# All tasks in PENDING\_NODE\_ASSIGNMENT but workers' CPUs are busy

**URL:** <https://discuss.ray.io/t/all-tasks-in-pending-node-assignment-but-workers-cpus-are-busy/10957>\
**Category:** Ray Data\
**Created:** [June 7, 2023, 2:37pm UTC](https://discuss.ray.io/t/all-tasks-in-pending-node-assignment-but-workers-cpus-are-busy/10957 "2023-06-07T14:37:42Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![mlts](https://avatars.discourse-cdn.com/v4/letter/m/a88e57/32.png) [@mlts](https://discuss.ray.io/u/mlts)\
**Post date:** [June 7, 2023, 2:37pm UTC](https://discuss.ray.io/t/all-tasks-in-pending-node-assignment-but-workers-cpus-are-busy/10957/1 "2023-06-07T14:37:42Z")

</div>

I am loading data from a gcs bucket path with large number of parquet files. I can see thousands of tasks called “\_map\_task” in PENDING\_NODE\_ASSIGNMENT mode, no task in Running state, but most of the workers’ CPU cores are more than 80% busy.

My code is like the following:

```auto
import gcsfs
data = ray.data.read_parquet("path", filesystem=gcsfs.GCSFileSystem()) # there are thousands of parquet files in the path
data = data.select_columns(cols=[...])
data.take(10)

```

How do I find out what the cluster is doing?

---

<div class="post-metadata">

**Author:** ![kai](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/kai/32/3380_2.png) [@kai](https://discuss.ray.io/u/kai)\
**Post date:** [June 14, 2023, 8:17am UTC](https://discuss.ray.io/t/all-tasks-in-pending-node-assignment-but-workers-cpus-are-busy/10957/2 "2023-06-14T08:17:19Z")

</div>

You can use the Ray Dashboard to examine which tasks and actors are running, and also get an insight on the current stacktraces of the different processes:

[https://docs.ray.io/en/latest/ray-observability/getting-started.html#set-up-dashboard](https://docs.ray.io/en/latest/ray-observability/getting-started.html#set-up-dashboard)