Boris et al, I put up a PR [1] to add ExecuteSQLRecord and QueryDatabaseTableRecord under NIFI-4517, in case anyone wants to play around with it :)
Regards, Matt [1] https://github.com/apache/nifi/pull/2945 On Tue, Aug 7, 2018 at 8:30 PM Boris Tyukin <bo...@boristyukin.com> wrote: > > Matt, you rock!! thank you!! > > On Tue, Aug 7, 2018 at 5:16 PM Matt Burgess <mattyb...@gmail.com> wrote: >> >> Sounds good, it makes the underlying code a bit more complicated but I see >> from y’all’s points that a “separate” processor is a better user experience. >> I’m knee deep in it as we speak, hope to have a PR up in a few days. >> >> Thanks, >> Matt >> >> >> On Aug 7, 2018, at 5:07 PM, Andrew Grande <apere...@gmail.com> wrote: >> >> I'd really like to see the Record suffix on the processor for >> discoverability, as already mentioned. >> >> Andrew >> >> On Tue, Aug 7, 2018, 2:16 PM Matt Burgess <mattyb...@apache.org> wrote: >>> >>> Yeah that's definitely doable, most of the logic for writing a >>> ResultSet to a Flow File is localized (currently to JdbcCommon but >>> also in ResultSetRecordSet), so I wouldn't think it would be too much >>> refactor. What are folks thoughts on whether to add a Record Writer >>> property to the existing ExecuteSQL or subclass it to a new processor >>> called ExecuteSQLRecord? The former is more consistent with how the >>> SiteToSite reporting tasks work, but this is a processor. The latter >>> is more consistent with the way we've done other record processors, >>> and the benefit there is that we don't have to add a bunch of >>> documentation to fields that will be ignored (such as the Use Avro >>> Logical Types property which we wouldn't need in a ExecuteSQLRecord). >>> Having said that, we will want to offer the same options in the Avro >>> Reader/Writer, but Peter is working on that under NIFI-5405 [1]. >>> >>> Thanks, >>> Matt >>> >>> [1] https://issues.apache.org/jira/browse/NIFI-5405 >>> >>> On Tue, Aug 7, 2018 at 2:06 PM Andy LoPresto <alopre...@apache.org> wrote: >>> > >>> > Matt, >>> > >>> > Would extending the core ExecuteSQL processor with an ExecuteSQLRecord >>> > processor also work? I wonder about discoverability if only one processor >>> > is present and in other places we explicitly name the processors which >>> > handle records as such. If the ExecuteSQL processor handled all the SQL >>> > logic, and the ExecuteSQLRecord processor just delegated most of the >>> > processing in its #onTrigger() method to super, do you foresee any >>> > substantial difficulties? It might require some refactoring of the parent >>> > #onTrigger() to service methods. >>> > >>> > >>> > Andy LoPresto >>> > alopre...@apache.org >>> > alopresto.apa...@gmail.com >>> > PGP Fingerprint: 70EC B3E5 98A6 5A3F D3C4 BACE 3C6E F65B 2F7D EF69 >>> > >>> > On Aug 7, 2018, at 10:25 AM, Andrew Grande <apere...@gmail.com> wrote: >>> > >>> > As a side note, one has to ha e a serious justification _not_ to use >>> > record-based processors. The benefits, including performance, are too >>> > numerous to call out here. >>> > >>> > Andrew >>> > >>> > On Tue, Aug 7, 2018, 1:15 PM Mark Payne <marka...@hotmail.com> wrote: >>> >> >>> >> Boris, >>> >> >>> >> Using a Record-based processor does not mean that you need to define a >>> >> schema upfront. This is >>> >> necessary if the source itself cannot provide a schema. However, since >>> >> it is pulling structured data >>> >> and the schema can be inferred from the database, you wouldn't need to. >>> >> As Matt was saying, your >>> >> Record Writer can simply be configured to Inherit Record Schema. It can >>> >> then write the schema to >>> >> the "avro.schema" attribute or you can choose "Do Not Write Schema". >>> >> This would still allow the data >>> >> to be written in JSON, CSV, etc. >>> >> >>> >> You could also have the Record Writer choose to write the schema using >>> >> the "avro.schema" attribute, >>> >> as mentioned above, and then have any down-stream processors read the >>> >> schema from this attribute. >>> >> This would allow you to use any record-oriented processors you'd like >>> >> without having to define the >>> >> schema yourself, if you don't want to. >>> >> >>> >> Thanks >>> >> -Mark >>> >> >>> >> >>> >> >>> >> On Aug 7, 2018, at 12:37 PM, Boris Tyukin <bo...