Hi Gyula, Thanks for putting this FLIP together. I'm very supportive of the goals of FLIP-599. A robust State Catalog is a fantastic step forward for state observability and management.
You and Shengkai landed on bumping RowDataSerializerSnapshot to include field names to support the catalog's schema inference. I agree with the direction, and FLIP-527 (State Schema Evolution for RowData) [1], which I'm driving, proposes the exact same version bump. I wanted to flag a design overlap early, while both FLIPs are still in DISCUSS, so we can align our approaches. When implementing FLIP-527, one option is that the presence of these field names acts as the explicit opt-in signal for schema evolution. The feature is off by default, the serializer is built with names only when it's enabled, and the compatibility/migration logic keys off whether those names are present. The catch with that approach is a coupling worth designing around. For the catalog to recover real names on jobs that never enabled schema evolution, those names would need to be written regardless of the evolution opt-in. But if name presence is what signals the opt-in, then writing names by default would flip the gate on for jobs that never asked, and trigger migration logic they didn't opt into. Since we're still discussing the high-level architecture for both FLIPs, this looks very solvable. We just need to decouple the "names persisted" metadata from the "evolution permitted" signal, perhaps by introducing an explicit toggle flag in the snapshot format rather than relying solely on name presence. That's the direction I'd favor for FLIP-527 as well. Getting this right while both FLIPs are in DISCUSS means whichever lands first can establish a format that serves both the catalog's metadata needs and the migration's safety requirements. Looking forward to your thoughts on how best to converge these designs. Best, Weiqing [1] https://cwiki.apache.org/confluence/spaces/FLINK/pages/353601981/FLIP-527+State+Schema+Evolution+for+RowData On Wed, Jul 8, 2026 at 6:41 AM Jingsong Li <[email protected]> wrote: > Hi Gyula, > > Thanks for your response. > > Sounds good to me. > > Best, > Jingsong > > On Wed, Jul 8, 2026 at 5:38 PM Gyula Fóra <[email protected]> wrote: > > > > Hi Jingsong! > > > > Thanks for the feedback. > > I totally agree with you that the current design is going to be most > useful > > for datastream / user defined operators and may surface some "strange" or > > slightly unexpected internals to the users for SQL jobs and SQL > operators. > > > > Big +1 for the idea that we should add operator specific views later to > > expose some important sql operator internals in a more human readable > > format. And I also completely agree that this is out of scope for the > > initial V1 version.Based on the interest I see on this FLIP I think there > > will be a demand for a lot of similar extension capabilities once we get > > the initial physical/raw state view version out. > > > > Regarding the documentation requirements for transparency, this is a very > > important point and I couldn't agree more. In addition I think we will > have > > to clearly document and treat the contents of the state catalog as fully > > experimental initially. With the great variety of internal > representations > > and use-cases surrounding Flink states, it's impossible to get this right > > on the first try and our goal should be to iterate on this over a few > flink > > minor versions. > > > > So specifically: > > 1. The physical state representation of SQL and other built in operators > > is a Flink internal and not part of the public api. Therefore the > structure > > / schema of these tables are subject to change without notice across > Flink > > versions. > > 2. The StateCatalog itself including configuration, operator/state to > > table mapping, metadata views, etc. are all initially experimental and > > provide no backward compatibility guarantees and can change without > notice > > initially. > > > > I think 1. will stay like this for the foreseeable future , we do not > want > > to make internal implementations as part of the public api. We should aim > > to stabilize 2. and make it part of the public api eventually, and the > > views on the internal operators could hopefully become part of 2 as well. > > > > Cheers > > Gyula > > > > On Wed, Jul 8, 2026 at 2:55 AM Jingsong Li <[email protected]> > wrote: > > > > > Hi Gyula and all, > > > > > > Thanks for driving this FLIP. I like the overall direction and think > making > > > savepoint/checkpoint state discoverable and queryable from SQL would be > > > very > > > useful. > > > > > > I have one concern/question around how the catalog presents state from > SQL > > > operators. > > > > > > For many SQL operators, the internal state layout can be quite > different > > > from > > > the logical SQL model. For example, streaming joins, window > aggregations, > > > deduplication, TopN/rank, and other optimized operators may maintain > > > multiple > > > internal states, timers, namespaces, accumulators, or > optimization-specific > > > auxiliary structures. If these are exposed directly as SQL tables, the > > > result > > > may be difficult for users to understand. It may also accidentally > make an > > > internal state layout look like a stable user-facing contract, even > though > > > it > > > can change with planner/runtime optimizations or Flink versions. > > > > > > Would it make sense to explicitly distinguish two levels in the FLIP? > > > > > > 1. Physical/raw state views > > > > > > These are generic views derived from checkpoint/savepoint metadata and > > > serializer snapshots. They expose the actual operator UID, state name, > > > state > > > type, key/namespace/value schema, serializer information, etc. I think > > > this is > > > a very reasonable scope for the first version, especially for > debugging, > > > observability, migration, and advanced operational use cases. > > > > > > However, it would be good to document that these tables represent > Flink's > > > physical state layout and should not be treated as stable logical SQL > > > tables. > > > > > > 2. Optional logical/operator-aware views > > > > > > For some common SQL/runtime operators, we could later add > operator-specific > > > views or descriptors that explain the state in terms of operator > semantics. > > > For example, a join operator could expose left-side rows, right-side > rows, > > > and > > > timers in a more understandable way; a window aggregate could expose > window > > > accumulators and timer/namespace metadata. > > > > > > I do not think this needs to be part of the initial implementation, but > > > making > > > the distinction explicit would help set the right expectations and > avoid > > > over-promising what automatic state-to-table mapping can provide. > > > > > > So my suggestion is that V1 focuses on the generic physical/raw state > view, > > > with clear metadata and documentation, while leaving > logical/operator-aware > > > views as a possible extension. > > > > > > Best, > > > Jingsong > > > > > > On Wed, Jul 8, 2026 at 3:39 AM Roman Khachatryan <[email protected]> > wrote: > > > > > > > > > 1. The catalog built on the regular state processor api (and > therefore > > > > > flink state restore) capabilities has limited scope to detect > exactly > > > what > > > > > happens when a state is no longer there. This will probably lead to > > > read > > > > > errors/not found exceptions etc, some of which happens in code > that is > > > a > > > > > bit tricky to control this way. Let's see how well this works in > > > practice > > > > > and error handling can always be improved in general. This is not > part > > > of > > > > > the catalog design itself. > > > > > > > > Makes sense. I think this can also be an extension. > > > > To clarify the ownership/pinning follow-up idea: it could use FS > > > mechanisms > > > > rather than HA (ZK/etcd). For example, a separate file > > > > with the lowest checkpoint that Flink should keep, protected by CAS > and > > > > limited to a specified TTL. > > > > > > > > > 2. The proposal in it's current form includes a global state > metadata > > > view > > > > > based on the existing metadata information ([1]) and based on > > > Shengkai's > > > > > feedback a per operator granular metadata table/view that would > expose > > > > > information of individual states. I don't see where file level > > > information > > > > > fits into this but if you have a good way / idea how to represent > this > > > as > > > > a > > > > > table this can definitely be a future extension/addition > > > > > > > > I was thinking about something like: > > > > > > > > USE `00000000000000000000/chk-42`; > > > > SELECT * > > > > FROM state_handles; > > > > > > > > -- id type parent path > > > > size timestamp operator/state/subtask_index > > > > local_path key_range > > > > -- 0 FileStateHandle - > > > s3://.../_metadata > > > > 0.8Kb 2026-07-02T22:56:30 - > > > > - - > > > > -- 1 IncrementalRemoteKeyedStateHandle 0 > > > > - 2026-07-02T22:56:14 > > > > uid_transaction_aggregator_keyed/users#0 - 0 .. 127 > > > > -- 2 FileStateHandle 1 > > > > s3://.../xxxx-xxxx... 5.4Mb 2026-07-02T22:56:12 - > > > > 000034.SST - > > > > -- 3 FileStateHandle 1 > > > > s3://.../yyyy-yyyy... 872Kb 2026-07-02T22:56:12 - > > > > 000035.SST - > > > > -- 4 IncrementalRemoteKeyedStateHandle 0 > > > > - 2026-07-02T22:56:24 > > > > uid_transaction_aggregator_keyed/users#1 - 128 .. > 255 > > > > -- 5 ByteStreamStateHandle 4 > > > > 2Kb 2026-07-02T22:56:24 - > > > > 000001.SST - > > > > > > > > The idea is to represent CompletedCheckpoint as a DAG so that it maps > > > > directly to the layout of the object in-memory. > > > > > > > > > 3. Did not think about this but if this becomes a requirement we > could > > > add > > > > > a flag to enable metadata only in the catalog. > > > > > > > > For our use-case (multi-tenant cloud environment), separate access > models > > > > for > > > > data and