Prashant, I just added the stackhere as comment to the opened jira.
Thanks for the help. -Rohini On Fri, Mar 23, 2012 at 12:46 PM, Prashant Kommireddi <[email protected]>wrote: > Rohini, it's fine even if you could reply with the stacktrace here. I can > add it to JIRA. > > Thanks, > Prashant > > On Thu, Mar 22, 2012 at 7:10 PM, Prashant Kommireddi <[email protected] > >wrote: > > > Rohini, > > > > Here is the JIRA. https://issues.apache.org/jira/browse/PIG-2610 > > > > Can you please post the stacktrace as a comment to it? > > > > Thanks, > > Prashant > > > > > > On Thu, Mar 22, 2012 at 2:37 PM, Jonathan Coveney <[email protected] > >wrote: > > > >> Rohini, > >> > >> In the meantime, something like the following should work: > >> > >> aw = LOAD 'input' using MyCustomLoader(); > >> > >> searches = FOREACH raw GENERATE > >> day, searchType, > >> FLATTEN(impBag) AS (adType, clickCount) > >> ; > >> > >> searches_2 = foreach searches generate *, ( adType == 'type1' ? > clickCount > >> : 0 ) as type1_clickCount, ( adType == 'type2' ? clickCount : 0 ) as > >> type2_clickCount; > >> > >> groupedSearches = GROUP searches_2 BY (day, searchType) PARALLEL 50; > >> counts = FOREACH groupedSearches{ > >> GENERATE > >> FLATTEN(group) AS (day, searchType), > >> COUNT(searches) numSearches, > >> SUM(clickCount) AS clickCountPerSearchType, > >> SUM(searches_2. type1_clickCount) AS type1ClickCount, > >> SUM(searches_2. type2_clickCount) AS type2ClickCount; > >> } > >> ; > >> > >> 2012/3/22 Rohini U <[email protected]> > >> > >> > Thanks Prashant, > >> > I am using Pig 0.9.1 and hadoop 0.20.205 > >> > > >> > Thanks, > >> > Rohini > >> > > >> > On Thu, Mar 22, 2012 at 1:27 PM, Prashant Kommireddi < > >> [email protected] > >> > >wrote: > >> > > >> > > This makes more sense, grouping and filter are on different > columns. I > >> > will > >> > > open a JIRA soon. > >> > > > >> > > What version of Pig and Hadoop are you using? > >> > > > >> > > Thanks, > >> > > Prashant > >> > > > >> > > On Thu, Mar 22, 2012 at 1:12 PM, Rohini U <[email protected]> > wrote: > >> > > > >> > > > Hi Prashant, > >> > > > > >> > > > Here is my script in full. > >> > > > > >> > > > > >> > > > raw = LOAD 'input' using MyCustomLoader(); > >> > > > > >> > > > searches = FOREACH raw GENERATE > >> > > > day, searchType, > >> > > > FLATTEN(impBag) AS (adType, clickCount) > >> > > > ; > >> > > > > >> > > > groupedSearches = GROUP searches BY (day, searchType) PARALLEL 50; > >> > > > counts = FOREACH groupedSearches{ > >> > > > type1 = FILTER searches BY adType == 'type1'; > >> > > > type2 = FILTER searches BY adType == 'type2'; > >> > > > GENERATE > >> > > > FLATTEN(group) AS (day, searchType), > >> > > > COUNT(searches) numSearches, > >> > > > SUM(clickCount) AS clickCountPerSearchType, > >> > > > SUM(type1.clickCount) AS type1ClickCount, > >> > > > SUM(type2.clickCount) AS type2ClickCount; > >> > > > } > >> > > > ; > >> > > > > >> > > > As you can see above, I am counting the counts by the day and > search > >> > type > >> > > > in clickCountPerSearchType and for each of them i need the counts > >> > broken > >> > > by > >> > > > the ad type. > >> > > > > >> > > > Thanks for your help! > >> > > > Thanks, > >> > > > Rohini > >> > > > > >> > > > > >> > > > On Thu, Mar 22, 2012 at 12:44 PM, Prashant Kommireddi > >> > > > <[email protected]>wrote: > >> > > > > >> > > > > Hi Rohini, > >> > > > > > >> > > > > From your query it looks like you are already grouping it by > >> TYPE, so > >> > > not > >> > > > > sure why you would want the SUM of, say "EMPLOYER" type in > >> "LOCATION" > >> > > and > >> > > > > vice-versa. Your output is already broken down by TYPE. > >> > > > > > >> > > > > Thanks, > >> > > > > Prashant > >> > > > > > >> > > > > On Thu, Mar 22, 2012 at 9:03 AM, Rohini U <[email protected]> > >> > wrote: > >> > > > > > >> > > > > > Thanks for the suggestion Prashant. However, that will not > work > >> in > >> > my > >> > > > > case. > >> > > > > > > >> > > > > > If I filter before the group and include the new field in > group > >> as > >> > > you > >> > > > > > suggested, I