Storing and retrieving object in ray.io

Question

I have a ray cluster running on a machine as below:

ray start --head --redis-port=6379

I have two files that need to run on the cluster. Producer p_ray.py:

import ray
ray.init(address='auto', redis_password='5241590000000000')


@ray.remote
class Counter(object):
    def __init__(self):
        self.n = 0

    def increment(self):
        self.n += 1

    def read(self):
        return self.n


counters = [Counter.remote() for i in range(4)]
[c.increment.remote() for c in counters]
futures = [c.read.remote() for c in counters]
print(futures, type(futures[0]))
obj_id = ray.put(ray.get(futures))
print(obj_id)
print(ray.get(obj_id))
while True:
    pass

Consumer c_ray.py:

import ray
ray.init(address='auto', redis_password='5241590000000000')
[objs] = ray.objects()
print('OBJ-ID:', objs, 'TYPE:', type(objs))
print(ray.get([objs]))

My intention is to store the futures objects from producer and retrieve it in the consumer. I can retrieve the Object ID in the consumer. However the get in the consumer never returns.

What am I doing wrong?

How do I resolve my requirement?

score 0 · Answer 1 · answered Apr 05 '20 at 05:30

This particular case can be a bug (I am not 100% sure). I created an issue at Ray Github.

But, this is not a good way to get object created by the p_ray.py. If you have many objects, it will be extremely complicated to manage. You can implement a similar thing using a detached actor. https://ray.readthedocs.io/en/latest/advanced.html#detached-actors.

The idea is to create a detached actor that can be retrieved by any driver/worker running in the same cluster.

p_ray.py

import ray
ray.init(address='auto', redis_password='5241590000000000')

@ray.remote
class DetachedQueue:
    def __init__(self):
        self.dict = {}
    def put(key, value):
        self.dict[key] = value
    def get(self):
        return self.dict


@ray.remote
class Counter(object):
    def __init__(self):
        self.n = 0

    def increment(self):
        self.n += 1

    def read(self):
        return self.n


queue = DetachedQueue.remote(name="queue_1", detached=True)
counters = [Counter.remote() for i in range(4)]
[c.increment.remote() for c in counters]
futures = [c.read.remote() for c in counters]
print(futures, type(futures[0]))
queue.put.remote("key", ray.get(futures)))
while True:
    pass

c_ray.py:

import ray
ray.init(address='auto', redis_password='5241590000000000')
queue = ray.util.get_actor("queue_1")
print(ray.get(queue.get.remote()))

Storing and retrieving object in ray.io

1 Answers1