde2020/hadoop-datanode:2.0.0-hadoop3.2.1-java8
    container_name: datanode2
    restart: always
    volumes:
      - hadoop_datanode2:/hadoop/dfs/data
    environment:
      SERVICE_PRECONDITION: "namenode:9870"
    env_file:
      - ./hadoop.env
  datanode3:
    image: bde2020/hadoop-datanode:2.0.0-hadoop3.2.1-java8
    container_name: datanode3
    restart: always
    volumes:
      - hadoop_datanode3:/hadoop/dfs/data
    environment:
      SERVICE_PRECONDITION: "namenode:9870"
    env_file:
      - ./hadoop.env
  resourcemanager:
    image: bde2020/hadoop-resourcemanager:2.0.0-hadoop3.2.1-java8
    container_name: resourcemanager
    restart: always
    environment:
      SERVICE_PRECONDITION: "namenode:9000 namenode:9870 datanode1:9864 datanode2:9864"
    env_file:
      - ./hadoop.env
  nodemanager1:
    image: bde2020/hadoop-nodemanager:2.0.0-hadoop3.2.1-java8
    container_name: nodemanager
    restart: always
    environment:
      SERVICE_PRECONDITION: "namenode:9000 namenode:9870 datanode1:9864 datanode2:9864 resourcemanager:8088"
    env_file:
      - ./hadoop.env
  historyserver:
    image: bde2020/hadoop-historyserver:2.0.0-hadoop3.2.1-java8
    container_name: historyserver
    restart: always
    environment:
      SERVICE_PRECONDITION: "namenode:9000 namenode:9870 datanode1:9864 datanode2:9864 resourcemanager:8088"
    volumes:
      - hadoop_historyserver:/hadoop/yarn/timeline
    env_file:
      - ./hadoop.env
volumes:
  hadoop_namenode:
  hadoop_datanode1:
  hadoop_datanode2:
  hadoop_datanode3:
  hadoop_historyserver:

任何帮助都将不胜感激。