How I unknowingly deviated from JPA

In a post from January 2015 I wrote about possibility to use plain foreign key values instead of @ManyToOne and @OneToOne mappings in order to avoid eager fetch. It built on the JPA 2.1 as it needed ON clause not available before and on EclipseLink which is a reference implementation of the specification.

To be fair, there are ways how to make to-one lazy, sure, but they are not portable and JPA does not assure that. They rely on bytecode magic and properly configured ORM. Otherwise lazy to-one mapping wouldn’t have spawned so many questions around the internet. And that’s why we decided to try it without them.

Total success

We applied this style on our project and we liked it. We didn’t have to worry about random fetch cascades – in complex domain models often triggering many dozens of fetches. Sure it can be “fixed” with second-level cache, but that’s another thing – we could stop worrying about cache too. Now we could think about caching things we wanted, not caching everything possibly reachable even if we don’t need it. Second-level cache should not exist for the sole reason of making this flawed eager fetch bearable.

When we needed a Breed for a Dog we could simply do:

Breed breed = em.find(Breed.class, dog.getBreedId());

Yes, it is noisier than dog.getBreed() but explicit solutions come with a price. We can still implement the method on an entity, but it must somehow access entityManager – directly or indirectly – and that adds some infrastructure dependency and makes it more active-record-ish. We did it, no problem.

Now this can be done in JPA with any version and probably with any ORM. The trouble is with queries. They require explicit join condition and for that we need ON. For inner joins WHERE is sufficient, but any outer join obviously needs ON clause. We don’t have dog.breed path to join, we need to join breed ON dog.breedId = But this is no problem really.

We really enjoyed this style while still benefiting from many perks of JPA like convenient and customizable type conversion, unit of work pattern, transaction support, etc.

I’ll write a book!

Having enough experiences and not knowing I’m already outside of JPA specification scope I decided to conjure a neat little book called Opinionated JPA. The name says it all, it should have been a book that adds a bit to the discussion about how to use and tweak JPA in case it really backfires at you with these eager fetches and you don’t mind to tune it down a bit. It should have been a book about fighting with JPA less.

Alas, it backfired on me in the most ironic way. I wrote a lot of material around it before I got to the core part. Sure, I felt I should not postpone it too long, but I wanted to build an argument, do the research and so on. What never occurred to me is I should have tested it with some other JPA too. And that’s what is so ironic.

In recent years I learned a lot about JPA, I have JPA specification open every other day to check something, I cross reference bugs in between EclipseLink and Hibernate – but trying to find a final argument in the specification – I really felt good at all this. But I never checked whether query with left join breed ON dog.breedId = works in anything else than EclipseLink (reference implementation, mind you!).

Shattered dreams

It does not. Today, I can even add “obviously”. JPA 2.1 specification defines Joins in section 4.4.5 as (selected important grammar rules):

join::= join_spec join_association_path_expression [AS] identification_variable [join_condition]
join_association_path_expression ::=
  join_collection_valued_path_expression |
  join_single_valued_path_expression |
  TREAT(join_collection_valued_path_expression AS subtype) |
  TREAT(join_single_valued_path_expression AS subtype)
join_spec::= [ LEFT [OUTER] | INNER ] JOIN
join_condition ::= ON conditional_expression

The trouble here is that breed in left join breed does not conform to any alternative of the join_association_path_expression.

Of course my live goes on, I’ve got a family to feed, I’ll ask my colleagues for forgiveness and try to build up my professional credit again. I can even say: “I told myself so!” Because the theme that JPA can surprise again and again is kinda repeating in my story.

Opinionated JPA revisited

What does it mean for my opinionated approach? Well, it works with EclipseLink! I’ll just drop JPA from the equation. I tried to be pure JPA for many years but even during these I never ruled out proprietary ORM features as “evil”. I don’t believe in an easy JPA provider switch anyway. You can use the most basic JPA elements and be able to switch, but I’d rather utilize chosen library better.

If you switch from Hibernate, where to-one seems to work lazily when you ask for it, to EclipseLink, you will need some non-trivial tweaking to get there. If JPA spec mandated lazy support and not define it as mere hint I wouldn’t mess around this topic at all. But I understand that the topic is deeper as Java language features don’t allow it easily. With explicit proxy wrapping the relation it is possible but we’re spoiling the domain. Still, with bytecode manipulation being rather ubiquitous now, I think they could have done it and remove this vague point once for all.

Not to mention very primitive alternative – let the user explicitly choose he does not want to cascade eager fetches at the moment of usage. He’ll get a Breed object when he calls dog.getBreed(), but this object will not be managed and will contain only breed’s ID – exactly what user has asked for. There is no room for confusion here and at least gives us the option to break the deadly fetching cascade.

And the book?

Well the main argument is now limited to EclipseLink and not to JPA. Maybe I should rename it to Opinionated ORM with EclipseLink (and Querydsl). I wouldn’t like to leave it in a plane of essay about JPA and various “horror stories”, although even that may help people to decide for or against it. If you don’t need ORM after all, use something different – like Querydsl over SQL or alternatives like JOOQ.

I’ll probably still describe this strategy, but not as a main point anymore. Main point now is that JPA is very strict ORM and limited in options how to control its behavior when it comes to fetching. These options are delegated to JPA providers and this may lock you to them nearly as much as not being JPA compliant at all.

Final concerns

But even when I accept that I’m stuck to EclipseLink feature… is it a feature? Wouldn’t it be better if reference implementation strictly complained about invalid JPQL just like Hibernate does? Put aside the thought that Hibernate is perfect JPA 2.1 implementation, it does not implement other things and is not strict in different areas.

What if EclipseLink reconsiders and removes this extension? I doubt the next JPA will support this type of paths after JOINs although that would save my butt (which is not so important after all). I honestly believed I’m still on the standard motorway just a little bit on the shoulder perhaps. Now I know I’m away from any mainstream… and the only way back is to re-introduce all the to-one relations into our entities which first kills the performance, then we turn on the cache for all, which hopefully does not kill memory, but definitely does not help. Not to mention we actually need distributed cache across multiple applications over the same database.

In the most honest attempt to get out of the quagmire before I get stuck deep in it I inadvertently found myself neck-deep already. ORM indeed is The Vietnam of Computer Science.

