Reader-Writer Problem: Concurrency Control

2 March 2024

When two overlapping transactions are executing concurrently, both involve modifying the same set of overlapping data, neither one of them should observe partial results of the other to maintain consistency. An example for partial results would be a state where a thread has updated some parts of the data but not all of them. In this case, any read to the data that is in the middle of being updated can be accessing potentially inconsistent and corrupted data.

Readers-writer lock

To solve the reader-writer problem, one of the solutions is to use a readers-writer lock.

  • Readers can access database when there are no writers
  • Writers can access database when there are no readers/writers
  • Only one thread can manipulate shared variables at any time

It means, when a writer is writing data, no other threads are able to do anything including both reads and writes. When a reader is reading data, then other readers are allowed to read the same data.

Granting only one thread to read or write at a time solves the problem. However, it can slow things down when we have a read-intensive process. For example, when there are only few threads want to write data while many threads want to read data. The RW lock improves the performance by allowing multiple readers to read data at the same time, reducing the synchronization overhead between the readers.


RWMutex in Go

In Go, the sync package provides a RWMutex type as the readers-writer lock. It allows multiple readers or a single writer to access a resource at the same time, ensuring safe concurrent access of shared resources by multiple goroutines.

In the following example, the map data is shared between multiple goroutines. However, maps in Go are not safe for concurrent use.

package main
import (
type resource struct {
	data map[string]int
	mu   sync.RWMutex
func (r *resource) read(key string) int {
func (r *resource) write(key string, value int) {[key] = value
func main() {
	r := &resource{data: make(map[string]int)}
	r.write("key", 1)
	go func() {
		r.write("key", 2)

If we run the code above with go run -race main.go, we'll encounter the data race error from the compiler. To fix the issue, we can use the RWMutex to synchronize the access to the shared data.

func (r *resource) read(key string) int {
func (r *resource) write(key string, value int) {
	defer[key] = value

The RLock() method is used to acquire a read lock, and RUnlock() is used to release the lock. If a goroutine tries to call Lock() while other goroutines are already reading, any read attempts calling RLock() will block & wait until the writing goroutine has acquired the lock and finished. This makes sure the lock is eventually free for writing.

Aside from this lock-based solution, there are other synchronization methods to deal with the reader-writer problem, such as semaphore and monitor-based solutions.