[ 
https://issues.apache.org/jira/browse/PIG-4345?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14229376#comment-14229376
 ] 

Rohini Palaniswamy commented on PIG-4345:
-----------------------------------------

Can you just add a order by in nested foreach instead? i.e

{code}
b =  foreach (group a all) {
 a1= ORDER a by name;
 generate FLATTEN(myfuncs.AppendIndex(a1));
}
{code}

> e2e test "RubyUDFs_13" fails because of the different result of "group a all" 
> in different engines like "spark", "mapreduce"
> ----------------------------------------------------------------------------------------------------------------------------
>
>                 Key: PIG-4345
>                 URL: https://issues.apache.org/jira/browse/PIG-4345
>             Project: Pig
>          Issue Type: Bug
>            Reporter: liyunzhang_intel
>            Assignee: liyunzhang_intel
>         Attachments: PIG-4345.patch
>
>
> RubyUDFs e2e scrip is on the line 3818 of nightly.conf : 
> {code}
>                     'num' => 13,
>                     'java_params' => ['-Dpig.accumulative.batchsize=5'],
>                     'pig' => q\
> register ':SCRIPTHOMEPATH:/ruby/morerubyudfs.rb' using jruby as myfuncs;
> a = load ':INPATH:/singlefile/studenttab10k' using PigStorage() as (name, 
> age:int, gpa:double);
> b = foreach (group a all) generate FLATTEN(myfuncs.AppendIndex(a));
> store b into ':OUTPATH:';\,
>                     'verify_pig_script' => q\
> register :FUNCPATH:/testudf.jar;
> a = load ':INPATH:/singlefile/studenttab10k' using PigStorage() as (name, 
> age:int, gpa:double);
> b = foreach (group a all) generate 
> FLATTEN(org.apache.pig.test.udf.evalfunc.AppendIndex(a));
> store b into ':OUTPATH:';\,
>                     },
>                 ]
>             },
> {code}
> RubyUDFs_13.pig tests ruby udf "AppendIndex" in "morerubyudfs.rb".  The 
> output is compared with verified script which use java udf 
> "org.apache.pig.test.udf.evalfunc.AppendIndex". The output of 
> "RubyUDFs_13.pig" is like following:
> If test file “studemttab10k” is 
> tom thompson  42      0.53
> nick johnson  34      0.47
> priscilla falkner     55      1.16
> the result in spark engine will be:
> tom thompson  42      0.53   1
> nick johnson  34      0.47   2
> priscilla falkner     55      1.16  3
> the result in mapreduce engine which verified script uses  will be 
> priscilla falkner     55      1.16  1
> nick johnson  34      0.47  2
> tom thompson  42      0.53  3
> The difference between the result in spark and mapreduce engine cause 
> RubyUDFs_13 e2e test failure .
> The root cause of the difference is because “group a all” has  different 
> result in different engines. 
>  In Spark engine, “group a all” :
> all { (tom thompson   42      0.53),( nick johnson    34      0.47),( 
> priscilla falkner       55      1.16)}
> In mapreduce engine , “group a all”:
> all {( priscilla falkner      55      1.16), ( nick johnson   34      
> 0.47),(tom thompson     42      0.53)}
> Using PIG-4345.patch, RubyUDF_13 e2e test passes.
> {code}
> {
>                     'num' => 13,
>                     'java_params' => ['-Dpig.accumulative.batchsize=5'],
>                     'pig' => q\
> register ':SCRIPTHOMEPATH:/ruby/morerubyudfs.rb' using jruby as myfuncs;
> a = load ':INPATH:/singlefile/studenttab10k' using PigStorage() as (name, 
> age:int, gpa:double);
> a1 = filter a by name == 'nick johnson';
> a2 = filter a1 by age == 34;
> b =  foreach (group a2 all) generate FLATTEN(myfuncs.AppendIndex(a2));
> store b into ':OUTPATH:';\,
>                     'verify_pig_script' => q\
> register :FUNCPATH:/testudf.jar;
> a = load ':INPATH:/singlefile/studenttab10k' using PigStorage() as (name, 
> age:int, gpa:double);
> a1 = filter a by name == 'nick johnson';
> a2 = filter a1 by age == 34;
> b =  foreach (group a2 all) generate 
> FLATTEN(org.apache.pig.test.udf.evalfunc.AppendIndex(a2));
> store b into ':OUTPATH:';\,
>                     },
>                 ]
>             },
> {code}
> using PIG-4345.patch, the result in spark and mapreduce engine will be:
> nick johnson  34      0.47  1



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

Reply via email to