JPA – modularity denied

Here we are for another story about JPA (Java Persistence API) and its problems. But before we start splitting our persistence unit into multiple JARs, let’s see – or rather hear – how much it is denied. I can’t even think about this word normally anymore after I’ve heard the sound. 🙂

Second thing to know before we go on – we will use Spring. If your application is pure Java EE this post will not work “out of the box” for you. It can still help you with summarizing the problem and show some options.

Everybody knows layers

I decided to modularize our application, because since reading Java Application Architecture book I couldn’t sleep that well with typical mega-jars containing all the classes at a particular architecture level. Yeah, we modularize but only by levels. That is, we typically have one JAR with all entity classes, some call it “domain”, some just “jpa-entities”, whatever… (not that I promote ad-lib names).

In our case we have @Service classes in different JAR (but yeah, all of them in one) – typically using DAO for group of the entities. Complete stack actually goes from REST resource class (again in separate JAR, using Jersey or Spring MVC) which uses @Service which in turns talks to DAOs (marked as @Repository, although it’s not a repository in the pure sense). Complex logic is pushed to specific @Components somewhere under service layer. It’s not DDD, but at least the dependencies flow nicely from top down.

Components based on features

But how about dependencies between parts of the system at the same level? Our system has a lot of entity classes, some are pure business (Clients, their Transactions, financial Instruments), some are rather infrastructural (meta model, localization, audit trail). Why can’t these be separated? Most of the stuff depends on meta model, localization is quite independent in our case, audit trail needs meta model and permission module (containing Users)… It all clicks when one thinks about it – and it is more or less in line with modularity based on features, not on technology or layers. Sure we can still use layer separation and have permission-persistence and permission-service as well.

Actually, this is quite repeating question: Should we base packages by features or by layer/technology/pattern? From sources I’ve read (though I might have read what I wanted to :-)) it seems that the consensus was reached – start by feature – which can be part of your business domain. If stuff gets big, you can split them into layers too.

Multiple JARs with JPA entities

So I carefully try to put different entity classes into different JAR modules. Sure, I can just repackage them in the same JAR and check how tangled they are with Sonar, but it is recommended to enforce the separation and to make dependencies explicit (not only in the Java Application Architecture book). My experience is not as rich as of the experts writing books, but it is much richer compared to people not reading any books at all – and, gosh, how many of them is there (both books and people not reading them)! And this experience confirms it quite clearly – things must be enforced.

And here comes the problem when your persistence is based on JPA. Because JPA clearly wasn’t designed to have a single persistence unit across multiple persistence.xml files. So what are these problems actually?

  1. How to distribute persistence.xml across these JARs? Do we even have to?
  2. What classes need to be mentioned where? E.g., we need to mention classes from upstream JARs in persistence.xml if they are used in relations (breaks DRY principle).
  3. When we have multiple persistence.xml files, how to merge them in our persistence unit configuration?
  4. What about configuration in persistence XML? What properties are used from what file? (Little spoiler, you just don’t know reliably!) Where to put them so you don’t have to repeat yourself again?
  5. We use EclipseLink – how to use static weaving for all these modules? How about a module with only abstract mapped superclass (some dao-common module)?

That’s quite a lot of problems for age when modularity is so often mentioned. And for technology that is from “enterprise” stack. And they are mostly phrased as questions – because the answers are not readily available.

Distributing persistence.xml – do I need it?

This one is difficult and may depend on the provider you use and the way you use it. We use EclipseLink and its static weaving. This requires persistence.xml. Sure we may try keep it together in some neutral module (or any path, as it can be configured for weaving plugin), but it kinda goes against the modularity quest. What options do we have?

  • I can create some union persistence.xml in module that depends on all needed JARs. This would be OK if I had just one such module – typically some downstream module like WAR or runnable JAR or something. But we have many. If I made persistence.xml for each they would contain a lot of repetition. And I’d reference downstream resource, which is ugly!
  • We can have dummy upstream module or out of module path with union persistence.xml. This would keep things simple, but it would be more difficult to develop modules independently, maybe even with different teams.
  • Keep persistence.xml in the JAR with related classes. This seems best from modularity point of view, but it means we need to merge multiple persistence.xml files when the persistence unit starts.
  • Or can we have different persistence unit for each persistence.xml? This is OK, if they truly are in different databases (different JDBC URL), otherwise it doesn’t make sense. In our case we have rich DB and any module can see the part it is interested in – that is entities from the JARs it has on the classpath. If you have data in different databases already, you’re probably sporting microservices anyway. 🙂

I went for third option – especially because EclipseLink’s weaving plugin likes it and I didn’t want to redirect to non-standard path to persistence.xml – but it also seems to be the right logical way. However, there is nothing like dependency between persistence.xml files. So if you have b.jar that uses a.jar, and there is entity class B in b.jar that contains @ManyToOne to A entity from a.jar, you have to mention A class in persistence.xml in b.jar. Yes, the class is already mentioned in a.jar, of course. Here, clearly, engineers of JPA didn’t even think about possibility of using multiple JARs in a really modular way.

In any case – this works, compiles, weaves your classes during build – and more or less answers questions 1 and 2 from our problem list. And now…

It doesn’t start anyway

When you have a single persistence.xml, it will get found as a unique resource, typically in META-INF/persistence.xml – in any JAR actually. But when you have more of them, they don’t get all picked and merged magically – and the application fails during startup. We need to merge all those persistence.xml files during the initialization of our persistence unit. Now we’re tackling questions 3 and 4 at once, for they are linked.

To merge all the configuration XMLs into one unit, you can use this configuration for PersistenceUnitManger in Spring (clearly, using MergingPersistenceUnitManager is the key):

public PersistenceUnitManager persistenceUnitManager(DataSource dataSource) {
    MergingPersistenceUnitManager persistenceUnitManager =
        new MergingPersistenceUnitManager();
    // default persistence.xml location is OK, goes through all classpath*
    return persistenceUnitManager;

But before I unveil the whole configuration we should talk about the configuration that was in the original singleton persistence.xml – which looked something like this:

    <property name="eclipselink.weaving" value="static"/>
    <property name="eclipselink.allow-zero-id" value="true"/>
Without this there were other corner cases when field change was ignored. This can be worked-around calling setter, but that sucks.
    <property name="eclipselink.weaving.changetracking" value="false"/>

The biggest question here is: What is used during build (e.g. by static weaving) and what can be put into runtime configuration somewhere else? Why somewhere else? Because we don’t want to repeat these properties in all XMLs.

But before finishing the programmatic configuration we should take a little detour to shared-cache-mode that showed the problem with merging persistence.xml files in the most bizarre way.

