dolphin 配置data 从文件导入hive 实践（一）

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原创 2024-11-08 16:24:55 724 阅读 AI 写同款· GEO 优化 ›

DATAX数据同步工具 1、DataX完成单个数据同步的作业，我们称之为Job，DataX接受到一个Job之后，将启动一个进程来完成整个作业同步过程。DataX Job模块是单个作业的中枢管理节点，承担了数据清理、子任务切分(将单一作业计算转化为多个子Task)、TaskGroup管理等功能。2、DataXJob启动后，会根据不同的源端切分策略，将Job切分成多个小的Task(子任务)，以便于并发执行。Task便是DataX作业的最小单元，每一个Task都会负责一部分数据的同步工作。阅读详情

datax 支持多种数据源的相互读写，作为开源软件，提供了离线采集功能，方便系统开发，过程中遇到诸多配置，需要开发者自己探索，免费同样有成本

配置模板

{
    "setting": {},
    "job": {
        "setting": {
            "speed": {
                "channel": 2
            }
        },
        "content": [
            {
                "reader": {
                    "name": "txtfilereader",
                    "parameter": {
                        "path": ["/data/test/test.txt"],
                        "encoding": "UTF-8",
                        "column": [
                            {
                                "index": 0,
                                "type": "string"
                            },
                            {
                                "index": 1,
                                "type": "string"
                            }
                        ],
                        "fieldDelimiter": "\t"
                    }
                },
                "writer": {
                    "name": "hdfswriter",
                    "parameter": {
                        "defaultFS": "hdfs://****:9000",
                        "fileType": "TEXT",
                        "path": "/user/hive/warehouse/sz_center_devdb.db/cat",
                        "fileName": "catfile",
                        "column": [
                            {
                                "name": "cat_id",
                                "type": "STRING"
                            },
                            {
                                "name": "cat_name",
                                "type": "STRING"
                            }
                        ],
                        "writeMode": "append",
                        "fieldDelimiter": "\t",
                        "compress":"NONE"
                    }
                }
            }
        ]
    }
}

注意：文本文件需要上传到datax 所在服务器

执行报错一：

Hadoop 权限异常

      Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.security.AccessControlException): Permission denied: user=default, access=WRITE, inode="/user/hive/warehouse/sz_center_devdb.db":anonymous:supergroup:drwxr-xr-x
                at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.check(FSPermissionChecker.java:496)
                at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.checkPermission(FSPermissionChecker.java:336)
                at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.checkPermission(FSPermissionChecker.java:241)
                at org.apache.hadoop.hdfs.server.namenode.FSDirectory.checkPermission(FSDirectory.java:1909)
                at org.apache.hadoop.hdfs.server.namenode.FSDirectory.checkPermission(FSDirectory.java:1893)
                at org.apache.hadoop.hdfs.server.namenode.FSDirectory.checkAncestorAccess(FSDirectory.java:1852)
                at org.apache.hadoop.hdfs.server.namenode.FSDirWriteFileOp.resolvePathForStartFile(FSDirWriteFileOp.java:323)
                at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2635)
                at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2577)
                at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:807)
                at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:494)
                at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
                at org.apache.hadoop.ipc.ProtobufRpcEngine2$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine2.java:532)
                at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1070)
                at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:1020)
                at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:948)
                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:1845)
                at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2952)

                at org.apache.hadoop.ipc.Client.call(Client.java:1476)
                at org.apache.hadoop.ipc.Client.call(Client.java:1407)
                at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
                at com.sun.proxy.$Proxy9.create(Unknown Source)
                at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.create(ClientNamenodeProtocolTranslatorPB.java:296)
                at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
                at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
                at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
                at java.lang.reflect.Method.invoke(Method.java:498)
                at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
                at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
                at com.sun.proxy.$Proxy10.create(Unknown Source)
                at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:1623)
                ... 18 more

这里是因为Hadoop 目录没有权限。
这里执行的用户是default
dataX 模板中没有配置用户的地方，这里先去Hadoop 配置目录权限

Hadoop 目录权限配置

hdfs dfs -ls /
hdfs dfs -mkdir /user
hdfs dfs -mkdir /hbase
hdfs dfs -ls /
hadoop fs -chmod 777 /user
hadoop fs -chmod 777 /hbase
# 循环所有子目录配置权限
hadoop fs -chmod -R 777 /hbase

