Principle:Duckdb Duckdb Lock Free Concurrency
| Knowledge Sources | |
|---|---|
| Domains | Concurrency, Data_Structure |
| Last Updated | 2026-02-07 12:00 GMT |
Overview
A class of concurrent data structures that guarantee system-wide progress without using mutual exclusion locks, relying instead on atomic operations to coordinate access between threads.
Description
Lock-free concurrency is a programming paradigm for multi-threaded systems where shared data structures are designed so that at least one thread is guaranteed to make progress in a finite number of steps, regardless of the behavior of other threads. Unlike lock-based approaches (mutexes, semaphores), lock-free algorithms never cause threads to block waiting for a resource held by another thread, eliminating problems such as deadlock, priority inversion, and convoying.
Lock-free data structures are built on atomic hardware primitives, primarily Compare-And-Swap (CAS). A CAS operation atomically compares a memory location to an expected value and, only if they match, replaces it with a new value. Algorithms typically use an optimistic approach: they read the current state, compute the desired new state, and attempt a CAS to install it. If the CAS fails (because another thread modified the state), the operation retries from the beginning.
Concurrent queues are a particularly important lock-free data structure for task scheduling systems. A high-performance concurrent queue must support multiple producers and multiple consumers without contention. Advanced designs use per-thread sub-queues, bulk operations, and careful memory reclamation to minimize cache-line bouncing and achieve throughput close to single-threaded queues.
Usage
Lock-free concurrent queues are used in DuckDB's task scheduler to distribute work items across worker threads. When the query execution engine generates parallel tasks (such as scanning different segments of a table or processing different pipeline stages), these tasks are enqueued into a concurrent queue. Worker threads dequeue tasks without locking, enabling efficient multi-core utilization with minimal synchronization overhead.
Theoretical Basis
Compare-And-Swap (CAS): The foundational atomic primitive:
// Atomic CAS operation (hardware-supported)
function CAS(address, expected, desired) -> bool:
atomically:
if *address == expected:
*address = desired
return true
else:
return false
Lock-Free Queue (Michael-Scott Algorithm):
// Linked-list based MPMC queue
structure Node { value, next: atomic<Node*> }
structure Queue { head: atomic<Node*>, tail: atomic<Node*> }
function enqueue(queue, value):
node = new Node(value, null)
loop:
tail = queue.tail
next = tail.next
if tail == queue.tail: // still consistent?
if next == null: // tail is at end?
if CAS(tail.next, null, node): // try append
CAS(queue.tail, tail, node) // advance tail
return
else:
CAS(queue.tail, tail, next) // help advance tail
function dequeue(queue) -> value:
loop:
head = queue.head
tail = queue.tail
next = head.next
if head == queue.head: // still consistent?
if head == tail: // empty or tail behind?
if next == null: return EMPTY
CAS(queue.tail, tail, next)
else:
value = next.value
if CAS(queue.head, head, next):
free(head)
return value
Progress Guarantees:
Lock-free: At least one thread completes in finite steps
Wait-free: Every thread completes in finite steps
Obstruction-free: A thread completes if run in isolation
Lock-free queues guarantee that if multiple threads
contend, at least one will succeed per CAS round.
Failed threads retry, but starvation is theoretically
possible (though rare in practice).