Shared cache mode

Firstly, if you mean it seriously with JPA, I cannot recommend enough one excellent and comprehensive book that answered tons of my questions – often before I even asked them. I’m talking about Pro JPA 2, of course. Like, seriously, go and read it unless you are super-solid in JPA already.

We wanted to enable cached entities selectively (to ensure that @Cacheable annotations have any effect). But I made a big mistake when I created another persistence.xml file – I forgot to mention shared-cache-mode there. My persistence unit picked both XMLs (using MergingPersistenceUnitManager), but my caching went completely nuts. It cached more than expected and I was totally confused. The trouble here is – persistence.xml don’t get really merged. The lists of classes in them do, but the configurations do not. Somehow my second persistence XML became dominant (one always does!) and because there was no shared-cache-mode specified, it used defaults – which is anything EclipseLink thinks is the best. No blame there, just another manifestation that JPA people didn’t even think about this setup scenarios.

It’s actually the other way around – you can have multiple persistence units in one XML, that’s a piece of cake.

If you really want to get some hard evidence how things are in your setup, put a breakpoint somewhere where you can reach your EntityManagerFactory, and when it stops there, dig deeper to find what your cache mode is. Or anything else – you can check the list of known entity classes, JPA properties, … anything really. And it’s much faster than mess around just guessing.

jpa-emf-debuggedIn the picture above you can see, that now I can be sure what shared cache mode I use. You can also see which XML file was used, in our case it was from meta-model module (JAR), so this one would dominate. Luckily, I don’t rely on this anymore, not for runtime configuration at least…

Putting the Spring configuration together

Now we’re ready to wrap up our configuration and move some stuff from persistence.xml into Spring configuration – in my case it’s Java-based configuration (XML works too, of course).

Most of our properties were related to EclipseLink. I read their weaving manual, but I still didn’t understand what works when and how. I had to debug some of the stuff to be really sure.

It seems that eclipselink.weaving is the crucial property namespace, that should stay in your persistence.xml, because it gets used by the plugin performing the static weaving. I debugged maven build and the plugin definitely uses eclipselink.weaving.changetracking property value (we set it to false which is not default). Funny enough, it doesn’t need eclipselink.weaving itself, because running the plugin implies you wish for static weaving. During startup it gets picked though, so EclipseLink knows it can treat classes as statically weaved – which means it can be pushed into programmatic configuration too.

The rest of the properties (and shared cache mode) are clearly used at the startup time. Spring configuration may then look like this:

@Bean public DataSource dataSource(...) { /* as usual */ }

public JpaVendorAdapter jpaVendorAdapter() {
    EclipseLinkJpaVendorAdapter jpaVendorAdapter = new EclipseLinkJpaVendorAdapter();
        Database.valueOf(env.getProperty("jpa.dbPlatform", "SQL_SERVER")));
    return jpaVendorAdapter;

public PersistenceUnitManager persistenceUnitManager(DataSource dataSource) {
    MergingPersistenceUnitManager persistenceUnitManager =
        new MergingPersistenceUnitManager();
    // default persistence.xml location is OK, goes through all classpath*

    return persistenceUnitManager;

public FactoryBean<EntityManagerFactory> entityManagerFactory(
    PersistenceUnitManager persistenceUnitManager, JpaVendorAdapter jpaVendorAdapter)
    LocalContainerEntityManagerFactoryBean emfFactoryBean =
        new LocalContainerEntityManagerFactoryBean();

    Properties jpaProperties = new Properties();
    jpaProperties.setProperty("eclipselink.weaving", "static");
        env.getProperty("eclipselink.allow-zero-id", "true"));
        env.getProperty("eclipselink.logging.parameters", "true"));
    return emfFactoryBean;

Clearly, we can set the database platform, shared cache mode and all runtime relevant properties programmatically – and we can do it just once. This is not a problem for a single persistence.xml, but in any case it offers better control. You can now use Spring’s @Autowired private Environment env; and override whatever you want with property files or even -D JVM arguments – and still fallback to default values – just as we do for database property of the JpaVendorAdapter. Or you can use SpEL. This is flexibility persistence.xml simply cannot provide.

And of course, all the things mentioned in the configuration can now be removed from all your persistence.xml files.

I’d love to get rid of eclipselink.weaving.changetracking in the XML too, but I don’t see any way how to provide this as the Maven plugin configuration option, which we have neatly unified in our parent POM. That would also eliminate some repeating.

Common DAO classes in separate JAR

This one (question 5 from our list) is no problem after all the previous, just a nuisance. EclipseLink refuses to weave your base class regardless of @MappedSuperclass usage. But as mentioned in one SO question/answer, just add dummy concrete @Entity class and you’re done. You never use it, it is no problem at all. And you can vote for this bug.

This is probably not problem for load-time weaving (haven’t tried it), or for Hibernate. I never had to solve any weaving problem with Hibernate, but on the other hand current project pushed my JPA limits further, so maybe I would learn something about Hibernate too (if it was willing to work for us in the first place).

Any Querydsl problems?

Ah, I forgot to mention my favourite over-JPA solution! Were there any Querydsl related problems? Well, not really. The only hiccup I got was NullPointerException when I moved some entity base classes and my subclasses were not compilable. Before javac could have printed reasonable error, Querydsl went in and gave up without good diagnostic on this most unexpected case. 🙂 I filed an issue for this, but after I fixed my import statements for the superclasses, everything was OK again.


Let’s do it in bullets, shall we?

  • JPA clearly wasn’t designed with modularity in mind – especially not when modules form a single persistence unit, which is perfectly legitimate usage.
  • It is possible to distribute persistence classes into multiple JARs, and then:
    • You can go either with a single union persistence.xml, which can be downstream or upstream – this depends, if you need it only in runtime or during build too.
    • I believe it is more proper to pack partial persistence.xml in each JAR, especially if you need it during build. Unfortunately, there is no escape from repeating some upstream classes in the module again, just because they are referenced in relations (typical culprit when “I don’t understand how this is not entity, when it clearly is!”).
  • If you have multiple persistence.xml files, it is possible to merge them using Spring’s MergingPersistenceUnitManager. I don’t know if you can use it for non-Spring applications, but I saw this idea reimplemented and it wasn’t that hard. (If I had to reimplement it, I’d try to merge the configuration part too!)
  • When you’re merging persistence.xml files, it is recommended to minimize configuration in them, so it doesn’t have to be repeated. E.g., for Eclipselink we leave only stuff necessary for built-time static weaving, the rest is set programmatically in our Spring @Configuration class.

