{
  "id": "java-jedis",
  "title": "Token bucket rate limiter with Redis and Java",
  "url": "https://redis.io/docs/latest/develop/use-cases/rate-limiter/java-jedis/",
  "summary": "Implement a token bucket rate limiter using Redis and Lua scripts in Java",
  "tags": [
    "docs",
    "develop",
    "stack",
    "oss",
    "rs",
    "rc"
  ],
  "last_updated": "2026-04-16T13:29:55-07:00",
  "children": [],
  "page_type": "content",
  "content_hash": "2a2be15bf9c80c73a3a9b40605ff1a3b5a8cb68904f9aadfc0b6c258b94fa23c",
  "sections": [
    {
      "id": "overview",
      "title": "Overview",
      "role": "overview",
      "text": "This guide shows you how to implement a distributed token bucket rate limiter using Redis and Lua scripts in Java with the [`Jedis`](https://redis.io/docs/latest/develop/clients/jedis) client library."
    },
    {
      "id": "overview",
      "title": "Overview",
      "role": "overview",
      "text": "Rate limiting is a critical technique for controlling the rate at which operations are performed. Common use cases include:\n\n* Limiting API requests per user or IP address\n* Preventing abuse and protecting against denial-of-service attacks\n* Ensuring fair resource allocation across multiple clients\n* Throttling background jobs or batch operations\n\nThe **token bucket algorithm** is a popular rate limiting approach that allows bursts of traffic while maintaining an average rate limit over time. This guide covers the Java implementation using the [`Jedis`](https://redis.io/docs/latest/develop/clients/jedis) client library, taking advantage of Java's `try-with-resources` for connection management, `JedisPool` for connection pooling, and checked exceptions for error handling."
    },
    {
      "id": "how-it-works",
      "title": "How it works",
      "role": "content",
      "text": "The token bucket algorithm works like a bucket that holds tokens:\n\n1. **Initialization**: The bucket starts with a maximum capacity of tokens\n2. **Refill**: Tokens are added to the bucket at a constant rate (for example, 1 token per second)\n3. **Consumption**: Each request consumes one token from the bucket\n4. **Decision**: If tokens are available, the request is allowed; otherwise, it's denied\n5. **Capacity limit**: The bucket never exceeds its maximum capacity\n\nThis approach allows for burst traffic (using accumulated tokens) while enforcing an average rate limit over time."
    },
    {
      "id": "why-use-redis",
      "title": "Why use Redis?",
      "role": "content",
      "text": "Redis is ideal for distributed rate limiting because:\n\n* **Atomic operations**: Lua scripts execute atomically, preventing race conditions\n* **Shared state**: Multiple application servers can share the same rate limit counters\n* **High performance**: In-memory operations provide microsecond latency\n* **Automatic expiration**: Keys can be set to expire automatically (though not used in this implementation)"
    },
    {
      "id": "the-lua-script",
      "title": "The Lua script",
      "role": "content",
      "text": "The core of this implementation is a Lua script that runs atomically on the Redis server. This ensures that checking and updating the token bucket happens in a single operation, preventing race conditions in distributed environments.\n\nHere's how the script works:\n\n[code example]"
    },
    {
      "id": "script-breakdown",
      "title": "Script breakdown",
      "role": "content",
      "text": "1. **State retrieval**: Uses [`HMGET`](https://redis.io/docs/latest/commands/hmget) to fetch the current token count and last refill time from a hash\n2. **Initialization**: On first use, sets tokens to full capacity\n3. **Token refill calculation**: Computes how many tokens should be added based on elapsed time\n4. **Capacity enforcement**: Uses `math.min()` to ensure tokens never exceed capacity\n5. **Token consumption**: Decrements the token count if available\n6. **State update**: Uses [`HMSET`](https://redis.io/docs/latest/commands/hmset) to save the new state\n7. **Return value**: Returns both the decision (allowed/denied) and remaining tokens"
    },
    {
      "id": "why-atomicity-matters",
      "title": "Why atomicity matters",
      "role": "content",
      "text": "Without atomic execution, race conditions could occur:\n\n* **Double spending**: Two requests could read the same token count and both succeed when only one should\n* **Lost updates**: Concurrent updates could overwrite each other's changes\n* **Inconsistent state**: Token count and refill time could become desynchronized\n\nUsing [`EVAL`](https://redis.io/docs/latest/commands/eval) or [`EVALSHA`](https://redis.io/docs/latest/commands/evalsha) ensures the entire operation executes atomically, making it safe for distributed systems."
