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https://issues.apache.org/jira/browse/SOLR-10317?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16019044#comment-16019044
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Vivek Narang commented on SOLR-10317:
-------------------------------------

Hi [~ichattopadhyaya], I hope you get well soon. Regarding my doubt (as 
mentioned in the fourth last comment), I have found out the cause of variation 
in performance. I am providing the details below. 

Concern: I have been noticing that there was a significant difference in the 
indexing (10000 documents) throughput (in documents/sec). Even for the same 
commit test executed at separate times, a significant difference in throughput 
was observed. Please see the following screenshot 
[http://162.243.101.83/Capture_Throughput_drop_reason.PNG]. I have marked the 
drops in throughput on the graph with red circles. You can observe the 
difference in throughput for example (322 - 263 doc/sec). This difference in 
throughput was reported by the system for the same commit id which was not 
making sense and should not be happening. After running a number of tests, I 
was able to pinpoint the cause of this abnormality in performance reporting. As 
guessed before this was a *memory issue*. The server that I am using has 
limited resources (2 GB RAM). I added more than 5GB of swap space. These 
specific drops (as marked on the graph with red circles), was happening when 
the test run required building the Solr server from fresh code before running 
the benchmark test. This additional activity (of building Solr from source) was 
causing the RAM to get utilized completely causing the OS to handle the 
situation with the swap space provided and this additional swap activity was 
causing the degradation in performance. Conclusion: I have figured out the 
cause of the abnormality in metric estimation and assume that with a suitable 
server (having required hardware resources), this abnormality in reporting will 
go away. Regards. 

> Solr Nightly Benchmarks
> -----------------------
>
>                 Key: SOLR-10317
>                 URL: https://issues.apache.org/jira/browse/SOLR-10317
>             Project: Solr
>          Issue Type: Task
>            Reporter: Ishan Chattopadhyaya
>              Labels: gsoc2017, mentor
>         Attachments: changes-lucene-20160907.json, 
> changes-solr-20160907.json, managed-schema, 
> Narang-Vivek-SOLR-10317-Solr-Nightly-Benchmarks.docx, 
> Narang-Vivek-SOLR-10317-Solr-Nightly-Benchmarks-FINAL-PROPOSAL.pdf, 
> solrconfig.xml
>
>
> Solr needs nightly benchmarks reporting. Similar Lucene benchmarks can be 
> found here, https://home.apache.org/~mikemccand/lucenebench/.
> Preferably, we need:
> # A suite of benchmarks that build Solr from a commit point, start Solr 
> nodes, both in SolrCloud and standalone mode, and record timing information 
> of various operations like indexing, querying, faceting, grouping, 
> replication etc.
> # It should be possible to run them either as an independent suite or as a 
> Jenkins job, and we should be able to report timings as graphs (Jenkins has 
> some charting plugins).
> # The code should eventually be integrated in the Solr codebase, so that it 
> never goes out of date.
> There is some prior work / discussion:
> # https://github.com/shalinmangar/solr-perf-tools (Shalin)
> # https://github.com/chatman/solr-upgrade-tests/blob/master/BENCHMARKS.md 
> (Ishan/Vivek)
> # SOLR-2646 & SOLR-9863 (Mark Miller)
> # https://home.apache.org/~mikemccand/lucenebench/ (Mike McCandless)
> # https://github.com/lucidworks/solr-scale-tk (Tim Potter)
> There is support for building, starting, indexing/querying and stopping Solr 
> in some of these frameworks above. However, the benchmarks run are very 
> limited. Any of these can be a starting point, or a new framework can as well 
> be used. The motivation is to be able to cover every functionality of Solr 
> with a corresponding benchmark that is run every night.
> Proposing this as a GSoC 2017 project. I'm willing to mentor, and I'm sure 
> [~shalinmangar] and [~markrmil...@gmail.com] would help here.



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