There are still some open questions, but I think they lead nowhere. Can I use multiple persistence units with a single data source? This way I can have each persistence.xml as a separate unit. But I doubt relationships would work across these and the same goes for transactions (without XA that is). If you think multiple units is relevant solution, let me know, please.

I hope this helps if you’re struggling with the noble quest of modularity. Don’t be shy to share your experiences in the comments too! No registration required. 😉

EclipseLink joins without mapped attributes

EDIT April 2016: Originally I believed I described pure JPA 2.1 solution, much later I found it is merely an EclipseLink extension to the JPQL that is not supported in standard.

OK, whoever knows it is possible, just stop reading right away (before my JPA rant starts). Note, that this post builds on JPA 2.1 syntax for ON and EclipseLink extension that allows to join root entities (JPA specification allows only association paths).

JPA is hard

Java Persistence API is not easy – let’s face it. Please. Because it is easy only for two kinds of programmers – those that know everything (again, congratulation) and those who think they know everything. Or something similar. While I’m all for minimizing complexity to make things easy, it is known fact that making things simple (that is non-complex) is hard. Everytime I hear “no problem, that’s easy” I know what I’ll get. Complex ball of mud that does not correspond to “easy” at all.

I’ve read parts of Hibernate reference, I’ve read Pro JPA 2/2.1 – and I’d love to read it all finally, but there is always something else to read too. And so while I was aching for solution how to get rid of some my @Many/OneToOne mappings from entities (because these are not guaranteed to be lazy and can trigger too many selects), I thought I couldn’t because I’ll be unable to join in the direction of that association. I was wrong, but first…

Can’t you avoid triggered selects for *ToOne somehow?

Yes, you can. You can eagerly fetch that association with JOIN, some smart ORMs do that for you to some depth. Let’s talk about this example:

A Dog points to a Breed. How can I populate a table on the user interface with selected attributes from the dog and its breed as well?

  • The worst case (and still traditionally used!) – select Dogs and don’t care. This will likely result in N+1 select (officially name does not reflect the cause and effect – as it is rather 1+N). This plain sucks. I really don’t know why some mainstream ORM solutions still execute this as N+1 even when it’s eager (*ToOne is by default), but that just underlines… well, the state of ORM, obviously.
  • Fetch the relationship! Of course. It is bound to happen anyway, so let’s deal with it in one select. Does it mean we’re done in single select? If you have more *ToOne relations on your Dog – or Breed – then you’re not. Any fetch may trigger additional selects for further to-one relation.
  • Fetch and select columns explicitly. This works, but you have to deal with Lists of arrays of Objects, or – in better case – Querydsl’s handy Tuple. Or you may use projection to DTO. When you need to do this with 60 columns you’ll know the pain.

But yes, it is possible. The question is if it’s worth to use JPA if 80% of time you go around these problems. Depending on relationship optionality you need to use LEFT JOIN of course. “Use LEFT JOIN, Luke!” is my answer when another developer asks me questions like “when I want to display fields from breed, some rows just disappear from my results!” or similar with a bit of fun in it “count select returns different count than is the size of final result!” – because you don’t need to join for count unless you perform WHERE part on joined columns.

Summed up, it’s hard. Gone is the premise that you’ll enjoy working with some mapped objects. No, no, deal with Lists of Object[] or DTOs! It’s hard to say what is better – DTO in theory, but if the list of columns is changing a lot then it’s just another place you’ll have to change. If you still use vanilla JPA, consider Querydsl, seriously. Tuple may be lightweight DTO for you and on the other side you can get the stuff out using expression paths that are compile time safe – without the need to mess with accessors. (Old enough to remember this article? :-))

Dropping @ManyToOne annotation

(The same applies for @OneToOne where relevant.)

To write left join from Dog to Breed you can find virtually exclusively examples like this (Querydsl, but the same goes for JPQL):

QBreed breed = new QBreed(“breed”); // alias
List<Tuple> result = new JPAQuery().from(
  .leftJoin(, breed)

That is, in left join you first state the path how to get to the breed from the dog and then you assign an alias to it (breed). Sometimes you can live without aliases, but in general you need them for any deeper joins. Notice also how the leftJoin implies ON clause. This is logical and expected, that’s why we have the mapping there.

But thing I never realized (and decided to try it the first time today) is that you can just leftJoin to alias and add your ON explicitly – just like you would in SQL! (This is not JPA standard, but EclipseLink QL extension. Querydsl does not have any problem to generate it for you.)

QBreed breed = new QBreed(“breed”); // alias
List<Tuple> result = new JPAQuery().from(

Obviously you have to have breedId attribute mapped on Dog – but that is probably some plain type like Integer. This will not trigger any additional select. If you really want, you can have dual mapping for the same column like this:

@Column(name = "breed_id", insertable = false, updatable = false)
private Integer breedId;

@ManyToOne(fetch = FetchType.LAZY)
@JoinColumn(name = "breed_id")
private Breed breed;

Notice the insertable/updatable=false – this has to be present on one of those mappings. The question is on which one. If you save/update the entity a lot and breed’s ID is good enough then move it to @JoinColumn annotation. But if you don’t need Breed in most cases at all, remove it completely. Also notice how the code is lying to you about LAZY fetch. It is not. In theory it can be with some byte-code modified Breed (Hibernate does it out of the box), but that is not portable anyway. If you absolutely need that attribute in Dog class, you can still make it @Transient, fetch it and list it explicitly (here I show it for singleResult for brevity):

QBreed breed = new QBreed(“breed”); // alias
Tuple result = new JPAQuery().from(
  .singleResult(, breed);
Dog dog = result.get(;
dog.setBreed(result.get(breed)); // sets transient field

No problem at all. Full control. Couple of lines longer. Probably way more performant on scale.

What if JPA allowed us to ignore relations on demand?

