Hi Sidharth, As it has been explained, HDFS is not just a file system. It's a part of the Hadoop platform. To take advantage of HDFS you have to understand how Hadoop storage (HDFS) AND Yarn processing (say MapReduce) work all together to implements jobs and parallel processing. That says that you will have to rethink the design of your programs to take advantage of HDFS.
You may start with this kind of tutorial https://www.tutorialspoint.com/map_reduce/map_reduce_introduction.htm Then have a deeper read of the Hadoop documentation http://hadoop.apache.org/docs/r2.7.3/hadoop-mapreduce-client/hadoop-mapreduce-client-core/MapReduceTutorial.html Regards, Philippe On Sun, Apr 9, 2017 at 11:13 PM, daemeon reiydelle <[email protected]> wrote: > Readers ARE parallel processes, one per map task. There are defaults in > map phase, about how many readers there are for the input file(s). Default > is one mapper task block (or file, where any file is smaller than the hdfs > block size). There is no java framework per se for splitting up an file > (technically not so, but let's simplify, outside of your own custom code). > > > *.......* > > > > *Daemeon C.M. ReiydelleUSA (+1) 415.501.0198 <(415)%20501-0198>London > (+44) (0) 20 8144 9872 <+44%2020%208144%209872>* > > On Sun, Apr 9, 2017 at 2:50 AM, Sidharth Kumar < > [email protected]> wrote: > >> Thanks Tariq, It really helped me to understand but just one another >> doubt that if reading is not a parallel process then to ready a file of >> 100GB and hdfs block size is 128MB. It will take lot much to read the >> complete file but it's not the scenerio in the real time. And second >> question is write operations as well is sequential process ? And will every >> datanode have their own data streamer which listen to data queue to get the >> packets and create pipeline. So, can you kindly help me to get clear idea >> of hdfs read and write operations. >> >> Regards >> Sidharth >> >> On 08-Apr-2017 12:49 PM, "Mohammad Tariq" <[email protected]> wrote: >> >> Hi Sidhart, >> >> When you read data from HDFS using a framework, like MapReduce, blocks of >> a HDFS file are read in parallel by multiple mappers created in that >> particular program. Input splits to be precise. >> >> On the other hand if you have a standalone java program then it's just a >> single thread process and will read the data sequentially. >> >> >> On Friday, April 7, 2017, Sidharth Kumar <[email protected]> >> wrote: >> >>> Thanks for your response . But I dint understand yet,if you don't mind >>> can you tell me what do you mean by "*With Hadoop, the idea is to >>> parallelize the readers (one per block for the mapper) with processing >>> framework like MapReduce.*" >>> >>> And also how the concept of parallelize the readers will work with hdfs >>> >>> Thanks a lot in advance for your help. >>> >>> >>> Regards >>> Sidharth >>> >>> On 07-Apr-2017 1:04 PM, "Philippe Kernévez" <[email protected]> wrote: >>> >>> Hi Sidharth, >>> >>> The reads are sequential. >>> With Hadoop, the idea is to parallelize the readers (one per block for >>> the mapper) with processing framework like MapReduce. >>> >>> Regards, >>> Philippe >>> >>> >>> On Thu, Apr 6, 2017 at 9:55 PM, Sidharth Kumar < >>> [email protected]> wrote: >>> >>>> Hi Genies, >>>> >>>> I have a small doubt that hdfs read operation is parallel or sequential >>>> process. Because from my understanding it should be parallel but if I read >>>> "hadoop definitive guide 4" in anatomy of read it says "*Data is >>>> streamed from the datanode back **to the client, which calls read() >>>> repeatedly on the stream (step 4). When the end of the **block is >>>> reached, DFSInputStream will close the connection to the datanode, then >>>> find **the best datanode for the next block (step 5). This happens >>>> transparently to the client, **which from its point of view is just >>>> reading a continuous stream*." >>>> >>>> So can you kindly explain me how read operation will exactly happens. >>>> >>>> >>>> Thanks for your help in advance >>>> >>>> Sidharth >>>> >>>> >>> >>> >>> -- >>> Philippe Kernévez >>> >>> >>> >>> Directeur technique (Suisse), >>> [email protected] >>> +41 79 888 33 32 <+41%2079%20888%2033%2032> >>> >>> Retrouvez OCTO sur OCTO Talk : http://blog.octo.com >>> OCTO Technology http://www.octo.ch >>> >>> >>> >> >> -- >> >> >> [image: http://] >> >> Tariq, Mohammad >> about.me/mti >> [image: http://] >> <http://about.me/mti> >> >> >> >> > -- Philippe Kernévez Directeur technique (Suisse), [email protected] +41 79 888 33 32 Retrouvez OCTO sur OCTO Talk : http://blog.octo.com OCTO Technology http://www.octo.ch