metadata are very likely a must have because of the security > > > > concerns: > > > > - internally, the operators should have access to metadata, but not > to > > > the > > > > customer data > > > > - externally, the users should have access to their data but not to > the > > > > metadata > > > > > > > > 5, 6. Thanks! :) > > > > > > > > 7. Yes, this should be available since metadata V4. > > > > > > > > Regards, > > > > Roman > > > > > > > > > > > > On Tue, Jul 7, 2026 at 9:56 AM Gyula Fóra <[email protected]> > wrote: > > > > > > > > > Hey Shengkai! > > > > > > > > > > Thanks for the questions, you hit on some very good practical > points. > > > Let > > > > > me provide my answers below, in the meantime I have already > updated the > > > > > FLIP to include some of your suggestions :) > > > > > > > > > > 1. How would schema inference work for RowDataSerializer? > > > > > > > > > > That's a good observation, I did not notice this. Probably the > simplest > > > > > solution would be to introduce a new version in the > > > > > RowDataSerializerSnapshot and include the names for this use-case. > > > > > This would not really impact checkpointing times/performance but > would > > > > > allow a straightforward mapping for sql states. > > > > > > > > > > If we feel that this is too much internal change, then we could > also > > > keep > > > > > it as is for now using simply f0, f1... > > > > > > > > > > 2. Is one keyed-state table per operator the right abstraction? > > > > > > > > > > This is a very good point and something that has bothered me as > well > > > from a > > > > > design perspective. There is no single good abstraction here > because > > > there > > > > > are completely different use cases. > > > > > When you just want to look into the state for a single / multiple > keys > > > and > > > > > you mostly have simple value list states, the single table > > > representation > > > > > is superior from both query syntax and performance perspective. It > > > avoids > > > > > JOINS and maps to the simple mental model that for a certain key > you > > > have > > > > > state x,y,z. Due to this straightforward mental model I still think > > > this is > > > > > the good default representation. With projection pushdown, it's > easy to > > > > > select one/several specific columns without reading / touching any > > > other. > > > > > > > > > > The big issue is however with large collection states that simply > > > cannot be > > > > > represented within a single row. This happens very often and is > one of > > > the > > > > > main reasons someone would even use a list state (if they > understand > > > how > > > > > they work internally, but not all users do...). Large map, window, > list > > > > > states won't work in the simple row model and are completely > > > impractical. > > > > > > > > > > Based on this, my recommendation would be to keep all keyed states > in a > > > > > single table as per the original proposal (one column per keyed > state) > > > but > > > > > also add an extra table per list / map state with the flattened > schema. > > > > > So if the operator has a value and list state, then there would be > 2 > > > > > tables. One with both states as columns (as per original design) + > 1 > > > > > flattened list state table (key, index, value) or for map states > (key, > > > > > map_key, value). > > > > > > > > > > This way we cover both use cases naturally. I am also open to > making > > > this > > > > > configurable on the catalog level. > > > > > > > > > > I have added this to the FLIP > > > > > > > > > > 3. Could you clarify the assumption of "reading state without user > > > > > classes"? > > > > > > > > > > Turns out from an implementation perspective it's not too bad and > > > pojo/avro > > > > > state schemas can be inferred quite naturally for most cases. > However > > > if > > > > > the user indeed provides the user jar on the classpath then the > whole > > > > > schema resolution will become even simpler because then we do not > need > > > any > > > > > custom inference. For our own use-cases and in general I would not > > > like to > > > > > assume that user classes will be easily available or that a catalog > > > will > > > > > represent mostly a single application. On the contrary the way We > > > intend to > > > > > use this, is definitely mostly without userjars and to represent > > > multiple > > > > > applications at the same time. > > > > > > > > > > 4. Could StateCatalog expose more fine-grained metadata? > > > > > > > > > > I think this is a very good idea. I have updated the FLIP to > include an > > > > > operator level metadata table as well (one for each operator). I > would > > > love > > > > > to include everything that you suggested, I think the practical > limit > > > is > > > > > what kind of information is part of the checkpoint and what isn't . > > > This > > > > > also ties to some questions Roman had about more detailed metadata. > > > Makes > > > > > sense > > > > > > > > > > Cheers > > > > > Gyula > > > > > > > > > > > > > > > On Tue, Jul 7, 2026 at 4:59 AM Shengkai Fang <[email protected]> > > > wrote: > > > > > > > > > > > Hi Gyula, > > > > > > > > > > > > Thanks for the FLIP. I like the direction of making > > > savepoint/checkpoint > > > > > > state discoverable and queryable from SQL. I have a few > questions and > > > > > > concerns about the proposed abstraction. > > > > > > > > > > > > 1. How would schema inference work for RowDataSerializer? > > > > > > > > > > > > From the current RowDataSerializer snapshot, it looks like the > > > snapshot > > > > > > persists the LogicalType[] and nested serializer snapshots, so > the > > > field > > > > > > types can be restored. However, the top-level RowDataSerializer > > > > > constructed > > > > > > from a RowType seems to store only the child LogicalTypes, not > the > > > > > RowType > > > > > > field names. Would StateCatalog expose generated names such as > > > f0/f1, or > > > > > is > > > > > > there another source for recovering the original field names? > > > > > > > > > > > > 2. Is one keyed-state table per operator the right abstraction? > > > > > > > > > > > > I wonder whether one table per named keyed state would be a > better > > > base > > > > > > abstraction, with an optional operator-level wide view on top. In > > > > > > particular, MapState can contain an unbounded or highly variable > > > number > > > > > of > > > > > > entries per state key. Exposing it as a MAP<K,V> column may > require > > > fully > > > > > > deserializing the map for a key into heap. A normalized table > shape > > > such > > > > > > as: > > > > > > > > > > > > (state_key, map_key, map_value) > > > > > > > > > > > > seems more scalable and SQL-friendly for MapState. Similarly, > > > > > > ValueState/ListState/MapState have different natural table > shapes, so > > > > > tying > > > > > > the physical table boundary to the operator may be too coarse. > > > > > > > > > > > > 3. Could you clarify the assumption of "reading state without > user > > > > > > classes"? > > > > > > > > > > > > This is a very attractive goal, but it also seems to introduce > > > > > substantial > > > > > > complexity for POJOs, Avro SpecificRecord, subclasses, and custom > > > > > > serializers. If StateCatalog is positioned as a > > > > > job-level/application-level > > > > > > catalog, would requiring the job jar or user artifacts be > acceptable > > > as a > > > > > > first step? That might simplify the design while still covering > many > > > > > > operational/debugging use cases. > > > > > > > > > > > > 4. Could StateCatalog expose more fine-grained metadata? > > > > > > > > > > > > For debugging state, it would be useful to expose state-level > > > metadata > > > > > such > > > > > > as state name, state type, serializer snapshot/serializer class, > TTL > > > > > > configuration, namespace/window information where applicable, > backend > > > > > state > > > > > > type, and possibly whether a state can be read > lazily/streamingly. > > > > > > > > > > > > Best, > > > > > > Shengkai > > > > > > > > > > > > Roman Khachatryan <[email protected]> 于2026年7月7日周二 08:44写道： > > > > > > > > > > > > > Hi Gyula, > > > > > > > > > > > > > > Thanks for the proposal, this looks very useful! A few > questions > > > and > > > > > > > comments: > > > > > > > > > > > > > > 1. Following up on Han's question about checkpoint retention: I > > > > > > understand > > > > > > > external coordination is out of scope for now, but could the > > > catalog at > > > > > > > least detect that a checkpoint was subsumed/deleted mid-query > and > > > fail > > > > > > with > > > > > > > a clear error, rather than a low-level file-not-found? And do > you > > > see > > > > > > > ownership/pinning as a possible follow-up FLIP once checkpoint > > > reading > > > > > > > picks up adoption? > > > > > > > 2. Does the proposal allow querying file-level metadata (file > size, > > > > > > > creation date, etc.)? This would be useful for debugging > > > > > > compaction-related > > > > > > > issues. > > > > > > > 3. If yes, could data and metadata queries have separate access > > > modes? > > > > > In > > > > > > > many environments access to data is much stricter than access > to > > > > > > metadata, > > > > > > > so being able to grant metadata-only access to the catalog > would > > > > > broaden > > > > > > > where it can be deployed. > > > > > > > 4. Just to confirm: incremental checkpoints are expected to > work > > > > > through > > > > > > > the regular restore mechanisms, given sufficient retention? > > > > > > > 5. +1 on bringing non-keyed state into scope — a concrete use > case: > > > > > > > inspecting Kafka transaction state (currently stored in > non-keyed > > > > > > operator > > > > > > > state) would be very valuable for debugging EOS issues. > > > > > > > 6. Could you explain why timers are not supported? They live in > > > keyed > > > > > > state > > > > > > > and the state processor API can read registered timers, so I'm > > > > > wondering > > > > > > > whether this is a fundamental limitation or just table-mapping > > > scope. > > > > > > > 7. Does the proposal allow querying checkpoint metadata (such > as > > > > > > > SharingFilesStrategy, isSavepoint, etc.)