I am Working on multiple database like MSSQL server and PostgreSQL with heavy transactions and complex queries. I have searched that simple jdbc is more faster then ORM. I was thinking of using ORM because I do not want to write different query for different database for same work, and also for standardized my dao layer. I am mapping my database tables without using foreign keys and for ORM like apache cayenne I have to map tables with foreign key constraint, so I can use my Joins or any other multiple table operations. Is it good to use and ORM or simple jdbc is fine.
From your problem dscription, you already have an understanding of the tradeoffs involved. So this is really a decision that you need to make for yourself based on those tradeoffs.
My only advice here will be to take a second look at performance requirements. While ORM does introduce an overhead of creating, storing and managing objects, in all but a few cases, you can safely ignore this overhead for the sake of a better abstraction. Also when working with JDBC very often you end up writing your own code to convert ResultSet to objects, which will encounter its own overhead. So you may not end up with faster code, while forfeiting all the benefits of a clean object model and a framework that manages it.
So my own preference is to go with a better abstraction (ORM in this case), and then use the framework tools for optimizing the performance. E.g. to speed up processing of large ResultSets Cayenne provides a few techniques: result iterators, DataRow queries, paginated queries, etc.
On the other hand I would use JDBC or something like MyBatis when it is not possible to cleanly model your data as entities. E.g. when there are no natural relationships, all access happens via stored procedures, etc. Doesn't seem like your case though.
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I am currently working on a project where I have to retrieve some rows from the database based on some filters (I also have to paginate them).
My solution was to make a function that generates the queries and to query the database directly (it works and it's fast)
When I presented this solution to the senior programmer he told me this is going to work but it's not a long-term solution and I should rather use Spring Specifications.
Now here comes my questions :
Why is Spring Specifications better than generating a query?
Is a query generated by Spring Specifications faster than a normal query?
Is it that big of a deal to use hard-coded queries ?
Is there a better approach to this problem ?
I have to mention that the tables in the database don't store a lot of data, the biggest one (which will be queried the least) has around 134.000 rows after 1 year since the application was launched.
The tables have indexes on the rows that we will use to filter.
A "function that generates the queries" sounds like building query strings by concatenating smaller parts based on conditions. Even presuming this is a JPQL query string and not a native SQL string that would be DB dependent, there are several problems:
you lose the IDEs help if you ever refactor your entities
not easy to modularize and reuse parts of the query generation logic (eg. if you want to extract a method that adds the same conditions to a bunch of different queries with different joins and aliases for the tables)
easy to break the syntax of the query by a typo (eg. "a=b" + "and c=d")
more difficult to debug
if your queries are native SQL then you also become dependent on a database (eg. maybe you want your integration tests to run on an in-memory DB while the production code is on a regular DB)
if in your project all the queries are generated in a way but yours is generated in a different way (without a good reason) then maintenance of the will be more difficult
JPA frameworks generate optimized queries for most common use cases, so generally speaking you'll get at least the same speed from a Specification query as you do from a native one. There are times when you need to write native SQL to further optimize a query but these are exceptional cases.
Yes, it's bad practice that makes maintenance a nightmare
I have multiple migrations (say around 10) and the corresponding models for the tables. The problem I am facing is that all the migrations/tables have multiple primary keys but the model has just a string variable to define primary key ($primaryKey), hence, when I save or update a table row using where clause it would just take one primary key and miss the other and hence end up changing multiple rows instead of one. So, basically I switched to DB Queries and it worked well.
So, my question to you is that is there any performance gain with model? Or it is just a designing paradigm? Is there any option to do the same thing (Have multiple primary key) within a model? I know by overriding the Eloquent methods we can do this but is there any other good option?
Using an ORM like Eloquent is a convenience, not a requirement. From what I've heard there's actually often a slight performance decrease when using an ORM because there's the additional overhead of translating that query into the relevant SQL.
Often, using an ORM makes for queries that are much easier to understand, and for that reason alone it's worth using. However, for more complex queries, an ORM is likely to get in the way, and so you should consider using another method to query the database. You don't have to use just an ORM - you can mix and match the different methods as you see fit.
Laravel has the Query Builder as an alternative to writing raw SQL or using the ORM, and that may be a better option for you here. I would avoid writing raw SQL if you can because both Eloquent and the Query Builder will handle escaping the parameters for you, to help avoid SQL injection vulnerabilities.
My choice would be to use the ORM where possible, and fall back to the Query Builder when the ORM gets in the way.
I have an MVC3 NHibernate/ActiveRecord project. The project is going okay, and I'm getting a bit of use out of my model objects (mostly one giant hierarchy of three or four classes).
My application is analytics based; I store hierarchial data, and later slice it up, display it in graphs, etc. so the actual relationship is not that complicated.
So far, I haven't benefited much from ORM; it makes querying easy (ActiveRecord), but I frequently need less information than full objects, and I need to write "hard" queries through complex and multiple selects and iterations over collections -- raw SQL would be much faster and cleaner.
