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
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
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
‘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.csdn.net/mn525520/article/details/106876384
https://blog.csdn.net/u010520724/article/details/121999575
https://blog.csdn.net/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