? This could be useful > for > > > > > > > debugging CLAIM mode issues. > > > > > > > > > > > > > > > > > > > > > Regards, > > > > > > > Roman > > > > > > > > > > > > > > > > > > > > > On Mon, Jul 6, 2026 at 1:02 PM Gyula Fóra < > [email protected]> > > > > > wrote: > > > > > > > > > > > > > > > Hi Zakelly! > > > > > > > > > > > > > > > > That's a good point and we have to ensure that it works. In > > > theory > > > > > SQL > > > > > > > > related states are relatively easy to cover and represent. > The > > > > > RowData > > > > > > > > state would be mapped directly to ROW<...> similar to other > pojo > > > key > > > > > > > > states. > > > > > > > > > > > > > > > > Cheers > > > > > > > > Gyula > > > > > > > > > > > > > > > > On Sun, Jul 5, 2026 at 4:03 PM Zakelly Lan < > > > [email protected]> > > > > > > > wrote: > > > > > > > > > > > > > > > > > Hi Gyula, > > > > > > > > > > > > > > > > > > Thanks for driving this, it's a nice addition and I fully > > > support > > > > > it. > > > > > > > One > > > > > > > > > thing to make sure: > > > > > > > > > > > > > > > > > > For the state generated by some Flink SQL jobs, does the > > > > > StateCatalog > > > > > > > > infer > > > > > > > > > this internal `RowData` structure and expose it as a SQL > > > `ROW<...>` > > > > > > > type? > > > > > > > > > For example, a regular streaming join side may be stored > as a > > > state > > > > > > > such > > > > > > > > as > > > > > > > > > `left-records` / `right-records`, whose value or map > key/value > > > > > > > contains a > > > > > > > > > `RowData` for the original input row. > > > > > > > > > > > > > > > > > > > > > > > > > > > Best, > > > > > > > > > Zakelly > > > > > > > > > > > > > > > > > > On Fri, Jul 3, 2026 at 4:13 PM Dennis-Mircea Ciupitu < > > > > > > > > > [email protected]> wrote: > > > > > > > > > > > > > > > > > > > Hi Gyula, > > > > > > > > > > > > > > > > > > > > Thanks for the detailed answers. This addresses my > questions > > > well > > > > > > and > > > > > > > > the > > > > > > > > > > direction sounds great. > > > > > > > > > > > > > > > > > > > > +1 (non-binding) from my side. > > > > > > > > > > > > > > > > > > > > Best regards, > > > > > > > > > > Dennis > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > On Thu, Jul 2, 2026 at 3:26 PM Gyula Fóra < > > > [email protected]> > > > > > > > > wrote: > > > > > > > > > > > > > > > > > > > > > Hi Dennis! > > > > > > > > > > > > > > > > > > > > > > Thank you for the questions. Much recent work in the > state > > > > > > > connector > > > > > > > > > api > > > > > > > > > > > has been done basically towards this type of nice > > > cataloging > > > > > and > > > > > > > > > flexible > > > > > > > > > > > access. There are a few holes and things that have to > be > > > > > changed, > > > > > > > not > > > > > > > > > > > everything is enumerated in the FLIP but we have to > have an > > > > > open > > > > > > > mind > > > > > > > > > and > > > > > > > > > > > make all necessary changes as you said to make this > truly > > > nice > > > > > > and > > > > > > > > > > > comprehensive as much as possible. Most state processor > > > apis > > > > > are > > > > > > > > marked > > > > > > > > > > > experimental so we can be flexible within reason :) > > > > > > > > > > > > > > > > > > > > > > Now to the concrete questions: > > > > > > > > > > > > > > > > > > > > > > 1. Non-keyed state support / scope > > > > > > > > > > > I think non-keyed states should definitely be in the > scope > > > of > > > > > the > > > > > > > > FLIP > > > > > > > > > in > > > > > > > > > > > terms of design , and my intention was not to exclude > them > > > I > > > > > just > > > > > > > > > focused > > > > > > > > > > > on the keyed state as that is readily available in our > > > > > prototype > > > > > > > > > > > implementation (without much changes to the existing > > > > > > connectors). I > > > > > > > > > will > > > > > > > > > > > try to update the FLIP to include non-keyed states > more in > > > > > detail > > > > > > > > but I > > > > > > > > > > > think the case is pretty straightforward. From a table > > > > > > > representation > > > > > > > > > > > perspective, they can follow a similar pattern such as: > > > > > > > > > > > uid_opUID_statename_broadcast , > uid_opUID_statename_list > > > . A > > > > > > > > > > corresponding > > > > > > > > > > > SQL connector can easily be added to support these > based > > > on the > > > > > > > > > existing > > > > > > > > > > > datastream connector. I will make sure to add separate > > > tickets > > > > > > for > > > > > > > > > these > > > > > > > > > > > types of states once the FLIP is accepted and this > work can > > > > > very > > > > > > > > easily > > > > > > > > > > be > > > > > > > > > > > parallelized across