然后运行dataX 任务成功。
但从hive 链接中发现数据乱码,这里就是 hive的文件类型和分隔符不一致导致

在这里插入图片描述
这里回顾日志发现读取文本异常

[WI-0][TI-0] - [INFO] 2024-11-06 16:16:36.229 +0800 o.a.d.p.t.a.AbstractTask:[169] -  -> 
        2024-11-06 16:16:35.230 [0-0-0-reader] INFO  TxtFileReader$Task - reading file : [/data/test/test.txt]
        2024-11-06 16:16:35.231 [taskGroup-0] INFO  TaskGroupContainer - taskGroup[0] taskId[0] attemptCount[1] is started
        2024-11-06 16:16:35.268 [0-0-0-writer] INFO  HdfsWriter$Task - begin do write...
        2024-11-06 16:16:35.268 [0-0-0-writer] INFO  HdfsWriter$Task - write to file : [hdfs://10.80.18.165:9000/user/hive/warehouse/sz_center_devdb.db/cat__f395492b_e42a_47e5_a52b_214ab8bf833a/catfile__d369974c_fdeb_4601_b118_67ae6e97e197]
        2024-11-06 16:16:35.341 [0-0-0-reader] INFO  UnstructuredStorageReaderUtil - CsvReader使用默认值[{"captureRawRecord":true,"columnCount":0,"comment":"#","currentRecord":-1,"delimiter":"\t","escapeMode":1,"headerCount":0,"rawRecord":"","recordDelimiter":"\u0000","safetySwitch":false,"skipEmptyRecords":true,"textQualifier":"\"","trimWhitespace":true,"useComments":false,"useTextQualifier":true,"values":[]}],csvReaderConfig值为[null]
        2024-11-06 16:16:35.351 [0-0-0-reader] WARN  UnstructuredStorageReaderUtil - 您尝试读取的列越界,源文件该行有 [1] 列,您尝试读取第 [2] 列, 数据详情[1 hello]
        2024-11-06 16:16:35.356 [0-0-0-reader] ERROR StdoutPluginCollector - 脏数据: 
        {"message":"您尝试读取的列越界,源文件该行有 [1] 列,您尝试读取第 [2] 列, 数据详情[1 hello]","record":[{"byteSize":7,"index":0,"rawData":"1 hello","type":"STRING"}],"type":"reader"}
        2024-11-06 16:16:35.357 [0-0-0-reader] WARN  UnstructuredStorageReaderUtil - 您尝试读取的列越界,源文件该行有 [1] 列,您尝试读取第 [2] 列, 数据详情[2 cat]
        2024-11-06 16:16:35.357 [0-0-0-reader] ERROR StdoutPluginCollector - 脏数据: 
        {"message":"您尝试读取的列越界,源文件该行有 [1] 列,您尝试读取第 [2] 列, 数据详情[2 cat]","record":[{"byteSize":5,"index":0,"rawData":"2 cat","type":"STRING"}],"type":"reader"}
        2024-11-06 16:16:35.793 [0-0-0-writer] INFO  HdfsWriter$Task - end do write
        2024-11-06 16:16:35.841 [taskGroup-0] INFO  TaskGroupContainer - taskGroup[0] taskId[0] is successed, used[623]ms
        2024-11-06 16:16:35.841 [taskGroup-0] INFO  TaskGroupContainer - taskGroup[0] completed it's tasks.
[WI-0][TI-0] - [INFO] 2024-11-06 16:16:45.231 +0800 o.a.d.p.t.a.AbstractTask:[169] -  -> 
        2024-11-06 16:16:45.222 [job-0] INFO  StandAloneJobContainerCommunicator - Total 2 records, 12 bytes | Speed 1B/s, 0 records/s | Error 2 records, 12 bytes |  All Task WaitWriterTime 0.000s |  All Task WaitReaderTime 0.000s | Percentage 100.00%
        2024-11-06 16:16:45.222 [job-0] INFO  AbstractScheduler - Scheduler accomplished all tasks.
        2024-11-06 16:16:45.223 [job-0] INFO  JobContainer - DataX Writer.Job [hdfswriter] do post work.
        2024-11-06 16:16:45.224 [job-0] INFO  HdfsWriter$Job - start rename file [hdfs://10.80.18.165:9000/user/hive/warehouse/sz_center_devdb.db/cat__f395492b_e42a_47e5_a52b_214ab8bf833a/catfile__d369974c_fdeb_4601_b118_67ae6e97e197] to file [hdfs://10.80.18.165:9000/user/hive/warehouse/sz_center_devdb.db/cat/catfile__d369974c_fdeb_4601_b118_67ae6e97e197].
[WI-0][TI-0] - [INFO] 2024-11-06 16:16:46.231 +0800 o.a.d.p.t.a.AbstractTask:[169] -  ->

暂时不确定是源文件格式问题还是编码问题

或者是任务配置问题。

后续出结果后更新。

执行异常二

在这里插入图片描述

数据为空，或者数据列不对应。
这种情况执行日志没有任何异常，执行结果也是成功，但是目标的hive 表里没有数据。

这时候就看hive的分隔符配置了。

如何查看hive表的分隔符

执行命令

show create table hello

查看

在这里插入图片描述

‘org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe’ # 默认分隔符，行分割符：“\n”，列分割符：“^A”
这个在data JSON 中还不能直接配置，必须使用转义字符

默认存储格式textfile

JSON 里配置 TEXT

参考资料：https://blog.youkuaiyun.com/mn525520/article/details/106876384
https://blog.youkuaiyun.com/u010520724/article/details/121999575
https://blog.youkuaiyun.com/qq_36039236/article/details/108101345

生效hive 建表语句、dataX json 任务配置参见

配置示例:www.fancv.com