    },
    {
      "id": "installation",
      "title": "Installation",
      "role": "setup",
      "text": "Add the Jedis dependency to your project:\n\n* If you use **Maven**:\n\n  [code example]\n\n* If you use **Gradle**:\n\n  [code example]"
    },
    {
      "id": "using-the-java-class",
      "title": "Using the Java class",
      "role": "content",
      "text": "The `TokenBucket` class provides a thread-safe interface for rate limiting\n([source](TokenBucket.java)):\n\n[code example]\n\nJedis operations are synchronous and thread-safe when using `JedisPool`, which manages a pool of connections internally. The `allow()` method returns a `RateLimitResult` record containing both the decision and the remaining token count."
    },
    {
      "id": "configuration-parameters",
      "title": "Configuration parameters",
      "role": "configuration",
      "text": "* **capacity**: Maximum number of tokens in the bucket (controls burst size)\n* **refillRate**: Number of tokens added per refill interval\n* **refillInterval**: Time in seconds between refills\n\nFor example:\n* `capacity=10, refillRate=1, refillInterval=1.0` allows 10 requests per second with bursts up to 10\n* `capacity=100, refillRate=10, refillInterval=1.0` allows 10 requests per second with bursts up to 100\n* `capacity=60, refillRate=1, refillInterval=60.0` allows 1 request per minute with bursts up to 60"
    },
    {
      "id": "rate-limit-keys",
      "title": "Rate limit keys",
      "role": "content",
      "text": "The `key` parameter identifies what you're rate limiting. Common patterns:\n\n* **Per user**: `user:{userId}` - Limit each user independently\n* **Per IP address**: `ip:{ipAddress}` - Limit by client IP\n* **Per API endpoint**: `api:{endpoint}:{userId}` - Different limits per endpoint\n* **Global**: `global:api` - Single limit shared across all requests"
    },
    {
      "id": "script-caching-with-evalsha",
      "title": "Script caching with EVALSHA",
      "role": "content",
      "text": "The Java implementation uses [`EVALSHA`](https://redis.io/docs/latest/commands/evalsha) for optimal performance. On first use, the Lua script is loaded into Redis with `SCRIPT LOAD`, and subsequent calls use the cached SHA1 hash. If the script is evicted from the cache, the class automatically falls back to [`EVAL`](https://redis.io/docs/latest/commands/eval) and reloads the script. The script loading uses `volatile` and synchronization to ensure thread safety across multiple threads.\n\n[code example]"
    },
    {
      "id": "thread-safety",
      "title": "Thread safety",
      "role": "content",
      "text": "The `TokenBucket` class is thread-safe. You can share a single instance across your application, including from multiple threads in a servlet container or web framework:\n\n[code example]"
    },
    {
      "id": "running-the-demo",
      "title": "Running the demo",
      "role": "content",
      "text": "A demonstration HTTP server is included to show the rate limiter in action\n([source](DemoServer.java)):\n\n[code example]\n\nThe demo provides an interactive web interface where you can:\n\n* Submit requests and see them allowed or denied in real-time\n* View the current token count\n* Adjust rate limit parameters dynamically\n* Test different rate limiting scenarios\n\nThe demo assumes Redis is running on `localhost:6379` but you can specify a different host and port using the `--redis-host HOST` and `--redis-port PORT` command-line arguments. Visit `http://localhost:8080` in your browser to try it out."
