...with the assumption that we would exclude null values in the Pair<A, B>?
On Tue, Aug 20, 2013 at 7:40 PM, Josh Wills <[email protected]> wrote: > That does sound pretty clean... > > > On Tue, Aug 20, 2013 at 7:34 PM, Chao Shi <[email protected]> wrote: > >> Is it possible to provide a utility that transforms PCollection<Pair<A, >> B>> to Pair<PCollection<A>, PCollection<B>>? So one can simply emit Pairs >> and then write them to two Targets. This could be generalized to Tuples. >> >> >> 2013/8/21 Josh Wills <[email protected]> >> >>> >>> On Tue, Aug 20, 2013 at 12:23 PM, Inman,Brandon < >>> [email protected]> wrote: >>> >>>> I like the flexibility of this approach, although would the idea of >>>> having some official constants defined for a small set of standard channels >>>> be reasonable (the concepts of "out" and "error" are pretty common, others >>>> may be warranted as well)? >>>> >>> >>> So I think the way I would handle this would be having a main output >>> directory and an error output directory that was underneath it. Cascading >>> does this trick within their existing flows where you can throw exceptions >>> to "traps," which is essentially the same idea, though I'm not wild about >>> control flow that relies on throwing exceptions. >>> >>> >>>> Is this something that you would see being added to core Crunch APIs >>>> (for example, directly to Pipeline), or implemented on top of Crunch with a >>>> filtering approach similar to my original post? If it's implemented on >>>> top, shouldn't materialization work as-is? >>>> >>> >>> Yes, your model would be simpler. I think that mine would require a >>> special kind of Target implementation, a custom implementation of the >>> Emitter interface that would be used for routing the outputs of the DoFn, >>> and possibly some post-processing code to move the data to a sensible >>> place. I don't know if that work is strictly necessary, and your impl is >>> certainly much more straightforward than mine. :) >>> >>> >>>> >>>> If the type was PTable<String, T>, could Union<S,U> be a choice for T >>>> as appropriate? In our case, we would likely be looking at a PTable<String, >>>> T extends SpecificRecordBase> and not necessarily need Union with this >>>> approach. >>>> >>> >>> Yeah, I think it would be fine, but we'd have to be cognizant of it when >>> we were implementing the union type, and it would be up to the client to >>> ensure that the right data type ended up in the right file, which is maybe >>> less good? >>> >>> >>>> >>>> >>>> From: Josh Wills <[email protected]> >>>> Reply-To: "[email protected]" <[email protected]> >>>> Date: Tuesday, August 20, 2013 1:00 PM >>>> To: "[email protected]" <[email protected]> >>>> Subject: Re: Multiple output channels from Crunch DoFn >>>> >>>> A related idea that has come up a few times has been the idea of >>>> having a way of writing values to different files based on a key: some kind >>>> of generalization of Target that would itself write multiple outputs under >>>> the covers, with the name of the output file indicated by some function of >>>> the key of the PTable. >>>> >>>> For this situation, we would have a PTable that was like PTable<String, >>>> Union<S, T>>, or just PTable<String, T> if the output types were all the >>>> same, and the String would specify the name of an output directory (that I >>>> suppose would live underneath some base output directory for the Target) >>>> that the record would be written to. >>>> >>>> There are a couple of limitations to this approach, I think: we >>>> couldn't consider this kind of PTable "materialized" w/o doing an overhaul >>>> of the materialization logic-- it would act sort of like an HTableTarget in >>>> that it would be write-only in flows. There are probably some others I >>>> can't think of off the top of my head. What do you guys think? >>>> >>>> J >>>> >>>> >>>> On Tue, Aug 20, 2013 at 9:49 AM, Brush,Ryan <[email protected]> wrote: >>>> >>>>> I happen to have some context around this, so I wanted to expand on >>>>> Brandon's question a bit. The use case here is we're dealing with a large >>>>> volume of third-party input and expect a certain percentage of bogus or >>>>> malformed data. Rather than simply logging instances of bad records, we >>>>> want to treat it as a signal we can learn from, both for improving our >>>>> processing logic and for creating structured reports we can use to >>>>> troubleshoot data sources. >>>>> >>>>> This leads to the "standard out" and "standard error" metaphors >>>>> Brandon mentions: in most cases, our Crunch DoFns would emit a processed >>>>> structure useful downstream. But we'd also like to be able to emit a >>>>> structured error -- probably as an Avro object in our case -- and persist >>>>> that as a byproduct of our main processing pipeline. >>>>> >>>>> Would it make sense for such DoFn's to emit something some form of >>>>> "Option" object? We could then