If you use only id value that copies exactly FK in your entities then you’ll lose some of the ORM benefits – but as said you’ll also dump a lot of its burden that is in many cases unconsidered. Imagine you could specify mappings like this:

@Column(name = "breed_id")
@ManyToOne(targetEntity = Breed.class) // exists, but invalid when types don’t match
private Integer breedId;

This way you’d say what the target entity is, generated metamodels could offer you joins, etc. I’m not going to evolve this idea at all because there are some obvious disadvantages. Your JOIN path would be dog.breedId, not breed, so if you followed it to Breed’s attributes it would read confusingly (assuming that when used as a path it would act as Breed of course). Then maybe this:

@ManyToOne(fetch = FetchType.JOIN_ONLY) // does not exist
@JoinColumn(name = "breed_id")
private Breed breed;

This would mean that unless you require JOIN explicitly in your select this field will NOT be populated. Actually, this would be best to combine with dual mapping as shown sooner. ID is easy to get without JOIN – and referenced entity would be insertable/updatable false. Otherwise semantics of save would be questionable. Does null mean that entity is removed and FK should be nulled? Or does it mean to ignore it? Should JPA ignore it you need that explicit breedId field. If not ignored even trivial find/change single attribute/save (or let it happen automatically at the transaction commit) would delete your relation unexpectedly. You can add some dirty checking magic of course (“if the attribute changes then do that, otherwise don’t do anything”), but we’d just add to existing mess. So this definitely breaks “least surprise” principle. But with dual mapping that is already possible, I’d love to have this really lazy fetch type.

In case you wonder why LAZY is not guaranteed (without byte-code modification magic) – the answer is that breed attribute should be null only if NULL in database. So if the FK is there, you need to instantiate some Breed and if that supposes to be lazy, it has to be some kind of proxy to a real one that is lazily loaded when you actually touch (get something from) the breed object. This is very easy with collections (*ToMany) and ORM’s can do that (although Eclipselink’s Vector is spectacularly wrong way to do it) – that’s why I’m so possessed with *ToOne problem.

There is also another alternative solution – we would have Breed instantiated as a wrapper for the FK value. That is would not be null, but other attributes of dog.breed would not be initialized. Programmer would have to know – after all he requested it this way. That would allow the mapping to be still object based, but we would have more low-level control over the fetches.

Is it still ORM?

With dual mapping or with FK wrapper it would still be ORM as we know it. You’d have bigger control, single em.find would not trigger 47 selects (real story, seriously, and all traversing *ToOne relationships) and there would be minimal implications to JPA (although there are more competent to say so or otherwise).

Currently I plan to drop quite a lot of *ToOne mappings because:

  • There is no portable way to avoid the fetch when I know I don’t want it.
  • When I want it, I can join it myself anyway.
  • If I want to pick specific relation I can just find it by ID that is available on the entity (and then store it to @Transient field for example).

Am I still using it as ORM then? I’m dropping a lot of “mappings” of my “relations(hips)” from my “objects”. But I can still utilize a lot of JPA (and Querydsl). There still is persistence context, you can use L2 cache (if you want), and maybe you don’t have uber-cool mapping to your domain… but let’s face it. How often we really map it? How often we just mirror our databases?

Do you map @ManyToMany or do you map the association table with two IDs instead? With explicit mapping you can get list of IDs of related object by ID of owning object. In SQL it is a single table query. Eclipselink joins Master, MasterDetail and Detail to get information that is clearly available on MasterDetail table alone (not mapped explicitly). Is it so difficult to treat IDs properly? It probably is. How does ORM lower the complexity here?

Execution postponed

JPA adds tons of accidental complexity every time. Not first, but later. And virtually all teams working with it have no real JPA expert. I study JPA more than most people I know and it still keeps surprising me. Rarely in a good way. Left join using unrelated alias (at least from mapping point of view) and explicit ON is the good one. I don’t even know why I never tried it when I officially longed for it! I ranted: “Why don’t we have free joins on any numbers (PK/FK) just like SQL can do?” And nobody ever contradicted me. Most examples always start with path going from FROM entity, using alias only as their second argument (Querydsl, but JPQL examples are the same). We are slaves of our *ToOne relations and can’t get rid of undesired selects – and there is a simple way how to do it all the time. Partial reason for this is that ON for JOIN requires JPA 2.1 and didn’t work before.

If you don’t care about *ToOne problem, no problem. To be fair, if you have lazy set up properly you may be happy with it. If you do want to get rid of to-one relations the treatment is:

  • Replace your *ToOne mapping with simple ID as a value attribute.
  • Change anyJoin(x.y, alias) to anyJoin(alias).on(x.yId.eq( – this is Querydsl example but it transforms to JPQL directly. List both entities in projection if you need it (maybe you just WHERE on it).
  • If you really want +1 select, do it with em.find yourself. That may actually use L2 cache (if it’s not in the persistence context already).

With this tiny speck of knowledge I’m backing off from my plans to get rid of ORM in our project (you can imagine what pain that would be). Now it gives me so-so enough control to contain the select explosions to required levels.

EDIT 2016: Just to repeat it – this is based on EclipseLink support for JOIN for root entities. Maybe it will get into JPA eventually (I’d love it), but as of 2.1 it is not there. ON condition is there already, but without root entity JOIN it is not enough.


JPA – is it worth it? Horror stories with EclipseLink and Hibernate

One friend of mine brought Hibernate to our dev-team back in 2004 or so. But now he uses something much simpler and avoids ORM/JPA whenever possible. He can, because he is mostly master of his projects.

I had to get more familiar with JPA on my path. There is always more and more to learn about it. When you discover something like orphanRemoval = true on @OneToMany, it may bring you to the brink of crying. Because of happiness of course. (Stockholm Syndrome probably.) But then there are other days, when you just suffer. Days when you find bugs in JPA implementations – or something close to them. And you actually can’t choose from so many providers, can you? There are just two mainstream players.

Right now we are using EclipseLink and there are two bugs (or missing features or what) that kinda provoked our big effort to switch to Hibernate. What were our problems and what was the result of our switch? Read on…

EclipseLink and Java 8

You can avoid this problem, although you have to be extra careful. EclipseLink’s lazy list – called IndirectList – cannot be used with streams. Actually – if it didn’t compile, it would be good. Worse is it works but very badly.

Guys creating Java do their best to make streams work effortlessly, there are those default methods in interfaces, etc. But no, no luck here. IndirectList returns empty stream. Why? Because of this bug. (It works fine for IndirectSet.)

What is the cause of this problem? Well… someone decided to extend Vector, but instead of sticking with it, they also decided that the extended Vector will not be the actual backing collection, but they added their Vector delegate too. This works fine for interfaces like List, but not so for extended things. Now add “ingenious” design of Vector – full of protected fields you have to take care of… here IndirectList clearly collided with Vector badly.

