DDevelopment & Design

Sorting strings in Oracle by national rules

  • byModulo
  • February 18, 2011
  • 1 minute read

Sometimes we need to sort a list by rules of a national letter order, e.g. in Polish the national charactes are mostly place between original the Latin ones: … b, c, ć, d, e, ę, f … In other languages, it can be even more sophisticated, like in Spanish, where ll is located after lz, so a single character replacement wouldn’t work.

If we sort the following way:

SELECT * FROM TABLE (SYS.ODCIVARCHAR2LIST(‘cde’, ‘ća’, ‘dx’, ‘ca’)) ORDER BY COLUMN_VALUE;

We’ll get: ca, cde, dx, ća and that’s wrong. To sort the list correctly, we can specify a language rule: NLSSORT(COLUMN_VALUE,’NLS_LANG=pl’):

SELECT * FROM TABLE (SYS.ODCIVARCHAR2LIST(‘cde’, ‘ća’, ‘dx’, ‘ca’)) RDER BY NLSSORT(COLUMN_VALUE,’NLS_LANG=pl’);

Finally we’ll get the correct result: ca, cde, ća, dx.

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DDevelopment & Design

Simple trick to DRY your Grails controller

Grails controllers are not very DRY. It's easy to find duplicated code fragments in default generated controller. Take a look at code sample below. It is duplicated four times in show, edit, update and delete actions:

class BookController {
def show() {
def bookInstance = Book.get(params.id)
if (!bookInstance) {
flash.message = message(code: 'default.not.found.message', args: [message(code: 'book.label', default: 'Book'), params.id])
redirect(action: "list")
return
        }
        [bookInstance: bookInstance]
    }
}

Why is it duplicated?

There is a reason for that duplication, though. If you move this snippet to a method, it can redirect to "list" action, but it can't prevent controller from further execution. After you call redirect, response status changes to 302, but after method exits, controller still runs subsequent code.

Solution

At TouK we've implemented a simple trick to resolve that situation:

  1. wrap everything with a simple withStoppingOnRender method,
  2. whenever you want to render or redirect AND stop controller execution - throw EndRenderingException.

We call it Big Return - return from a method and return from a controller at once. Here is how it works:

class BookController {
def show(Long id) {
withStoppingOnRender {
Book bookInstance = Book.get(id)
validateInstanceExists(bookInstance)
            [bookInstance: bookInstance]
        }
    }

protected Object withStoppingOnRender(Closure closure) {
try {
return closure.call()
        } catch (EndRenderingException e) {}
    }

private void validateInstanceExists(Book instance) {
if (!instance) {
flash.message = message(code: 'default.not.found.message', args: [message(code: 'book.label', default: 'Book'), params.id])
redirect(action: "list")
throw new EndRenderingException()
        }
    }
}

class EndRenderingException extends RuntimeException {}

Example usage

For simple CRUD controllers, you can use this solution and create some BaseController class for your controllers. We use withStoppingOnRender in every controller so code doesn't look like a spaghetti, we follow DRY principle and code is self-documented. Win-win-win! Here is a more complex example:

class DealerController {
@Transactional
def update() {
withStoppingOnRender {
Dealer dealerInstance = Dealer.get(params.id)
validateInstanceExists(dealerInstance)
validateAccountInExternalService(dealerInstance)
checkIfInstanceWasConcurrentlyModified(dealerInstance, params.version)
            dealerInstance.properties = params
saveUpdatedInstance(dealerInstance)
redirectToAfterUpdate(dealerInstance)
        }
    }
}
DDevelopment & Design

JBoss Envers and Spring transaction managers

I've stumbled upon a bug with my configuration for JBoss Envers today, despite having integration tests all over the application. I have to admit, it casted a dark shadow of doubt about the value of all the tests for a moment. I've been practicing TDD since 2005, and frankly speaking, I should have been smarter than that.

