# Timing based RayTaskError(JSONDecodeError) error?

**URL:** <https://discuss.ray.io/t/timing-based-raytaskerror-jsondecodeerror-error/1475>\
**Category:** Ray Core\
**Created:** [March 30, 2021, 6:46pm UTC](https://discuss.ray.io/t/timing-based-raytaskerror-jsondecodeerror-error/1475 "2021-03-30T18:46:19Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![ricklamers](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/ricklamers/32/709_2.png) [@ricklamers](https://discuss.ray.io/u/ricklamers)\
**Post date:** [March 30, 2021, 6:46pm UTC](https://discuss.ray.io/t/timing-based-raytaskerror-jsondecodeerror-error/1475/1 "2021-03-30T18:46:19Z")

</div>

I ran into an issue with [GitHub - DerwenAI/ray\_tutorial: An introductory tutorial about leveraging Ray core features for distributed patterns.](https://github.com/DerwenAI/ray_tutorial) not sure if it’s Ray or not causing the issue.

```auto
RayTaskError(JSONDecodeError) Traceback (most recent call last)
<ipython-input-13-2a75d4802248> in <module>
      1 wc_sum = defaultdict(int)
      2 
----> 3 for wc in ray.get(work):
      4 for token, count in wc.items():
      5 wc_sum[token] += count
/opt/conda/lib/python3.7/site-packages/ray/_private/client_mode_hook.py in wrapper(*args, **kwargs)
     45 if client_mode_enabled and _client_hook_enabled:
     46 return getattr(ray, func. __name__ )(*args, **kwargs)
---> 47 return func(*args, **kwargs)
     48 
     49 return wrapper
/opt/conda/lib/python3.7/site-packages/ray/worker.py in get(object_refs, timeout)
   1454 worker.core_worker.dump_object_store_memory_usage()
   1455 if isinstance(value, RayTaskError):
-> 1456 raise value.as_instanceof_cause()
   1457 else:
   1458 raise value

```

It’s in `ex_para_iter.ipynb` [[link](https://github.com/DerwenAI/ray_tutorial/blob/main/ex_para_iter.ipynb)].

Is it expected to fail if execution of this cell:

```auto
nb_items = list(Path(".").glob("ex_*.ipynb"))

iter3 = ray.util.iter.from_items(nb_items, num_shards=3)

work = [nb_word_count.remote(shard) for shard in iter3.shards()]

```

is quickly succeeded by

```auto
wc_sum = defaultdict(int)for wc in ray.get(work):
   for token, count in wc.items():
       wc_sum[token] += count

```