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February 5, 2020 14:25
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Zarr vs Zarr-HDF5 read time comparison\n", | |
"Compute the maximum water level during Hurricane Ike on a 9 million node triangular mesh storm surge model. This reads 53GB of data. " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import xarray as xr\n", | |
"from dask.distributed import Client, progress, performance_report\n", | |
"from dask_kubernetes import KubeCluster\n", | |
"import fsspec\n", | |
"\n", | |
"from zarr.storage import FileChunkStore" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"### Start a dask cluster to crunch the data" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"cluster = KubeCluster()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"cluster.scale(30);" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"application/vnd.jupyter.widget-view+json": { | |
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"version_major": 2, | |
"version_minor": 0 | |
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"text/plain": [ | |
"VBox(children=(HTML(value='<h2>KubeCluster</h2>'), HBox(children=(HTML(value='\\n<div>\\n <style scoped>\\n .…" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"cluster" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"client = Client(cluster)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<table style=\"border: 2px solid white;\">\n", | |
"<tr>\n", | |
"<td style=\"vertical-align: top; border: 0px solid white\">\n", | |
"<h3 style=\"text-align: left;\">Client</h3>\n", | |
"<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n", | |
" <li><b>Scheduler: </b>tcp://192.168.173.238:33959</li>\n", | |
" <li><b>Dashboard: </b><a href='/user/rsignell-usgs-h-ke-water-levels-urb2n6zi/proxy/8787/status' target='_blank'>/user/rsignell-usgs-h-ke-water-levels-urb2n6zi/proxy/8787/status</a>\n", | |
"</ul>\n", | |
"</td>\n", | |
"<td style=\"vertical-align: top; border: 0px solid white\">\n", | |
"<h3 style=\"text-align: left;\">Cluster</h3>\n", | |
"<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n", | |
" <li><b>Workers: </b>30</li>\n", | |
" <li><b>Cores: </b>60</li>\n", | |
" <li><b>Memory: </b>210.00 GB</li>\n", | |
"</ul>\n", | |
"</td>\n", | |
"</tr>\n", | |
"</table>" | |
], | |
"text/plain": [ | |
"<Client: 'tcp://192.168.173.238:33959' processes=30 threads=60, memory=210.00 GB>" | |
] | |
}, | |
"execution_count": 6, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"client" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"### Read the data from Zarr format" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"CPU times: user 1.05 s, sys: 38.9 ms, total: 1.09 s\n", | |
"Wall time: 4.76 s\n" | |
] | |
} | |
], | |
"source": [ | |
"%%time\n", | |
"ds = xr.open_zarr(fsspec.get_mapper('s3://pangeo-data-uswest2/esip/adcirc/adcirc_01d', anon=False, requester_pays=True))" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Compute the max water level at each grid cell (reads all the data):" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 8, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"CPU times: user 12.7 s, sys: 1.01 s, total: 13.7 s\n", | |
"Wall time: 32.1 s\n" | |
] | |
} | |
], | |
"source": [ | |
"%%time\n", | |
"with performance_report(filename=\"dask-zarr-report.html\"):\n", | |
" max_var1 = ds['zeta'].max(dim='time').compute()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"### Read the data from NetCDF4/HDF5 format, using the Zarr-HDF5 Connection\n", | |
"\n", | |
"The chunk locations from the netCDF4/HDF5 file are added to the Zarr consolidated `.zmetadata` file. Access to these chunks is then enabled via a `chunk_store` argument to zarr, which then reads chunk data directly from the netCDF4/HDF5 file. " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 9, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"CPU times: user 269 ms, sys: 41.9 ms, total: 311 ms\n", | |
"Wall time: 1.01 s\n" | |
] | |
} | |
], | |
"source": [ | |
"%%time\n", | |
"store = fsspec.get_mapper('s3://hdf5-zarr/adcirc_01d.nc.chunkstore', anon=True)\n", | |
"\n", | |
"ncfile = fsspec.open('s3://pangeo-data-uswest2/esip/adcirc/adcirc_01d.nc', mode='rb', \n", | |
" anon=False, requester_pays=True, default_fill_cache=False)\n", | |
"\n", | |
"chunk_store = FileChunkStore(store, chunk_source=ncfile.open())\n", | |
"\n", | |
"ds = xr.open_zarr(store, consolidated=True, chunk_store=chunk_store)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 10, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"CPU times: user 12.6 s, sys: 1.12 s, total: 13.8 s\n", | |
"Wall time: 32 s\n" | |
] | |
} | |
], | |
"source": [ | |
"%%time\n", | |
"with performance_report(filename=\"dask-hdf5-report.html\"):\n", | |
" max_var2 = ds['zeta'].max(dim='time').compute()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Check a value to see if the two methods match" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 11, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array(4.90311857)" | |
] | |
}, | |
"execution_count": 11, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"max_var1[1000].values" | |
] | |
}, | |
{ | |
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"execution_count": 12, | |
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{ | |
"data": { | |
"text/plain": [ | |
"array(4.90311857)" | |
] | |
}, | |
"execution_count": 12, | |
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} | |
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"max_var2[1000].values" | |
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} | |
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