My fault was simple. I've started using Envers the right way, with exploratory tests and a prototype. Then I've deleted the prototype and created some integration tests using in-memory H2 that looked more or less like this example:

@Test
public void savingAndUpdatingPersonShouldCreateTwoHistoricalVersions() {
    //given
    Person person = createAndSavePerson();
    String oldFirstName = person.getFirstName();
    String newFirstName = oldFirstName + "NEW";

    //when
    updatePersonWithNewName(person, newFirstName);

    //then
    verifyTwoHistoricalVersionsWereSaved(oldFirstName, newFirstName);
}

private Person createAndSavePerson() {
    Transaction transaction = session.beginTransaction();
    Person person = PersonFactory.createPerson();
    session.save(person);
    transaction.commit();
    return person;
}    

private void updatePersonWithNewName(Person person, String newName) {
    Transaction transaction = session.beginTransaction();
    person.setFirstName(newName);
    session.update(person);
    transaction.commit();
}

private void verifyTwoHistoricalVersionsWereSaved(String oldFirstName, String newFirstName) {
    List<Object[]> personRevisions = getPersonRevisions();
    assertEquals(2, personRevisions.size());
    assertEquals(oldFirstName, ((Person)personRevisions.get(0)[0]).getFirstName());
    assertEquals(newFirstName, ((Person)personRevisions.get(1)[0]).getFirstName());
}

private List<Object[]> getPersonRevisions() {
    Transaction transaction = session.beginTransaction();
    AuditReader auditReader = AuditReaderFactory.get(session);
    List<Object[]> personRevisions = auditReader.createQuery()
            .forRevisionsOfEntity(Person.class, false, true)
            .getResultList();
    transaction.commit();
    return personRevisions;
}

Because Envers inserts audit data when the transaction is commited (in a new temporary session), I thought I have to create and commit the transaction manually. And that is true to some point.

My fault was that I didn't have an end-to-end integration/acceptance test, that would call to entry point of the application (in this case a service which is called by GWT via RPC), because then I'd notice, that the Spring @Transactional annotation, and calling transaction.commit() are two, very different things.

Spring @Transactional annotation will use a transaction manager configured for the application. Envers on the other hand is used by subscribing a listener to hibernate's SessionFactory like this:

<bean id="sessionFactory" class="org.springframework.orm.hibernate3.annotation.AnnotationSessionFactoryBean" >        
...
 <property name="eventListeners">
     <map key-type="java.lang.String" value-type="org.hibernate.event.EventListeners">
         <entry key="post-insert" value-ref="auditEventListener"/>
         <entry key="post-update" value-ref="auditEventListener"/>
         <entry key="post-delete" value-ref="auditEventListener"/>
         <entry key="pre-collection-update" value-ref="auditEventListener"/>
         <entry key="pre-collection-remove" value-ref="auditEventListener"/>
         <entry key="post-collection-recreate" value-ref="auditEventListener"/>
     </map>
 </property>
</bean>

<bean id="auditEventListener" class="org.hibernate.envers.event.AuditEventListener" />

Envers creates and collects something called AuditWorkUnits whenever you update/delete/insert audited entities, but audit tables are not populated until something calls AuditProcess.beforeCompletion, which makes sense. If you are using org.hibernate.transaction.JDBCTransaction manually, this is called on commit() when notifying all subscribed javax.transaction.Synchronization objects (and enver's AuditProcess is one of them).

The problem was, that I used a wrong transaction manager.

<bean id="transactionManager" class="org.springframework.jdbc.datasource.DataSourceTransactionManager" >
    <property name="dataSource" ref="dataSource"/>
</bean>

This transaction manager doesn't know anything about hibernate and doesn't use org.hibernate.transaction.JDBCTransaction. While Synchronization is an interface from javax.transaction package, DataSourceTransactionManager doesn't use it (maybe because of simplicity, I didn't dig deep enough in org.springframework.jdbc.datasource), and thus Envers works fine except not pushing the data to the database.

Which is the whole point of using Envers.

Use right tools for the task, they say. The whole problem is solved by using a transaction manager that is well aware of hibernate underneath.

<bean id="transactionManager" class="org.springframework.orm.hibernate3.HibernateTransactionManager" >
    <property name="sessionFactory" ref="sessionFactory"/>
</bean>

Lesson learned: always make sure your acceptance tests are testing the right thing. If there is a doubt about the value of your tests, you just don't have enough of them,
DDevelopment & Design

Recently at storm-users

I've been reading through storm-users Google Group recently. This resolution was heavily inspired by Adam Kawa's post "Football zero, Apache Pig hero". Since I've encountered a lot of insightful and very interesting information I've decided to describe some of those in this post.

