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From Paul Rogers <par0...@yahoo.com.INVALID>
Subject Re: [DISCUSSION] current project state
Date Tue, 14 Aug 2018 20:25:38 GMT
I wonder if we should pop the discussion up a level? What goals should Drill have as an Apache
project?

Drill is a big data query engine, and shares that description with Impala, Presto, Hive and
(to some degree) Spark. Drill's adoption is currently lower than Impala or Spark. What unique
use cases can Drill address that are unserved (or under-served) by the Impala and Spark juggernauts?

To grow, Drill must define its sweet spot: what it does better than any other project. Let's
identify why organizations might want to use Drill rather than (or in addition to) the better-known
alternatives. Answer that, and we enter a virtuous cycle: organizations will adopt Drill because
it does things that other tools don't do (or do poorly). Some of those adopters will want
to contribute to Drill for new use cases, which will encourage more adoption.

Drill is like many other projects in their early years: one core vendor has graciously contributed
the bulk of the code. (Impala, Hadoop, Spark, Kudu and Kafka are other examples.) Naturally,
the work of the core team focuses on the specific needs of that vendor's customers. Ideally,
Drill would, like those other tools, gain sufficient adoption that many other organizations
contribute as well, broadening the set of supported use cases, and entering that virtuous
growth cycle, to everyone's benefit.


The core question: what does the community see as gaps in their big data stacks that Drill
can serve?

Thanks,

- Paul

 

    On Tuesday, August 14, 2018, 7:08:51 AM PDT, Arina Yelchiyeva <arina.yelchiyeva@gmail.com>
wrote:  
 
 1. Regarding Drill metastore, its under investigation, please follow up
with DRILL-6552.
2. UDFs: I would not say, it's that quit to write UDFs in Drill.
Definitely, it could have been done easier but even for current state we
have good manuals. Regarding adding support for different languages like
python, that would require full re-write on UDFs code handling, since Drill
heavily relies on Java source code when during UDFs initialization. Though
generally it's a good idea since, Hive, for example, supports Scala, Python
for UDFs.
3. Drill vs Arrow is the topic I heard since I have started working with
Drill. But so far nobody dared to tackle it. I would suspect Drill first
would have to contribute changes in Arrow to be able to migrate which could
be a show-stopper if Arrow community does not accept them.

On Tue, Aug 14, 2018 at 6:37 AM Charles Givre <cgivre@gmail.com> wrote:

