I would suggest study spark ,flink,strom and based on your understanding and finding prepare your research paper.
May be you will invented new spark ☺ Regards, Vaquar khan On 16 Jul 2015 00:47, "Michael Segel" <msegel_had...@hotmail.com> wrote: > Silly question… > > When thinking about a PhD thesis… do you want to tie it to a specific > technology or do you want to investigate an idea but then use a specific > technology. > Or is this an outdated way of thinking? > > "I am doing my PHD thesis on large scale machine learning e.g Online > learning, batch and mini batch learning.” > > So before we look at technologies like Spark… could the OP break down a > more specific concept or idea that he wants to pursue? > > Looking at what Jorn said… > > Using machine learning to better predict workloads in terms of managing > clusters… This could be interesting… but is it enough for a PhD thesis, or > of interest to the OP? > > > On Jul 15, 2015, at 9:43 AM, Jörn Franke <jornfra...@gmail.com> wrote: > > Well one of the strength of spark is standardized general distributed > processing allowing many different types of processing, such as graph > processing, stream processing etc. The limitation is that it is less > performant than one system focusing only on one type of processing (eg > graph processing). I miss - and this may not be spark specific - some > artificial intelligence to manage a cluster, e.g. Predicting workloads, how > long a job may run based on previously executed similar jobs etc. > Furthermore, many optimizations you have do to manually, e.g. Bloom > filters, partitioning etc - if you find here as well some intelligence that > does this automatically based on previously executed jobs taking into > account that optimizations themselves change over time would be great... > You may also explore feature interaction > > Le mar. 14 juil. 2015 à 7:19, Shashidhar Rao <raoshashidhar...@gmail.com> > a écrit : > >> Hi, >> >> I am doing my PHD thesis on large scale machine learning e.g Online >> learning, batch and mini batch learning. >> >> Could somebody help me with ideas especially in the context of Spark and >> to the above learning methods. >> >> Some ideas like improvement to existing algorithms, implementing new >> features especially the above learning methods and algorithms that have not >> been implemented etc. >> >> If somebody could help me with some ideas it would really accelerate my >> work. >> >> Plus few ideas on research papers regarding Spark or Mahout. >> >> Thanks in advance. >> >> Regards >> > > >
