Thanks for the help so much, Mike. I learned a lot from this discussion. So, the conclusion I learned from the discussion should be, since how/when JT merge counter in the middle of the process of a job is undefined and internal behavior, it is more reliable to read counter after the whole job completes? Agree?
regards, Lin On Sun, Oct 21, 2012 at 8:15 PM, Michael Segel <[email protected]>wrote: > > On Oct 21, 2012, at 1:45 AM, Lin Ma <[email protected]> wrote: > > Thanks for the detailed reply, Mike. Yes, my most confusion is resolved by > you. The last two questions (or comments) are used to confirm my > understanding is correct, > > - is it normal use case or best practices for a job to consume/read the > counters from previous completed job in an automatic way? I ask this > because I am not sure whether the most use case of counter is human read > and manual analysis, other then using another job to automatic consume the > counters? > > > Lin, > Every job has a set of counters to maintain job statistics. > This is specifically for human analysis and to help understand what > happened with your job. > It allows you to see how much data is read in by the job, how many records > processed to be measured against how long the job took to complete. It > also showed you how much data is written back out. > > In addition to this, a set of use cases for counters in Hadoop center on > quality control. Its normal to chain jobs together to form a job flow. > A typical use case for Hadoop is to pull data from various sources, > combine them and do some process on them, resulting in a data set that gets > sent to another system for visualization. > > In this use case, there are usually data cleansing and validation jobs. As > they run, its possible to track a number of defective records. At the end > of that specific job, from the ToolRunner, or whichever job class you used > to launch your job, you can then get these aggregated counters for the job > and determine if the process passed or failed. Based on this, you can exit > your program with either a success or failed flag. Job Flow control tools > like Oozie can capture this and then decide to continue or to stop and > alert an operator of an error. > > - I want to confirm my understanding is correct, when each task completes, > JT will aggregate/update the global counter values from the specific > counter values updated by the complete task, but never expose global > counters values until job completes? If it is correct, I am wondering why > JT doing aggregation each time when a task completes, other than doing a > one time aggregation when the job completes? Is there any design choice > reasons? thanks. > > > That's a good question. I haven't looked at the code, so I can't say > definitively when the JT performs its aggregation. However, as the job runs > and in process, we can look at the job tracker web page(s) and see the > counter summary. This would imply that there has to be some aggregation > occurring mid-flight. (It would be trivial to sum the list of counters > periodically to update the job statistics.) Note too that if the JT web > pages can show a counter, its possible to then write a monitoring tool that > can monitor the job while running and then kill the job mid flight if a > certain threshold of a counter is met. > > That is to say you could in theory write a monitoring process and watch > the counters. If lets say an error counter hits a predetermined threshold, > you could then issue a 'hadoop job -kill <job-id>' command. > > > regards, > Lin > > On Sat, Oct 20, 2012 at 3:12 PM, Michael Segel > <[email protected]>wrote: > >> >> On Oct 19, 2012, at 10:27 PM, Lin Ma <[email protected]> wrote: >> >> Thanks for the detailed reply Mike, I learned a lot from the discussion. >> >> - I just want to confirm with you that, supposing in the same job, when a >> specific task completed (and counter is aggregated in JT after the task >> completed from our discussion?), the other running task in the same job >> cannot get the updated counter value from the previous completed task? I am >> asking this because I am thinking whether I can use counter to share a >> global value between tasks. >> >> >> Yes that is correct. >> While I haven't looked at YARN (M/R 2.0) , M/R 1.x doesn't have an easy >> way for a task to query the job tracker. This might have changed in YARN >> >> - If so, what is the traditional use case of counter, only use counter >> values after the whole job completes? >> >> Yes the counters are used to provide data at the end of the job... >> >> BTW: appreciate if you could share me a few use cases from your >> experience about how counters are used. >> >> Well you have your typical job data like the number of records processed, >> total number of bytes read, bytes written... >> >> But suppose you wanted to do some quality control on your input. >> So you need to keep a track on the count of bad records. If this job is >> part of a process, you may want to include business logic in your job to >> halt the job flow if X% of the records contain bad data. >> >> Or your process takes input records and in processing them, they sort the >> records based on some characteristic and you want to count those sorted >> records as you processed them. >> >> For a more concrete example, the Illinois Tollway has these 'fast pass' >> lanes where cars equipped with RFID tags can have the tolls automatically >> deducted from their accounts rather