fleet-memory/hindsight-api/hindsight_api/worker/poller.py
Nicolò Boschi 4c792400c1
feat: new 'worker' service (#176)
* feat: new 'worker' service

* doc

* docs

* tests
2026-01-20 10:17:56 +01:00

281 lines
10 KiB
Python

"""
Worker poller for distributed task execution.
Polls PostgreSQL for pending tasks and executes them using
FOR UPDATE SKIP LOCKED for safe concurrent claiming.
"""
import asyncio
import json
import logging
import traceback
from collections.abc import Awaitable, Callable
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
import asyncpg
logger = logging.getLogger(__name__)
def fq_table(table: str, schema: str | None = None) -> str:
"""Get fully-qualified table name with optional schema prefix."""
if schema:
return f'"{schema}".{table}'
return table
class WorkerPoller:
"""
Polls PostgreSQL for pending tasks and executes them.
Uses FOR UPDATE SKIP LOCKED for safe distributed claiming,
allowing multiple workers to process tasks without conflicts.
"""
def __init__(
self,
pool: "asyncpg.Pool",
worker_id: str,
executor: Callable[[dict[str, Any]], Awaitable[None]],
poll_interval_ms: int = 500,
batch_size: int = 10,
max_retries: int = 3,
schema: str | None = None,
):
"""
Initialize the worker poller.
Args:
pool: asyncpg connection pool
worker_id: Unique identifier for this worker
executor: Async function to execute tasks (typically MemoryEngine.execute_task)
poll_interval_ms: Interval between polls when no tasks found (milliseconds)
batch_size: Maximum number of tasks to claim per poll cycle
max_retries: Maximum retry attempts before marking task as failed
schema: Database schema for multi-tenant support (optional)
"""
self._pool = pool
self._worker_id = worker_id
self._executor = executor
self._poll_interval_ms = poll_interval_ms
self._batch_size = batch_size
self._max_retries = max_retries
self._schema = schema
self._shutdown = asyncio.Event()
self._current_tasks: set[asyncio.Task] = set()
self._in_flight_count = 0
self._in_flight_lock = asyncio.Lock()
async def claim_batch(self) -> list[tuple[str, dict[str, Any]]]:
"""
Claim up to batch_size pending tasks atomically.
Uses FOR UPDATE SKIP LOCKED to ensure no conflicts with other workers.
Returns:
List of tuples (operation_id, task_dict)
"""
table = fq_table("async_operations", self._schema)
async with self._pool.acquire() as conn:
async with conn.transaction():
# Select and lock pending tasks
rows = await conn.fetch(
f"""
SELECT operation_id, task_payload
FROM {table}
WHERE status = 'pending' AND task_payload IS NOT NULL
ORDER BY created_at
LIMIT $1
FOR UPDATE SKIP LOCKED
""",
self._batch_size,
)
if not rows:
return []
# Claim the tasks by updating status and worker_id
operation_ids = [row["operation_id"] for row in rows]
await conn.execute(
f"""
UPDATE {table}
SET status = 'processing', worker_id = $1, claimed_at = now(), updated_at = now()
WHERE operation_id = ANY($2)
""",
self._worker_id,
operation_ids,
)
# Parse and return task payloads
return [(str(row["operation_id"]), json.loads(row["task_payload"])) for row in rows]
async def _mark_completed(self, operation_id: str):
"""Mark a task as completed."""
table = fq_table("async_operations", self._schema)
await self._pool.execute(
f"""
UPDATE {table}
SET status = 'completed', completed_at = now(), updated_at = now()
WHERE operation_id = $1
""",
operation_id,
)
async def _mark_failed(self, operation_id: str, error_message: str):
"""Mark a task as failed with error message."""
table = fq_table("async_operations", self._schema)
# Truncate error message if too long (max 5000 chars in schema)
error_message = error_message[:5000] if len(error_message) > 5000 else error_message
await self._pool.execute(
f"""
UPDATE {table}
SET status = 'failed', error_message = $2, completed_at = now(), updated_at = now()
WHERE operation_id = $1
""",
operation_id,
error_message,
)
async def _retry_or_fail(self, operation_id: str, error_message: str):
"""Increment retry count or mark as failed if max retries exceeded."""
table = fq_table("async_operations", self._schema)
# Get current retry count
row = await self._pool.fetchrow(
f"SELECT retry_count FROM {table} WHERE operation_id = $1",
operation_id,
)
if row is None:
logger.warning(f"Operation {operation_id} not found, cannot retry")
return
retry_count = row["retry_count"]
if retry_count >= self._max_retries:
# Max retries exceeded, mark as failed
await self._mark_failed(
operation_id, f"Max retries ({self._max_retries}) exceeded. Last error: {error_message}"
)
logger.error(f"Task {operation_id} failed after {retry_count} retries")
else:
# Increment retry and reset to pending
await self._pool.execute(
f"""
UPDATE {table}
SET status = 'pending', worker_id = NULL, claimed_at = NULL,
retry_count = retry_count + 1, updated_at = now()
WHERE operation_id = $1
""",
operation_id,
)
logger.warning(f"Task {operation_id} failed, will retry (attempt {retry_count + 1}/{self._max_retries})")
async def execute_task(self, operation_id: str, task_dict: dict[str, Any]):
"""Execute a single task and update its status."""
task_type = task_dict.get("type", "unknown")
bank_id = task_dict.get("bank_id", "unknown")
try:
logger.debug(f"Executing task {operation_id} (type={task_type}, bank={bank_id})")
await self._executor(task_dict)
await self._mark_completed(operation_id)
logger.debug(f"Task {operation_id} completed successfully")
except Exception as e:
error_msg = f"{type(e).__name__}: {e}\n{traceback.format_exc()}"
logger.error(f"Task {operation_id} failed: {e}")
await self._retry_or_fail(operation_id, error_msg)
async def run(self):
"""
Main polling loop.
Continuously polls for pending tasks, claims them, and executes them
until shutdown is signaled.
"""
logger.info(f"Worker {self._worker_id} starting polling loop")
while not self._shutdown.is_set():
try:
# Claim a batch of tasks
tasks = await self.claim_batch()
if tasks:
# Log batch info
task_types = {}
for _, task_dict in tasks:
t = task_dict.get("type", "unknown")
task_types[t] = task_types.get(t, 0) + 1
types_str = ", ".join(f"{k}:{v}" for k, v in task_types.items())
logger.info(f"Worker {self._worker_id} claimed {len(tasks)} tasks: {types_str}")
# Track in-flight tasks
async with self._in_flight_lock:
self._in_flight_count += len(tasks)
# Execute tasks concurrently
try:
await asyncio.gather(
*[self.execute_task(op_id, task_dict) for op_id, task_dict in tasks],
return_exceptions=True,
)
finally:
async with self._in_flight_lock:
self._in_flight_count -= len(tasks)
else:
# No tasks found, wait before polling again
try:
await asyncio.wait_for(
self._shutdown.wait(),
timeout=self._poll_interval_ms / 1000,
)
except asyncio.TimeoutError:
pass # Normal timeout, continue polling
except asyncio.CancelledError:
logger.info(f"Worker {self._worker_id} polling loop cancelled")
break
except Exception as e:
logger.error(f"Worker {self._worker_id} error in polling loop: {e}")
traceback.print_exc()
# Backoff on error
await asyncio.sleep(1)
logger.info(f"Worker {self._worker_id} polling loop stopped")
async def shutdown_graceful(self, timeout: float = 30.0):
"""
Signal shutdown and wait for current tasks to complete.
Args:
timeout: Maximum time to wait for in-flight tasks (seconds)
"""
logger.info(f"Worker {self._worker_id} initiating graceful shutdown")
self._shutdown.set()
# Wait for in-flight tasks to complete
start_time = asyncio.get_event_loop().time()
while asyncio.get_event_loop().time() - start_time < timeout:
async with self._in_flight_lock:
in_flight = self._in_flight_count
if in_flight == 0:
logger.info(f"Worker {self._worker_id} graceful shutdown complete")
return
logger.info(f"Worker {self._worker_id} waiting for {in_flight} in-flight tasks")
await asyncio.sleep(0.5)
logger.warning(f"Worker {self._worker_id} shutdown timeout after {timeout}s")
@property
def worker_id(self) -> str:
"""Get the worker ID."""
return self._worker_id
@property
def is_shutdown(self) -> bool:
"""Check if shutdown has been signaled."""
return self._shutdown.is_set()