我无法将表格从HBase导出到HDFS。以下是错误跟踪。它的体积很大。有没有其他方法可以将其导出？
我使用下面的命令导出。我增加了rpc超时但仍然失败了。
sudo -u hdfs hbase -Dhbase.rpc.timeout=1000000 org.apache.hadoop.hbase.mapreduce.Export My_Table /hdfs_path
15/05/05 08:50:27 INFO mapreduce.Job: map 0% reduce 0%
15/05/05 08:50:55 INFO mapreduce.Job: Task Id : attempt_1424936551928_0234_m_000001_0, Status : FAILED
Error: org.apache.hadoop.hbase.DoNotRetryIOException: Failed after retry of OutOfOrderScannerNextException: was there a rpc timeout?
at org.apache.hadoop.hbase.client.ClientScanner.next(ClientScanner.java:410)
at org.apache.hadoop.hbase.mapreduce.TableRecordReaderImpl.nextKeyValue(TableRecordReaderImpl.java:230)
at org.apache.hadoop.hbase.mapreduce.TableRecordReader.nextKeyValue(TableRecordReader.java:138)
at org.apache.hadoop.mapred.MapTask$NewTrackingRecordReader.nextKeyValue(MapTask.java:553)
at org.apache.hadoop.mapreduce.task.MapContextImpl.nextKeyValue(MapContextImpl.java:80)
at org.apache.hadoop.mapreduce.lib.map.WrappedMapper$Context.nextKeyValue(WrappedMapper.java:91)
at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:144)
at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:784)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:341)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:168)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1642)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:163)
Caused by: org.apache.hadoop.hbase.exceptions.OutOfOrderScannerNextException: org.apache.hadoop.hbase.exceptions.OutOfOrderScannerNextException: Expected nextCallSeq: 1 But the nextCallSeq got from client: 0; request=scanner_id: 229 number_of_rows: 100 close_scanner: false next_call_seq: 0
at org.apache.hadoop.hbase.regionserver.HRegionServer.scan(HRegionServer.java:3198)
at org.apache.hadoop.hbase.protobuf.generated.ClientProtos$ClientService$2.callBlockingMethod(ClientProtos.java:29925)
at org.apache.hadoop.hbase.ipc.RpcServer.call(RpcServer.java:2031)
at org.apache.hadoop.hbase.ipc.CallRunner.run(CallRunner.java:108)
at org.apache.hadoop.hbase.ipc.RpcExecutor.consumerLoop(RpcExecutor.java:116)
at org.apache.hadoop.hbase.ipc.RpcExecutor$1.run(RpcExecutor.java:96)
at java.lang.Thread.run(Thread.java:745)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at org.apache.hadoop.ipc.RemoteException.instantiateException(RemoteException.java:106)
at org.apache.hadoop.ipc.RemoteException.unwrapRemoteException(RemoteException.java:95)
at org.apache.hadoop.hbase.protobuf.ProtobufUtil.getRemoteException(ProtobufUtil.java:304)
at org.apache.hadoop.hbase.client.ScannerCallable.call(ScannerCallable.java:204)
at org.apache.hadoop.hbase.client.ScannerCallable.call(ScannerCallable.java:59)
at org.apache.hadoop.hbase.client.RpcRetryingCaller.callWithRetries(RpcRetryingCaller.java:114)
at org.apache.hadoop.hbase.client.RpcRetryingCaller.callWithRetries(RpcRetryingCaller.java:90)
at org.apache.hadoop.hbase.client.ClientScanner.next(ClientScanner.java:355)
... 13 more
Caused by: org.apache.hadoop.hbase.ipc.RemoteWithExtrasException(org.apache.hadoop.hbase.exceptions.OutOfOrderScannerNextException): org.apache.hadoop.hbase.exceptions.OutOfOrderScannerNextException: Expected nextCallSeq: 1 But the nextCallSeq got from client: 0; request=scanner_id: 229 number_of_rows: 100 close_scanner: false next_call_seq: 0
at org.apache.hadoop.hbase.regionserver.HRegionServer.scan(HRegionServer.java:3198)