than pay the toll manually each time. >> >> Suppose we wanted to determine how many cars in the 'Fast Pass' lanes are >> cheaters where they drive through the sensor and the sensor doesn't capture >> the RFID tag. (Note its possible that you have a false positive where the >> car has an RFID chip but doesn't trip the sensor.) Pushing the data in a >> map/reduce job would require the use of counters. >> >> Does that help? >> >> -Mike >> >> regards, >> Lin >> >> On Sat, Oct 20, 2012 at 5:05 AM, Michael Segel <[email protected] >> > wrote: >> >>> Yeah, sorry... >>> >>> I meant that if you were dynamically creating a counter foo in the >>> Mapper task, then each mapper would be creating their own counter foo. >>> As the job runs, these counters will eventually be sent up to the JT. >>> The job tracker would keep a separate counter for each task. >>> >>> At the end, the final count is aggregated from the list of counters for >>> foo. >>> >>> >>> I don't know how you can get a task to ask information from the Job >>> Tracker on how things are going in other tasks. That is what I meant that >>> you couldn't get information about the other counters or even the status of >>> the other tasks running in the same job. >>> >>> I didn't see anything in the APIs that allowed for that type of flow... >>> Of course having said that... someone pops up with a way to do just that. >>> ;-) >>> >>> >>> Does that clarify things? >>> >>> -Mike >>> >>> >>> On Oct 19, 2012, at 11:56 AM, Lin Ma <[email protected]> wrote: >>> >>> Hi Mike, >>> >>> Sorry I am a bit lost... As you are thinking faster than me. :-P >>> >>> From your this statement "It would make sense that the JT maintains a >>> unique counter for each task until the tasks complete." -- it seems each >>> task cannot see counters from each other, since JT maintains a unique >>> counter for each tasks; >>> >>> From your this comment "I meant that if a Task created and updated a >>> counter, a different Task has access to that counter. " -- it seems >>> different tasks could share/access the same counter. >>> >>> Appreciate if you could help to clarify a bit. >>> >>> regards, >>> Lin >>> >>> On Sat, Oct 20, 2012 at 12:42 AM, Michael Segel < >>> [email protected]> wrote: >>> >>>> >>>> On Oct 19, 2012, at 11:27 AM, Lin Ma <[email protected]> wrote: >>>> >>>> Hi Mike, >>>> >>>> Thanks for the detailed reply. Two quick questions/comments, >>>> >>>> 1. For "task", you mean a specific mapper instance, or a specific >>>> reducer instance? >>>> >>>> >>>> Either. >>>> >>>> 2. "However, I do not believe that a separate Task could connect with >>>> the JT and see if the counter exists or if it could get a value or even an >>>> accurate value since the updates are asynchronous." -- do you mean if a >>>> mapper is updating custom counter ABC, and another mapper is updating the >>>> same customer counter ABC, their counter values are updated independently >>>> by different mappers, and will not published (aggregated) externally until >>>> job completed successfully? >>>> >>>> I meant that if a Task created and updated a counter, a different Task >>>> has access to that counter. >>>> >>>> To give you an example, if I want to count the number of quality errors >>>> and then fail after X number of errors, I can't use Global counters to do >>>> this. >>>> >>>> regards, >>>> Lin >>>> >>>> On Fri, Oct 19, 2012 at 10:35 PM, Michael Segel < >>>> [email protected]> wrote: >>>> >>>>> As I understand it... each Task has its own counters and are >>>>> independently updated. As they report back to the JT, they update the >>>>> counter(s)' status. >>>>> The JT then will aggregate them. >>>>> >>>>> In terms of performance, Counters take up some memory in the JT so >>>>> while its OK to use them, if you abuse them, you can run in to issues. >>>>> As to limits... I guess that will depend on the amount of memory on >>>>> the JT machine, the size of the cluster (Number of TT) and the number of >>>>> counters. >>>>> >>>>> In terms of global accessibility... Maybe. >>>>> >>>>> The reason I say maybe is that I'm not sure by what you mean by >>>>> globally accessible. >>>>> If a task creates and implements a dynamic counter... I know that it >>>>> will eventually be reflected in the JT. However, I do not believe that a >>>>> separate Task could connect with the JT and see if the counter exists or >>>>> if >>>>> it could get a value or even an accurate value since the updates are >>>>> asynchronous. Not to mention that I don't believe that the counters are >>>>> aggregated until the job ends. It would make sense that the JT maintains a >>>>> unique counter for each task until the tasks complete. (If a task fails, >>>>> it >>>>> would have to delete the counters so that when the task is restarted the >>>>> correct count is maintained. ) Note, I haven't looked at the source code >>>>> so I am probably wrong. >>>>> >>>>> HTH >>>>> Mike >>>>> On Oct 19, 2012, at 5:50 AM, Lin Ma <[email protected]> wrote: >>>>> >>>>> Hi guys, >>>>> >>>>> I have some quick questions regarding to Hadoop counter, >>>>> >>>>> >>>>> - Hadoop counter (customer defined) is global accessible (for both >>>>> read and write) for all Mappers and Reducers in a job? >>>>> - What is the performance and best practices of using Hadoop >>>>> counters? I am not sure if using Hadoop counters too heavy, there will >>>>> be >>>>> performance downgrade to the whole job? >>>>> >>>>> regards, >>>>> Lin >>>>> >>>>> >>>>> >>>> >>>> >>> >>> >> >> > >
