Mastering Liteflow: Build Scalable Rule Engines in Java

1 Introduction

During development, serial or parallel business processes often have no correlation. Traditional strategy/template coding creates many files, making it hard to see the overall flow. A rule engine from a global perspective can solve this problem, which is the focus of this article.

2 liteflow Rule Engine

liteflow is a lightweight yet powerful rule engine that works out‑of‑the‑box and can orchestrate complex rules quickly. It supports multiple rule file formats such as XML, JSON, YAML and storage options like SQL, Zookeeper, Nacos, Apollo.

liteflow can also handle hot‑deployment, allowing rule files to be updated in real time.

3 How to Use liteflow

3.1 Components

Ordinary Component – implements NodeComponent, used in when and then logic. Override process, iaAccess, isContinueOnError, isEnd as needed.

Switch Component – extends NodeSwitchComponent and implements processSwitch to decide the next node, similar to a Java switch.

Condition Component – extends NodeIfComponent and overrides processIf to return a boolean result.

3.2 EL Rule Files

Rule files can be written in XML using the following expressions:

# Serial execution
THEN(a, b, c, d);
# Parallel execution
WHEN(a, b, c);
# Nested serial and parallel
THEN(a, WHEN(b, c, d), e);
# Switch
SWITCH(a).to(b, c, d);
# Conditional
THEN(IF(x, a), b);

3.3 Data Context

The data context carries parameters between nodes. It is passed as a class type to the executor:

LiteflowResponse response = flowExecutor.execute2Resp(
    "chain1",
    initialParams,
    CustomContext.class
);

3.4 Parameter Configuration

Typical liteflow configuration (application.yml) includes rule source location, retry count, thread‑pool settings, and monitoring options:

liteflow:
  ruleSource: liteflow/*.el.xml
  retry-count: 0
  print-execution-log: true
  monitor:
    enable-log: true
    period: 300000
  request-id-generator-class: com.platform.orderserver.config.AppRequestIdGenerator
  slot-size: 10240
  main-executor-works: 64
  when-max-wait-seconds: 15
  when-max-workers: 16
  when-queue-limit: 5120
  parse-on-start: true
  enable: true

4 Business Practice

Example: after an order is completed, the flow grants points, sends a message, and concurrently sends email and SMS.

<?xml version="1.0" encoding="UTF-8"?>
<flow>
    <chain name="test_flow">
        THEN(
            prepareTrade,
            grantScore,
            sendMq,
            WHEN(sendEmail, sendPhone)
        );
    </chain>
</flow>

Images illustrate the execution steps and context handling.

5 Summary

Most of liteflow’s work—rule parsing, component registration, and assembly—is performed at startup, giving it high execution performance. It can also log each node’s duration and statistics. This article introduced liteflow’s core concepts and demonstrated how to configure and use it in a Spring Boot environment.