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Apache Beam Dask Limitation MRE
import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions
from apache_beam.runners.dask.dask_runner import DaskRunner
from dask.distributed import Client, performance_report
class NoopDoFn(beam.DoFn):
def process(self, item):
import time
time.sleep(0.1)
return [item]
def run_pipeline(n_items):
client = Client()
pipeline = beam.Pipeline(
runner=DaskRunner(),
options=PipelineOptions(["--dask_client_address", client.cluster.scheduler_address]),
)
(
pipeline
| "Create collection" >> beam.Create(range(n_items))
| "Noop 1" >> beam.ParDo(NoopDoFn())
| "Noop 2" >> beam.ParDo(NoopDoFn())
| "Noop 3" >> beam.ParDo(NoopDoFn())
)
with performance_report(filename=f"dask-report-{n_items}.html"):
result = pipeline.run()
result.wait_until_finish()
def main() -> None:
# If this is 199 I get one task per item per stage (800 tasks, 199 concurrent)
run_pipeline(199)
# If this is 200 I get max 100 tasks per stage (404 tasks, 100 concurrent)
run_pipeline(200)
if __name__ == "__main__":
main()
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Dask Performance Report</title>
<link rel="shortcut icon" href="https://docs.dask.org/en/latest/_static/images/favicon.ico" />
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js"></script>
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js"></script>
<script type="text/javascript">
Bokeh.set_log_level("info");
</script>
</head>
<body>
<div class="bk-root" id="aa632539-3edc-406c-8b82-48154332fe35" data-root-id="1413"></div>
<script type="application/json" id="3214">
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lightgray","height":"100%","max-height":"1080px","max-width":"1920px","overflow":"auto","padding":"12px","width":"100%"},"text":"\n &lt;h1&gt; Dask Performance Report &lt;/h1&gt;\n\n &lt;i&gt; Select different tabs on the top for additional information &lt;/i&gt;\n\n &lt;h2&gt; Duration: 6.46 s &lt;/h2&gt;\n &lt;h2&gt; Tasks Information &lt;/h2&gt;\n &lt;ul&gt;\n &lt;li&gt; number of tasks: 800 &lt;/li&gt;\n \n&lt;li&gt; compute time: 60.03 s &lt;/li&gt;\n&lt;li&gt; transfer time: 325.85 ms &lt;/li&gt;\n &lt;/ul&gt;\n\n &lt;h2&gt; Scheduler Information &lt;/h2&gt;\n &lt;ul&gt;\n &lt;li&gt; Address: tcp://127.0.0.1:37139 &lt;/li&gt;\n &lt;li&gt; Workers: 4 &lt;/li&gt;\n &lt;li&gt; Threads: 12 &lt;/li&gt;\n &lt;li&gt; Memory: 93.03 GiB &lt;/li&gt;\n &lt;li&gt; Dask Version: 2023.4.1 &lt;/li&gt;\n &lt;li&gt; Dask.Distributed Version: 2023.4.1 &lt;/li&gt;\n &lt;/ul&gt;\n\n &lt;h2&gt; Calling Code &lt;/h2&gt;\n &lt;pre&gt;\ndef run_pipeline(n_items):\n client = Client()\n pipeline = 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