Yes, I think so. Do we generally allow nulls in crunch APIs? I'm a afraid that it would be confusing if some excludes null values while others don't.
2013/8/21 Josh Wills <[email protected]> > ...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> >
