Hi Thanks for your comments. My driving point is instead of loading Hbase data entirely I want to process record by record lookup and that is best done in UDF or map function. I also would loved to do it in Spark but no production cluster yet here :(
@Franke: I do not have enough competency on coprocessors so I am not able to visualize the solution as you are suggesting, so it would be really helpful if you shed some more light to it? Best Ayan On Fri, Sep 4, 2015 at 1:44 AM, Tao Lu <taolu2...@gmail.com> wrote: > But I don't see how it works here with phoenix or hbase coprocessor. > Remember we are joining 2 big data sets here, one is the big file in HDFS, > and records in HBASE. The driving force comes from Hadoop cluster. > > > > > On Thu, Sep 3, 2015 at 11:37 AM, Jörn Franke <jornfra...@gmail.com> wrote: > >> If you use pig or spark you increase the complexity from an operations >> management perspective significantly. Spark should be seen from a platform >> perspective if it make sense. If you can do it directly with hbase/phoenix >> or only hbase coprocessor then this should be preferred. Otherwise you pay >> more money for maintenance and development. >> >> Le jeu. 3 sept. 2015 à 17:16, Tao Lu <taolu2...@gmail.com> a écrit : >> >>> Yes. Ayan, you approach will work. >>> >>> Or alternatively, use Spark, and write a Scala/Java function which >>> implements similar logic in your Pig UDF. >>> >>> Both approaches look similar. >>> >>> Personally, I would go with Spark solution, it will be slightly faster, >>> and easier if you already have Spark cluster setup on top of your hadoop >>> cluster in your infrastructure. >>> >>> Cheers, >>> Tao >>> >>> >>> On Thu, Sep 3, 2015 at 1:15 AM, ayan guha <guha.a...@gmail.com> wrote: >>> >>>> Thanks for your info. I am planning to implement a pig udf to do record >>>> look ups. Kindly let me know if this is a good idea. >>>> >>>> Best >>>> Ayan >>>> >>>> On Thu, Sep 3, 2015 at 2:55 PM, Jörn Franke <jornfra...@gmail.com> >>>> wrote: >>>> >>>>> >>>>> You may check if it makes sense to write a coprocessor doing an upsert >>>>> for you, if it does not exist already. Maybe phoenix for Hbase supports >>>>> this already. >>>>> >>>>> Another alternative, if the records do not have an unique Id, is to >>>>> put them into a text index engine, such as Solr or Elasticsearch, which >>>>> does in this case a fast matching with relevancy scores. >>>>> >>>>> >>>>> You can use also Spark and Pig there. However, I am not sure if Spark >>>>> is suitable for these one row lookups. Same holds for Pig. >>>>> >>>>> >>>>> Le mer. 2 sept. 2015 à 23:53, ayan guha <guha.a...@gmail.com> a >>>>> écrit : >>>>> >>>>> Hello group >>>>> >>>>> I am trying to use pig or spark in order to achieve following: >>>>> >>>>> 1. Write a batch process which will read from a file >>>>> 2. Lookup hbase to see if the record exists. If so then need to >>>>> compare incoming values with hbase and update fields which do not match. >>>>> Else create a new record. >>>>> >>>>> My questions: >>>>> 1. Is this a good use case for pig or spark? >>>>> 2. Is there any way to read hbase for each incoming record in pig >>>>> without writing map reduce code? >>>>> 3. In case of spark I think we have to connect to hbase for every >>>>> record. Is thr any other way? >>>>> 4. What is the best connector for hbase which gives this functionality? >>>>> >>>>> Best >>>>> >>>>> Ayan >>>>> >>>>> >>>>> >>>> >>>> >>>> -- >>>> Best Regards, >>>> Ayan Guha >>>> >>> >>> >>> >>> -- >>> ------------------------------------------------ >>> Thanks! >>> Tao >>> >> > > > -- > ------------------------------------------------ > Thanks! > Tao > -- Best Regards, Ayan Guha
