## Project description

If you're using Dask with tasks that use a lot of memory, RAM is your bottleneck for parallelism. That means you want to know how much memory each task uses:

1. So you can set the highest parallelism level (process or threads) for each machine, given available to RAM.
2. In order to know where to focus memory optimization efforts.

dask-memusage is an MIT-licensed statistical memory profiler for Dask's Distributed scheduler that can help you with both these problems.

dask-memusage polls your processes for memory usage and records the minimum and maximum usage in a CSV:

task_key,min_memory_mb,max_memory_mb
"('from_sequence-map-sum-part-e15703211a549e75b11c63e0054b53e5', 0)",44.84765625,96.98046875
"('from_sequence-map-sum-part-e15703211a549e75b11c63e0054b53e5', 1)",47.015625,97.015625
"('sum-part-e15703211a549e75b11c63e0054b53e5', 0)",0,0
"('sum-part-e15703211a549e75b11c63e0054b53e5', 1)",0,0
sum-aggregate-apply-no_allocate-4c30eb545d4c778f0320d973d9fc8ea6,0,0
apply-no_allocate-4c30eb545d4c778f0320d973d9fc8ea6,47.265625,47.265625
"('from_sequence-map-sum-part-e15703211a549e75b11c63e0054b53e5', 0)",44.84765625,96.98046875
"('from_sequence-map-sum-part-e15703211a549e75b11c63e0054b53e5', 1)",47.015625,97.015625
"('sum-part-e15703211a549e75b11c63e0054b53e5', 0)",0,0
"('sum-part-e15703211a549e75b11c63e0054b53e5', 1)",0,0
sum-aggregate-apply-no_allocate-4c30eb545d4c778f0320d973d9fc8ea6,0,0
apply-no_allocate-4c30eb545d4c778f0320d973d9fc8ea6,47.265625,47.265625


## Usage

Important: Make sure your workers only have a single thread! Otherwise the results will be wrong.

### Installation

On the machine where you are running the Distributed scheduler, run:



## Limitations

• Again, make sure you only have one thread per worker process.
• This is statistical profiling, running every 10ms. Tasks that take less than that won't have accurate information.

## Help

Need help? File a ticket at https://github.com/itamarst/dask-memusage/issues/new

## Project details

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