Why do you need to take care of protected fields? Because creating the stream on Vector uses its special java.util.Vector.VectorSpliterator, that uses these protected values. So if you delegate to other Vector, you either delegate java.util.Vector#spliterator too (but then it won’t compile with earlier Java) or – preferably – don’t delegate to other vector and use that extended one as your backing collection. Of course, guys at Java might have used size() and get(int) instead of accessing Vector’s protected elementCount, elementData, etc. – but that would not be as efficient.

BTW: Anybody here likes Vector? I personally hate Java’s wannabe compatibility that really hurts its progress as we need to drag more and more burden with us.

JPA and counts on joins with distinct

The other trouble was related to a specific select where we used join with distinct instead of subquery with exists. We have an entity called Client that can be bound to any number of Domains, @ManyToMany mapping is used on Client side. Domain does not know about Client – hence the arrow.


We often need to obtain Clients where any of their domains is in a provided list (actual input parameter contains IDs of those domains). Using Querydsl, it looks like this:

QDomain cd = new QDomain("cd");
JPAQuery query = new JPAQuery(em).from(QClient.client)
    .join(, cd)

I’m sure you can easily transform it mentally to Criteria or JPQL – Querydsl produces JPQL, BTW. Distinct here has a special meaning that is used by JPA specification. Now you can call query.list(QClient.client) – it produces nice join and returns only distinct Clients. You try query.count(), and it works as expected as well.

But imagine that Client has composite primary key. We actually have exactly the same case, an entity bound again to domains, everything looks the same – just that entity has composite PK. List works alright, but if you try query.count() you’ll get completely different illogical query using exists and the join to Domains is lost completely. Results are wrong, definitely not the size of the list result.

There are some bugs filed for this – for instance this one. Because there was a discussion about this behavior we decided to find out how Hibernate treats this.


The trouble is that it is not the bug after all – at least not according to JPA 2.1specification which reads in section 4.8.5: The use of DISTINCT with COUNT is not supported for arguments of embeddable types or map entry types.

I found this today when I was gathering proofs for this post. Our story however would unfold in different direction. Are we using JPA? Yes. Are there other options? Yes!

Spoiler 2:

We used subselect with exists in the end, but that’s not the point. 😉

So we switch to Hibernate, right?

We got kinda carried away by some bug reports resolved as FIXED – like this one or the ones you can see in its links. But switching JPA provider isn’t that easy as promised. In the end we found out that count distinct for entities with composite PKs doesn’t work with SQL Server anyway. But we learned a lot of interesting things about how far both implementations are apart when it comes to translating JPQL to SQL. Mind you, I’m not actually sure whether everything we wrote in Querydsl (that generates JPQL) is 100% correct, but then it should say something. When it works I expect it to work after changing a JPA implementation.

Hibernate screwing deletes with “joins”

We have a lot of delete clauses that worked just fine in EclipseLink:

new JPADeleteClause(em, QGuiRolePermission.guiRolePermission)

This essentially means “delete all role permission assignments for role with specified description”. Piece-a-cake, right? We’re using implicit join there again, but it is the same story all over again – and it worked in EclipseLink just fine. EclipseLink creates proper SQL with exists:

  SELECT t1.gui_role_id FROM GUI_Roles t0, GUI_RolePermissions t1
    WHERE ((t0.description = ?) AND ( = t1.gui_role_id)) AND t1.gui_role_id = GUI_RolePermissions.gui_role_id
      AND t1.domain_id = GUI_RolePermissions.domain_id AND t1.permission_id = GUI_RolePermissions.permission_id)

It is not perfect – and we get back to it in section Random Query Generator – but it works. Let’s just compare it to Hibernate now. This is JPQL (actually this is the same for both providers as it’s produced by Querydsl):

delete from GuiRolePermission guiRolePermission
  where guiRolePermission.guiRole.description = ?1

This does not seem alarming – but the SQL is completely off:

delete from GUI_RolePermissions cross join GUI_Roles guirole1_ where description=?

This does not work on our currently used SQL Server, whatever dialect we choose. Why not go with exists? We have helper method that takes entity (Querydsl base path) and its where condition and performs delete. Now instead of:


We have to write this:

    new JPASubQuery().from(QGuiRolePermission.guiRolePermission)

Not terrible… but why? EDIT 2016-01-07: There is an issue filed for this, so far not fixed.

Another Hibernate’s twist

Things may get complicated when more relationships are involved. Take this simple JPQL for instance:

delete from Security security
  where security.issuer.priority = ?1

We want to remove all Securities with issuer (Client) having specific priority value:


There is another implicit join there, but one subquery with exists should cover it. Security class contains @ManyToMany relationships to Domain class through intermediate table Securities_Domains. That’s why we need two deletes here – and this is what EclipseLink generates (issuer is of class Client):

  SELECT FROM "Clients" t0, Securities t1
    WHERE ((t0."priority" = ?) AND (t0."id" = t1."issuer_id"))
      AND = Securities_Domains.security_id);
  SELECT FROM "Clients" t0, Securities t1
    WHERE ((t0."priority" = ?) AND (t0."id" = t1."issuer_id"))
      AND =;

It works just fine. But Hibernate shows its muscles really strong here!

delete from Securities_Domains where (security_id) in (
   select id from Securities where priority=?)

Obviously right the first delete is missing join to the Client entity in that subselect – and fails spectacularly. And we’re actually lucky we don’t have any other column called priority on Securities as well. 🙂 That could hide the error for ages.

With or without id?

Love that song… I mean the U2 one, not the Hibernate’s one. When you see JPQL with equality test on two entities you assume it is performed on their ids. So if you actually specify those ids, it should be still the same, right? Maybe it’s just some JPA myth after all. Consider this JPQL:

delete from MetaObjectSetup metaObjectSetup
  where not exists (select 1 from Permission permission
    where permission.metaObjectSetup = metaObjectSetup)

This produces query that does not work properly, probably taking last id from permission1_.

delete from META_Object_Setups where  not (exists (
  select 1 from Permissions permission1_
    where permission1_.meta_object_setup_id=id))

Version working with Hibernate must perform eq on id fields explicitly (EclipseLink doesn’t mind either):

   new JPASubQuery().from(QPermission.permission)

SQL result:

delete from META_Object_Setups where  not (exists (
  select 1 from Permissions permission1_

Experiences like these were the last drop for us and we reverted all the efforts to start using Hibernate.

Happy ending?