@boristyukin.com> wrote: >>> >> >>> >> thanks for all the responses! it means I am not the only one interested >>> >> in this topic. >>> >> >>> >> Record-aware version would be really nice, but a lot of times I do not >>> >> want to use record-based processors since I need to define a schema for >>> >> input/output upfront and just want to run SQL query and get whatever >>> >> results back. It just adds an extra step that will be subject to >>> >> break/support. >>> >> >>> >> Similar to Kafka processors, it is nice to have an option of >>> >> record-based processor vs. message oriented processor. But if one >>> >> processor can do it all, it is even better :) >>> >> >>> >> >>> >> On Tue, Aug 7, 2018 at 9:28 AM Matt Burgess <mattyb...@apache.org> wrote: >>> >>> >>> >>> I'm definitely interested in supporting a record-aware version as well >>> >>> (I wrote the Jira up last year [1] but haven't gotten around to >>> >>> implementing it), however I agree with Peter's comment on the Jira. >>> >>> Since ExecuteSQL is an oft-touched processor, if we had two processors >>> >>> that only differed in how the output is formatted, it could be harder >>> >>> to maintain (bugs to be fixed in two places, e.g.). I think we should >>> >>> add an optional RecordWriter property to ExecuteSQL, and the >>> >>> documentation would reflect that if it is not set, the output will be >>> >>> Avro with embedded schema as it has always been. If the RecordWriter >>> >>> is set, either the schema can be hardcoded, or they can use "Inherit >>> >>> Record Schema" even though there's no reader, and that would mimic the >>> >>> current behavior where the schema is inferred from the database >>> >>> columns and used for the writer. There is precedence for this pattern >>> >>> in the SiteToSite reporting tasks. >>> >>> >>> >>> To Bryan's point about history, Avro at the time was the most >>> >>> descriptive of the solutions because it maintains the schema and >>> >>> datatypes with the data, unlike JSON, CSV, etc. Also before the record >>> >>> readers/writers, as Bryan said, you pretty much had to split, >>> >>> transform, merge. We just need to make that processor (and others with >>> >>> specific input/output formats) "record-aware" for better performance. >>> >>> >>> >>> Regards, >>> >>> Matt >>> >>> >>> >>> [1] https://issues.apache.org/jira/browse/NIFI-4517 >>> >>> On Tue, Aug 7, 2018 at 9:20 AM Bryan Bende <bbe...@gmail.com> wrote: >>> >>> > >>> >>> > I would also add that the pattern of splitting to 1 record per flow >>> >>> > file was common before the record processors existed, and generally >>> >>> > this can/should be avoided now in favor of processing/manipulating >>> >>> > records in place, and keeping them together in large batches. >>> >>> > >>> >>> > >>> >>> > >>> >>> > On Tue, Aug 7, 2018 at 9:10 AM, Andrew Grande <apere...@gmail.com> >>> >>> > wrote: >>> >>> > > Careful, that makes too much sense, Joe ;) >>> >>> > > >>> >>> > > >>> >>> > > On Tue, Aug 7, 2018, 8:45 AM Joe Witt <joe.w...@gmail.com> wrote: >>> >>> > >> >>> >>> > >> i think we just need to make an ExecuteSqlRecord processor. >>> >>> > >> >>> >>> > >> thanks >>> >>> > >> >>> >>> > >> On Tue, Aug 7, 2018, 8:41 AM Mike Thomsen <mikerthom...@gmail.com> >>> >>> > >> wrote: >>> >>> > >>> >>> >>> > >>> My guess is that it is due to the fact that Avro is the only >>> >>> > >>> record type >>> >>> > >>> that can match sql pretty closely feature to feature on data >>> >>> > >>> types. >>> >>> > >>> On Tue, Aug 7, 2018 at 8:33 AM Boris Tyukin >>> >>> > >>> <bo...@boristyukin.com> >>> >>> > >>> wrote: >>> >>> > >>>> >>> >>> > >>>> I've been wondering since I started learning NiFi why ExecuteSQL >>> >>> > >>>> processor only returns AVRO formatted data. All community >>> >>> > >>>> examples I've seen >>> >>> > >>>> then convert AVRO to json and pretty much all of them then split >>> >>> > >>>> json to >>> >>> > >>>> multiple flows. >>> >>> > >>>> >>> >>> > >>>> I found myself doing the same thing over and over and over again. >>> >>> > >>>> >>> >>> > >>>> Since everyone is doing it, is there a strong reason why AVRO is >>> >>> > >>>> liked >>> >>> > >>>> so much? And why everyone continues doing this 3 step pattern >>> >>> > >>>> rather than >>> >>> > >>>> providing users with an option to output json instead and >>> >>> > >>>> another option to >>> >>> > >>>> output one flowfile or multiple (one per record). >>> >>> > >>>> >>> >>> > >>>> thanks >>> >>> > >>>> Boris >>> >> >>> >> >>> >
