Nice, it'd be great if someone finally implemented this :)
On Wed, Apr 1, 2015 at 10:10 PM, Szehon Ho <sze...@cloudera.com> wrote: > From Hive side, there has been some thought on the subject here: > https://cwiki.apache.org/confluence/display/Hive/Theta+Join, it has some > ideas but nobody has gotten around to giving it a try. It might be of > interest. > > Thanks > Szehon > > > On Wed, Apr 1, 2015 at 10:05 PM, Lefty Leverenz <leftylever...@gmail.com> > wrote: > >> D'oh! Thanks Chao. >> >> -- Lefty >> >> On Thu, Apr 2, 2015 at 12:59 AM, Chao Sun <c...@cloudera.com> wrote: >> >> > Hey Lefty, >> > >> > You need to use the ftp protocol, not http. >> > After clicking the link, you'll need to remove "http://"; from the >> address >> > bar. >> > >> > Best, >> > Chao >> > >> > On Wed, Apr 1, 2015 at 9:41 PM, Lefty Leverenz <leftylever...@gmail.com> >> > wrote: >> > >> > > Andrés, I followed that link and got the dread 404 Not Found: >> > > >> > > "The requested URI /pub/torres/Hiperfuse/extended_hiperfuse.pdf was not >> > > found on this server." >> > > >> > > -- Lefty >> > > >> > > On Wed, Apr 1, 2015 at 7:23 PM, <andres.qui...@parc.com> wrote: >> > > >> > > > Dear Lefty, >> > > > >> > > > Thank you very much for pointing that out and for your initial >> > pointers. >> > > > Here is the missing link: >> > > > >> > > > ftp.parc.com/pub/torres/Hiperfuse/extended_hiperfuse.pdf >> > > > >> > > > Regards, >> > > > >> > > > Andrés >> > > > >> > > > -----Original Message----- >> > > > From: Lefty Leverenz [mailto:leftylever...@gmail.com] >> > > > Sent: Wednesday, April 01, 2015 12:48 AM >> > > > To: dev@hive.apache.org >> > > > Subject: Re: Request for feedback on work intent for non-equijoin >> > support >> > > > >> > > > Hello Andres, the link to your paper is missing: >> > > > >> > > > In our preliminary work, which you can find here (pointer to the >> paper) >> > > ... >> > > > >> > > > >> > > > You can find general information about contributing to Hive in the >> > > > wiki: Resources >> > > > for Contributors >> > > > < >> > > > >> > > >> > >> https://cwiki.apache.org/confluence/display/Hive/Home#Home-ResourcesforContributors >> > > > > >> > > > , How to Contribute >> > > > <https://cwiki.apache.org/confluence/display/Hive/HowToContribute>. >> > > > >> > > > -- Lefty >> > > > >> > > > On Tue, Mar 31, 2015 at 10:42 PM, <andres.qui...@parc.com> wrote: >> > > > >> > > > > Dear Hive development community members, >> > > > > >> > > > > >> > > > > >> > > > > I am interested in learning more about the current support for >> > > > > non-equijoins in Hive and/or other Hadoop SQL engines, and in >> getting >> > > > > feedback about community interest in more extensive support for >> such >> > a >> > > > > feature. I intend to work on this challenge, assuming people find >> it >> > > > > compelling, and I intend to contribute results to the community. >> > Where >> > > > > possible, it would be great to receive feedback and engage in >> > > > > collaborations along the way (for a bit more context, see the >> > > > > postscript of this message). >> > > > > >> > > > > >> > > > > >> > > > > My initial goal is to support query conditions such as the >> following: >> > > > > >> > > > > >> > > > > >> > > > > A.x < B.y >> > > > > >> > > > > A.x in_range [B.y, B.z] >> > > > > >> > > > > distance(A.x, B.y) < D >> > > > > >> > > > > >> > > > > >> > > > > where A and B are distinct tables/files. It is my understanding >> that >> > > > > current support for performing non-equijoins like those above is >> > quite >> > > > > limited, and where some forms are supported (like in Cloudera's >> > > > > Impala), this support is based on doing a potentially expensive >> cross >> > > > product join. >> > > > > Depending on the data types involved, I believe that joins with >> these >> > > > > conditions can be made to be tractable (at least on the average) >> with >> > > > > join algorithms that exploit properties of the data types, possibly >> > > > > with some pre-scanning of the data. >> > > > > >> > > > > >> > > > > >> > > > > I am asking for feedback on the interest & need in the community >> for >> > > > > this work, as well as any pointers to similar work. In particular, >> I >> > > > > would appreciate any