  • nimbus will work in HA mode - There's a pull request open for it already... but some recent work (distributing topology files via Bittorrent) will greatly simplify the implementation. Once the Bittorrent work is done we'll look at reworking the HA pull request. (storm’s pull request)

  • pig on storm - Pig on Trident would be a cool and welcome project. Join and groupBy have very clear semantics there, as those concepts exist directly in Trident. The extensions needed to Pig are the concept of incremental, persistent state across batches (mirroring those concepts in Trident). You can read a complete proposal.

  • implementing topologies in pure python with petrel looks like this:

class Bolt(storm.BasicBolt):
    def initialize(self, conf, context):
       ''' This method executed only once '''
        storm.log('initializing bolt')

    def process(self, tup):
       ''' This method executed every time a new tuple arrived '''       
       msg = tup.values[0]
       storm.log('Got tuple %s' %msg)

if __name__ == "__main__":
    Bolt().run()

  • Fliptop is happy with storm - see their presentation here

  • topology metrics in 0.9.0: The new metrics feature allows you to collect arbitrarily custom metrics over fixed windows. Those metrics are exported to a metrics stream that you can consume by implementing IMetricsConsumer and configure with Config.java#L473. Use TopologyContext#registerMetric to register new metrics.

  • storm vs flume - some users' point of view: I use Storm and Flume and find that they are better at different things - it really depends on your use case as to which one is better suited. First and foremost, they were originally designed to do different things: Flume is a reliable service for collecting, aggregating, and moving large amounts of data from source to destination (e.g. log data from many web servers to HDFS). Storm is more for real-time computation (e.g. streaming analytics) where you analyse data in flight and don't necessarily land it anywhere. Having said that, Storm is also fault-tolerant and can write to external data stores (e.g. HBase) and you can do real-time computation in Flume (using interceptors)

That's all for this day - however, I'll keep on reading through storm-users, so watch this space for more info on storm development.

I've been reading through storm-users Google Group recently. This resolution was heavily inspired by Adam Kawa's post "Football zero, Apache Pig hero". Since I've encountered a lot of insightful and very interesting information I've decided to describe some of those in this post.

  • nimbus will work in HA mode - There's a pull request open for it already... but some recent work (distributing topology files via Bittorrent) will greatly simplify the implementation. Once the Bittorrent work is done we'll look at reworking the HA pull request. (storm’s pull request)

  • pig on storm - Pig on Trident would be a cool and welcome project. Join and groupBy have very clear semantics there, as those concepts exist directly in Trident. The extensions needed to Pig are the concept of incremental, persistent state across batches (mirroring those concepts in Trident). You can read a complete proposal.

  • implementing topologies in pure python with petrel looks like this:

class Bolt(storm.BasicBolt):
    def initialize(self, conf, context):
       ''' This method executed only once '''
        storm.log('initializing bolt')

    def process(self, tup):
       ''' This method executed every time a new tuple arrived '''       
       msg = tup.values[0]
       storm.log('Got tuple %s' %msg)

if __name__ == "__main__":
    Bolt().run()

  • Fliptop is happy with storm - see their presentation here

  • topology metrics in 0.9.0: The new metrics feature allows you to collect arbitrarily custom metrics over fixed windows. Those metrics are exported to a metrics stream that you can consume by implementing IMetricsConsumer and configure with Config.java#L473. Use TopologyContext#registerMetric to register new metrics.

  • storm vs flume - some users' point of view: I use Storm and Flume and find that they are better at different things - it really depends on your use case as to which one is better suited. First and foremost, they were originally designed to do different things: Flume is a reliable service for collecting, aggregating, and moving large amounts of data from source to destination (e.g. log data from many web servers to HDFS). Storm is more for real-time computation (e.g. streaming analytics) where you analyse data in flight and don't necessarily land it anywhere. Having said that, Storm is also fault-tolerant and can write to external data stores (e.g. HBase) and you can do real-time computation in Flume (using interceptors)

That's all for this day - however, I'll keep on reading through storm-users, so watch this space for more info on storm development.