What happened:

As part of a really long multi-day debug session I've finally figured out the root of my problem. I replaced some old code with a single no-dependency map_blocks function and started to run into some issues when the result was included a larger application that involved rechunking. I've discovered that the main issue is that the chunks keyword argument isn't considered in the tokenized name so you can produce two different arrays that result in the same name. This isn't a big problem at first glance as you can do .compute() and get the final array you expect, but it is a problem when these arrays start getting used in other tasks that may or may not include chunking. In my use case I ran into cases where if I computed two arrays that were dependent on these similar map_blocks results the scheduler would choose one or the other depending on the order that they were passed to da.compute(.

What you expected to happen:

Either:

1. Documentation in the map_blocks docstring about needing inputs to make the name unique including chunks and dtype. Or how to generate a name "manually" that will include this information as well as the args, kwargs, and function name.
2. Include chunks (and maybe other meta information) in the name generation for the output.

This would be similar to how you can call da.zeros multiple times with the same shape but different chunk size and get arrays with different names.

Minimal Complete Verifiable Example:

def test_func(fake_in, block_info=None):
    return np.zeros(block_info[None]['chunk-shape'])

fake_input = 1
res1 = da.map_blocks(test_func, fake_input, chunks=((2,), (3, 3, 2, 1, 1), (2, 2, 2, 1, 1, 1, 1)), meta=np.array((), dtype=np.float64), dtype=np.float64)
res2 = da.map_blocks(test_func, fake_input, chunks=((2,), (6, 2, 2), (6, 4)), meta=np.array((), dtype=np.float64), dtype=np.float64)

res1.name
# 'test_func-7ea2153c7f07c8abd6f3181bc0975958'

res2.name
# 'test_func-7ea2153c7f07c8abd6f3181bc0975958'

## Looks like dtype is the same way

res3 = da.map_blocks(test_func, fake_input, chunks=((2,), (3, 3, 2, 1, 1), (2, 2, 2, 1, 1, 1, 1)), meta=np.array((), dtype=np.float32), dtype=np.float32)

res3.name
# 'test_func-7ea2153c7f07c8abd6f3181bc0975958'

Anything else we need to know?:

This may be related to #6649.

Environment:

• Dask version: 2021.11.2 (but seen on multiple)
• Python version: 3.9
• Operating System: PopOS
• Install method (conda, pip, source): conda/conda-forge