    },
    {
      "id": "response-headers",
      "title": "Response headers",
      "role": "returns",
      "text": "It's common to include rate limit information in HTTP response headers:\n\n[code example]"
    },
    {
      "id": "customization",
      "title": "Customization",
      "role": "content",
      "text": ""
    },
    {
      "id": "using-as-a-servlet-filter",
      "title": "Using as a servlet filter",
      "role": "content",
      "text": "You can wrap the rate limiter as a servlet filter for use with any Java web framework:\n\n[code example]"
    },
    {
      "id": "error-handling",
      "title": "Error handling",
      "role": "errors",
      "text": "The `allow()` method may throw a `JedisException` if the Redis connection is lost. Wrap calls in try/catch blocks for production use:\n\n[code example]"
    },
    {
      "id": "learn-more",
      "title": "Learn more",
      "role": "related",
      "text": "* [EVAL command](https://redis.io/docs/latest/commands/eval) - Execute Lua scripts\n* [EVALSHA command](https://redis.io/docs/latest/commands/evalsha) - Execute cached Lua scripts\n* [Lua scripting](https://redis.io/docs/latest/develop/programmability/eval-intro) - Introduction to Redis Lua scripting\n* [HMGET command](https://redis.io/docs/latest/commands/hmget) - Get multiple hash fields\n* [HMSET command](https://redis.io/docs/latest/commands/hmset) - Set multiple hash fields\n* [Jedis client](https://redis.io/docs/latest/develop/clients/jedis) - Redis Java client documentation"
    }
  ],
  "examples": [
    {
      "id": "the-lua-script-ex0",
      "language": "lua",
      "code": "local key = KEYS[1]\nlocal capacity = tonumber(ARGV[1])\nlocal refill_rate = tonumber(ARGV[2])\nlocal refill_interval = tonumber(ARGV[3])\nlocal now = tonumber(ARGV[4])\n\n-- Get current state or initialize\nlocal bucket = redis.call('HMGET', key, 'tokens', 'last_refill')\nlocal tokens = tonumber(bucket[1])\nlocal last_refill = tonumber(bucket[2])\n\n-- Initialize if this is the first request\nif tokens == nil then\n    tokens = capacity\n    last_refill = now\nend\n\n-- Calculate token refill\nlocal time_passed = now - last_refill\nlocal refills = math.floor(time_passed / refill_interval)\n\nif refills > 0 then\n    tokens = math.min(capacity, tokens + (refills * refill_rate))\n    last_refill = last_refill + (refills * refill_interval)\nend\n\n-- Try to consume a token\nlocal allowed = 0\nif tokens >= 1 then\n    tokens = tokens - 1\n    allowed = 1\nend\n\n-- Update state\nredis.call('HMSET', key, 'tokens', tokens, 'last_refill', last_refill)\n\n-- Return result: allowed (1 or 0) and remaining tokens\nreturn {allowed, tokens}",
      "section_id": "the-lua-script"
    },
    {
      "id": "installation-ex0",
      "language": "xml",
      "code": "<dependency>\n      <groupId>redis.clients</groupId>\n      <artifactId>jedis</artifactId>\n      <version>5.2.0</version>\n  </dependency>",
      "section_id": "installation"
    },
    {
      "id": "installation-ex1",
      "language": "groovy",
      "code": "implementation 'redis.clients:jedis:5.2.0'",
      "section_id": "installation"
    },
    {
      "id": "using-the-java-class-ex0",
      "language": "java",
      "code": "import redis.clients.jedis.JedisPool;\n\npublic class Main {\n    public static void main(String[] args) {\n        // Create a Redis connection pool\n        JedisPool jedisPool = new JedisPool(\"localhost\", 6379);\n\n        // Create a rate limiter: 10 requests per second\n        TokenBucket limiter = new TokenBucket(10, 1, 1.0, jedisPool);\n\n        // Check if a request should be allowed\n        TokenBucket.RateLimitResult result = limiter.allow(\"user:123\");\n\n        if (result.allowed()) {\n            System.out.printf(\"Request allowed. %.0f tokens remaining.%n\", result.remaining());\n            // Process the request\n        } else {\n            System.out.println(\"Request denied. Rate limit exceeded.\");\n            // Return 429 Too Many Requests\n        }\n    }\n}",