attach two consuming functions to it: one >>>>> that handles the "success" case, sending the resulting Avro object >>>>> downstream. Another DoFn attached to the "Option" object would be a no-op >>>>> unless the Option contained an "error" structure, at which point we >>>>> persist >>>>> it to some well-known location for later analysis. >>>>> >>>>> I think this is entirely achievable using existing mechanisms...but it >>>>> seems like common enough use case (at least for us) to establish some >>>>> idioms for dealing it. >>>>> >>>>> On Aug 20, 2013, at 11:13 AM, Inman,Brandon wrote: >>>>> >>>>> > >>>>> > We've been looking at ways to do multiple outputs in Crunch jobs, >>>>> > specifically writing out some kind of Status or Error Avro object, >>>>> based >>>>> > on failures that occur processing individual records in various >>>>> jobs. It >>>>> > had been suggested that, rather than logging these errors to >>>>> traditional >>>>> > loggers, to consider them an output of the Crunch job. After some >>>>> > internal discussion, it was suggested to run the ideas past the >>>>> Crunch >>>>> > community. >>>>> > >>>>> > >>>>> > A major goal we have is to end with all the error output in a >>>>> location >>>>> > that makes it easy to run Hive queries or perform other >>>>> MapReduce-style >>>>> > analysis to quickly view all errors across the larger system without >>>>> the >>>>> > need go to multiple facilities. This means standardizing on the Avro >>>>> > object, but it also necessitates decoupling the storage of the >>>>> object from >>>>> > the "standard output" of the job. >>>>> > >>>>> > >>>>> > As Crunch DoFns support a single Emitter per invocation of >>>>> process(), the >>>>> > solution that gathered the most support would be to emit an object >>>>> similar >>>>> > to Pair<>, where first would be the "standard out" and second would >>>>> be the >>>>> > "standard error". A DoFn would generally only populate one (nothing >>>>> > preventing it from populating both if appropriate, but not really >>>>> intended >>>>> > as a part of general use), and separate DoFns would filter out the >>>>> two >>>>> > components of the pair and write the values to the appropriate >>>>> targets. >>>>> > >>>>> > As far as the emitted pairing object; the concept of a tagged union >>>>> was >>>>> > suggested although there currently isn't support in Java or Avro for >>>>> the >>>>> > concept; it was noted that >>>>> > https://issues.apache.org/jira/browse/CRUNCH-239<https://urldefense.proofpoint.com/v1/url?u=https://issues.apache.org/jira/browse/CRUNCH-239&k=PmKqfXspAHNo6iYJ48Q45A%3D%3D%0A&r=RiPWMqlVaSiSs74U1fVjrSpZO%2FvyTEWUW1RhCH7Ftlg%3D%0A&m=ZOuvUFJf2XiQL4mXsKMy9ArJwoDf7VP6eNKgaIHMafc%3D%0A&s=dceef88f8fadf4d34b61b47e1728bc63dda36ad51151ccfceb5c84ea45be0e82>might >>>>> > be a close >>>>> > candidate. Pair<> would meet the requirements, although it was >>>>> suggested >>>>> > that a simple object dedicated to the task could make a cleaner >>>>> approach. >>>>> > >>>>> > Any general thoughts on this approach? Are there any other patterns >>>>> that >>>>> > might serve us better, or anything on the Crunch roadmap that might >>>>> be >>>>> > more appropriate? >>>>> > >>>>> > >>>>> > Brandon Inman >>>>> > Software Architect >>>>> > www.cerner.com >>>>> > >>>>> > >>>>> > CONFIDENTIALITY NOTICE This message and any included attachments are >>>>> from Cerner Corporation and are intended only for the addressee. The >>>>> information contained in this message is confidential and may constitute >>>>> inside or non-public information under international, federal, or state >>>>> securities laws. Unauthorized forwarding, printing, copying, distribution, >>>>> or use of such information is strictly prohibited and may be unlawful. If >>>>> you are not the addressee, please promptly delete this message and notify >>>>> the sender of the delivery error by e-mail or you may call Cerner's >>>>> corporate offices in Kansas City, Missouri, U.S.A at (+1) >>>>> (816)221-1024. >>>>> >>>>> >>>>> >>>> >>>> >>>> -- >>>> Director of Data Science >>>> Cloudera<https://urldefense.proofpoint.com/v1/url?u=http://www.cloudera.com&k=PmKqfXspAHNo6iYJ48Q45A%3D%3D%0A&r=RiPWMqlVaSiSs74U1fVjrSpZO%2FvyTEWUW1RhCH7Ftlg%3D%0A&m=ZOuvUFJf2XiQL4mXsKMy9ArJwoDf7VP6eNKgaIHMafc%3D%0A&s=508adfd2097ef3f7c9738fe9f729f47d95ae1d6568dabe09697317fd6d53f9d1> >>>> Twitter: >>>> @josh_wills<https://urldefense.proofpoint.com/v1/url?u=http://twitter.com/josh_wills&k=PmKqfXspAHNo6iYJ48Q45A%3D%3D%0A&r=RiPWMqlVaSiSs74U1fVjrSpZO%2FvyTEWUW1RhCH7Ftlg%3D%0A&m=ZOuvUFJf2XiQL4mXsKMy9ArJwoDf7VP6eNKgaIHMafc%3D%0A&s=585b666e290f5104a6f13a0fcbc52f4fc6cd93365dc1d44d3e49ed09c2fe1996> >>>> >>> >>> >> > > > -- > Director of Data Science > Cloudera <http://www.cloudera.com> > Twitter: @josh_wills <http://twitter.com/josh_wills> > -- Director of Data Science Cloudera <http://www.cloudera.com> Twitter: @josh_wills <http://twitter.com/josh_wills>
