I want response time below 3 seconds. And fyi I'm already using 32 cores. My cache is already full too and obviously same requests don't occur in my case.
On Fri 16 Aug, 2019, 11:47 AM Jörn Franke, <jornfra...@gmail.com> wrote: > How much response time do you require? > I think you have to solve the issue in your code by introducing higher > parallelism during calculation and potentially more cores. > > Maybe you can also precalculate what you do, cache it and use during > request the precalculated values. > > > Am 16.08.2019 um 05:08 schrieb Vignan Malyala <dsmsvig...@gmail.com>: > > > > Hi > > Any solution for this? Taking around 50 seconds to get response. > > > >> On Mon 12 Aug, 2019, 3:28 PM Vignan Malyala, <dsmsvig...@gmail.com> > wrote: > >> > >> Hi Doug / Walter, > >> > >> I'm just using this methodology. > >> PFB link of my sample code. > >> https://github.com/saaay71/solr-vector-scoring > >> > >> The only issue is speed of response for 1M records. > >> > >> On Mon, Aug 12, 2019 at 12:24 AM Walter Underwood < > wun...@wunderwood.org> > >> wrote: > >> > >>> tf.idf was invented because cosine similarity is too much computation. > >>> tf.idf gives similar results much, much faster than cosine distance. > >>> > >>> I would expect cosine similarity to be slow. I would also expect > >>> retrieving 1 million records to be slow. Doing both of those in one > minute > >>> is pretty good. > >>> > >>> As Kernighan and Paugher said in 1978, "Don’t diddle code to make it > >>> faster—find a better algorithm.” > >>> > >>> https://en.wikipedia.org/wiki/The_Elements_of_Programming_Style > >>> > >>> wunder > >>> Walter Underwood > >>> wun...@wunderwood.org > >>> http://observer.wunderwood.org/ (my blog) > >>> > >>>> On Aug 11, 2019, at 10:40 AM, Doug Turnbull < > >>> dturnb...@opensourceconnections.com> wrote: > >>>> > >>>> Hi Vignan, > >>>> > >>>> We need to see more details / code of what your query parser plugin > does > >>>> exactly with term vectors, we can't really help you without more > >>> details. > >>>> Is it open source? Can you share a minimal example that recreates the > >>>> problem? > >>>> > >>>> On Sun, Aug 11, 2019 at 1:19 PM Vignan Malyala <dsmsvig...@gmail.com> > >>> wrote: > >>>> > >>>>> Hi guys, > >>>>> > >>>>> I made my custom qparser plugin in Solr for scoring. The plugin only > >>> does > >>>>> cosine similarity of vectors for each record. I use term vectors > here. > >>>>> Results are fine! > >>>>> > >>>>> BUT, Solr response is very slow with term vectors. It takes around 55 > >>>>> seconds for each request for 1000000 records. > >>>>> How do I make it faster to get my results in ms ? > >>>>> Please respond soon as its lil urgent. > >>>>> > >>>>> Note: All my values are stored and indexed. I am not using Solr > Cloud. > >>>>> > >>>> > >>>> > >>>> -- > >>>> *Doug Turnbull **| CTO* | OpenSource Connections > >>>> <http://opensourceconnections.com>, LLC | 240.476.9983 > >>>> Author: Relevant Search <http://manning.com/turnbull> > >>>> This e-mail and all contents, including attachments, is considered to > be > >>>> Company Confidential unless explicitly stated otherwise, regardless > >>>> of whether attachments are marked as such. > >>> > >>> >