      "section_id": "using-the-java-class"
    },
    {
      "id": "script-caching-with-evalsha-ex0",
      "language": "java",
      "code": "// The class handles script caching automatically.\n// First call loads the script, subsequent calls use EVALSHA.\nTokenBucket.RateLimitResult result1 = limiter.allow(\"user:123\"); // Uses EVAL + caches\nTokenBucket.RateLimitResult result2 = limiter.allow(\"user:123\"); // Uses EVALSHA (faster)",
      "section_id": "script-caching-with-evalsha"
    },
    {
      "id": "thread-safety-ex0",
      "language": "java",
      "code": "// Create a shared limiter instance\nTokenBucket limiter = new TokenBucket(10, 1, 1.0, jedisPool);\n\n// Safe to call from multiple threads\nExecutorService executor = Executors.newFixedThreadPool(10);\nfor (int i = 0; i < 20; i++) {\n    final int id = i;\n    executor.submit(() -> {\n        TokenBucket.RateLimitResult result = limiter.allow(\"shared:resource\");\n        System.out.printf(\"thread %d: allowed=%b remaining=%.0f%n\",\n                id, result.allowed(), result.remaining());\n    });\n}\nexecutor.shutdown();",
      "section_id": "thread-safety"
    },
    {
      "id": "running-the-demo-ex0",
      "language": "bash",
      "code": "# Compile\njavac -cp jedis-5.2.0.jar TokenBucket.java DemoServer.java\n\n# Run the demo server\njava -cp .:jedis-5.2.0.jar DemoServer",
      "section_id": "running-the-demo"
    },
    {
      "id": "response-headers-ex0",
      "language": "java",
      "code": "int capacity = 10;\ndouble refillInterval = 1.0;\nTokenBucket limiter = new TokenBucket(capacity, 1, refillInterval, jedisPool);\n\nTokenBucket.RateLimitResult result = limiter.allow(\"user:\" + userId);\n\n// Add standard rate limit headers\nresponse.setHeader(\"X-RateLimit-Limit\", String.valueOf(capacity));\nresponse.setHeader(\"X-RateLimit-Remaining\", String.valueOf((int) result.remaining()));\nresponse.setHeader(\"X-RateLimit-Reset\",\n        String.valueOf(System.currentTimeMillis() / 1000 + (long) refillInterval));\n\nif (!result.allowed()) {\n    response.setHeader(\"Retry-After\", String.valueOf((int) refillInterval));\n    response.setStatus(429); // Too Many Requests\n}",
      "section_id": "response-headers"
    },
    {
      "id": "using-as-a-servlet-filter-ex0",
      "language": "java",
      "code": "public class RateLimitFilter implements Filter {\n    private TokenBucket limiter;\n\n    @Override\n    public void init(FilterConfig config) {\n        JedisPool jedisPool = new JedisPool(\"localhost\", 6379);\n        limiter = new TokenBucket(10, 1, 1.0, jedisPool);\n    }\n\n    @Override\n    public void doFilter(ServletRequest req, ServletResponse res, FilterChain chain)\n            throws IOException, ServletException {\n        HttpServletRequest httpReq = (HttpServletRequest) req;\n        HttpServletResponse httpRes = (HttpServletResponse) res;\n\n        String key = \"ip:\" + httpReq.getRemoteAddr();\n        TokenBucket.RateLimitResult result = limiter.allow(key);\n\n        httpRes.setHeader(\"X-RateLimit-Remaining\",\n                String.valueOf((int) result.remaining()));\n\n        if (!result.allowed()) {\n            httpRes.setStatus(429);\n            httpRes.getWriter().write(\"{\\\"error\\\": \\\"Rate limit exceeded\\\"}\");\n            return;\n        }\n        chain.doFilter(req, res);\n    }\n}",
      "section_id": "using-as-a-servlet-filter"
    },
    {
      "id": "error-handling-ex0",
      "language": "java",
      "code": "try {\n    TokenBucket.RateLimitResult result = limiter.allow(\"user:123\");\n    // Handle result\n} catch (JedisException e) {\n    System.err.println(\"Rate limiter error: \" + e.getMessage());\n    // Fail open: allow the request when Redis is unavailable\n    // Or fail closed: deny the request\n}",
      "section_id": "error-handling"
    }
  ]
}