get the individual counts broken by the select > >> field > >> > > > > > critieria. However, I want the totals also without taking the > >> > select > >> > > > > fields > >> > > > > > into account. That is why I took the approach I described in > my > >> > > earlier > >> > > > > > emails. > >> > > > > > > >> > > > > > Thanks > >> > > > > > Rohini > >> > > > > > > >> > > > > > On Wed, Mar 21, 2012 at 5:02 PM, Prashant Kommireddi < > >> > > > > [email protected] > >> > > > > > >wrote: > >> > > > > > > >> > > > > > > Please pull your FILTER out of GROUP BY and do it earlier > >> > > > > > > http://pig.apache.org/docs/r0.9.1/perf.html#filter > >> > > > > > > > >> > > > > > > In this case, you could use a FILTER followed by a bincond > to > >> > > > > introduce a > >> > > > > > > new field "employerOrLocation", then do a group by and > include > >> > the > >> > > > new > >> > > > > > > field in the GROUP BY clause. > >> > > > > > > > >> > > > > > > Thanks, > >> > > > > > > Prashant > >> > > > > > > > >> > > > > > > On Wed, Mar 21, 2012 at 4:45 PM, Rohini U < > [email protected] > >> > > >> > > > wrote: > >> > > > > > > > >> > > > > > > > My input data size is 9GB and I am using 20 machines. > >> > > > > > > > > >> > > > > > > > My grouped criteria has two cases so I want 1) counts by > the > >> > > > > criteria I > >> > > > > > > > have grouped 2) counts of the two inviduals cases in each > >> of my > >> > > > > group. > >> > > > > > > > > >> > > > > > > > So my script in detail is: > >> > > > > > > > > >> > > > > > > > counts = FOREACH grouped { > >> > > > > > > > selectedFields1 = FILTER rawItems BY > >> > > > > > > type="EMPLOYER"; > >> > > > > > > > selectedFields2 = FILTER rawItems BY > >> > > > > > type="LOCATION"; > >> > > > > > > > GENERATE > >> > > > > > > > FLATTEN(group) as (item1, > item2, > >> > > item3, > >> > > > > > > type) , > >> > > > > > > > SUM(selectedFields1.count) > as > >> > > > > > > > selectFields1Count, > >> > > > > > > > SUM(selectedFields2.count) as > >> > > > > > > > selectFields2Count, > >> > > > > > > > COUNT(rawItems) as > >> > groupCriteriaCount > >> > > > > > > > > >> > > > > > > > } > >> > > > > > > > > >> > > > > > > > Is there a way way to do this? > >> > > > > > > > > >> > > > > > > > > >> > > > > > > > On Wed, Mar 21, 2012 at 4:29 PM, Dmitriy Ryaboy < > >> > > > [email protected]> > >> > > > > > > > wrote: > >> > > > > > > > > >> > > > > > > > > you are not doing grouping followed by counting. You are > >> > doing > >> > > > > > grouping > >> > > > > > > > > followed by filtering followed by counting. > >> > > > > > > > > Try filtering before grouping. > >> > > > > > > > > > >> > > > > > > > > D > >> > > > > > > > > > >> > > > > > > > > On Wed, Mar 21, 2012 at 12:34 PM, Rohini U < > >> > [email protected] > >> > > > > >> > > > > > wrote: > >> > > > > > > > > > >> > > > > > > > > > Hi, > >> > > > > > > > > > > >> > > > > > > > > > I have a pig script which does a simple GROUPing > >> followed > >> > by > >> > > > > > couting > >> > > > > > > > and > >> > > > > > > > > I > >> > > > > > > > > > get this error. My data is certaining not that big > for > >> it > >> > to > >> > > > > cause > >> > > > > > > > this > >> > > > > > > > > > out of memory error. Is there a chance that this is > >> because > >> > > of > >> > > > > some > >> > > > > > > > bug ? > >> > > > > > > > > > Did any one come across this kind of error before? > >> > > > > > > > > > > >> > > > > > > > > > I am using pig 0.9.1 with hadoop 0.20.205 > >> > > > > > > > > > > >> > > > > > > > > > My script: > >> > > > > > > > > > rawItems = LOAD 'in' as (item1, item2, item3, type, > >> count); > >> > > > > > > > > > > >> > > > > > > > > > grouped = GROUP rawItems BY (item1, item2, item3, > type); > >> > > > > > > > > > > >> > > > > > > > > > counts = FOREACH grouped { > >> > > > > > > > > > selectedFields = FILTER rawItems > BY > >> > > > > > > > type="EMPLOYER"; > >> > > > > > > > > > GENERATE > >> > > > > > > > > > FLATTEN(group) as (item1, > >> > item2, > >> > > > > item3, > >> > > > > > > > > type) , > >> > > > > > > > > > SUM(selectedFields.count) > >> as > >> > > count > >> > > > > > > > > > > >> > > > > > > > > > } > >> > > > > > > > > > > >> > > > > > > > > > Stack Trace: > >> > > > > > > > > > > >> > > > > > > > > > 2012-03-21 19:19:59,346 FATAL > >> > org.apache.hadoop.mapred.Child > >> > > > > > (main): > >> > > > > > > > > Error > >> > > > > > > > > > running child : java.lang.OutOfMemoryError: GC > overhead > >> > limit > >> > > > > > > exceeded > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POProject.getNext(POProject.java:387) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.PhysicalOperator.processInput(PhysicalOperator.java:290) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POFilter.getNext(POFilter.java:95) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.PhysicalOperator.getNext(PhysicalOperator.java:406) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POProject.processInputBag(POProject.java:570) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.PORelationToExprProject.getNext(PORelationToExprProject.java:107) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POProject.processInputBag(POProject.java:570) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POProject.getNext(POProject.java:248) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.PhysicalOperator.getNext(PhysicalOperator.java:316) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.processInput(POUserFunc.java:159) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.getNext(POUserFunc.java:184) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.getNext(POUserFunc.java:293) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POCast.getNext(POCast.java:453) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.PhysicalOperator.getNext(PhysicalOperator.java:324) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.processInput(POUserFunc.java:159) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.getNext(POUserFunc.java:184) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.expressionOperators.POUserFunc.getNext(POUserFunc.java:281) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.PhysicalOperator.getNext(PhysicalOperator.java:324) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POForEach.processPlan(POForEach.java:332) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POForEach.getNext(POForEach.java:284) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapReduce$Reduce.runPipeline(PigGenericMapReduce.java:459) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapReduce$Reduce.processOnePackageOutput(PigGenericMapReduce.java:427) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapReduce$Reduce.reduce(PigGenericMapReduce.java:407) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapReduce$Reduce.reduce(PigGenericMapReduce.java:261) > >> > > > > > > > > > at > >> > > > > org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:176) > >> > > > > > > > > > at > >> > > > > > > > > > > >> > > > > > > > >> > > > > >> org.apache.hadoop.mapred.ReduceTask.runNewReducer(ReduceTask.java:662) > >> > > > > > > > > > at > >> > > > > > > org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:425) > >> > > > > > > > > > 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:1059) > >> > > > > > > > > > at > >> > org.apache.hadoop.mapred.Child.main(Child.java:249) > >> > > > > > > > > > > >> > > > > > > > > > Thanks > >> > > > > > > > > > -Rohini > >> > > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > > >> > > > > > > > > >> > > > > > > > -- > >> > > > > > > > Regards > >> > > > > > > > -Rohini > >> > > > > > > > > >> > > > > > > > -- > >> > > > > > > > ** > >> > > > > > > > People of accomplishment rarely sat back & let things > >> happen to > >> > > > them. > >> > > > > > > They > >> > > > > > > > went out & happened to things - Leonardo Da Vinci > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > > >> > > >> > -- > >> > Regards > >> > -Rohini > >> > > >> > -- > >> > ** > >> > People of accomplishment rarely sat back & let things happen to them. > >> They > >> > went out & happened to things - Leonardo Da Vinci > >> > > >> > > > > >
