Using DashDB as a database (instead of a Data warehouse) - java

Note: This is not a programming question (at least at the moment). Once I start progressing further would seek assistance from the community on programming questions. Feel free to delete this, if this question is deemed inappropriate.
I am trying to start using DashDB as a Database on Bluemix. The DashDB data would be consumed by a Java/Java EE app
I am not planning to use this as a Data warehouse.
DashDB as I understand it has two flavours - Regular (using this term loosely here to refer to the standard offering ) and DashDB Transactional.
DashDB Transaction, i believe is used for transactional workloads.
I wanted to understand if JPA would play well with DashDB. I am unable to locate good information in this space.
Should we use denormalized design for both DashDB Regular and Transactional?

The dashDB Transactional Bluemix plan provides a dashDB database that is optimized for online transaction processing (OLTP). This means that it is designed for highly structured repetitive processing and it supports ACID transactions. That said you should use all the best practices you would use with a classic RDBMS: normalization, constraints and so on. I confirm that the dashDB-JPA integration is not well documented yet, but there should be no particular problem in using it with JPA. Since your application will run on Liberty Runtime, when you bind the dashDB service instance the server.xml is automatically configured with dataSource with a JNDI name and the database driver jars are also added.

JPA does not work seamlessly with DashDB today. DashDB uses organized by column be default and JPA does not work well with it. There is no specific way today to set organize by row using an annotation in JPA. We tried to override the DB2Dictionary but that did not work either.
If i drop the table using sql statement and recreate the table using sql statement appended with organize by row, then JPA is able to read the table.
Not sure who should be fixing this issue - JPA or DashDB :)

Related

JAVA - Bad practice to use both JPA and PreparedStatements?

I am writing a java application in which I am using Spring Boot and JPA in order to map classes to my database tables.
However, due to a somewhat complex database structure I also have the need of creating custom queries that are not mapped to any specific POJOs / Entities.
Therefore I am using PreparedStatement together with a DataSource with #Autowired annotation.
It hit me that using both of these DB Access methods might not be suitable to use together?
So far everything has worked out in my dev environment, but are there any pitfalls that I should look out for when using both of these together or is there a preferred way of doing custom queries when using JPA?
It should be noted that my database calls are fairly short and happen in a stateless manner, so there should hopefully not be any problems with interfering sessions (?)
JPA EntityManager will not know anything about your changes made with PreparedStatement. This will cause issues with JPA built-in caching, maybe with versioning and also with transaction support.
Though you may need to check this question: Is it OK to use both JPA (for normal CRUDs) and JDBC (for batch update & call stored proc) in the same project
Invan's answer makes a clear point.
On the other hand your fine when:
you need complex queries to SHOW data (read only).
you infrequently need to do some batch updates and do a clear cache entityManager.getEntityManagerFactory().getCache().evictAll()

Hibernate + MySQL Best practices for reporting data

I am creating a webapp in Spring Boot (Spring + Hibernate + MySQL).
I have already created all the CRUD operations for the data of my app, and now I need to process the data and create reports.
As per the complexity of these reports, I will create some summary or pre proccesed tables. This way, I can trigger the reports creation once, and then get them efficiently.
My doubt is if I should build all the reports in Java or in Stored Procedures in MySQL.
Pros of doing it in Java:
More logging
More control of the structures (entities, maps, list, etc)
Catching exceptions
If I change my db engine (it would not happen, but never know)
Cons of doing it in Java:
Maybe memory?
Any thoughts on this?
Thanks!
Java. Though both are possible. It depends on what is most important and what skills are available for maintenance and the price of maintaining. Stored procedures are usually very fast, but availability and performance also depends on what exact database you use. You will need special skills, and then you have it all working on that specific database.
Hibernate does come with a special dialect written for every database to get the best performance out of the persistence layer. It’s not that fast as a stored procedure, but it comes pretty close. With Spring Data on top of that, all difficulty is gone. Maintenance will not cost that much and people who know Spring Data are more available than any special database vendor.
You can still create various “difficult” queries easily with HQL, so no block there. But Hibernate comes with more possibilities. You can have your caching done by eh-cache and with Hibernate envers you will have your audit done in no time. That’s the nice thing about this framework. It’s widely used and many free to use maven dependencies are there for the taking. And if in future you want to change your database, you can do it by changing like 3 parameters in your application.properties file when using Spring Data.
You can play with some annotations and see what performs better. For example you have the #Inheritance annotation where you can have some classes end up in the same table or split it to more tables. Also you have the #MappedSuperclass where you can have one JpaObject with the id which all your entities can extend. If you want some more tricks on JPA, maybe check this post with my answer on how to use a superclass and a general repository.
As per the complexity of these reports, I will create some summary or
pre proccesed tables. This way, I can trigger the reports creation
once, and then get them efficiently.
My first thought is, is this required? It seems like adding complexity to the application that perhaps isn't needed. Premature optimisation and all that. Try writing the reports in SQL and running an execution plan. If it's good enough, you have less code to maintain and no added batch jobs to administer. Consider load testing using E.G. jmeter or gatling to see how it holds up under stress.
Consider using querydsl or jooq for reporting. Both provide a database abstraction layer and fluent API for querying databases, which deliver the benefits listed in the "Pros of doing it in Java" section of the question and may be more suited to the problem. This blog post jOOQ vs. Hibernate: When to Choose Which is well worth a read.

