我有以下 pig 脚本,它使用 grunt shell 完美运行(将结果存储到 HDFS 没有任何问题);但是,如果我使用 Java EmbeddedPig 运行相同的脚本,最后一个作业 (ORDER BY) 会失败。如果我将 ORDER BY 作业替换为其他作业,例如 GROUP 或 FOREACH GENERATE,则整个脚本将在 Java EmbeddedPig 中成功运行。所以我认为是 ORDER BY 导致了这个问题。有人有这方面的经验吗?任何帮助将不胜感激!
Pig 脚本:
REGISTER pig-udf-0.0.1-SNAPSHOT.jar;
user_similarity = LOAD '/tmp/sample-sim-score-results-31/part-r-00000' USING PigStorage('\t') AS (user_id: chararray, sim_user_id: chararray, basic_sim_score: float, alt_sim_score: float);
simplified_user_similarity = FOREACH user_similarity GENERATE $0 AS user_id, $1 AS sim_user_id, $2 AS sim_score;
grouped_user_similarity = GROUP simplified_user_similarity BY user_id;
ordered_user_similarity = FOREACH grouped_user_similarity {
sorted = ORDER simplified_user_similarity BY sim_score DESC;
top = LIMIT sorted 10;
GENERATE group, top;
};
top_influencers = FOREACH ordered_user_similarity GENERATE com.aol.grapevine.similarity.pig.udf.AssignPointsToTopInfluencer($1, 10);
all_influence_scores = FOREACH top_influencers GENERATE FLATTEN($0);
grouped_influence_scores = GROUP all_influence_scores BY bag_of_topSimUserTuples::user_id;
influence_scores = FOREACH grouped_influence_scores GENERATE group AS user_id, SUM(all_influence_scores.bag_of_topSimUserTuples::points) AS influence_score;
ordered_influence_scores = ORDER influence_scores BY influence_score DESC;
STORE ordered_influence_scores INTO '/tmp/cc-test-results-1' USING PigStorage();
Pig 的错误日志:
12/04/05 10:00:56 INFO pigstats.ScriptState: Pig script settings are added to the job
12/04/05 10:00:56 INFO mapReduceLayer.JobControlCompiler: mapred.job.reduce.markreset.buffer.percent is not set, set to default 0.3
12/04/05 10:00:58 INFO mapReduceLayer.JobControlCompiler: Setting up single store job
12/04/05 10:00:58 INFO jvm.JvmMetrics: Cannot initialize JVM Metrics with processName=JobTracker, sessionId= - already initialized
12/04/05 10:00:58 INFO mapReduceLayer.MapReduceLauncher: 1 map-reduce job(s) waiting for submission.
12/04/05 10:00:58 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
12/04/05 10:00:58 INFO input.FileInputFormat: Total input paths to process : 1
12/04/05 10:00:58 INFO util.MapRedUtil: Total input paths to process : 1
12/04/05 10:00:58 INFO util.MapRedUtil: Total input paths (combined) to process : 1
12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Creating tmp-1546565755 in /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134-work-6955502337234509704 with rwxr-xr-x
12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Cached hdfs://localhost/tmp/temp1725960134/tmp-1546565755#pigsample_854728855_1333645258470 as /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755
12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Cached hdfs://localhost/tmp/temp1725960134/tmp-1546565755#pigsample_854728855_1333645258470 as /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755
12/04/05 10:00:58 WARN mapred.LocalJobRunner: LocalJobRunner does not support symlinking into current working dir.
