Thanks, Ken! I was wondering how other systems handle these issues. Fortunately, the deep copy - shallow copy problem doesn't arise in Flink: when we copy an object, it is always a deep copy (at least, I hope so :)).
Best, Gábor 2016-02-19 22:29 GMT+01:00 Ken Krugler <kkrugler_li...@transpac.com>: > Not sure how useful this is, but we'd run into similar issues with Cascading > over the years. > > This wasn't an issue for input data, as Cascading "locks" the Tuple such that > attempts to modify it will fail. > > And in general Hadoop always re-uses the data container being passed to > operations, so you quickly learn to not cache those :) > > When trying to re-use a Tuple as the output in an operation, things get a bit > more complicated. > > If the Tuple only contains primitive types, then there's no issue as the > (effectively) shallow copy created by the execution platform doesn't create a > problem. > > If the Tuple contains an object (e.g. a nested Tuple) then there were > situations where a deep copy would need to be made before passing the Tuple > to the operation's output collector. > > For example, if the next (chained) operation was a map-side aggregator, then > a shallow copy of the Tuple would be cached. If there's a non-primitive > object then changes to this in the upstream operation obviously bork the > cached data. > > Net-net is that it we wanted a way to find out, from inside an operation, > whether we needed to make a deep copy of the output Tuple. But that doesn't > exist (yet), so we have some utility code to check if a deep copy is needed > (non-primitive types), and if so then it auto-clones the Tuple. Which isn't > very efficient, but for most of our workflows we only have primitive types. > > -- Ken > >> From: Fabian Hueske >> Sent: February 17, 2016 9:17:27am PST >> To: dev@flink.apache.org >> Subject: Guarantees for object reuse modes and documentation >> >> Hi, >> >> >> >> Flink's DataSet API features a configuration parameter called >> enableObjectReuse(). If activated, Flink's runtime will create fewer >> objects which results in better performance and lower garbage collection >> overhead. Depending on whether the configuration switch is enabled or not, >> user functions may or may not perform certain operations on objects they >> receive from Flink or emit to Flink. >> >> >> >> At the moment, there are quite a few open issues and discussions going on >> about the object reuse mode, including the JIRA issues FLINK-3333, >> FLINK-1521, FLINK-3335, FLINK-3340, FLINK-3394, and FLINK-3291. >> >> >> >> IMO, the most important issue is FLINK-3333 which is about improving the >> documentation of the object reuse mode. The current version [1] is >> ambiguous and includes details about operator chaining which are hard to >> understand and to reason about for users. Hence it is not very clear which >> guarantees Flink gives for objects in user functions under which >> conditions. This documentation needs to be improved and I think this should >> happen together with the 1.0 release. >> >> >> >> Greg and Gabor proposed two new versions: >> >> 1. Greg's version [2] improves and clarifies the current documentation >> without significantly changing the semantics. It also discusses operator >> chaining, but gives more details. >> 2. Gabor's proposal [3] aims to make the discussion of object reuse >> independent of operator chaining which I think is a very good idea because >> it is not transparent to the user when function chaining happens. Gabor >> formulated four questions to answer what users can do with and expect from >> objects that they received or emitted from a function. In order to make the >> answers to these questions independent of function chaining and still keep >> the contracts as defined by the current documentation, we have to default >> to rather restrictive rules. For instance, functions must always emit new >> object instances in case of disabled object reuse mode. These strict rules >> would for example also require DataSourceFunctions to copy all records >> which they receive from an InputFormat (see FLINK-3335). IMO, the strict >> guarantees make the disableObjectReuse mode harder to use and reason about >> than the enableObjectReuse mode whereas the opposite should be the case. >> >> >> >> I would like to suggest a third option. Similar as Gabor, I think the rules >> should be independent of function chaining and I would like to break it >> down into a handful of easy rules. However, I think we should loosen up the >> guarantees for user functions under disableObjectReuse mode a bit. >> >> Right now, the documentation states that under enableObjectReuse mode, >> input objects are not changed across functions calls. Hence users can >> remember these objects across functions calls and their value will not >> change. I propose to give this guarantee only within functions calls and >> only for objects which are not emitted. Hence, this rule only applies for >> functions that can consume multiple values through an iterator such as >> GroupReduce, CoGroup, or MapPartition. In object disableObjectReuse mode, >> these functions are allowed to remember the values e.g., in a collection, >> and their value will not change when the iterator is forwarded. Once the >> function call returns, the values might change. Since functions with >> iterators cannot be directly chained, it will be safe to emit the same >> object instance several times (hence FLINK-3335 would become invalid). >> >> >> >> The difference to the current guarantees is that input objects become >> invalid after the function call returned. Since, the disableObjectReuse >> mode was mainly introduced to allow for caching objects across iterator >> calls within a GroupReduceFunction or CoGroupFunction (not across function >> calls), I think this is a reasonable restriction. >> >> >> >> tl;dr; >> >> If we want to make the documentation of object reuse independent of >> chaining we have to >> >> - EITHER, give tighter guarantees / be more restrictive than now and update >> internals which might lead to performance regression. This would be in-line >> with the current documentation but somewhat defeat the purpose of the >> disabledObjectReuse mode, IMO. >> >> - OR, give weaker guarantees, which breaks with the current documentation, >> but would not affect performance or be easier to follow for users, IMO. >> >> >> Greg and Gabor, please correct me if I did not get your points right or >> missed something. >> >> What do others think? >> >> >> Fabian >> >> >> >> [1] >> https://ci.apache.org/projects/flink/flink-docs-master/apis/batch/index.html#object-reuse-behavior >> >> [2] >> https://issues.apache.org/jira/browse/FLINK-3333?focusedCommentId=15139151 >> >> [3] >> https://docs.google.com/document/d/1cgkuttvmj4jUonG7E2RdFVjKlfQDm_hE6gvFcgAfzXg > > -------------------------- > Ken Krugler > +1 530-210-6378 > http://www.scaleunlimited.com > custom big data solutions & training > Hadoop, Cascading, Cassandra & Solr > > > > > > -------------------------- > Ken Krugler > +1 530-210-6378 > http://www.scaleunlimited.com > custom big data solutions & training > Hadoop, Cascading, Cassandra & Solr > > > > >
