I am a little surprised by the very positive reception to Gandiva (which doubtless is very useful - I know very little about it) versus when I brought up the prospect of using oamap ( https://github.com/diana-hep/oamap ) on this mailing list.
oamap uses numba to compile *python* functions at run-time and can walk complex nested schema down to leaf nodes in native python syntax (for-loops and attribute/item lookup) but at full machine speed, and without materialising any objects along the way. It was written for the ROOT format, but has implementations for simple types in parquet and arrow, which each do the nested lists and dict things similarly but differently. Would someone care to explain the silence over oamap? > On 25 Jun 2018, at 02:06, Praveen Kumar <prav...@dremio.com> wrote: > > Hi Everyone, > > I am Praveen, another engineer working on Gandiva. The interest and speed of > engagement around this is great !!Excited to engage with you folks on this. > > Thx. > > On 2018/06/22 18:09:42, Julian Hyde <j...@apache.org> wrote: >> This is exciting. We have wanted to build an Arrow adapter in Calcite for >> some time and have a prototype (see >> https://issues.apache.org/jira/browse/CALCITE-2173 >> <https://issues.apache.org/jira/browse/CALCITE-2173>) but I hope that we can >> use Gandiva. I know that Gandiva has Java bindings, but will these allow >> queries to be compiled and executed from a pure Java process?> >> >> Can you describe Gandiva’s governance model? Without an open governance >> model, companies that compete with Dremio may be wary about contributing.> >> >> Can you compare and contrast your approach to Hyper[1]? Hyper is also >> concerned with efficient use to the bus, and also uses LLVM, but it has a >> different memory format and places much emphasis on lock-free data >> structures.> >> >> I just attended SIGMOD and there were interesting industry papers from >> MemSQL[2][3] and Oracle RAPID[4]. I was impressed with some of the tricks >> MemSQL uses to achieve SIMD parallelism on queries such as “select k4, >> sum(x) from t group by k4” (where k4 has 4 values).> >> >> I missed part of the RAPID talk, but I got the impression that they are >> using disk-based algorithms (e.g. hybrid hash join) to handle data spread >> between fast and slow memory.> >> >> MemSQL uses TPC-H query 1 as a motivating benchmark and I think this would >> be good target for Gandiva also. It is a table scan with a range filter >> (returning 98% of rows), a low-cardinality aggregate (grouping by two fields >> with 3 values each), and several aggregate functions, the arguments of which >> contain common sub-expressions.> >> >> SELECT> >> l_returnflag,> >> l_linestatus,> >> sum(l_quantity),> >> sum(l_extendedprice),> >> sum(l_extendedprice * (1 - l_discount)),> >> sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)),> >> avg(l_quantity),> >> avg(l_extendedprice),> >> avg(l_discount),> >> count(*)> >> FROM lineitem> >> WHERE l_shipdate <= date '1998-12-01' - interval '90’ day> >> GROUP BY> >> l_returnflag,> >> l_linestatus> >> ORDER BY> >> l_returnflag,> >> l_linestatus;> >> >> Julian> >> >> [1] http://www.vldb.org/pvldb/vol4/p539-neumann.pdf >> <http://www.vldb.org/pvldb/vol4/p539-neumann.pdf>> >> >> [2] >> http://blog.memsql.com/how-careful-engineering-lead-to-processing-over-a-trillion-rows-per-second/ >> >> <http://blog.memsql.com/how-careful-engineering-lead-to-processing-over-a-trillion-rows-per-second/>> >> >> >> [3] https://dl.acm.org/citation.cfm?id=3183713.3190658 >> <https://dl.acm.org/citation.cfm?id=3183713.3190658>> >> >> [4] https://dl.acm.org/citation.cfm?id=3183713.3190655 >> <https://dl.acm.org/citation.cfm?id=3183713.3190655>> >> >>> On Jun 22, 2018, at 7:22 AM, ravind...@gmail.com wrote:> >>>> >>> Hi everyone,> >>>> >>> I'm Ravindra and I'm a developer on the Gandiva project. I do believe that >>> the combination of arrow and llvm for efficient expression evaluation is >>> powerful, and has a broad range of use-cases. We've just started and hope >>> to finesse and add a lot of functionality over the next few months.> >>>> >>> Welcome your feedback and participation in gandiva !!> >>>> >>> thanks & regards,> >>> ravindra.> >>>> >>> On 2018/06/21 19:15:20, Jacques Nadeau <ja...@apache.org> wrote: > >>>> Hey Guys,> >>>>> >>>> Dremio just open sourced a new framework for processing data in Arrow >>>> data> >>>> structures [1], built on top of the Apache Arrow C++ APIs and leveraging> >>>> LLVM (Apache licensed). It also includes Java APIs that leverage the >>>> Apache> >>>> Arrow Java libraries. I expect the developers who have been working on >>>> this> >>>> will introduce themselves soon. To read more about it, take a look at our> >>>> Ravindra's blog post (he's the lead developer driving this work): [2].> >>>> Hopefully people will find this interesting/useful.> >>>>> >>>> Let us know what you all think!> >>>>> >>>> thanks,> >>>> Jacques> >>>>> >>>>> >>>> [1] https://github.com/dremio/gandiva> >>>> [2] >>>> https://www.dremio.com/announcing-gandiva-initiative-for-apache-arrow/> >>>>> >> — Martin Durant martin.dur...@utoronto.ca