So I'm thinking about ditching ORM in this case, and going back to raw SQL. But I'm not sure how to rearchitect my solution. How should I handle the database tier?
Should I still have one class per model, with static methods to query for objects? Or should I have one class representing the DB?
Should I write my own layer under ActiveRecord (or my own ActiveRecord-like implementation) to keep the existing code more or less sound?
Should I combine ORM methods (like Save/Delete) into my model classes or not?
Should I change my table structure (one table per class with all of the fields)?
Any advice would be appreciated. I'm trying to figure out the best architecture and design to go with.
Many, including myself, think the ActiveRecord pattern is an anti-pattern mainly because it breaks the SRP and doesn't allow POCO objects (tightly coupling your domain to a particular ORM).
In saying that, you can't beat an ORM for simple CRUD stuff, so I would keep some kind of ORM around for that kind of work. Just re-architect your application to use POCO objects and some kind or repository pattern with your ORM implementation specifics in another project.
As for your "hard" queries, I would consider creating one class per view using a tiny ORM (like Dapper, PetaPoco, or Massive), to query the objects with your own raw sql.
According to Martin Fowler:
... "Client objects construct query
specifications declaratively and
submit them to Repository for
satisfaction" ...
Why? What are the advantages at that point?
I see one disadvantage: database queries are spread and hidden over ties. That makes it harder to debug.
The advantage is that the "what" (the declarative specification) is separated from the "how" or implemenation details. So the client doesn't need to know whether it's querying a relational database, a Web service, an object database (eg Mongo), an XML data store, etc.
Let's assume you're using an RDBMS. Even so, the client is isolated from needing to know whether the database is Oracle, MS SQL, SQLite, mySQL, PostGres, etc. This will save you a lot of headache when the commandment "thou shalt (not) use MS SQL" (or whatever) comes down from the mountain.
The additional layer does introduce some overhead. But (1) ORM tools like (N)Hibernate are quite good at optimizing the generated queries for whatever back-end you're using, and (2) the overhead is generally negligible compared to the cost of database read, let alone a web service call.
We're converting from LINQ to NHibernate right now to avoid the "N+1" problem (ie you generate one query/hit for each "master" database record, plus a query/hit for each "child" record).
And BTW ... there is such a thing as LINQ to NHibernate.
I have a daily batch process that involves selecting out a large number of records and formatting up a file to send to an external system. I also need to mark these records as sent so they are not transmitted again tomorrow.
In my naive JDBC way, I would prepare and execute a statement and then begin to loop through the recordset. As I only go forwards through the recordset there is no need for my application server to hold the whole result set in memory at one time. Groups of records can be feed across from the database server.
Now, lets say I'm using hibernate. Won't I endup with a bunch of objects representing the whole result set in memory at once?
Hibernate does also iterate over the result set so only one row is kept in memory. This is the default. If it to load greedily, you must tell it so.
Reasons to use Hibernate:
"Someone" was "creative" with the column names (PRXFC0315.XXFZZCC12)
The DB design is still in flux and/or you want one place where column names are mapped to Java.
You're using Hibernate anyway
You have complex queries and you're not fluent in SQL
Reasons not to use Hibernate:
The rest of your app is pure JDBC
You don't need any of the power of Hibernate
You have complex queries and you're fluent in SQL
You need a specific feature of your DB to make the SQL perform
Hibernate offers some possibilities to keep the session small.
You can use Query.scroll(), Criteria.scroll() for JDBC-like scrolling. You can use Session.evict(Object entity) to remove entities from the session. You can use a StatelessSession to suppress dirty-checking. And there are some more performance optimizations, see the Hibernate documentation.
Hibernate as any ORM framework is intended for developing and maintaining systems based on object oriented programming principal. But most of the databases are relational and not object oriented, so in any case ORM is always a trade off between convenient OOP programming and optimized/most effective DB access.
I wouldn't use ORM for specific isolated tasks, but rather as an overall architectural choice for application persistence layer.
In my opinion I would NOT use Hibernate, since it makes your application a whole lot bigger and less maintainable and you do not really have a chance of optimizing the generated sql-scripts in a quick way.
Furthermore you could use all the SQL functionality the JDBC-bridge supports and are not limited to the hibernate functionality. Another thing is that you have the limitations too that come along with each layer of legacy code.
But in the end it is a philosophical question and you should do it the way it fits you're way of thinking best.
If there are possible performance issues then stick with the JDBC code.
There are a number of well known pure SQL optimisations which
which would be very difficult to do in Hibernate.
Only select the columns you use! (No "select *" stuff ).
Keep the SQl as simple as possible. e.g. Dont include small reference tables like currency codes in the join. Instead load the currency table into memory and resolve currency descriptions with a program lookup.
Depending on the DBMS minor re-ordering of the SQL where predicates can have a major effect on performance.
If you are updateing/inserting only commit every 100 to 1000 updates. i.e. Do not commit every unit of work but keep some counter so you commit less often.
Take advantage of the aggregate functions of your database. If you want totals by DEPT code then do it in the SQL with " SUM(amount) ... GROUP BY DEPT ".