We switched back to EclipseLink after this. I don’t remember so much resistance from Hibernate like… ever. Maybe our JPQLs were too loose for it, joins were not explicit, aliases were missing, etc. But in the end it did not solve our problem.

It is really shame that count and distinct are not possible in the way making using query.list and query.count operations consistent in libraries like Querydsl. It is also shame that when it is not supported (as officially stated in the specification) it does not throw exception and does something fishy instead – silently.

You can do the same in SQL wrapping the select into another one with count – but JPQL does not support queries in the FROM clause. Pitty. However this is one of those cases when you can’t go wrong with correlated subquery. You just have to remember that subquery does not imply any equality implied by JPA joins (it can’t actually, there are cases when this would be an obstacle) and you have to do it yourselves – see the last examples from previous part (With Or Without Id).

This is all really crazy. Remotely, it reminds me horror stories about JSF and bugs of its various implementations (always different). Sure, things are really complicated, but then maybe the trouble is they are. Maybe it can be simpler. Maybe it’s wrong that I have to define @ManyToOne to be able to express joins. (Edit: Not true for JPA 2.1 as fixed in this post.) Any @XToOne has consequences often unseen even by experienced JPA users. Maybe some jOOQ or Querydsl over plain SQL is better than this stuff. I just don’t know…

Random Query Generator in EclipseLink

Let’s look at something else while we stick with JPA. Here we are back to Eclipse and there is one very easy thing I want to do in SQL:

  SELECT FROM Clients t0 WHERE ((t0.priority = ?) AND =

In plain wording – I want to remove all Client’s Contacts when this Client has some specific priority. If you ask for mapping… I hope there is nothing screwed here:

@Table(name = "Clients")
public class Client {
    @OneToMany(mappedBy = "client", cascade = CascadeType.ALL)
    private List<ClientContact> contacts;

@Table(name = "Contacts")
public class ClientContact {
    @Column(name = "client_id", insertable = false, updatable = false)
    private Integer clientId;

    @JoinColumn(name = "client_id")
    private Client client;

Back reference to client is mapped both ways, but one mapping is read-only. Both primary keys are simple Integers. No miracles here. And now three ways we tried, always with Querydsl, JPQL and SQL:

new JPADeleteClause(em, QClientContact.clientContact).where(
    new JPASubQuery().from(QClient.client)

// JPQL - logically exactly what we want
delete from ClientContact clientContact
  where exists (select client from Client client
    where client.priority = ?1 and client = clientContact.client)

// SQL contains double EXISTS and two unnecessary Clients more
    SELECT ? FROM Clients t2, Clients t1
      WHERE ((t2.priority = ?) AND ( = t0.client_id)))  AND =
bind => [1, 47]

Ok, it works, right? Can we help it when we mention id equality explicitly (…

new JPADeleteClause(em, QClientContact.clientContact).where(
    new JPASubQuery().from(QClient.client)

// JPQL looks promising again, I bet this must generate proper query - or at least the same
delete from ClientContact clientContact
  where exists (select client from Client client
    where client.priority = ?1 and =

// Three clients?!
    SELECT ? FROM Clients t3, Clients t2, Clients t1
      WHERE (((t2.priority = ?) AND ( = AND ( = t0.client_id)))
        AND =
bind => [1, 47]

You gotta be kidding me, right? What for?! I always believed that if id is entitie’s @Id, than it can do virtually the same with or without it. I even dreamt about using foreign key directly – but that’s way beyond capabilities of current JPA providers, so it seems.

Ok, let’s try something lame. Something I’d write only in JPA, not in real SQL, of course. Something with a lot of implicit identity equality hidden between the lines:

new JPADeleteClause(em, QClientContact.clientContact)

// not like SQL at all, but pretty logical if you know the mapping
delete from ClientContact clientContact
  where clientContact.client.priority = ?1

/* Surprise! Still one unnecessary Contacts in inner join that could go through FK,
 * but definitely the best result so far.
 * Mind though - this refused to work with Hibernate, at least with SQL Server dialect (any). */
  SELECT FROM Clients t0, Contacts t1
    WHERE ((t0.priority = ?) AND ( = t1.client_id)) AND =
bind => [47]

I hope this demonstrates the impotence of this field of human activity after more than a decade of effort. I’m not saying it all sucks – but after seeing this I’m not far from that.

With JPA doing too many things you don’t want or expect (unless you’re an expert) and many limitations compared to SQL I’d expect at least semi-good SQL. This is not close really.

Ramble On

So that’s another day with JPA. With proper query (or best approximation when it’s not critical) there is just one last thing we have to pay attention to… those IndirectLists that can’t be streamed. Just one last thing I said? Ouch… of course, we have to check our SQLs still and watch for any bugs or gray zones.

Yeah, we’re staying with JPA for a while on this project. But the next one I’ll start with metamodel directly over DB. I hope I can’t suffer more that way. 🙂 And maybe I’ll be able to do ad-hoc joins without @XToY annotations that always bring in stuff you don’t want. That’s actually one of my biggest gripes with JPA.

Many people avoid as much relation mappings as possible while they still can express their joins. Many people avoid @ManyToMany and map the association table explicitly, so they can reach all entities A for B’s id (or list of ids) – with a single join. Otherwise EclipseLink stubbornly joins all three tables as it’s understanding of PKs and FKs is obviously lacking.

Lessons learned? Not that much actually. But we’re definitely not switching provider for another couple of months at least!

JPA Pagination of entities with @OneToMany/@ManyToMany

Displaying paginated results of entities with their *-to-many sub-entities is a tricky thing and many people actually don’t even know about the problems. Let’s check what JPA does and what it does not for you. Besides standard JPA I’ll use Querydsl for queries – this effectively results in JPQL. Querydsl is type-safe and compared to Criteria API much more readable.

Source of N+1 select problem

Imagine having an entity called User that can have many Roles. Mapping looks like this:

@JoinTable(name = "user_roles",
  joinColumns = @JoinColumn(name = "user_id", referencedColumnName = "id"),
  inverseJoinColumns = @JoinColumn(name = "role_id", referencedColumnName = "id"))
@ManyToMany(fetch = FetchType.EAGER)
private Set<Role> roles;

You want to display a paginated list of users that contains list of their roles – for instance as tiny icons with tooltips containing role names.