12/04/05 10:00:58 INFO mapred.TaskRunner: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755 <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/pigsample_854728855_1333645258470
12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.jar.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.jar.crc
12/04/05 10:00:58 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.split.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.split.crc
12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.splitmetainfo.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.splitmetainfo.crc
12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/.job.xml.crc <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/.job.xml.crc
12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.jar <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.jar
12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.split <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.split
12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.splitmetainfo <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.splitmetainfo
12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Creating symlink: /var/lib/hadoop-0.20/cache/cchuang/mapred/staging/cchuang402164468/.staging/job_local_0004/job.xml <- /var/lib/hadoop-0.20/cache/cchuang/mapred/local/localRunner/job.xml
12/04/05 10:00:59 INFO mapred.Task: Using ResourceCalculatorPlugin : null
12/04/05 10:00:59 INFO mapred.MapTask: io.sort.mb = 100
12/04/05 10:00:59 INFO mapred.MapTask: data buffer = 79691776/99614720
12/04/05 10:00:59 INFO mapred.MapTask: record buffer = 262144/327680
12/04/05 10:00:59 WARN mapred.LocalJobRunner: job_local_0004
java.lang.RuntimeException: org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: file:/Users/cchuang/workspace/grapevine-rec/pigsample_854728855_1333645258470
at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.partitioners.WeightedRangePartitioner.setConf(WeightedRangePartitioner.java:139)
at org.apache.hadoop.util.ReflectionUtils.setConf(ReflectionUtils.java:62)
at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:117)
at org.apache.hadoop.mapred.MapTask$NewOutputCollector.<init>(MapTask.java:560)
at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:639)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:323)
at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:210)
Caused by: org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: file:/Users/cchuang/workspace/grapevine-rec/pigsample_854728855_1333645258470
at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.listStatus(FileInputFormat.java:231)
at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigFileInputFormat.listStatus(PigFileInputFormat.java:37)
at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.getSplits(FileInputFormat.java:248)
at org.apache.pig.impl.io.ReadToEndLoader.init(ReadToEndLoader.java:153)
at org.apache.pig.impl.io.ReadToEndLoader.<init>(ReadToEndLoader.java:115)
at org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.partitioners.WeightedRangePartitioner.setConf(WeightedRangePartitioner.java:112)
... 6 more
12/04/05 10:00:59 INFO filecache.TrackerDistributedCacheManager: Deleted path /var/lib/hadoop-0.20/cache/cchuang/mapred/local/archive/4334795313006396107_361978491_57907159/localhost/tmp/temp1725960134/tmp-1546565755
12/04/05 10:00:59 INFO mapReduceLayer.MapReduceLauncher: HadoopJobId: job_local_0004
12/04/05 10:01:04 INFO mapReduceLayer.MapReduceLauncher: job job_local_0004 has failed! Stop running all dependent jobs
12/04/05 10:01:04 INFO mapReduceLayer.MapReduceLauncher: 100% complete
12/04/05 10:01:04 ERROR pigstats.PigStatsUtil: 1 map reduce job(s) failed!
12/04/05 10:01:04 INFO pigstats.PigStats: Script Statistics:
HadoopVersion PigVersion UserId StartedAt FinishedAt Features
0.20.2-cdh3u3 0.8.1-cdh3u3 cchuang 2012-04-05 10:00:34 2012-04-05 10:01:04 GROUP_BY,ORDER_BY
Some jobs have failed! Stop running all dependent jobs
Job Stats (time in seconds):
JobId Maps Reduces MaxMapTime MinMapTIme AvgMapTime MaxReduceTime MinReduceTime AvgReduceTime Alias Feature Outputs
