Thanks for your help On Thursday, November 17, 2016, Rudraneel chakraborty < [email protected]> wrote:
> Hi, > > For any kin of performance analysis, first determine the following > 1. How many topologies? > 2. What are the workload parameters (e.g. tuple arrival rate, number of > executors per component, size of each tuple) > 3. System environment ( Number of cores in each supervisor node, Available > RAM) > 4. What is the nature of the algorithm? Is it CPU intensive? > > > Next determine the performance metric. Usually, for storm it can be > average tuple processing latency/ throughput etc. > > Then you need to follow the factor at a time approach where you change one > workload parameter per experiment and measure the performance metric while > keeping others same. This will help you to identify the effect of each > parameter on the performance. > > > > > > > On Wed, Nov 16, 2016 at 4:46 PM, Matt Lowe <[email protected] > <javascript:_e(%7B%7D,'cvml','[email protected]');>> wrote: > >> Performance in what way? >> >> If you mean from the storm Twitter example, that is part of the business >> logic. It is a way of filtering. >> >> Best Regards >> Matthew Lowe >> >> On 16 Nov 2016, at 22:34, sam mohel <[email protected] >> <javascript:_e(%7B%7D,'cvml','[email protected]');>> wrote: >> >> Please .Is there any help ? >> >> On Wednesday, November 16, 2016, sam mohel <[email protected] >> <javascript:_e(%7B%7D,'cvml','[email protected]');>> wrote: >> >>> How can algoritm like" text similarity between tweets" affect on the >>> performance of storm topology ? >> >> > > > -- > >