different state types within the > > > existing > > > > > > > catalog > > > > > > > > > > > frameworks. This way keyed/non-keyed states will live > > > directly > > > > > > > > together > > > > > > > > > > in > > > > > > > > > > > a single catalog/db. > > > > > > > > > > > > > > > > > > > > > > In the future we can even go a step further and include > > > > > connector > > > > > > > > > > specific > > > > > > > > > > > state views such as kafka offsets etc with custom > connector > > > > > > > specific > > > > > > > > > > > plugins > > > > > > > > > > > > > > > > > > > > > > 2/3. Serializer transparency and robustness > > > > > > > > > > > From a practical standpoint both generated (synthetic) > > > > > > serializers > > > > > > > > and > > > > > > > > > > > custom classes / kryo and pluggable logic could work > but > > > the > > > > > > whole > > > > > > > > > > catalog > > > > > > > > > > > concepts requires a certain behaviour to be useful. The > > > catalog > > > > > > > would > > > > > > > > > > point > > > > > > > > > > > to savepoint directories and discover all state in it > > > > > > (potentially > > > > > > > > from > > > > > > > > > > > multiple jobs). Configuration has to be done in a > generic > > > way, > > > > > I > > > > > > > > don't > > > > > > > > > > see > > > > > > > > > > > a problem with introducing configs for specifying > custom > > > > > > > > > > > serializers/factories either generically for certain > > > specific > > > > > > > > classes. > > > > > > > > > In > > > > > > > > > > > most cases however this won't be necessary as the state > > > > > snapshot > > > > > > > > itself > > > > > > > > > > > usually has a reference (classname) of the original > user > > > > > classes. > > > > > > > If > > > > > > > > > the > > > > > > > > > > > catalog process has access to those classes it will use > > > that > > > > > > > > directly, > > > > > > > > > or > > > > > > > > > > > other confugred serializers, and only if not available > fall > > > > > back > > > > > > to > > > > > > > > > > > generating serializers for POJO/TUPLE types. There is > > > > > obviously a > > > > > > > > limit > > > > > > > > > > to > > > > > > > > > > > what is possible here initially, Kryo being one > exception > > > where > > > > > > you > > > > > > > > > > either > > > > > > > > > > > have the class or not. > > > > > > > > > > > > > > > > > > > > > > I would like to however point out that we do not have > to > > > > > support > > > > > > > > > > everything > > > > > > > > > > > initially, we can start with what is currently > available, > > > use > > > > > the > > > > > > > > > > classpath > > > > > > > > > > > / generated serializers and as we develop we will find > the > > > > > limits > > > > > > > of > > > > > > > > > this > > > > > > > > > > > approach and then can extend with configuration as it > feels > > > > > > natural > > > > > > > > > > instead > > > > > > > > > > > of trying to create a super complex initial solution. > But I > > > > > > > > definitely > > > > > > > > > > > agree that we should support custom serializer already > > > > > specified > > > > > > in > > > > > > > > the > > > > > > > > > > > config that is otherwise used by flink for the jobs > (but I > > > > > think > > > > > > > this > > > > > > > > > > > should more or less work out of the box). > > > > > > > > > > > > > > > > > > > > > > 4. The metadata view is currently reused based on the > > > existing > > > > > > > table > > > > > > > > > > valued > > > > > > > > > > > function. Let's take this as a followup under this > > > umbrella to > > > > > > > > improve > > > > > > > > > / > > > > > > > > > > > extend the metadata view. I don't think we need a > separate > > > FLIP > > > > > > but > > > > > > > > it > > > > > > > > > > also > > > > > > > > > > > feels out of scope here. > > > > > > > > > > > > > > > > > > > > > > Cheers > > > > > > > > > > > Gyula > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > On Thu, Jul 2, 2026 at 1:02 PM Dennis-Mircea Ciupitu < > > > > > > > > > > > [email protected]> wrote: > > > > > > > > > > > > > > > > > > > > > > > Hi all, > > > > > > > > > > > > > > > > > > > > > > > > Thank you for driving this. Being able to discover > > > > > > > > > > savepoints/checkpoints > > > > > > > > > > > > and query their state as SQL tables without shipping > the > > > > > > original > > > > > > > > > user > > > > > > > > > > > > classes is a genuinely valuable addition, and it's > nice > > > that > > > > > it > > > > > > > > > builds > > > > > > > > > > on > > > > > > > > > > > > the existing state-table connector and > savepoint_metadata > > > > > work > > > > > > > > rather > > > > > > > > > > > than > > > > > > > > > > > > starting from scratch. > > > > > > > > > > > > > > > > > > > > > > > > A few points and questions, mostly around scope and > the > > > > > > > serializer > > > > > > > > > > story: > > > > > > > > > > > > > > > > > > > > > > > > 1. Non-keyed state and the DataStream path. > > > > > > > > > > > > - The FLIP