answers people could give on the following >> > > > questions: >> > > > > >> > > > > >> > > > > >> > > > > - Is my understanding of the state of the art in Hive and similar >> > > > > tools accurate? Are there groups currently working on similar or >> > > > > related issues, or tools that already accomplish some or all of >> what >> > I >> > > > have proposed? >> > > > > >> > > > > - Is there significant value to the community in the support of >> such >> > a >> > > > > feature? In other words, are the manual workarounds necessary >> because >> > > > > of the absence of non-equijoins such as these enough of a pain to >> > > > > justify the work I propose? >> > > > > >> > > > > - Being aware that the potential pre-scanning adds to the cost of >> the >> > > > > join, and that data could still blow-up in the worst case, am I >> > > > > missing any other important considerations and tradeoffs for this >> > > > problem? >> > > > > >> > > > > - What would be a good avenue to contribute this feature to the >> > > > > community (e.g. as a standalone tool on top of Hadoop, or as a Hive >> > > > > extension or plugin)? >> > > > > >> > > > > - What is the best way to get started in working with the >> community? >> > > > > >> > > > > >> > > > > >> > > > > Thanks for your attention and any info you can provide! >> > > > > >> > > > > >> > > > > >> > > > > Andres Quiroz >> > > > > >> > > > > >> > > > > >> > > > > P.S. If you are interested in some context, and why/how I am >> > proposing >> > > > > to do this work, please read on. >> > > > > >> > > > > >> > > > > >> > > > > I am part of a small project team at PARC working on the general >> > > > > problems of data integration and automated ETL. We have proposed a >> > > > > tool called HiperFuse that is designed to accept declarative, >> > > > > high-level queries in order to produce joined (fused) data sets >> from >> > > > > multiple heterogeneous raw data sources. In our preliminary work, >> > > > > which you can find here (pointer to the paper), we designed the >> > > > > architecture of the tool and obtained some results separately on >> the >> > > > > problems of automated data cleansing, data type inference, and >> query >> > > > > planning. One of the planned prototype implementations of HiperFuse >> > > > > relies on Hadoop MR, and because the declarative language we >> proposed >> > > > > was closely related to SQL, we thought that we could exploit the >> > > > > existing work in Hive and/or other open-source tools for handling >> the >> > > > > SQL part and layer our work on top of that. For example, the query >> > > > > given in the paper could easily be expressed in SQL-like form with >> a >> > > > > non-equijoin >> > > > > condition: >> > > > > >> > > > > >> > > > > >> > > > > SELECT web_access_log.ip, census.income >> > > > > >> > > > > FROM web_access_log, ip2zip, census >> > > > > >> > > > > WHERE web_access_log.ip in_range [ip2zip.ip_low, ip2zip.ip_high] >> > > > > >> > > > > AND ip2zip.zip = census.zip >> > > > > >> > > > > >> > > > > >> > > > > As you can see, the first impasse that we hit in order to bring the >> > > > > elements together to solve this query end-to-end was the >> realization >> > > > > and performance of the non-equality join in the query. The intent >> now >> > > > > is to tackle this problem in a general sense and provide a solution >> > > > > for a wide range of queries. >> > > > > >> > > > > >> > > > > >> > > > > The work I propose to do would be based on three main components >> > > > > within >> > > > > HiperFuse: >> > > > > >> > > > > >> > > > > >> > > > > - Enhancements to the extensible data type framework in HiperFuse >> > that >> > > > > would categorize data types based on the properties needed to >> support >> > > > > the join algorithms, in order to write join-ready domain-specific >> > data >> > > > > type libraries. >> > > > > >> > > > > - The join algorithms themselves, based on Hive or directly on >> Hadoop >> > > MR. >> > > > > >> > > > > - A query planner, which would determine the right algorithm to >> apply >> > > > > and automatically schedule any necessary pre-scanning of the data. >> > > > > >> > > > > >> > > > > >> > > > >> > > >> > >> > >> > >> > -- >> > Best, >> > Chao >> > >>
