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HBase >> mail # user >> Coprocessor end point vs MapReduce?


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Re: Coprocessor end point vs MapReduce?

To echo what Mike said about KISS, would you use triggers for a large
time-sensitive batch job in an RDBMS?  It's possible, but probably not.
Then you might want to think twice about using co-processors for such a
purpose with HBase.

On 10/17/12 9:50 PM, "Michael Segel" <[EMAIL PROTECTED]> wrote:

>Run your weekly job in a low priority fair scheduler/capacity scheduler
>queue.
>
>Maybe its just me, but I look at Coprocessors as a similar structure to
>RDBMS triggers and stored procedures.
>You need to restrain and use them sparingly otherwise you end up creating
>performance issues.
>
>Just IMHO.
>
>-Mike
>
>On Oct 17, 2012, at 8:44 PM, Jean-Marc Spaggiari
><[EMAIL PROTECTED]> wrote:
>
>> I don't have any concern about the time it's taking. It's more about
>> the load it's putting on the cluster. I have other jobs that I need to
>> run (secondary index, data processing, etc.). So the more time this
>> new job is taking, the less CPU the others will have.
>>
>> I tried the M/R and I really liked the way it's done. So my only
>> concern will really be the performance of the delete part.
>>
>> That's why I'm wondering what's the best practice to move a row to
>> another table.
>>
>> 2012/10/17, Michael Segel <[EMAIL PROTECTED]>:
>>> If you're going to be running this weekly, I would suggest that you
>>>stick
>>> with the M/R job.
>>>
>>> Is there any reason why you need to be worried about the time it takes
>>>to do
>>> the deletes?
>>>
>>>
>>> On Oct 17, 2012, at 8:19 PM, Jean-Marc Spaggiari
>>><[EMAIL PROTECTED]>
>>> wrote:
>>>
>>>> Hi Mike,
>>>>
>>>> I'm expecting to run the job weekly. I initially thought about using
>>>> end points because I found HBASE-6942 which was a good example for my
>>>> needs.
>>>>
>>>> I'm fine with the Put part for the Map/Reduce, but I'm not sure about
>>>> the delete. That's why I look at coprocessors. Then I figure that I
>>>> also can do the Put on the coprocessor side.
>>>>
>>>> On a M/R, can I delete the row I'm dealing with based on some criteria
>>>> like timestamp? If I do that, I will not do bulk deletes, but I will
>>>> delete the rows one by one, right? Which might be very slow.
>>>>
>>>> If in the future I want to run the job daily, might that be an issue?
>>>>
>>>> Or should I go with the initial idea of doing the Put with the M/R job
>>>> and the delete with HBASE-6942?
>>>>
>>>> Thanks,
>>>>
>>>> JM
>>>>
>>>>
>>>> 2012/10/17, Michael Segel <[EMAIL PROTECTED]>:
>>>>> Hi,
>>>>>
>>>>> I'm a firm believer in KISS (Keep It Simple, Stupid)
>>>>>
>>>>> The Map/Reduce (map job only) is the simplest and least prone to
>>>>> failure.
>>>>>
>>>>> Not sure why you would want to do this using coprocessors.
>>>>>
>>>>> How often are you running this job? It sounds like its going to be
>>>>> sporadic.
>>>>>
>>>>> -Mike
>>>>>
>>>>> On Oct 17, 2012, at 7:11 PM, Jean-Marc Spaggiari
>>>>> <[EMAIL PROTECTED]>
>>>>> wrote:
>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> Can someone please help me to understand the pros and cons between
>>>>>> those 2 options for the following usecase?
>>>>>>
>>>>>> I need to transfer all the rows between 2 timestamps to another
>>>>>>table.
>>>>>>
>>>>>> My first idea was to run a MapReduce to map the rows and store them
>>>>>>on
>>>>>> another table, and then delete them using an end point coprocessor.
>>>>>> But the more I look into it, the more I think the MapReduce is not a
>>>>>> good idea and I should use a coprocessor instead.
>>>>>>
>>>>>> BUT... The MapReduce framework guarantee me that it will run against
>>>>>> all the regions. I tried to stop a regionserver while the job was
>>>>>> running. The region moved, and the MapReduce restarted the job from
>>>>>> the new location. Will the coprocessor do the same thing?
>>>>>>
>>>>>> Also, I found the webconsole for the MapReduce with the number of
>>>>>> jobs, the status, etc. Is there the same thing with the
>>>>>>coprocessors?
>>>>>>
>>>>>> Are all coprocessors running at the same time on all regions, which
NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB