Clojure Performance and benchmarks

There are several aspects to performance testing

  • time taken by individual functions / expressions
  • time through a specific path in your application
  • response times under different loads

The purpose of performance testing and bench-marking is to understand the expected behaviour of your application under various usage patterns. This kind of testing can also suggest areas of the application that might benefit from optomisation

Performance tools for Clojure

Gatling

The Gatling Project is another free and open source performance testing tool, primarily developed and maintained by Stephane Landelle. Gatling has a basic GUI that's limited to test recorder only. However, the tests can be developed in easily readable/writable domain-specific language (DSL).

Key Features of Gatling:

  • HTTP Recorder
  • An expressive self-explanatory DSL for test development
  • Scala-based
  • Production of higher load using an asynchronous non-blocking approach
  • Full support of HTTP(S) protocols and can also be used for JDBC and JMS load testing
  • Multiple input sources for data-driven tests
  • Powerful and flexible validation and assertions system
  • Comprehensive informative load reports

Reference: Other performance tools

Other notable performance tools include:

  • The Grinder
  • Apache JMeter (Java desktop app)
  • Tsung (required Erlang)
  • Locust (python)

Key Features of The Grinder:

  • TCP proxy to record network activity into the Grinder test script
  • Distributed testing that scales with an the increasing number of agent instances
  • Power of Python or Closure, combined with any Java API, for test script creation or modification
  • Flexible parameterization, which includes creating test data on the fly and the ability to use external data sources like files and databases
  • Post-processing and assertion with full access to test results for correlation and content verification
  • Support of multiple protocols

Key Features of JMeter:

  • Desktop GUI tool
  • Cross-platform. JMeter can run on any operating system with Java
  • Scalable. When you need a higher load than a single machine can create, JMeter can execute in a distributed mode, meaning one master JMeter machine controls a number of remote hosts.
  • Multi-protocol support. The following protocols are all supported out-of-the-box: HTTP, SMTP, POP3, LDAP, JDBC, FTP, JMS, SOAP, TCP
  • Multiple implementations of pre- and post-processors around sampler. This provides advanced setup, teardo* wn parametrization, and correlation capabilities
  • Various assertions to define criteria
  • Multiple built-in and external listeners to visualize and analyze performance test results
  • Integration with major build and continuous integration systems, making JMeter performance tests part of the full software development life cycle
  • Extensions via plugins

Resources

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