gpt4 book ai didi

regex - 级联-正则表达式解析器-错​​误的字段数

转载 作者:行者123 更新时间:2023-12-02 20:10:19 24 4
gpt4 key购买 nike

开始在Amazon EMR上使用Cascading,并设法使其运行但以一个相当简单的障碍下降,而我希望有人能对此有所了解。

我的代码:

import java.util.Properties;

import cascading.flow.Flow;
import cascading.flow.FlowDef;
import cascading.flow.hadoop.HadoopFlowConnector;
import cascading.pipe.Pipe;
import cascading.property.AppProps;
import cascading.scheme.hadoop.TextLine;
import cascading.tap.Tap;
import cascading.tap.hadoop.Hfs;
import cascading.tuple.Fields;
import cascading.operation.regex.RegexParser;
import cascading.pipe.Each;
import cascading.tap.SinkMode;

public class Main
{
public static void
main( String[] args )
{
String inPath = args[ 0 ];
String outPath = args[ 1 ];

Properties properties = new Properties();
AppProps.setApplicationJarClass( properties, Main.class );
HadoopFlowConnector flowConnector = new HadoopFlowConnector( properties );

// create the source tap
TextLine sourceScheme = new TextLine(new Fields("line"));
Tap inTap = new Hfs( sourceScheme, inPath );

// create the sink tap
TextLine sinkScheme = new TextLine( new Fields("custid", "movieids"));
Tap outTap = new Hfs( sinkScheme, outPath, SinkMode.REPLACE );

Fields filmFields = new Fields("custid", "movieids");

String filmRegex = "([0-9]:*[,.]*)";

RegexParser parser = new RegexParser(filmFields, filmRegex);

Pipe importPipe = new Each("import", new Fields("line"), parser, Fields.RESULTS );

// connect the taps, pipes, etc., into a flow
Flow parsedFlow = new HadoopFlowConnector(properties).connect(inTap, outTap, importPipe);

// run the flow
parsedFlow.start();
parsedFlow.complete();
}
}

我的输入(无空行):

1:2

2:4

5:1

3:9

我的输出:
Task TASKID="task_201305241444_0003_m_000000" TASK_TYPE="MAP" TASK_STATUS="FAILED" FINISH_TIME="1369408133954" ERROR="cascading\.tuple\.TupleException: operation added the wrong number of fields, expected: ['custid', 'movieids'], got result size: 1
at cascading\.tuple\.TupleEntryCollector\.add(TupleEntryCollector\.java:82)
at cascading\.operation\.regex\.RegexParser\.onFoundGroups(RegexParser\.java:168)
at cascading\.operation\.regex\.RegexParser\.operate(RegexParser\.java:151)
at cascading\.flow\.stream\.FunctionEachStage\.receive(FunctionEachStage\.java:99)
at cascading\.flow\.stream\.FunctionEachStage\.receive(FunctionEachStage\.java:39)
at cascading\.flow\.stream\.SourceStage\.map(SourceStage\.java:102)
at cascading\.flow\.stream\.SourceStage\.run(SourceStage\.java:58)
at cascading\.flow\.hadoop\.FlowMapper\.run(FlowMapper\.java:127)
at org\.apache\.hadoop\.mapred\.MapTask\.runOldMapper(MapTask\.java:441)
at org\.apache\.hadoop\.mapred\.MapTask\.run(MapTask\.java:377)
at org\.apache\.hadoop\.mapred\.Child$4\.run(Child\.java:255)
at java\.security\.AccessController\.doPrivileged(Native Method)
at javax\.security\.auth\.Subject\.doAs(Subject\.java:396)
at org\.apache\.hadoop\.security\.UserGroupInformation\.doAs(UserGroupInformation\.java:1132)
at org\.apache\.hadoop\.mapred\.Child\.main(Child\.java:249)

reg ex在 http://regexpal.com/处罚款

非常感谢

邓肯

最佳答案

您会得到一个异常(exception),因为您的正则表达式产生一个结果,其中两个结果字段除外(即“custid”和“movieids”),因为正则表达式仅包含一个组(...)。

如果只想在冒号处分割,则可以使用带有两个组的表达式,例如:

String filmRegex = "(\\d):(\\d)";

\d+,如果您的数字可以超过一位。

或者,更容易地,使用 TextDelimited输入方案从文件中读取数据时,只需将输入数据自动拆分到其字段中即可:
Scheme sourceScheme = new TextDelimited(new Fields("custid", "movieids"), ":");

关于regex - 级联-正则表达式解析器-错​​误的字段数,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/16738794/

24 4 0
Copyright 2021 - 2024 cfsdn All Rights Reserved 蜀ICP备2022000587号
广告合作:1813099741@qq.com 6ren.com