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Timing spring-data-cassandra repository methods


This post showcases how to make use of Spring AOP / AspectJ for timing the duration of both synchronous and asynchrnous methods belonging to spring data cassandra repositories.

Metrics in the data access layer of the application

Having an overview on the Prometheus for how each of the operations exposed by the Data Access Layer performs is a tremendous improvement for monitoring and tackling production issues on a live application.

To give a pretty common example, say that with a new release of the application one SELECT statement from a repository class gets changed that causes the application to run normal on the testing environment, but on the productive environment where there’s much more data to perform much worse than it did before. In that case after the release, the Quality of Service will drop to a significant amount, and the engineer responsible for the release will need to investigate what has changed for the worse since the last release.

This is where nowadays metric collector services (like Prometheus) shine and provide a lot of meaningful answers in such situations. It would obviously be very helpful to see in Grafana or even receive a Prometheus alert whether an operation or a set of operations performed by the application performs much more slowly than before.

Seeing a continuous increase of average duration or repeated failures on the data access layer for a certain operation from a repository in the data access layer of the application since the last release would help to identify very fast the problem and subsequently revert the change or fix the problem.

Timing the methods of spring data repositories

When using the io.micrometer.core.annotation.Timed annotation that comes with micrometer library in a spring-boot application there is obtained the emission of timing metrics for the methods annotated with this annotation.

When annotating the class with the @Timed annotation, all the public methods of the spring bean class will be timed.

This seems like a good solution, but very often it happens that through omission/refactoring in the code, the annotation is being removed by mistake from the class and therefore the valuable metrics and not emitted anymore to the micrometer’s MeterRegistry.

Another drawback of the io.micrometer.core.annotation.Timed annotation (and the io.micrometer.core.aop.TimedAspect which takes care of intercepting the methods annotated with Timed annotation) is that it doesn’t have support for dealing with asynchronous methods.

Through spring data cassandra utility classes:


there can be executed statements on the Cassandra database in both fashions, synchronous and asynchronous.

The project spring-data-cassandra-repository-methods-timing developed a custom AspectJ class for taking care of timing all the public methods exposed by the spring data repository bean classes from the project.

Spring data repository classes are considered any of the following:

  • the class is annotated with the @org.springframework.stereotype.Repository annotation
  • the class implements class

In a similar fashion to the micrometer’s io.micrometer.core.aop.TimedAspect, the AspectJ com.findinpath.aop.RepositoryTimerAspect class from the proof of concept project intercepts the methods of spring data repository beans from the project and emits timer information to micrometer’s io.micrometer.core.instrument.MeterRegistry.

The information get emitted to the micrometer metric named repository with the following tags:

.tags("class", className) 
.tags("method", methodName)
.tags("successful", successful) 

The className can be on of the following:

  • the interface corresponding to the repository - see com.findinpath.repository.ConfigRepository
  • the concrete class annotated with @org.springframework.stereotype.Repository annotation - see com.findinpath.repository.UserBookmarkRepository

The successful flag states whether the call was or not successfully executed.

Dealing with asynchronous methods

As mentioned earlier, there can be executed asynchronous methods on Cassandra. The implementation of the asynchronous methods with spring data cassandra is straightforward (see com.findinpath.repository.UserBookmarkRepository for more details):

  public ListenableFuture<UserBookmark> saveAsync(UserBookmark userBookmark) {
    return asyncCassandraOperations.insert(userBookmark);

A little trick needs therefor to be employed in the AspectJ RepositoryTimerAspectclass for timing such non-blocking methods. After retrieving the result from the target method invocation, a callback is being registered for emiting the metrics in both success and failure cases after the completion of the method:

    var asyncResult = (ListenableFuture) proceedingJoinPoint.proceed();
        result -> emitMetrics(meterRegistry, sample, className, methodName, Optional.empty()),
        ex -> emitMetrics(meterRegistry, sample, className, methodName, Optional.of(ex)));
    return asyncResult;

Spring AOP

In case that it is needed for reference a Spring AOP implementation for timing the spring data repositories, the project source code provides also such an implementation, although commented, in order to avoid causing issues with the AspectJ `RepositoryTimerAspect.

See com.findinpath.config.RepositoryTimerConfiguration for details.


The project spring-data-cassandra-repository-methods-timing comes with a com.findinpath.DemoTest class which contains test scenarios for timing both kinds of spring data repositories:

  • the class is annotated with the @org.springframework.stereotype.Repository annotation
  • the class implements class

and also both synchronous and asynchronous methods.

Below are the measurements logged from one of the runs of the DemoTest:

The timer MeterId{name='repository', tags=[tag(class=ConfigRepository),tag(method=save),tag(successful=true)]} has max value: 176 ms and mean value: 25 ms
The timer MeterId{name='repository', tags=[tag(class=ConfigRepository),tag(method=findById),tag(successful=true)]} has max value: 22 ms and mean value: 8 ms
The timer MeterId{name='repository', tags=[tag(class=UserBookmarkRepository),tag(method=save),tag(successful=true)]} has max value: 32 ms and mean value: 9 ms
The timer MeterId{name='repository', tags=[tag(class=UserBookmarkRepository),tag(method=saveAsync),tag(successful=true)]} has max value: 33 ms and mean value: 8 ms
The timer MeterId{name='repository', tags=[tag(class=UserBookmarkRepository),tag(method=findLatestBookmarks),tag(successful=true)]} has max value: 12 ms and mean value: 7 ms
The timer MeterId{name='repository', tags=[tag(class=UserBookmarkRepository),tag(method=findLatestBookmarksAsync),tag(successful=true)]} has max value: 25 ms and mean value: 12 ms

The test is being executed against a throwaway Cassandra database container (through the help of the genius team formed from docker and the testcontainers library).

In order to keep the demo project simple to go through, no setup has been made for a web application that would expose operations to interact with Cassandra database. This is why in order to test the concepts showcased by the project, only the com.findinpath.DemoTest class is provided.

Simply use mvn clean install for trying out the project.