Everything you have to code manually requires explicit tests.
Immutables is a very mature library that has exceptionally good test
coverage that prevents a ton of accidental coding mistakes. We've been
using it for many many years in multiple projects and literally never
produced wrong code.
We already have code generators in the code base for openapi. I'd okay
to remove that, because the code generated by that generator is IMHO not
great.
Overall we should focus on the "real stuff" and not bother about
manually writing builders and really immutable types.
On 17.02.25 18:10, Michael Collado wrote:
I prefer native Java constructs over third party libraries and compiler
plugins, whenever possible. I’m a fan of Java records.
Mike
On Mon, Feb 17, 2025 at 6:55 AM Jean-Baptiste Onofré <j...@nanthrax.net>
wrote:
Hi Robert,
Yes, my intention about Java records (e.g.
https://openjdk.org/jeps/395) is to leverage:
- Devise an object-oriented construct that expresses a simple
aggregation of values.
- Focus on modeling immutable data rather than extensible behavior.
- Automatically implement data-driven methods such as equals and accessors.
- Preserve long-standing Java principles such as nominal typing and
migration compatibility.
- Provide inner builder, optionally with technical validation
(Objects.NotNull, etc), for instance:
public record CatalogDAO(String id, String name, ...) {
public static final class Builder {
String id;
String name;
public Builder() {}
public Builder id(String id) {
this.id = id;
return this;
}
public Builder name(String name) {
this.name = name;
return this;
}
public CatalogDAO build() {
return new CatalogDAO(id, name);
}
}
}
NB: that's just a "raw" example :)
That could help us for the "DAO" layer, with clean isolation and data
"transport". The "conversion" from Polaris Entity to DAO could be
performed by the intermediate logic layer (e.g.
PolarisMetaStoreManager), the pure persistence layer can deal with DAO
only (e.g. PolarisStore).
Good point about immutable collections. In some projects, I "force"
the copy of a collection to ensure immutability, something like:
record NamespaceDAO(Set<String> children) {
public NamespaceDAO {
children = Set.copyOf(children);
}
}
OK, that's not super elegant :) but it does the trick ;)
Regards
JB
On Mon, Feb 17, 2025 at 5:28 PM Robert Stupp <sn...@snazy.de> wrote:
Agree with JB, except I think "immutables" serves the need much better.
Java records are okay, but do not ensure that all fields are immutable -
especially collections. The other pro of immutables is that there are
proper, descriptive builders - hence no need to constructors with a
gazillion parameters.
On 17.02.25 11:42, Jean-Baptiste Onofré wrote:
Hi Yufei
I left comments in the PR.
Thanks for that. That's an interesting approach but slightly different
to what I had in mind.
My proposal was:
1. The DAOs are Java records clearly descriptive, without "storage
operations".
For instance, we can imagine:
public record CatalogDao(String id, String name, String location, ...)
{
...
}
public record NamespaceDao(String id, String name, String parent, ...)
{}
public record TableDao(String id, String name, ...) {}
etc
The advantages are:
- very simple and descriptive
- common to any backend implementation
2. The PolarisStore defines the DAO backend operations and mapping to
"internal" Polaris entities. Each persistence adapter implements the
PolarisStore.
For the persistence adapter implementer, he just has to implement the
DAO persistence (no need to understand other Polaris parts).
Each persistence adapter is in its own module (for isolation and
dependencies).
During the Polaris Persistence Meeting last week, we already got
consensus on the approach proposed by Dennis and I. I propose to do a
new sync/review with Dennis.
Regards
JB
On Mon, Feb 17, 2025 at 9:40 AM Yufei Gu <flyrain...@gmail.com> wrote:
Hi Folks:
Here is a POC for persistence layer refactor. Please check it out and
let
me know what you think. Please note this is a POC, we still need a
lot of
effort to complete the refactor.
PR: https://github.com/apache/polaris/pull/1011.
Design doc:
https://docs.google.com/document/d/1Vuhw5b9-6KAol2vU3HUs9FJwcgWtiVVXMYhLtGmz53s/edit?tab=t.0
Experiment:
- Added a DAO layer for the business entity namespace(except the
read).
- Integrated with existing DAO components
(PolarisMetaStoreManager and
PolarisMetaStoreSession).
- All tests passed successfully, including a manual local run
with Spark
sql.
Benefits:
- Compatible with the existing backend(FDB), as we hide it behind
the
new DAO.
- Adding new backends(Postgres/MongoDB) is much easier now, esp
for
Postgres, we could be able to use a similar model as Iceberg Jdbc
catalog.
- Allows gradual refactoring to remove old DAO dependencies
(PolarisMetaStoreManager and PolarisMetaStoreSession).
- Enables parallel development of new backend implementations.
Next Steps:
- Define business entities one by one to decouple them from FDB.
- Create DAO interfaces for each entity to standardize operations
(e.g.,
CRUD, ID generation).
- Expand DAO implementations to support additional backends over
time.
Yufei
--
Robert Stupp
@snazy
--
Robert Stupp
@snazy
