Hi, Really nice to see people chime into this thread. I agree with Martijn about the development approach. There will be some iterations until we can stabilize this anyways, so we can try to shoot getting out a good enough MVP, then fix issues + reach feature parity with the existing implementations on the go.
I am not a licensing expert but AFAIK the previous images that were released under the acceptable license can be continued to use. For most integration tests, we use an ancient image anyways [1]. There is another place where the latest img gets pulled [2], I guess it would be good to apply an explicit that tag there. But AFAIK they stop publishing to Docker Hub, so I would anticipate we cannot end up pulling an image with a forbidden license. Best, Ferenc [1] https://github.com/apache/flink/blob/fd1a97768b661f19783afe70d93a0a8d3d625b2a/flink-test-utils-parent/flink-test-utils-junit/src/main/java/org/apache/flink/util/DockerImageVersions.java#L39 [2] https://github.com/apache/flink/blob/fd1a97768b661f19783afe70d93a0a8d3d625b2a/flink-end-to-end-tests/test-scripts/common_s3_minio.sh#L51 On Sunday, October 26th, 2025 at 22:05, Martijn Visser <[email protected]> wrote: > > > Hi Samrat, > > First of all, thanks for the proposal. It's long overdue to get this in a > better state. > > With regards to the schemes, I would say to ship an initial release that > does not include support for s3a and s3p, and focus first on getting this > new implementation into a stable state. When that's done, as a follow-up, > we can consider adding support for s3a and s3p on this implementation, and > when that's there consider deprecating the older implementations. It will > probably take multiple releases before we have this in a stable state. > > Not directly related to this, but given that MinIO decided to change their > license, do we also need to refactor existing tests to not use MinIO > anymore but something else? > > Thanks, > > Martijn > > On Sat, Oct 25, 2025 at 1:38 AM Samrat Deb [email protected] wrote: > > > Hi all, > > > > One clarifying question regarding the URI schemes: > > > > Currently, the Flink ecosystem uses multiple schemes to differentiate > > between S3 implementations: s3a:// for the Hadoop-based connector and > > s3p://[1] for the Presto-based one, which is often recommended for > > checkpointing. > > > > A key goal of the proposed flink-s3-fs-native is to unify these into a > > single implementation. With that in mind, what should be the strategy for > > scheme support? Should the new native s3 filesystem register only for the > > simple s3:// scheme, aiming to deprecate the others? Or would it be > > beneficial to also support s3a:// and s3p:// to provide a smoother > > migration path for users who may have these schemes in their existing job > > configurations? > > Cheers, > > Samrat > > > > [1] https://github.com/generalui/s3p > > > > On Wed, Oct 22, 2025 at 6:31 PM Piotr Nowojski [email protected] > > wrote: > > > > > Hi Samrat, > > > > > > > 1. Even if the specifics are hazy, could you recall the general > > > > nature of those concerns? For instance, were they related to S3's > > > > eventual > > > > consistency model, which has since improved, the atomicity of Multipart > > > > Upload commits, or perhaps complex failure/recovery scenarios during > > > > the > > > > commit phase? > > > > > > and > > > > > > > *8. *The flink-s3-fs-presto connector explicitly throws an > > > > `UnsupportedOperationException` when `createRecoverableWriter()` is > > > > called. > > > > Was this a deliberate design choice to keep the Presto connector > > > > lightweight and optimized specifically for checkpointing, or were there > > > > other technical challenges that prevented its implementation at the > > > > time? > > > > Any context on this would be very helpful > > > > > > I very vaguely remember that at least one of those concerns was with > > > respect to how long > > > does it take for the S3 to make some certain operations visible. That you > > > think you have > > > uploaded and committed a file, but in reality it might not be visible for > > > tens of seconds. > > > > > > Sorry, I don't remember more (or even if there was more). I was only > > > superficially involved > > > in the S3 connector back then - just participated/overheard some > > > discussions. > > > > > > > 2. It's clear that implementing an efficient > > > > PathsCopyingFileSystem[2] > > > > is > > > > a non-negotiable requirement for performance. Is there any benchmark > > > > numbers available that can be used as reference and evaluate new > > > > implementation deviation ? > > > > > > I only have the numbers that I put in the original Flip [1]. I don't > > > remember the benchmark > > > setup, but it must have been something simple. Like just let some job > > > accumulate 1GB of state > > > and measure how long the state downloading phase of recovery was taking. > > > > > > > 3. Do you recall the workload characteristics for that PoC? > > > > Specifically, > > > > was the 30-40% performance advantage of s5cmd observed when copying > > > > many > > > > small files (like checkpoint state) or larger, multi-gigabyte files? > > > > > > It was just a regular mix of compacted RocksDB sst files, with total > > > state > > > size 1 or at most > > > a couple of GBs. So most of the files were around ~64MB or ~128MB, with a > > > couple of > > > smaller L0 files, and maybe one larger L2 file. > > > > > > > 4. The idea of a switchable implementation sounds great. Would you > > > > envision this as a configuration flag (e.g., > > > > s3.native.copy.strategy=s5cmd > > > > or s3.native.copy.strategy=sdk) that selects the backend implementation > > > > at > > > > runtime? Also on contrary is it worth adding configuration that exposes > > > > some level of implementation level information ? > > > > > > I think something like that should be fine, assuming that `s5cmd` will > > > again > > > prove significantly faster and/or more cpu efficient. If not, if the > > > SDKv2 > > > has > > > already improved and caught up with the `s5cmd`, then it probably doesn't > > > make sense to keep `s5cmd` support. > > > > > > > 5. My understanding is that the key takeaway here is to avoid the > > > > file-by-file stream-based copy used in the vanilla connector and > > > > leverage > > > > bulk operations, which PathsCopyingFileSystem[2] enables. This seems > > > > most > > > > critical during state download on recovery. please suggest if my > > > > inference > > > > is in right direction > > > > > > Yes, but you should also make the bult transfer configurable. How many > > > bulk > > > transfers > > > can be happening in parallel etc. > > > > > > > 6. The warning about `s5cmd` causing OOMs sounds like indication to > > > > consider `S3TransferManager`[3] implementation, which might offer more > > > > granular control over buffering and in-flight requests. Do you think > > > > exploring more on `S3TransferManager` would be valuable ? > > > > > > I'm pretty sure if you start hundreds of bulk transfers in parallel via > > > the > > > `S3TransferManager` you can get the same problems with running out of > > > memory or exceeding available network throughput. I don't know if > > > `S3TransferManager` is better or worse in that regard to be honest. > > > > > > > 7. The insight on AWS aggressively dropping packets instead of > > > > gracefully > > > > throttling is invaluable. Currently i have limited understanding on how > > > > aws > > > > behaves at throttling I will deep dive more into it and > > > > look for clarification based on findings or doubt. To counter this, > > > > were > > > > you thinking of a configurable rate limiter within the filesystem > > > > itself > > > > (e.g., setting max bandwidth or max concurrent requests), or something > > > > more > > > > dynamic that could adapt to network conditions? > > > > > > Flat rate limiting is tricky because AWS offers burst network capacity, > > > which > > > comes very handy, and in the vast majority of cases works fine. But for > > > some jobs > > > if you exceed that burst capacity, AWS starts dropping your packets and > > > then the > > > problems happen. On the other hand, if rate limit to your normal > > > capacity, > > > you > > > are leaving a lot of network throughput unused during recoveries. > > > > > > At the same time AWS doesn't share details for the burst capacity, so > > > it's > > > sometimes > > > tricky to configure the whole system properly. I don't have an universal > > > good answer > > > for that :( > > > > > > Best, > > > Piotrek > > > > > > wt., 21 paź 2025 o 21:40 Samrat Deb [email protected] napisał(a): > > > > > > > Hi Gabor/ Ferenc > > > > > > > > Thank you for sharing the pointer and valuable feedback. > > > > > > > > The link to the custom `XmlResponsesSaxParser`[1] looks scary 😦 > > > > and contains hidden complexity. > > > > > > > > 1. Could you share some context on why this custom parser was > > > > necessary? > > > > Was it to work around a specific bug, a performance issue, or an > > > > inconsistency in the S3 XML API responses that the default AWS SDK > > > > parser > > > > couldn't handle at the time? With sdk v2 what are core functionality > > > > that > > > > is required to be intensively tested ? > > > > > > > > 2. You mentioned it has no Hadoop dependency, which is great news. > > > > For > > > > a > > > > new native S3 connector, would integration simply require implementing > > > > a > > > > new S3DelegationTokenProvider/Receiver pair using the AWS SDK, or are > > > > there > > > > more subtle integration points with the framework that should be > > > > accounted? > > > > > > > > 3. I remember solving Serialized Throwable exception issue [2] > > > > leading > > > > to > > > > a new bug [3], where an initial fix led to a regression that Gabor > > > > later > > > > solved with Ferenc providing a detailed root cause insights [4] 😅. > > > > Its hard to fully sure that all scenarios are covered properly. This is > > > > one > > > > of the example, there can be other unknowns. > > > > what would be the best approach to test for and prevent such > > > > regressions > > > > or > > > > unknown unknowns, especially in the most sensitive parts of the > > > > filesystem > > > > logic? > > > > > > > > Cheers, > > > > Samrat > > > > > > > > [1] > > > > https://github.com/apache/flink/blob/0e4e6d7082e83f098d0c1a94351babb3ea407aa8/flink-filesystems/flink-s3-fs-base/src/main/java/com/amazonaws/services/s3/model/transform/XmlResponsesSaxParser.java > > > > > > [2] https://issues.apache.org/jira/browse/FLINK-28513 > > > > [3] https://github.com/apache/flink/pull/25231 > > > > [4] https://github.com/apache/flink/pull/25231#issuecomment-2312059662 > > > > > > > > On Tue, 21 Oct 2025 at 3:49 PM, Gabor Somogyi < > > > > [email protected] > > > > > > > > wrote: > > > > > > > > > Hi Samrat, > > > > > > > > > > +1 on the direction that we move away from hadoop. > > > > > > > > > > This is a long standing discussion to replace the mentioned 2 > > > > > connectors > > > > > with something better. > > > > > Both of them has it's own weaknesses, I've fixed several blockers > > > > > inside > > > > > them. > > > > > > > > > > There are definitely magic inside them, please see this [1] for > > > > > example > > > > > and > > > > > there are more🙂 > > > > > I think the most sensitive part is the recovery because hard to test > > > > > all > > > > > cases. > > > > > > > > > > @Ferenc > > > > > > > > > > > One thing that comes to my mind that will need some changes and its > > > > > > involvement > > > > > > to this change is not trivial is the delegation token framework. > > > > > > Currently > > > > > > it > > > > > > is also tied to the Hadoop stuff and has some abstract classes in > > > > > > the > > > > > > base > > > > > > S3 FS > > > > > > module. > > > > > > > > > > The delegation token framework has no dependency on hadoop so there > > > > > is > > > > > no > > > > > blocker on the road, > > > > > but I'm here to help if any question appears. > > > > > > > > > > BR, > > > > > G > > > > > > > > > > [1] > > > > https://github.com/apache/flink/blob/0e4e6d7082e83f098d0c1a94351babb3ea407aa8/flink-filesystems/flink-s3-fs-base/src/main/java/com/amazonaws/services/s3/model/transform/XmlResponsesSaxParser.java#L95-L104 > > > > > > > On Tue, Oct 14, 2025 at 8:19 PM Samrat Deb [email protected] > > > > > wrote: > > > > > > > > > > > Hi All, > > > > > > > > > > > > Poorvank (cc'ed) and I are writing to start a discussion about a > > > > > > potential > > > > > > improvement for Flink, creating a new, native S3 filesystem > > > > > > independent > > > > > > of > > > > > > Hadoop/Presto. > > > > > > > > > > > > The goal of this proposal is to address several challenges related > > > > > > to > > > > > > Flink's S3 integration, simplifying flink-s3-filesystem. If this > > > > > > discussion > > > > > > gains positive traction, the next