Hibernate OGM with mongodb in an enterprise solution

I wanted to ask you, if you have any experience that Hibernate OGM works as much fine with mongodb, that it could be used in an enterprise solution without any worries. With other words - does this combination work as fine as for example Hibernate ORM with MySQL and is is also that easy to set up? Is it worth to use it - meant the level of afford needed to set it up compared to the level of improvement of the work with the database? Would you prefer another OGM framework or even don't use any? I read about it some time ago, but it was in the early stages of this project and didn't work too well yet. Thanks for advices and experiences.
(Disclaimer: I'm one of the Hibernate OGM authors)
With other words - does this combination work as fine as for example Hibernate ORM with MySQL?
The 4.1 release is the first final we consider to be ready to use in production. The general user experience should be not much different from using the classic Hibernate ORM (which still is what you use under the hood when using Hibernate OGM). Also the MongoDB dialect probably is the one we put most effort in, so it is in good shape.
But as Hibernate OGM is a fairly young project, of course there may be bugs and glitches which need to be ironed out. Feature-wise, there are some things not supported yet (e.g. secondary tables, criteria API, more complex JPA queries), but you either shouldn't really need those in most kinds of applications or there are work-arounds (e.g. native queries).
and is is also that easy to set up?
Yes, absolutely. The set-up is not different from using Hibernate ORM / JPA with an RDBMS. You only use another JPA provider class (HibernateOgmPersistence) and need to set some OGM-specific options (which NoSQL store to use, host name etc.). Check out this blog post which walks you through the set-up. For store-specific settings (e.g. how to store associations in document stores) there is an easy-to-use option system based on annotations and/or a fluent API.
[Is it worth the effort] to set it up compared to the level of improvement of the work with the database?
I don't think there is a general answer to that. In many cases object mappers like Hibernate ORM/OGM are great, in others cases working with plain SQL or NoSQL APIs might be a better option. It depends on your use case and its specific requirements. In general, OxMs work well if there is a defined domain model which you want to persist, navigate its associations etc.
Would you prefer another OGM framework
I'm obviously biased, but let me say that using Hibernate OGM allows you to
benefit from the eco-system existing around JPA/Hibernate, be it integration with other libraries such as Hibernate Validator or Hibernate Search (or your in-house developed Hibernate-based API) or tooling such as modelling tools which emit JPA entities.
work with different NoSQL backends using the same API. So if chances are you need to integrate another NoSQL store (e.g. Neo4j to run graph queries) or an RDMBS, then Hibernate OGM will allow you to do so easily.
I read about it some time ago, but it was in the early stages of this project
Much work has been put into Hibernate OGM over the last year, so my recommendation definitely is to try it out and see in a prototype or spike how it works for your requirements.
If you have any feature requests or questions, please let us know and we'll see what we can do for you.

Combining SQL and NOSQL databases using Hibernate ORM and OGM

I have an application that uses SQL Server. I wanted to use a NOSQL store and I decided it to be graph since my data is highly connected. Neo4j is an option.
I want optimally to be able to switch the databases without touching the application layer, say, just modifying some xml configuration files.
I've taken a look at some examples public on the web, I've seen that ORM and OGM don't configure applications the same way, the config file of each has it's own name and more importantly its own structure. Looking at the code of each revealed that they also differ in the way they initialize the session, which doesn't sound good for what I'm thinking of.
My question is: "is it possible or feasible-without-great-overhead to switch between the two databases without touching the existing application code? I may add things but not touch what exists already". It would be a great idea to establish a pure polyglot persistence between SQL and NOSQL databases, for example, using Hibernate.
I want to hear from you guys before digging deeper. Do we have one of Hibernate men with us here in SO?
The goal of Hibernate OGM is to offer an unified abstraction for various NoSQL data stores. The project is still young, as we speak, so I am not sure if you can adopt it right out-of-the-box.
There is also the problem of transactions. If your application was designed to use SQL transactions, then things will radically change when you switch to a NOSQL solution.
Using an abstraction layer is good for portability but doesn't offer all the power of native querying. That's the same problem with JP-QL, which only covers SQL-92, lacking support for window functions or CTE.
Polyglot persistence is a great feature, but try using separate repositories, like Spring Data offers. I find that much more flexible from an architectural point of view.

How to change JPA 2.0 SQL/JPQL queries dynamically in production

I have a problem with the architecture of JPA 2.0/ORM,
in our production system (and i believe in a lot of systems) we need the ability to change the SQL queries dynamically because slow queries and bugs in queries that was exposed only in production (heavy load and heavy data),
as a result we used in stored procedures and call them from iBatis.
As i see the pattern, the best practice is to seperate between the DB layer and the application layer so i can tell to my DBA to fix buggy stored procedures/indexes tables in production without deployed new application (distribute system - long time of deployment).
In ORM/JPA 2.0 the named queries defined in the code and it's cause to the programmer to catch the whole DB problems in development/QA - very bad!
I saw in the API that the framework give an option to define native query - but in the books/tutorials the best practice is to use the named queries...
After i read the Hibernate/JPA 2.0 SPEC to see if there is a solution for this problem,
i understand that there is no solution...?
Its look to me very wired that i need to define the queries hard coded in the application code layer...
also to define the queries in XML descriptor and to load the XML via patch solution of hot deploy - very bad and not as standard!
Did you have design pattern/solution
Thank you all!!!
Uri.
I'd advise that you do unit and performance testing before you deploy. You shouldn't be finding out about buggy or slow queries at that late juncture.
JPA/ORM is not like iBatis, as you are finding out.
"Buggy" sounds like a lack of thorough unit testing.
"Slow" sounds like your DBAs aren't checking the SQL generated by JPA. EXPLAIN PLAN for all of it. You might have indexing or schema issues on the database side that no amount of playing with JPA will fix.
Patterns aren't the solution.
You should be able to have your entities read data from views as well as tables. Then the sql for the views can be altered on the fly.

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