For users of Equality Deletes, what are the key benefits to Equality Deletes that you would like to preserve and could you please share some concrete examples of the queries you want to run (and the schemas and data sizes you would like to run them against) and the latencies that would be acceptable?
On Thu, Oct 31, 2024 at 10:05 AM Jason Fine <ja...@upsolver.com.invalid> wrote: > Hi, > > Representing Upsolver here, we also make use of Equality Deletes to > deliver high frequency low latency updates to our clients at scale. We have > customers using them at scale and demonstrating the need and viability. We > automate the process of converting them into positional deletes (or fully > applying them) for more efficient engine queries in the background giving > our users both low latency and good query performance. > > Equality Deletes were added since there isn't a good way to solve frequent > updates otherwise. It would require some sort of index keeping track of > every record in the table (by a predetermined PK) and maintaining such an > index is a huge task that every tool interested in this would need to > re-implement. It also becomes a bottleneck limiting table sizes. > > I don't think they should be removed without providing an alternative. > Positional Deletes have a different performance profile inherently, > requiring more upfront work proportional to the table size. > > On Thu, Oct 31, 2024 at 2:45 PM Jean-Baptiste Onofré <j...@nanthrax.net> > wrote: > >> Hi Russell >> >> Thanks for the nice writeup and the proposal. >> >> I agree with your analysis, and I have the same feeling. However, I >> think there are more than Flink that write equality delete files. So, >> I agree to deprecate in V3, but maybe be more "flexible" about removal >> in V4 in order to give time to engines to update. >> I think that by deprecating equality deletes, we are clearly focusing >> on read performance and "consistency" (more than write). It's not >> necessarily a bad thing but the streaming platform and data ingestion >> platforms will be probably concerned about that (by using positional >> deletes, they will have to scan/read all datafiles to find the >> position, so painful). >> >> So, to summarize: >> 1. Agree to deprecate equality deletes, but -1 to commit any target >> for deletion before having a clear path for streaming platforms >> (Flink, Beam, ...) >> 2. In the meantime (during the deprecation period), I propose to >> explore possible improvements for streaming platforms (maybe finding a >> way to avoid full data files scan, ...) >> >> Thanks ! >> Regards >> JB >> >> On Wed, Oct 30, 2024 at 10:06 PM Russell Spitzer >> <russell.spit...@gmail.com> wrote: >> > >> > Background: >> > >> > 1) Position Deletes >> > >> > >> > Writers determine what rows are deleted and mark them in a 1 for 1 >> representation. With delete vectors this means every data file has at most >> 1 delete vector that it is read in conjunction with to excise deleted rows. >> Reader overhead is more or less constant and is very predictable. >> > >> > >> > The main cost of this mode is that deletes must be determined at write >> time which is expensive and can be more difficult for conflict resolution >> > >> > 2) Equality Deletes >> > >> > Writers write out reference to what values are deleted (in a partition >> or globally). There can be an unlimited number of equality deletes and they >> all must be checked for every data file that is read. The cost of >> determining deleted rows is essentially given to the reader. >> > >> > Conflicts almost never happen since data files are not actually changed >> and there is almost no cost to the writer to generate these. Almost all >> costs related to equality deletes are passed on to the reader. >> > >> > Proposal: >> > >> > Equality deletes are, in my opinion, unsustainable and we should work >> on deprecating and removing them from the specification. At this time, I >> know of only one engine (Apache Flink) which produces these deletes but >> almost all engines have implementations to read them. The cost of >> implementing equality deletes on the read path is difficult and >> unpredictable in terms of memory usage and compute complexity. We’ve had >> suggestions of implementing rocksdb inorder to handle ever growing sets of >> equality deletes which in my opinion shows that we are going down the wrong >> path. >> > >> > Outside of performance, Equality deletes are also difficult to use in >> conjunction with many other features. For example, any features requiring >> CDC or Row lineage are basically impossible when equality deletes are in >> use. When Equality deletes are present, the state of the table can only be >> determined with a full scan making it difficult to update differential >> structures. This means materialized views or indexes need to essentially be >> fully rebuilt whenever an equality delete is added to the table. >> > >> > Equality deletes essentially remove complexity from the write side but >> then add what I believe is an unacceptable level of complexity to the read >> side. >> > >> > Because of this I suggest we deprecate Equality Deletes in V3 and slate >> them for full removal from the Iceberg Spec in V4. >> > >> > I know this is a big change and compatibility breakage so I would like >> to introduce this idea to the community and solicit feedback from all >> stakeholders. I am very flexible on this issue and would like to hear the >> best issues both for and against removal of Equality Deletes. >> > >> > Thanks everyone for your time, >> > >> > Russ Spitzer >> > >> > >> > > > -- > > *Jason Fine* > Chief Software Architect > ja...@upsolver.com | www.upsolver.com >
