Saturday, October 21, 2017

Object pooling made simple using Apache Commons Pool2

If you are looking for a quick implementation of an object pool, then look no further than the excellent Apache Commons Pool2 implementation. Pool2 is far better and faster than the original commons pool library.

Object pool can be used to cache those objects that are expensive to setup and cannot be created for every request or thread - e.g. DB connections, MQTT broker connections, AMQP broker connections, etc. 

The following code snippets would show you how simple it is to create a pool for your 'expensive-to-create' objects. 
Any object pool typically requires 2 parameters  [] --- 
1) A factory object to handle creation and destruction of your objects []
2) A configuration object to configure your pool. [GenericObjectPoolConfig,java]

Friday, October 20, 2017

Caching Simplified - Magic of Spring Annotations - Part 2

In the previous blog-post, we saw how we can enable caching with the magic of annotations.
Now, let's consider how to evict the cache based on our application needs.

Spring provides a simple annotation called @CacheEvict that can be used to evict the cache. In the below example, we add two methods that can be used to evict the cache 'SomeStaticData' and 'CountryList'.

But when do we call the evict method? We can schedule it to be called by the Spring Scheduler as per defined schedule. In the above example, we have scheduled the evict method once per day. Again so simple using the magic of annotations in Spring !

To enable scheduling by a background thread in Spring Boot, we need to just add the @EnableScheduling annotation on the Spring Boot main class. If Actuator is enabled, then it automatically creates a background thread and the @EnableScheduling annotation is then NOT required. 

 Another option is to have a "/evict/{CacheName}" endpoint registered in Spring MVC and call it from a browser to manually evict the cache.

Caching Simplified - Magic of Spring Annotations

Spring Boot makes is super simple to add caching abilities to your application. With just a few lines of code and some annotation magic, you have a complete caching solution available with you.

Spring provides wrappers for many cache implementations - Google Guava, ehcache, MongoDB, Redis, etc. At the simplest level, you can also use a ConcurrentHashMap as the cache manager.

Given below are three code snippets that shows how simple it is to enable caching for static data in a Spring Boot application - Welcome to the power of Spring !

Step 1:  []  Configure a ConcurrentHashMap cache manager

Step 2:  [] Annotate your Spring Boot application with @EnableCaching.

Magic behind the scenes: The @EnableCaching annotation triggers a post processor that inspects every Spring bean for the presence of caching annotations  on public methods. If such an annotation is found, a proxy is automatically created to intercept the method call  and handle the caching behavior accordingly.

Step 3: [] Annotate your methods that return the static data with  @Cacheable annotation. You can pass the cache name in the annotation - e.g.  @Cacheable("SomeStaticData")


That's it! You have configured caching. In the next blog-post, we will see how we can evict items from the cache when necessary.

Tuesday, October 17, 2017

Circular Dependencies in Spring Boot

Recently one of my team member was struggling with a strange issue in Spring Boot. The application was running fine on his local machine, but when deployed to the cloud it started giving errors - throwing BeanCurrentlyInCreationException.

 The core issue was identified as Circular Dependencies in Spring. An excellent article on how to identify such dependencies and resolve them is here -

It is recommended best to avoid circular dependencies, but in worst case if you must have them, then there are multiple options such as:
1. Using the @Lazy annotation on one of the dependency.
2. Not use Constructor injection, but use a Setter injection
3. Use @PostConstruct to set the Bean

Tuesday, October 10, 2017

Generating secure keys for encryption

Very often, we need to create secure keys that can be used in digital signatures or for signing a JWT.
It is very important to create a secure key so that the encryption is strong. A good post about this is here -

Jotting down some snippets from the article:

The strength of encryption is related to the difficulty of discovering the key, which in turn depends on both the cipher used and the length of the key. 

Encryption strength is often described in terms of the size of the keys used to perform the encryption: in general, longer keys provide stronger encryption. Key length is measured in bits.

Different ciphers may require different key lengths to achieve the same level of encryption strength

A key is nothing but a byte array that is passed to the encryption algorithm.  Hence if you are storing the key in a properties file, please makes sure that you have stored it in Base64 format.

Spring provides very simple methods for generating secure keys as shown below.

Monday, October 09, 2017

Handling RabbitMQ broker re-connections

The RabbitMQ Java Client Library has default support for auto-recovery (since version 4.0.0). Hence the client will try to recover a broken connection unless you explicitly disable it.

If you want to fine-tune the retry mechanism, then the examples given in the below link would help.

Or alternatively, you can use the super easy Spring RabbitTemplate class that has retry options. The RabbitTemplate class wraps the RabbitMQ Java client and provides all the goodies of Spring. 

Handling MQTT broker re-connections

Any client that connects to an MQTT broker needs the ability to handle a connection failure.

The popular Eclipse Paho library now has support for reconnects as described here -
Sample client code available here -

If you want to understand how Paho implements reconnect, then have a look at this source file -

Alternatively, we can use the Spring Integration Framework that encapsulates the Paho library and provides options to configure connection retry logic.

Sunday, October 08, 2017

Ruminating on MQTT load balancing for scalable IoT event processing

MQTT brokers support the publish/subscribe paradigm. But what if you need to scale out the processing of MQTT messages over a cluster of nodes (message consumers)?

In IoT environments, we need to process thousands of events per second and hence need to load-balance incoming messages across multiple processing nodes. 
Unfortunately, the standard MQTT specification does not support this concept.

But many MQTT brokers support this as a non-standard feature - e.g. HiveMQ supports Shared Subscriptions

The IBM Watson IoT platform also supports shared subscriptions as described here -
If you are using the IBM Watson IoT java libraries, you need to "Shared-Subscription” property is set to “true”. If you are using any other client like Eclipse Paho, then you must use the client id of the form “A:org_id:app_id”

Note: Please note the capital 'A' in the client ID. This marks the application as a scalable application for load-balancing. We just changed the small 'a' to a capital 'A' and could load-balance our mqtt consumers. 