> I’d like to weigh in here as well. As a long time user of Drill, I really
> would like to see more people using it and I think there are a few key
> aspects that could really help on that front.
>
> The first of which is the Arrow integration.  I’m not enough of a software
> engineer to understand all the internal details here, but as I understand
> it, the promise of Arrow is that many tools will share a common memory
> model and that it will be possible to transfer data from one tool to the
> other without having to serialize/deserialize the data.  In the data
> science community many of the major platforms, Python-pandas, R, and Spark
> are moving or have adopted Arrow.
> Drill’s strength is the ease that it can query many different data sources
> and if Drill were to adopt Arrow, I suspect that many people would adopt it
> as a part of a machine learning pipeline.  Just recently, I attempted to do
> some data manipulation using Spark, and couldn’t help but notice how
> difficult ti was in contrast with Drill. I’m sure this is a very complex
> task, but I do think that it could be worth it in the end.
>
> Secondly, I’d like to second Paul’s call to simplify the interfaces for
> UDFs, Format and ideally storage plugins.  A core strength of Drill is its
> extensibility and making it easier would be a great thing.  I was wondering
> whether it would be possible or even a good idea, to enable users to write
> UDFs in a scripting language such as python.
>
> Thirdly,
> i would really like to see us add more functionality to Drill.  @Arina,
> your work to build a storage plugin for ElasticSearch is really great and I
> think more capabilities like that are really needed.  I’d like to see a
> generic HTTP storage plugin, a storage plugin for Google Sheets,  If I can
> figure out how storage plugins work, I’ll gladly work on some of these.
>
> Just my .02.
> — C
>
>
>
>
>
> > On Aug 13, 2018, at 21:21, Paul Rogers <par0328@yahoo.com.INVALID>
> wrote:
> >
> > Hi Arina,
> >
> > Another topic would be whether/how to round out Drill's data model.
> Drill's scalar and nullable types are pretty solid. Great work was done
> recently for Decimal (though the old types still remain.) Good support is
> now available for nested types to do implicit joins to produce SQL-friendly
> flat records.
> > But, opportunities for improvement still remain. Date/Time has timezone
> issues. Union, List and Repeated List never quite worked. There are a few
> types identified in the code, but not implemented (dates with TZ, tiny
> ints, etc.) How should Drill bridge. the gap from arrays and maps (really,
> structs) on the one hand, and plain-old-relational ODBC/JDBC/BI tools on
> the other?
> >
> > Would be good to finalize the data types and their mapping to plain SQL:
> either keep a type and make it fully work if it has holes, or drop it.
> Unions and Lists are the messiest. They are incomplete in part, because
> they are trying to do the impossible: to predict the future well enough
> that Drill can handle columns with varying or ambiguous data types (that
> is, to handle schema changes.) Is there a better way to handle this issue
> (such as with metadata hints)? That is, rather than fight with conflicting
> types at run time, simply declare the common type in metadata so all
> operators and record batches agree on the type.
> >
> > And, of course, there is the lingering issue of Drill vectors vs. Arrow.
> Arrow did great work in metadata, but seems to have kept some of the
> awkward aspects of Drill's original memory model (lack of control over
> batch sizes, ability to fragment memory.) Might there be a resyncing of the
> two projects: Drill picks up Arrow's metadata and APIs, Arrow picks up
> Drill's memory improvements, such as the size-limiting "result set loader"
> framework.
> >
> > Big-picture issues such as this tend to get lost in the 2270 open Jira
> tickets. How might the project create some "theme" tickets (or Wiki pages
> or whatever) to help pull the main issues out of the wealth of detail in
> Jira?
> >
> > Thanks,
> > - Paul
> >
> >
> >
> >    On Monday, August 13, 2018, 11:07:39 AM PDT, Paul Rogers <
> par0328@yahoo.com> wrote:
> >
> > Hi Arina,
> >
> > Thanks for launching this discussion. A few minor suggestions.
> >
> > The developers have done a fantastic job stabilizing and improving
> Drill's core functionality. Now the opportunity is to expand the use cases
> for Drill so that it gets wider adoption within the community. Drill
> competes for mindshare with Impala, Presto, Hive, Spark and others. A key
> differentiator for Drill can be the ability to extend the core and
> integrate Drill into user applications. Of these tools, only Spark has a
> fully ostensible model. Can Drill provide some of the flexibility that has
> powered Spark to success?
> >
> > 1. You mentioned the metastore is under active investigation. Anything
> yet to share? Didn't see any activity on the JIRA ticket. Metadata is a key
> gap in Drill. Simply adding a Hive-like metastore would repeat the very
> errors that Drill was meant to address. Maybe we can toss around ideas for
> a metadata API that provides greater flexibility.
> >
> > 2. Users can extend the core with custom UDFs, storage engines, formats
> and so on. At present, the code to do this is rather hard to write, debug
> and maintain. Is there value in streamlining those interfaces so that a
> wider audience can extend Drill for their specific needs?
> >
> > 3. Similarly, we've seen interest in integrating Drill with other
> systems, which suggests an opportunity for improved APIs. Ability to
> associate options, defaults and restrictions with users. Ability to use the
> REST API for larger data sets and with stateful session options. And so on.
> >
> > Such extensions are best guided by user demands: what can Drill provide
> for production applications to enable simpler/faster/more complete
> integration?
> >
> > Thanks,
> >
> > - Paul
> >
> >
> >
> >    On Monday, August 13, 2018, 5:42:08 AM PDT, Arina Ielchiieva <
> arina@apache.org> wrote:
> >
> > Hi all,
> >
> > as a new PMC Chair I would like to thank users for choosing and using
> > Apache Drill and contributors /  committers for making improvements and
> > fixes. Recently Apache Drill 1.14 was released bundled up with many
> > improvements and new features. Please feel free to try it out and share
> > your experience. As always we would love to hear your success stories of
> > using Apache Drill.
> >
> > Also I encourage users to share any problems found in Drill, as well as
> any
> > suggestions for future improvements. Feel free to start discussion on the
> > mailing list and then file a Jira with the summary. Contributions are
> > always welcome: minor, major, doc improvements or grammar fixes. Just
> file
> > a Jira and open the PR. Do not hesitate to ping developers on the mailing
> > list if PR is not being timely reviewed.
> >
> > Latest project reports show:
> > Apache Drill project has healthy release schedule, each release includes
> > lots of features.
> > Mailing list (user / dev) are getting substantial support from the active
> > developers, including Stackoverflow and Twitter.
> > New committers are added on the steady basis.
> >
> > Overall project is growing and moving forward. There have been
> discussions
> > about Drill 2.0 last year and currently Drill metastore feature is under
> > active investigation which might the breaking change for 2.0.
> >
> > Please feel free to reply to this email with your comments / concerns /
> > ideas about current project state.
> >
> > Kind regards,
> > Arina
>
>  
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