at org.apache.hadoop.hbase.protobuf.generated.ClientProtos$ClientService$2.callBlockingMethod(ClientProtos.java:29925)
at org.apache.hadoop.hbase.ipc.RpcServer.call(RpcServer.java:2031)
at org.apache.hadoop.hbase.ipc.CallRunner.run(CallRunner.java:108)
at org.apache.hadoop.hbase.ipc.RpcExecutor.consumerLoop(RpcExecutor.java:116)
at org.apache.hadoop.hbase.ipc.RpcExecutor$1.run(RpcExecutor.java:96)
at java.lang.Thread.run(Thread.java:745)
at org.apache.hadoop.hbase.ipc.RpcClient.call(RpcClient.java:1457)
at org.apache.hadoop.hbase.ipc.RpcClient.callBlockingMethod(RpcClient.java:1661)
at org.apache.hadoop.hbase.ipc.RpcClient$BlockingRpcChannelImplementation.callBlockingMethod(RpcClient.java:1719)
at org.apache.hadoop.hbase.protobuf.generated.ClientProtos$ClientService$BlockingStub.scan(ClientProtos.java:30328)
at org.apache.hadoop.hbase.client.ScannerCallable.call(ScannerCallable.java:174)
... 17 more
答案 0 :(得分：1)
如果表格非常大，以下是一些 提示 ，您可以通过查看Export命令的代码来尝试
您可以调整缓存大小，应用扫描过滤器
请参阅hbase
下面的Export api请参阅使用命令：它为您提供了更多选项。
根据我的经验cachesize（不是批量大小=时间列数）和/或
自定义过滤条件应该适合您。
例如：如果您的密钥开始为0_，其中0是区域名称，请首先通过指定过滤器来导出这些行
然后是下一个区域数据......等等。下面是ExportFilter片段，通过它您可以了解它是如何工作的。
private static Filter getExportFilter(String[] args) {
138 Filter exportFilter = null;
139 String filterCriteria = (args.length > 5) ? args[5]: null;
140 if (filterCriteria == null) return null;
141 if (filterCriteria.startsWith("^")) {
142 String regexPattern = filterCriteria.substring(1, filterCriteria.length());
143 exportFilter = new RowFilter(CompareOp.EQUAL, new RegexStringComparator(regexPattern));
144 } else {
145 exportFilter = new PrefixFilter(Bytes.toBytesBinary(filterCriteria));
146 }
147 return exportFilter;
148 }
/*
151 * @param errorMsg Error message. Can be null.
152 */
153 private static void usage(final String errorMsg) {
154 if (errorMsg != null && errorMsg.length() > 0) {
155 System.err.println("ERROR: " + errorMsg);
156 }
157 System.err.println("Usage: Export [-D <property=value>]* <tablename> <outputdir> [<versions> " +
158 "[<starttime> [<endtime>]] [^[regex pattern] or [Prefix] to filter]]\n");
159 System.err.println(" Note: -D properties will be applied to the conf used. ");
160 System.err.println(" For example: ");
161 System.err.println(" -D mapreduce.output.fileoutputformat.compress=true");
162 System.err.println(" -D mapreduce.output.fileoutputformat.compress.codec=org.apache.hadoop.io.compress.GzipCodec");
163 System.err.println(" -D mapreduce.output.fileoutputformat.compress.type=BLOCK");
164 System.err.println(" Additionally, the following SCAN properties can be specified");
165 System.err.println(" to control/limit what is exported..");
166 System.err.println(" -D " + TableInputFormat.SCAN_COLUMN_FAMILY + "=<familyName>");
167 System.err.println(" -D " + RAW_SCAN + "=true");
168 System.err.println(" -D " + TableInputFormat.SCAN_ROW_START + "=<ROWSTART>");
169 System.err.println(" -D " + TableInputFormat.SCAN_ROW_STOP + "=<ROWSTOP>");
170 System.err.println(" -D " + JOB_NAME_CONF_KEY
171 + "=jobName - use the specified mapreduce job name for the export");
172 System.err.println("For performance consider the following properties:\n"
173 + " -Dhbase.client.scanner.caching=100\n"
174 + " -Dmapreduce.map.speculative=false\n"
175 + " -Dmapreduce.reduce.speculative=false");
176 System.err.println("For tables with very wide rows consider setting the batch size as below:\n"
177 + " -D" + EXPORT_BATCHING + "=10");
178 }