Database connection reconnection strategy

In any database connection pool, there is a risk of stale connections due to network outages or database server restarts. How do we refresh the connection pool without restarting the client application?

The standard technique used is to plug-in a validation query; that gets fired every time a connection is requested from the pool. This validation query is typically a default test query that does not result in any IO / disk access.  Examples of validation queries for different databases are given below:
  • Oracle - select 1 from dual
  • SQL Server - select 1 (tested on SQL-Server 9.0, 10.5 [2008])
  • Postgresql - select 1
  • hsqldb - select 1 from INFORMATION_SCHEMA.SYSTEM_USERS
  • derby - values 1
  • H2 - select 1
  • DB2 - select 1 from sysibm.sysdummy1
  • Mysql - select 1
We were using Spring Boot that uses the Tomcat JDBC Connection Pool by default. We tried setting all the parameters required for the validation check as given here, but in vain. 
Finally we decided to go with HikariCP connection pool as suggested here

First, we added the dependency in our maven pom as shown below. 

Next we added the following properties in our file. We will pick up these properties to create our HikariCP connection. pool.
Finally we wrote a @Configuration bean to wire up the HirakiCP datasource as below:

Saturday, October 07, 2017

Accessing Spring beans in a static method

Very often, we need to access a Spring bean in a static method. This is a bit tricky as you can only directly access static fields in a static method and Spring beans are not static.

But there are a couple of neat tricks that we can employ. One option is given below wherein we create a static field and populate it in the constructor when Spring auto-wires the bean. In the below example, MyThing is a spring managed (and created) bean.

Another option is to store the ApplicationContext instance in a static field and use that to get any bean managed by Spring. Sample code given below.

Spring beans annotations, scope and loading sequence

Spring beans can have different scopes as listed here . By default, the scope is singleton and the bean is eagerly initialized on start-up. If you want to lazy load a bean, then you have to decorate it with the @Lazy annotation.

By default, a bean has singleton scope and does not have the lazy-init property set to true. Hence by default all beans are eagerly created by the application context. This will affect the time taken for your Spring Boot application to start-up. 

The @Lazy annotation can be used on both @Component and @Bean. It is also important to understand how objects are constructed in Spring. The whole Spring framework works on the fundamental design pattern of 'Inversion of Control'or 'Dependency Injection'. Using Spring, you just declare components and Spring wires them up and manages the dependency between them.

When we mark a class with a @Component annotation, Spring will automatically create an instance of this class (make a bean) by scanning the classpath. This bean can be assessed anywhere in your application using the @Autowired annotation on fields, constructors, or methods in a component.

But what if you don't want Spring to auto-create the bean and want to control how the bean is constructed. To do this, you write a method that constructs your bean as you want and annotate that method with the @Bean tag. Please note that the @Bean annotation decorates a method and not a class. Thus a method marked with the @Bean annotation is a bean producer.

But how will Spring know where you have created @Bean annotated methods? Scanning all the classes will take a lot of time. Hence you annotate these classes which have @Bean methods with two annotations - @Configuration and @ComponentScan.
@Configuration annotation marks a class as a source of the bean definitions.
@ComponentScan annotation is used to declare the packages where Spring should scan for annotated components.

An excellent cheat sheet on Spring Annotations is available here.

Ruminating on Builder design pattern in Spring Security

While configuring Spring Security, you can use the properties file to configure the filters and other classes, but another popular option is declaring the configuration using code - using the Builder design pattern.

Understanding the way to use the builder is a bit tricky. Lets look at the below code and try to dissect it.

The 'http' object represents the object and is similar to Spring Security's XML element.
The .authorizeRequests() method returns the ExpressionInterceptUrlRegistry method that can be used to add HTTP URL matching patterns. After this, you can add additional information as required. 

A good blog-post explaining more such options is given here -

Wednesday, October 04, 2017

Spring Sleuth Tips and Tricks

Spring Sleuth coupled with Zipkin in an excellent tool to measure the performance bottlenecks in your distributed microservices architecture.

Spring Sleuth automatically creates HTTP and Messaging interceptors when calls are made to other microservices over REST or RabbitMQ. But what if you want to instrument the time taken to execute a method or time take for a third-party service to respond?

Initially we tried with the @NewSpan annotation on methods, but soon realized that this annotation DOES NOT work in the same class. A detailed discussion thread on this limitation is available here -

The core reason is that the proxies that Spring creates do not work for the method calls in the same object. Sleuth creates a proxy of the object so if we are calling a proxied method from the proxy itself then the method will be called directly without going through the proxy logic, hence no span will be created. Hence we need to manually add the span as follows and it would show up in the beautiful Zipkin UI.

Another great blog post around these techniques is here -

Tuesday, October 03, 2017

Parsing an arbitrary JSON string and extracting values

Developers use libraries such as Jackson to convert JSON strings to Java objects and vice-versa.
But what if you need to parse a JSON string and do not know the complete schema of it. Since you do not have the complete schema of the JSON, you cannot create the Java class.

Another situation could be when you don't want to create a Java class and just want to extract a few values from the JSON string. Given below are 2 techniques for achieving this:

Option 1:

Convert the JSON string to a HashMap. All libraries such as Jackson, Gson provide methods to convert the JSON string into a map. Then by using standard map functions, you can extract the values you are interested in. Sample code available here.

Option 2: 

Convert the JSON string into a 'tree model' object. Jackson has a default tree model object called JsonNode. Jackson also supports JSON Pointer Expression, so you can directly access a node value like this: