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 > > > > > > > > > > > > > > >
