It all depends on the context and what is really meant by realtime. Impala (and other concurrent alternatives) are not listed among the tools you have tried. Maybe you should not focus only on batch frameworks for providing a realtime access? The results are not surprising.
Bertrand Dechoux On Thu, Jul 31, 2014 at 9:38 AM, Kumar, Deepak8 <deepak8.ku...@citi.com> wrote: > Hi, > > As far as I know, real time queries are only possible using HBase & > cloudera search. Hive would be a batch process, it is not real time. So > instead of tuning different parameters , may be you could look for > different architecture design so that you could use HBase. > > > > Regards, > > Deepak > > > > *From:* Natarajan, Prabakaran 1. (NSN - IN/Bangalore) [mailto: > prabakaran.1.natara...@nsn.com] > *Sent:* Thursday, July 31, 2014 3:32 AM > *To:* user@hadoop.apache.org > *Subject:* Hadoop Realtime Queries > > > > Hi > > > > I want to perform realtime query on HDFS data. I tried > hadoop/yarnt/hive, shark on spark, Tez, etc., > > But still I couldn’t get subsecond performance on the large data that I > have. > > I understand hadoop is not meant for this, but still want to achieve as > max as possible > > > > 1. How can we tune RHEL OS for this? > > 2. How can we tune yarn? > > 3. Is there is any stable framework like Tez which can perform much > better > > 4. Is there is any caching strategy that we can adopt? > > 5. Any articles related to this are welcome > > > > Thanks in Advance > > > > Prabakaran.N > > > > > > >