job_local_0001 0 0 0 0 0 0 0 0 all_influence_scores,grouped_user_similarity,simplified_user_similarity,user_similarity GROUP_BY
job_local_0002 0 0 0 0 0 0 0 0 grouped_influence_scores,influence_scores GROUP_BY,COMBINER
job_local_0003 0 0 0 0 0 0 0 0 ordered_influence_scores SAMPLER
Failed Jobs:
JobId Alias Feature Message Outputs
job_local_0004 ordered_influence_scores ORDER_BY Message: Job failed! Error - NA /tmp/cc-test-results-1,
Input(s):
Successfully read 0 records from: "/tmp/sample-sim-score-results-31/part-r-00000"
Output(s):
Failed to produce result in "/tmp/cc-test-results-1"
Counters:
Total records written : 0
Total bytes written : 0
Spillable Memory Manager spill count : 0
Total bags proactively spilled: 0
Total records proactively spilled: 0
Job DAG:
job_local_0001 -> job_local_0002,
job_local_0002 -> job_local_0003,
job_local_0003 -> job_local_0004,
job_local_0004
12/04/05 10:01:04 INFO mapReduceLayer.MapReduceLauncher: Some jobs have failed! Stop running all dependent jobs
最佳答案
确保 PIG_HOME 环境变量设置为 pig 安装。
关于hadoop - 使用 Java 运行 EmbeddedPig 时,Pig 脚本中的 ORDER BY 作业失败,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/10033131/
我正在学习如何使用Nokogiri,根据这段代码我遇到了一些问题:require'rubygems'require'mechanize'post_agent=WWW::Mechanize.newpost_page=post_agent.get('http://www.vbulletin.org/forum/showthread.php?t=230708')puts"\nabsolutepathwithtbodygivesnil"putspost_page.parser.xpath('/html/body/div/div/div/div/div/table/tbody/tr/td/div
总的来说,我对ruby还比较陌生,我正在为我正在创建的对象编写一些rspec测试用例。许多测试用例都非常基础,我只是想确保正确填充和返回值。我想知道是否有办法使用循环结构来执行此操作。不必为我要测试的每个方法都设置一个assertEquals。例如:describeitem,"TestingtheItem"doit"willhaveanullvaluetostart"doitem=Item.new#HereIcoulddotheitem.name.shouldbe_nil#thenIcoulddoitem.category.shouldbe_nilendend但我想要一些方法来使用
我有一个Ruby程序,它使用rubyzip压缩XML文件的目录树。gem。我的问题是文件开始变得很重,我想提高压缩级别,因为压缩时间不是问题。我在rubyzipdocumentation中找不到一种为创建的ZIP文件指定压缩级别的方法。有人知道如何更改此设置吗?是否有另一个允许指定压缩级别的Ruby库? 最佳答案 这是我通过查看rubyzip内部创建的代码。level=Zlib::BEST_COMPRESSIONZip::ZipOutputStream.open(zip_file)do|zip|Dir.glob("**/*")d
类classAprivatedeffooputs:fooendpublicdefbarputs:barendprivatedefzimputs:zimendprotecteddefdibputs:dibendendA的实例a=A.new测试a.foorescueputs:faila.barrescueputs:faila.zimrescueputs:faila.dibrescueputs:faila.gazrescueputs:fail测试输出failbarfailfailfail.发送测试[:foo,:bar,:zim,:dib,:gaz].each{|m|a.send(m)resc
很好奇,就使用rubyonrails自动化单元测试而言,你们正在做什么?您是否创建了一个脚本来在cron中运行rake作业并将结果邮寄给您?git中的预提交Hook?只是手动调用?我完全理解测试,但想知道在错误发生之前捕获错误的最佳实践是什么。让我们理所当然地认为测试本身是完美无缺的,并且可以正常工作。下一步是什么以确保他们在正确的时间将可能有害的结果传达给您? 最佳答案 不确定您到底想听什么,但是有几个级别的自动代码库控制:在处理某项功能时,您可以使用类似autotest的内容获得关于哪些有效,哪些无效的即时反馈。要确保您的提
假设我做了一个模块如下:m=Module.newdoclassCendend三个问题:除了对m的引用之外,还有什么方法可以访问C和m中的其他内容?我可以在创建匿名模块后为其命名吗(就像我输入“module...”一样)?如何在使用完匿名模块后将其删除,使其定义的常量不再存在? 最佳答案 三个答案:是的,使用ObjectSpace.此代码使c引用你的类(class)C不引用m:c=nilObjectSpace.each_object{|obj|c=objif(Class===objandobj.name=~/::C$/)}当然这取决于
我试图在一个项目中使用rake,如果我把所有东西都放到Rakefile中,它会很大并且很难读取/找到东西,所以我试着将每个命名空间放在lib/rake中它自己的文件中,我添加了这个到我的rake文件的顶部:Dir['#{File.dirname(__FILE__)}/lib/rake/*.rake'].map{|f|requiref}它加载文件没问题,但没有任务。我现在只有一个.rake文件作为测试,名为“servers.rake”,它看起来像这样:namespace:serverdotask:testdoputs"test"endend所以当我运行rakeserver:testid时
作为我的Rails应用程序的一部分,我编写了一个小导入程序,它从我们的LDAP系统中吸取数据并将其塞入一个用户表中。不幸的是,与LDAP相关的代码在遍历我们的32K用户时泄漏了大量内存,我一直无法弄清楚如何解决这个问题。这个问题似乎在某种程度上与LDAP库有关,因为当我删除对LDAP内容的调用时,内存使用情况会很好地稳定下来。此外,不断增加的对象是Net::BER::BerIdentifiedString和Net::BER::BerIdentifiedArray,它们都是LDAP库的一部分。当我运行导入时,内存使用量最终达到超过1GB的峰值。如果问题存在,我需要找到一些方法来更正我的代
我正在尝试使用ruby和Savon来使用网络服务。测试服务为http://www.webservicex.net/WS/WSDetails.aspx?WSID=9&CATID=2require'rubygems'require'savon'client=Savon::Client.new"http://www.webservicex.net/stockquote.asmx?WSDL"client.get_quotedo|soap|soap.body={:symbol=>"AAPL"}end返回SOAP异常。检查soap信封,在我看来soap请求没有正确的命名空间。任何人都可以建议我
关闭。这个问题是opinion-based.它目前不接受答案。想要改进这个问题?更新问题,以便editingthispost可以用事实和引用来回答它.关闭4年前。Improvethisquestion我想在固定时间创建一系列低音和高音调的哔哔声。例如:在150毫秒时发出高音调的蜂鸣声在151毫秒时发出低音调的蜂鸣声200毫秒时发出低音调的蜂鸣声250毫秒的高音调蜂鸣声有没有办法在Ruby或Python中做到这一点?我真的不在乎输出编码是什么(.wav、.mp3、.ogg等等),但我确实想创建一个输出文件。