Naive approach is to query the Users and then wait for whatever may come:

QUser u = QUser.user; // we will use this alias further
List<User> result = new JPAQuery(em).from(u)
    .offset((page - 1) * pageSize)

Now something may or may not happen. Simple select from USER is definitely executed and if you don’t touch user.role that will be all. But you want those roles and you want to display them – for instance when you iterate the results. Each such access executes another select from ROLE where user_id = iterated user’s id. This is the infamous N+1 select problem (although the order is rather 1+N :-)). It is extremely bad for selects with large result sets, while for pages N has reasonable limits. But still – no reason to do additional 25 selects instead of… how many actually?

Left join for the help?

Were the mapping @…ToOne, then you could just left join this entity (e.g. user’s Address assuming there is a single address needed for a user). Left join in this case does not change the number of rows in the result – even for optional addresses, whereas inner join would omit users without addresses (also surprisingly common error for programmers who try to avoid SQL for no good reasons).

Left join for *ToOne relations is good solution for both paginated and non-paginated results.

But for *ToMany paginating and left join don’t go well together. The problem is that SQL can only paginate rows of the resulting join, it cannot know the proper offset and limit to select for instance second user only. Here we want page 2 with page size 2:

List<User> result = new JPAQuery(em).from(u)

The result is delivered in a single select – but what a result…

We definitely don’t want User1 with a single RoleC and User2 with RoleA. That is not only not the page we want (we should get User3 on the final page 2), but it’s just plain disinformation (aka lie).

(Don’t) Use Eager!

For most cases EAGER mapping for *ToMany is not a good default. But in case you’re asking what will happen… JPA provider at least knows at the time of select from USER that we want the ROLEs too. EclipseLink performs N additional selects to get users’ roles although it utilizes any cached data possible. Actually I tested it with cache turned off with these lines in persistence.xml:

<property name="eclipselink.query-results-cache" value="false"/>
<property name="eclipselink.cache.shared.default" value="false"/>
<property name="eclipselink.cache.size.default" value="0"/>
<property name="eclipselink.cache.type.default" value="None"/>

Cache can bring some relief, but it actually just obscures the problem and may mislead you that the problem is not there. Especially if you create the data using JPA just before the test. 🙂

In case of LAZY JPA provider has to wait when we touch the role list – and it always loads only the one that is needed. But for our page we need to check all of them, so we will end up with N selects again. Provider has no way to optimize for this, not to mention that you may end up with LazyInitializationException (your fault) unless you use OSIV (open session in view), which I consider bad design after my previous experiences with it.

If provider knows that you want the roles upfront (EAGER) it may optimize, but I would not count on that. EclipseLink does not, and you simply cannot know. So let’s just do it ourselves, shall we? And switch that EAGER back to LAZY, which is default, so you can just as well remove the fetch parameter altogether.

1+1 select, no problem

We need to get the proper page of users and then load their roles. There are two ways how to do this:

  1. if you have reverse mappings (role.users) then you can get List<User> and then select roles containing these roles;
  2. if there is no reverse mappings, you list users first and then again with left join to roles – again only where user is in the first list.

In both cases list of user IDs may be enough. Because our role does not have reverse mapping (I don’t like it that much for @ManyToMany relations) we end up with code like this:

List<Integer> uids = find.queryFrom(u)
List<GuiUser> users = find.queryFrom(u)

What you display is the result of the second query, obviously. There are two important points here though:

  • You have to repeat the order. While in the first select it is essential for paging (paging without order is meaningless, right?) in the second case you could do it in memory, but there is no reason why, as you let DB to order just a single page and you save Java lines of code. Not to mention Java possibly (and quite probably!) using different collator… this really is not worth it.
  • You have to use distinct() before the list() of the second query. This not only adds distinct to the select, but also instructs Querydsl or JPA (really don’t know who does the job, sorry :-)) to give you the list of distinct users, not list of size of that joined select. Such distinct is required in most leftJoins on *ToMany entities (unless you create projection results for them).

1+1 for OneToMany

Now let’s pretend we have different situation – some @OneToMany case, like an Invoice and its Items. Item will have invoice attribute and Invoice will have @OneToMany items mapped by Item.invoice – like this:

@OneToMany(<b>mappedBy = "invoice"</b>)
private Set<Item> items;

And now the select part:

QInvoice i = QInvoice.invoice;
Map<Integer, Invoice> invoices = find.queryFrom(i)
    .map(, i);
// this performs items = new HashSet<>() for each invoice

QItem ii = QItem.item;
List<Item> items = find.queryFrom(ii)
for (Item item : items) {
    // addItem is always nicer than getItems().add(item)

Always check what selects are generated in the end. In my case performs no additional join and puts ids into the IN list – and that’s how it should be.

Also note the usage of map(, i) – this returns LinkedHashMap, so the order is preserved (cool!) and makes getting the invoice for item much easier. Difference in select is just one redundant id which is no problem at all.


We demonstrated the essential problem with pagination of one/many-to-many joins and checked two solutions that are both based on one additional select. These solutions are not necessary if pagination is not required, obviously. There may be other ways to do it, there are even some extensions for specific JPA providers (like @BatchFetch for EclipseLink), but I’d prefer this for couple of reasons:

  • Full control over selects – well, at least as full as you can get with Querydsl over JPQL. You can select into DTOs, you can enumerate required columns – there is much more you can do around the basic idea. (Funny. Just minutes after writing this sentence I travelled home from work, reading neat little book SQL Performance Explained – and coincidentally I was going through the part about Joins and Nested Loops. Markus Winard provided also short analysis of ORMs in various languages, how they perform joins and what you can do about it. The final tip was pretty clear about it: Get to know your ORM and take control of joins.)
  • It scales! There is no N. As long as your pagination is reasonably fast (but this is separate problem and you have to do what you have to do), second select goes after IDs, which should be pretty fast anyway.
  • It is unrelated to any specific features of any specific JPA provider.
  • And after all – you have full control over your contract. Don’t leave presentation layer trigger your selects. Even better – close that persistence context after leaving the service layer.

The only problem you should be aware of is limitation about amount of expressions in the IN clause. Check it out, read documentation (both for your JPA provider and RDBMS), experiment, find out what the maximum page size will be – and (obviously) cover it in your tests (at least when it crashes the first time ;-)).

The most important takeaway from this post should be: 1) EAGER is not a solution, 2) result of the left join with “to-many” cardinality cannot be reasonably paginated in SQL. We’re not talking about specific solutions here – hell, clever DB guys can even provide you procedures delivering you the right page plus total count of all records – all in a single call to DB. But that’s beyond basic SQL/JPA. 🙂