Lightweight Parallel Tasks in Java Microservices

Lightweight Parallel Tasks in Java Microservices

BascomTask lightweight in-process task orchestration helps reign in the complexities involved with processing data from multiple sources. Lightweight Parallel Tasks in Java Microservices. The Importance of Lightweight Tasks.

BascomTask lightweight in-process task orchestration helps reign in the complexities involved with processing data from multiple sources.

The Importance of Lightweight Tasks

One of the corollaries of embracing microservices is the increased need to aggregate information from multiple remote sources. In turn, exploiting every opportunity to execute such operations in parallel becomes more important and managing the resulting complexities becomes more central to the organization of your code. There are several core Java language and library options available to achieve this, but their generality makes them relatively low-level for this purpose: they lack a task abstraction.

A task in this context is a class that performs a non-trivial, track-worthy unit of work in an execution graph, potentially comprised of many such tasks. Tasks are important because interacting with an external system or database often involves details that are best encapsulated in a separate class. Done well, this separation of concerns facilitates refactoring at a logical level without impedance from the particular complexities involved with any external interaction. Such refactoring is to be expected as business goals evolve – which is one of the reasons for embracing microservices in the first place.

The need, however, extends beyond just class structure. While any Java code can create and call task classes, cross-cutting functionality such as tracing and profiling are best injected automatically rather than requiring explicit programmer coding. Representing non-trivial units of work, tasks should be parallelizable across multiple threads where possible while maintaining proper ordering so that tasks supplying values are executed prior to tasks consuming those values, preferably without requiring the latter to block-wait. The mechanism for wiring tasks together (which tasks to execute, how to execute them, and what dependencies they have) becomes a central focus. How this is accomplished, for better or worse, involves several considerations:

  • How is parallelism among tasks specified, preferably with as little manual programmer effort as possible? It is not always so easy to choose the optimal path, and manually-expressed optimization decisions may have to be revisited after every refactoring.
  • The required idioms should require minimal syntax elaboration with correspondingly minimal opportunities for introducing programming errors, all the more critical because timing errors or hidden inefficiencies among parallel threads can be non-deterministic, difficult to reproduce, and difficult to trace.
  • Composing the actual task classes should not require compromising core language capabilities such as type safety. One does not use Java only to have to make compromises on behalf of libraries or frameworks that dictate things you cannot do without extra effort or not at all. 
  • The solution should allow that simple cases remain simple while being scalable for endpoints which can grow to 10s or 100s of tasks. One does not want to have to rethink your application code design just because you're adding more tasks.

java java threads java microservices microservices

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