step would be to move forward > > > > > > with > > > > > > a > > > > > > formalised FLIP. > > > > > > > > > > > > The Challenges with the Current S3 Connectors > > > > > > Currently, Flink offers two primary S3 filesystems, > > > > > > flink-s3-fs-hadoop[1] > > > > > > and flink-s3-fs-presto[2]. While functional, this dual-connector > > > > > > approach > > > > > > has few issues: > > > > > > > > > > > > 1. The flink-s3-fs-hadoop connector adds an additional dependency > > > > > > to > > > > > > manage. Upgrades like AWS SDK v2 are more dependent on > > > > > > Hadoop/Presto > > > > > > to > > > > > > support first and leverage in flink-s3-filesystem. Sometimes it's > > > > > > restrictive to leverage features directly from the AWS SDK. > > > > > > > > > > > > 2. The flink-s3-fs-presto connector was introduced to mitigate the > > > > > > performance issues of the Hadoop connector, especially for > > > > > > checkpointing. > > > > > > However, it lacks a RecoverableWriter implementation. > > > > > > Sometimes it's confusing for Flink users, highlighting the need > > > > > > for a > > > > > > single, unified solution. > > > > > > > > > > > > Proposed Solution: > > > > > > A Native, Hadoop-Free S3 Filesystem > > > > > > > > > > > > I propose we develop a new filesystem, let's call it > > > > > > flink-s3-fs-native, > > > > > > built directly on the modern AWS SDK for Java v2. This approach > > > > > > would > > > > > > be > > > > > > free of any Hadoop or Presto dependencies. I have done a small > > > > > > prototype > > > > > > to > > > > > > validate [3] > > > > > > > > > > > > This is motivated by trino<>s3 [4]. The Trino project successfully > > > > > > undertook a similar migration, moving from Hadoop-based object > > > > > > storage > > > > > > clients to their own native implementations. > > > > > > > > > > > > The new Flink S3 filesystem would: > > > > > > > > > > > > 1. Provide a single, unified connector for all S3 interactions, > > > > > > from > > > > > > state > > > > > > backends to sinks. > > > > > > > > > > > > 2. Implement a high-performance S3RecoverableWriter using S3's > > > > > > Multipart > > > > > > Upload feature, ensuring exactly-once sink semantics. > > > > > > > > > > > > 3. Offer a clean, self-contained dependency, drastically > > > > > > simplifying > > > > > > setup > > > > > > and eliminating external dependencies. > > > > > > > > > > > > A Phased Migration Path > > > > > > To ensure a smooth transition, we could adopt a phased approach on > > > > > > a > > > > > > very > > > > > > high level : > > > > > > > > > > > > Phase 1: > > > > > > Introduce the new native S3 filesystem as an optional, parallel > > > > > > plugin. > > > > > > This would allow for community testing and adoption without > > > > > > breaking > > > > > > existing setups. > > > > > > > > > > > > Phase 2: > > > > > > Once the native connector achieves feature parity and proven > > > > > > stability, > > > > > > we > > > > > > will update the documentation to recommend it as the default choice > > > > > > for > > > > > > all > > > > > > S3 use cases. > > > > > > > > > > > > Phase 3: > > > > > > In a future major release, the legacy flink-s3-fs-hadoop and > > > > > > flink-s3-fs-presto connectors could be formally deprecated, with > > > > > > clear > > > > > > migration guides provided for users. > > > > > > > > > > > > I would love to hear the community's thoughts on this. > > > > > > > > > > > > A few questions to start the discussion: > > > > > > > > > > > > 1. What are the biggest pain points with the current S3 filesystem? > > > > > > > > > > > > 2. Are there any critical features from the Hadoop S3A client that > > > > > > are > > > > > > essential to replicate in a native implementation? > > > > > > > > > > > > 3. Would a simplified, non-dependent S3 experience be a valuable > > > > > > improvement for Flink use cases? > > > > > > > > > > > > Cheers, > > > > > > Samrat > > > > > > > > > > > > [1] > > > > https://github.com/apache/flink/tree/master/flink-filesystems/flink-s3-fs-hadoop > > > > > > > > [2] > > > > https://github.com/apache/flink/tree/master/flink-filesystems/flink-s3-fs-presto > > > > > > > > [3] https://github.com/Samrat002/flink/pull/4 > > > > > > [4] > > > > > > https://github.com/trinodb/trino/tree/master/lib/trino-filesystem-s3
