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https://issues.apache.org/jira/browse/DERBY-6921?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15942357#comment-15942357
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Bryan Pendleton commented on DERBY-6921:
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Thank you for sharing your draft proposal with the development community, this
sort of open collaboration is precisely the approach we like to take in the
Open Source process. Since this project, and Apache as a whole, receive many
proposals, you should make sure that you give as complete and thorough a
proposal as you can.
In particular, I suggest you add any relevant information for the "Other
Commitments" section that is mentioned in the Apache template proposal:
https://community.apache.org/gsoc.html
You should also review the Google student guide, particularly the section where
it discusses the important elements of the proposal:
http://write.flossmanuals.net/gsocstudentguide/writing-a-proposal/
Lastly, you might want to read the Apache mentor's page which describe what
Apache is looking for in a proposal:
https://community.apache.org/mentee-ranking-process.html
Your proposal looks quite good to me, but I see no downside for you to take a
careful look at these other resources, and ensure that you are including all
those details in the proposal on the Google site, too, since it makes it easier
for people who may be reviewing your proposal to find it.
> How good is the Derby Query Optimizer, really
> ---------------------------------------------
>
> Key: DERBY-6921
> URL: https://issues.apache.org/jira/browse/DERBY-6921
> Project: Derby
> Issue Type: Improvement
> Components: SQL
> Reporter: Bryan Pendleton
> Priority: Minor
> Labels: database, gsoc2017, java, optimizer
> Original Estimate: 2,016h
> Remaining Estimate: 2,016h
>
> At the 2015 VLDB conference, a team led by Dr. Viktor Leis at Munich
> Technical University introduced a new benchmark suite for evaluating
> database query optimizers: http://www.vldb.org/pvldb/vol9/p204-leis.pdf
> The benchmark test suite is publically available:
> http://db.in.tum.de/people/sites/leis/qo/job.tgz
> The data set for running the benchmark is publically available:
> ftp://ftp.fu-berlin.de/pub/misc/movies/database/
> As part of Google Summer of Code 2017, I am volunteering to mentor
> a Summer of Code intern who is interested in using these tools to
> improve the Derby query optimizer.
> My suggestion for the overall process is this:
> 1) Acquire the benchmark tools, and the data set
> 2) Run the benchmark.
> 2a) Some of the benchmark queries may reveal bugs in Derby.
> For each such bug, we need to isolate the bug and fix it.
> 3) Once we are able to run the entire benchmark, we need to
> analyze the results.
> 3a) Some of the benchmark queries may reveal opportunities
> for Derby to improve the query plans that it chooses for
> various classes of queries (this is explained in detail in the
> VLDB paper and other information available at Dr. Leis's site)
> For each such improvement, we need to isolate the issue,
> report it as a separable improvement, and fix it (if we can)
> While the benchmark is an interesting exercise in and of itself,
> the overall goal of the project is to find-and-fix problems in the
> Derby query optimizer, specifically in the 3 areas which are
> the focus of the benchmark tool:
> 1) How good is the Derby cardinality estimator and when does
> it lead to slow queries?
> 2) How good it the Derby cost model, and how well is it guiding
> the overall query optimization process?
> 3) How large is the Derby enumerated plan space, and is it
> appropriately-sized?
> While other Derby issues have been filed against these questions
> in the past, the intent of this specific project is to use the concrete
> tools provided by the VLDB paper to make this effort rigorous and
> successful at making concrete improvements to the Derby query
> optimizer.
> If you are interested in pursuing this project, please take these
> considerations into mind:
> 1) This is NOT an introductory project. You must be quite familiar
> with DBMS systems, and with SQL, and in particular with
> cost-based query optimization. If terms such as "cardinality
> estimation", "correlated query predicates", or "bushy trees"
> aren't comfortable terms for you ,this probably isn't the
> project you're interested in.
> 2) If you are new to Derby, that is fine, but please take advantage
> of the extensive body of introductory material on Derby to
> become familiar with it: read the Derby Getting Started manual,
> download the software and follow the tutorials, read the documentation,
> download the source code and learn how to build and run the
> test suites, etc.
> 3) All I have presented here is an **outline** of the project. You will
> need to read the paper(s), study the benchmark queries, and
> propose a detailed plan for how to use this benchmark as a tool
> for improving the Derby query optimizer.
> If these sorts of tasks sound like exciting things to do, then please
> let us know!
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