scopes out BroadcastState, operator > > > > > ListState > > > > > > > and > > > > > > > > > > > > UnionState because "no readily available Table > API > > > > > > > connectors > > > > > > > > > > exist > > > > > > > > > > > > for > > > > > > > > > > > > these state types." That's a fair > characterization > > > of > > > > > the > > > > > > > > Table > > > > > > > > > > > > layer, but > > > > > > > > > > > > the state-processor DataStream API already > reads > > > all > > > > > > three > > > > > > > > > today > > > > > > > > > > > > (SavepointReader#readBroadcastState / > > > #readUnionState / > > > > > > > > > > > > #readListState). So > > > > > > > > > > > > the limitation is really in the keyed-only SQL > > > mapping > > > > > > > > > > > > (KeyedStateReader > > > > > > > > > > > > runs inside a keyed backend), not in the > snapshots > > > > > > > > themselves. > > > > > > > > > > > > - Is the keyed-only scope a deliberate > > > UX/table-mapping > > > > > > > > > decision, > > > > > > > > > > > or > > > > > > > > > > > > would a DataStream-backed reader be considered > so > > > the > > > > > > > catalog > > > > > > > > > > isn't > > > > > > > > > > > > strictly less capable than the API it extends? > > > Even if > > > > > > > > > non-keyed > > > > > > > > > > > > contents > > > > > > > > > > > > stay out of scope initially, it would be good > to > > > frame > > > > > > this > > > > > > > > > > > > explicitly as a > > > > > > > > > > > > Table-mapping constraint rather than a general > one. > > > > > > > > > > > > 2. Serializer transparency - the "no user classes" > > > premise > > > > > > vs. > > > > > > > > > > custom > > > > > > > > > > > > serializers. > > > > > > > > > > > > - The design relies on Flink's transparent > > > serializer > > > > > > > formats > > > > > > > > > to > > > > > > > > > > > > decode state without user dependencies, which > is > > > great > > > > > > for > > > > > > > > > > > > POJO/Avro/basic > > > > > > > > > > > > types. But two serialization efforts point the > > > other > > > > > way: > > > > > > > > > > FLIP-398 > > > > > > > > > > > > [1] > > > > > > > > > > > > (released) already lets users configure > > > serializers per > > > > > > > type > > > > > > > > > via > > > > > > > > > > > > pipeline.serialization-config, and FLIP-538 > [2] (in > > > > > > > > discussion) > > > > > > > > > > > adds > > > > > > > > > > > > pluggable custom generic-type serializers (e.g. > > > Apache > > > > > > > Fory) > > > > > > > > > and > > > > > > > > > > > > promotes > > > > > > > > > > > > TypeSerializer/TypeSerializerSnapshot to > @Public. > > > As > > > > > > > FLIP-538 > > > > > > > > > > > > itself notes, > > > > > > > > > > > > state written with a custom serializer becomes > > > > > dependent > > > > > > on > > > > > > > > > that > > > > > > > > > > > > serializer > > > > > > > > > > > > to decode - external tooling without it cannot > read > > > > > those > > > > > > > > > bytes. > > > > > > > > > > > > - Could we make the deserialization side > pluggable > > > and > > > > > > > > > > > config-driven, > > > > > > > > > > > > mirroring FLIP-398's serialization-config, > with a > > > > > > graceful > > > > > > > > > > fallback > > > > > > > > > > > > (e.g. > > > > > > > > > > > > expose the raw bytes / skip the column) when a > > > format > > > > > > isn't > > > > > > > > > > > > transparently > > > > > > > > > > > > decodable? There already seems to be a seam for > > > this > > > > > > > > > > > > (SavepointTypeInformationFactory), and making > it a > > > > > > > > first-class, > > > > > > > > > > > > config-selectable option would keep the catalog > > > > > > > > > > forward-compatible > > > > > > > > > > > as > > > > > > > > > > > > serialization support grows. > > > > > > > > > > > > 3. Robustness of the transparent decoding path. > > > > > > > > > > > > - Related to (2): reconstructing values by > > > mirroring > > > > > the > > > > > > > > binary > > > > > > > > > > > > layout (PojoToRowDataDeserializer) is the most > > > powerful > > > > > > but > > > > > > > > > also > > > > > > > > > > > the > > > > > > > > > > > > most > > > > > > > > > > > > fragile part of the design. How is it expected > to > > > > > behave > > > > > > > > across > > > > > > > > > > > > serializer > > > > > > > > > > > > schema evolution / state migration (a > serializer > > > > > snapshot > > > > > > > > that > > > > > > > > > > > > differs from > > > > > > > > > > > > the writer's), Kryo-fallback fields, > nested/generic > > > > > > types, > > > > > > > > and > > > > > > > > > > > > nullability? > > > > > > > > > > > > - It would help to spell out the supported > matrix > > > and > > > > > the > > > > > > > > > failure > > > > > > > > > > > > mode (hard error vs. degrade to raw bytes) up > > > front, > > > > > > since > > > > > > > > this > > > > > > > > > > > > is exactly > > > > > > > > > > > > where "read without the user classes" is most > > > likely to > > > > > > > break > > > > > > > > > in > > > > > > > > > > > > practice. > > > > > > > > > > > > 4. Observability / summary reporting. > > > > > > > > > > > > - The metadata view is a great start. Two small > > > asks: > > > > > > > > > > > > - per-subtask (or per-key-group) size > > > granularity in > > > > > > > > > addition > > > > > > > > > > to > > > > > > > > > > > > per-operator, since skew is usually what > you are > > > > > > chasing > > > > > > > > on > > > > > > > > > > > > large state; > > > > > > > > > > > > - optionally rounding out the size breakdown > > > with > > > > > > > > > managed/raw > > > > > > > > > > > > operator state and channel state sizes for a > > > full > > > > > > > picture > > > > > > > > > > > (noting > > > > > > > > > > > > the > > > > > > > > > > > > latter are in-flight / unaligned-checkpoint > > > buffers > > > > > > > rather > > > > > > > > > > > > than user state). > > > > > > > > > > > > - A prominent upfront summary of the largest > > > operators > > > > > / > > > > > > > > state > > > > > > > > > is > > > > > > > > > > > > often what users want before drilling in. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > Best regards, > > > > > > > > > > > > Dennis > > > > > > > > > > > > > > > > > > > > > > > > [1] > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/spaces/FLINK/pages/282102217/FLIP-398+Improve+Serialization+Configuration+And+Usage+In+Flink > > > > > > > > > > > > [2] > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/spaces/FLINK/pages/373886828/FLIP-538+Support+Custom+Generic+Type+Serializer > > > > > > > > > > > > > > > > > > > > > > > > On Mon, Jun 29, 2026 at 12:53 PM Gyula Fóra < > > > > > [email protected] > > > > > > > > > > > > > > > > wrote: > > > > > > > > > > > > > > > > > > > > > > > > > Hi Flink Devs! > > > > > > > > > > > > > > > > > > > > > > > > > > I would like to start the discussion about > FLIP-599: > > > State > > > > > > > > Catalog > > > > > > > > > > [1] > > > > > > > > > > > > > > > > > > > > > > > > > > State and stateful processing has always been one > of > > > the > > > > > most > > > > > > > > > > > fundamental > > > > > > > > > > > > > features of Flink and a major contributor to its > > > success > > > > > and > > > > > > > > global > > > > > > > > > > > > > adoption. > > > > > > > > > > > > > > > > > > > > > > > > > > Over the years several apis and methods have been > > > developed > > > > > > to > > > > > > > > > > address > > > > > > > > > > > > the > > > > > > > > > > > > > need for external access and analytics such as the > > > state > > > > > > > > processor > > > > > > > > > > > > > datastream / java apis, the since deprecated > queryable > > > > > state > > > > > > > > > > > abstractions > > > > > > > > > > > > > and more recently a number of table / SQL api > > > connectors to > > > > > > > > access > > > > > > > > > > > state > > > > > > > > > > > > > metadata and keyed states in a somewhat limited > way. > > > > > > > > > > > > > > > > > > > > > > > > > > Extending the current capabilities of the > > > > > state-process-api, > > > > > > > this > > > > > > > > > > FLIP > > > > > > > > > > > > aims > > > > > > > > > > > > > to lift state processing, analytics and > observability > > > to a > > > > > > new > > > > > > > > > level > > > > > > > > > > > by > > > > > > > > > > > > > introducing the State Catalog. > > > > > > > > > > > > > > > > > > > > > > > > > > State Catalog is a Flink SQL Catalog implementation > > > that > > > > > > allows > > > > > > > > > > > > discovering > > > > > > > > > > > > > savepoints/checkpoints and mapping their state > > > > > automatically > > > > > > to > > > > > > > > SQL > > > > > > > > > > > > tables. > > > > > > > > > > > > > The tables are derived for the different operators > and > > > > > their > > > > > > > > keyed > > > > > > > > > > > states > > > > > > > > > > > > > with schema matching the state structure. Most > > > importantly > > > > > it > > > > > > > > > > supports > > > > > > > > > > > > > reading POJO / Avro and other structured and basic > type > > > > > > states > > > > > > > > > > without > > > > > > > > > > > > the > > > > > > > > > > > > > original user classes (dependencies) by relying on > > > Flink's > > > > > > > > > > transparent > > > > > > > > > > > > and > > > > > > > > > > > > > efficiently structured serializer formats. > > > > > > > > > > > > > > > > > > > > > > > > > > We have a fully functional prototype implementation > > > > > developed > > > > > > > > with > > > > > > > > > > > Gabor > > > > > > > > > > > > > Somogyi that we will be happy to share if the > community > > > > > > accepts > > > > > > > > the > > > > > > > > > > > > > proposal! > > > > > > > > > > > > > > > > > > > > > > > > > > Looking forward to your feedback and suggestions! > > > > > > > > > > > > > > > > > > > > > > > > > > Gyula > > > > > > > > > > > > > > > > > > > > > > > > > > [1] > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/spaces/FLINK/pages/438009922/FLIP-599+State+Catalog > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >
