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crusaderky/internalize_keys_v2.ipynb

Created December 12, 2022 17:13
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internalize_keys_v2.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "074c04bc",
"metadata": {},
"outputs": [],
"source": [
"import dask\n",
"import dask.array as da\n",
"import distributed\n",
"\n",
"dask.config.set({\"distributed.comm.recent-messages-log-length\": int(1e9)})\n",
"c = distributed.Client(n_workers=10, threads_per_worker=2)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "2e01a4c6",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/crusaderky/miniconda3/envs/distributed39/lib/python3.9/site-packages/dask/array/routines.py:446: PerformanceWarning: Increasing number of chunks by factor of 20\n",
" out = blockwise(\n"
]
},
{
"data": {
"text/plain": [
"2051.608"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a = da.random.random((20, 20), chunks=(1, 1))\n",
"b = (a @ a.T).sum().round(3)\n",
"c.compute(b).result()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "eaa5d31e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2237"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"msgs = [\n",
" msg\n",
" for comm in c.cluster.scheduler.stream_comms.values()\n",
" for msg in comm.recent_message_log\n",
"]\n",
"len(msgs)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "3212423f",
"metadata": {},
"outputs": [],
"source": [
"from distributed.comm.utils import to_frames\n",
"\n",
"kwargs = {\n",
" \"allow_offload\": False,\n",
" \"context\": {\n",
" \"sender\": {\n",
" \"compression\": \"lz4\",\n",
" \"python\": (3, 9, 15),\n",
" \"pickle-protocol\": 5,\n",
" \"address\": \"tcp://127.0.0.1:43761\",\n",
" },\n",
" \"recipient\": {\n",
" \"compression\": \"lz4\",\n",
" \"python\": (3, 9, 15),\n",
" \"pickle-protocol\": 5,\n",
" \"address\": \"tcp://127.0.0.1:47634\",\n",
" },\n",
" \"pickle-protocol\": 5,\n",
" \"compression\": \"lz4\",\n",
" },\n",
" \"frame_split_size\": 67108864,\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "a99145ed",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5445"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"frames = [frame for msg in msgs for frame in await to_frames(msg, **kwargs)]\n",
"len(frames)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e1a1d1d1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"19118676"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum(len(frame) for frame in frames)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "b5d26fb6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"19198169"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum(comm.byte_count for comm in c.cluster.scheduler.stream_comms.values())"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "cd9e1d6e",
"metadata": {},
"outputs": [],
"source": [
"from collections import UserDict\n",
"from typing import TypeVar\n",
"\n",
"KT = TypeVar(\"KT\")\n",
"VT = TypeVar(\"VT\")\n",
"\n",
"\n",
"class FastLRU(UserDict[KT, VT]):\n",
" n: int\n",
"\n",
" def __init__(self, n: int):\n",
" super().__init__()\n",
" self.n = n\n",
"\n",
" def __getitem__(self, key: KT) -> VT:\n",
" value = self.data.pop(key)\n",
" self.data[key] = value\n",
" return value\n",
"\n",
" def __setitem__(self, key: KT, value: VT) -> None:\n",
" self.data.pop(key, None)\n",
" self.data[key] = value\n",
" if len(self.data) > self.n:\n",
" evict_key = next(iter(self.data))\n",
" del self.data[evict_key]"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "c8ab7289",
"metadata": {},
"outputs": [],
"source": [
"from typing import Any\n",
"from collections import defaultdict\n",
"\n",
"internalized = defaultdict(lambda: FastLRU(1000))\n",
"internalized_inc = defaultdict(lambda: -31)\n",
"\n",
"\n",
"def internalize(addr: str, msg: dict[str, Any]) -> dict[int, Any]:\n",
" intmap = internalized[addr]\n",
" new_keys = {}\n",
" out = {}\n",
"\n",
" def _internalize_one(k: str) -> tuple[int, bool]:\n",
" assert isinstance(k, str)\n",
"\n",
" if k in intmap:\n",
" return intmap[k]\n",
"\n",
" ki = intmap[k] = internalized_inc[addr]\n",
" internalized_inc[addr] += 1\n",
" new_keys[ki] = k\n",
" return ki\n",
"\n",
" for k, v in msg.items():\n",
" ki = _internalize_one(k)\n",
" if k in (\"op\", \"key\"):\n",
" vi = _internalize_one(v)\n",
" elif k == \"keys\":\n",
" vi = [_internalize_one(task_key) for task_key in v]\n",
" elif k == \"who_has\":\n",
" vi = {\n",
" _internalize_one(task_key): [\n",
" _internalize_one(peer_addr) for peer_addr in peers\n",
" ]\n",
" for task_key, peers in v.items()\n",
" }\n",
" elif k == \"nbytes\" and isinstance(v, dict):\n",
" vi = {\n",
" _internalize_one(task_key): nbytes_key\n",
" for task_key, nbytes_key in v.items()\n",
" }\n",
" else:\n",
" vi = v\n",
"\n",
" out[ki] = vi\n",
"\n",
" if new_keys:\n",
" out[-32] = new_keys\n",
" return out"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "1c2f6830",
"metadata": {},
"outputs": [],
"source": [
"internalized.clear()\n",
"msgs2 = [\n",
" [internalize(addr, msg_i) for msg_i in msg]\n",
" for addr, comm in c.cluster.scheduler.stream_comms.items()\n",
" for msg in comm.recent_message_log\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "b2f1c4ec",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"12374752"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"frames2 = [frame for msg in msgs2 for frame in await to_frames(msg, **kwargs)]\n",
"sum(len(frame) for frame in frames2)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "ab6105a1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.6472598834772868"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum(len(frame) for frame in frames2) / sum(len(frame) for frame in frames)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "9f3bfe24",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{-31: -30,\n",
" -29: -28,\n",
" -27: (0, 1, 3),\n",
" -26: 0.5,\n",
" -25: 'compute-task-1670865102.2892962',\n",
" -24: {},\n",
" -23: {},\n",
" -22: None,\n",
" -21: b\"\\x80\\x05\\x95'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x8c\\x11dask.array.random\\x94\\x8c\\r_apply_random\\x94\\x93\\x94.\",\n",
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" -19: None,\n",
" -18: {},\n",
" -17: False,\n",
" -16: {},\n",
" -32: {-31: 'op',\n",
" -30: 'compute-task',\n",
" -29: 'key',\n",
" -28: \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 0, 1)\",\n",
" -27: 'priority',\n",
" -26: 'duration',\n",
" -25: 'stimulus_id',\n",
" -24: 'who_has',\n",
" -23: 'nbytes',\n",
" -22: 'run_spec',\n",
" -21: 'function',\n",
" -20: 'args',\n",
" -19: 'kwargs',\n",
" -18: 'resource_restrictions',\n",
" -17: 'actor',\n",
" -16: 'annotations'}}"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"msgs2[0][0]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "4d0a4f3e",
"metadata": {},
"outputs": [
{
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" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 14, 10)\": 1106,\n",
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" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 3, 13)\": 1956,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 2, 13)\": 1955,\n",
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" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 8, 4, 19)\": 1919,\n",
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" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 8, 7, 19)\": 1979,\n",
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" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 2, 5)\": 1961,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 0, 5)\": 1871,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 7, 14)\": 1969,\n",
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" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 4, 14)\": 1968,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 13, 5, 19)\": 1931,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 17, 3, 19)\": 1917,\n",
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" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 18, 5, 19)\": 1977,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 18, 7, 19)\": 1976,\n",
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" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 18, 4, 19)\": 1926,\n",
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" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 4, 9)\": 115,\n",
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" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 12, 9)\": 844,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 9, 9)\": 2021,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 15, 9)\": 1231,\n",
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" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 1, 13)\": 988,\n",
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" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 7, 12)\": 1408,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 5, 12)\": 1401,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 15, 13)\": 1217,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 14, 13)\": 1104,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 18, 12)\": 1765,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 19, 12)\": 1987,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 18, 9)\": 1744,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 3, 13)\": 992,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 17, 13)\": 1579,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 4, 13)\": 2045,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 8, 9)\": 392,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 14, 9)\": 2046,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 19, 9)\": 1997,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 16, 9)\": 1394,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 19, 13)\": 2002,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 16, 13)\": 1413,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 6, 14)\": 979,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 12, 15)\": 886,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 13, 14)\": 974,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 10, 15)\": 2055,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 9, 15)\": 523,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 18, 14)\": 1770,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 8, 14)\": 983,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 15, 14)\": 1228,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 18, 15)\": 1772,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 0, 15)\": 2060,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 2, 15)\": 64,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 3, 14)\": 977,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 3, 15)\": 2065,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 1, 15)\": 2066,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 17, 15)\": 1584,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 11, 15)\": 2067,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 17, 14)\": 1572,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 13, 15)\": 2068,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 4, 14)\": 981,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 4, 15)\": 124,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 5, 15)\": 2072,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 5, 8, 19)\": 2020,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 5, 9, 19)\": 2019,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 5, 10, 19)\": 1901,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 5, 11, 19)\": 2018,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 14, 15)\": 2077,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 7, 15)\": 2078,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 8, 15)\": 435,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 10, 18)\": 1910,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 6, 15)\": 2083,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 15, 15)\": 2084,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 19, 14)\": 2009,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 19, 15)\": 2013,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 7, 10, 19)\": 1903,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 9, 10, 19)\": 1904,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 3, 10, 19)\": 1897,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 4, 10, 19)\": 1899,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 13, 13, 19)\": 2001,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 15, 4)\": 2014,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 13, 1)\": 2004,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 14, 12, 19)\": 1990,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 12, 11)\": 1993,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 12, 7)\": 1992,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 13, 5)\": 2005,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 15, 13, 19)\": 2003,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 17, 9, 19)\": 2000,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 17, 11, 19)\": 2025,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 17, 10, 19)\": 2024,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 17, 8, 19)\": 2023,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 9, 13)\": 2044,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 11, 13)\": 2043,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 8, 13)\": 2042,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 10, 13)\": 1908,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 18, 19)\": 1814,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 15, 18)\": 2016,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 12, 18)\": 1995,\n",
" \"('random_sample-6ce13c13cb36fbcde1b268a4383d2e0b', 0, 19)\": 1823,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 12, 9, 19)\": 2033,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 12, 10, 19)\": 1905,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 12, 11, 19)\": 2032,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 12, 8, 19)\": 2031,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 10, 3)\": 1906,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 9, 3)\": 2029,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 8, 3)\": 2028,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 11, 3)\": 2027,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 2, 12, 19)\": 1986,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 2, 13, 19)\": 2064,\n",
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" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 5, 14, 19)\": 2076,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 5, 13, 19)\": 2075,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 5, 12, 19)\": 1988,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 5, 15, 19)\": 2074,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 8, 14, 19)\": 2082,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 8, 12, 19)\": 1989,\n",
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" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 5, 2, 19)\": 2017,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 0, 3)\": 2105,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 2, 3)\": 2026,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 3, 3)\": 2051,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 1, 3)\": 2104,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 2, 5)\": 2034,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 0, 5)\": 1960,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 17, 18)\": 2097,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 8, 1, 19)\": 1978,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 8, 3, 19)\": 2079,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 16, 16, 19)\": 2098,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 16, 19, 19)\": 2087,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 16, 18, 19)\": 2088,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 3, 13)\": 2069,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 2, 13)\": 2041,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 1, 13)\": 2112,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 0, 13)\": 1953,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 12, 2, 19)\": 2030,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 12, 3, 19)\": 2110,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 12, 1, 19)\": 2109,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 12, 0, 19)\": 2108,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 16, 14)\": 2125,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 19, 14)\": 2124,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 18, 14)\": 2123,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 17, 14)\": 2096,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 19, 16)\": 2136,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 17, 16)\": 2135,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 18, 16)\": 2091,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 16, 16)\": 2134,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 14, 17, 19)\": 2093,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 19, 9)\": 2085,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 3, 12)\": 2047,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 18, 2, 19)\": 2128,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 18, 1, 19)\": 1974,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 18, 0, 19)\": 2127,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 18, 3, 19)\": 2056,\n",
" 'tcp://127.0.0.1:38803': 96,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 19, 5)\": 2140,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 18, 5)\": 2139,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 17, 5)\": 2095,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 16, 5)\": 2138,\n",
" \"('chunk_sum-c78e699c9856a5e466f40bf2cdcbd1d8', 19, 18, 17)\": 2092,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 19, 2, 11)\": 2037,\n",
" \"('_chunk_sum-partial-0f7bbd226243ccf7712ab3482dc5a8d5', 17, 2, 19)\": 2022,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 5, 0, 19)\": 2100,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 19, 1, 5)\": 2137,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 12, 1, 19)\": 2142,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 12, 0, 19)\": 2107,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 19, 1, 14)\": 2122,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 19, 0, 14)\": 2144,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 19, 0, 13)\": 2111,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 19, 0, 3)\": 2103,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 18, 0, 19)\": 2126,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 18, 1, 19)\": 2148,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 19, 1, 16)\": 2133,\n",
" \"('_chunk_sum-partial-486467af6bb4ef77d3c8543498498fcd', 19, 0, 16)\": 2146,\n",
" \"('chunk_sum-aggregate-sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 12, 19)\": 2141,\n",
" \"('chunk_sum-aggregate-sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 19, 14)\": 2143,\n",
" \"('chunk_sum-aggregate-sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 19, 16)\": 2145,\n",
" 'tcp://127.0.0.1:44275': 34,\n",
" 'tcp://127.0.0.1:45867': 7,\n",
" 'tcp://127.0.0.1:40631': 5,\n",
" \"('chunk_sum-aggregate-sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 18, 19)\": 2147,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 18, 10)\": 1936,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 11, 19)\": 2156,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 10, 18)\": 1937,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 10, 19)\": 2155,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 11, 18)\": 2154,\n",
" 'tcp://127.0.0.1:34747': 38,\n",
" 'tcp://127.0.0.1:43503': 14,\n",
" 'tcp://127.0.0.1:41751': -5,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 18, 0)\": 1894,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 18, 16)\": 2160,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 19, 16)\": 2152,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 18, 17)\": 2159,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 19, 17)\": 2158,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 12, 18)\": 1918,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 12, 19)\": 2149,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 18, 19)\": 2151,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 19, 14)\": 2150,\n",
" \"('sum-a4c1f3dbb8ba1cd8f98d98306a8f6e73', 18, 15)\": 1938,\n",
" \"('sum-partial-0f3d1bb65e7292a26cc8796719c3b36b', 5, 9)\": 2153,\n",
" \"('sum-partial-0f3d1bb65e7292a26cc8796719c3b36b', 5, 8)\": 2164,\n",
" \"('sum-partial-0f3d1bb65e7292a26cc8796719c3b36b', 4, 9)\": 2163,\n",
" \"('sum-partial-0f3d1bb65e7292a26cc8796719c3b36b', 4, 8)\": 2162,\n",
" \"('sum-partial-0f3d1bb65e7292a26cc8796719c3b36b', 6, 8)\": 1703,\n",
" 'compute-task': -30,\n",
" 'key': -29,\n",
" 'priority': -27,\n",
" 'duration': -26,\n",
" 'who_has': -24,\n",
" 'tcp://127.0.0.1:33555': -12,\n",
" 'tcp://127.0.0.1:44633': 36,\n",
" 'nbytes': -23,\n",
" 'run_spec': -22,\n",
" 'function': -21,\n",
" 'args': -20,\n",
" 'kwargs': -19,\n",
" 'resource_restrictions': -18,\n",
" 'actor': -17,\n",
" 'annotations': -16,\n",
" \"('sum-partial-0f3d1bb65e7292a26cc8796719c3b36b', 9, 8)\": 2157,\n",
" \"('sum-partial-5d075da542faf75ef5f0a732f660e461', 3, 4)\": 2166,\n",
" \"('sum-partial-5d075da542faf75ef5f0a732f660e461', 2, 4)\": 2161,\n",
" 'op': -31,\n",
" 'free-keys': 10,\n",
" 'keys': 11,\n",
" \"('sum-partial-bb10a823a628d807e0e8697e383a1da9', 1, 2)\": 2165,\n",
" 'stimulus_id': -25}"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"next(iter(internalized.values())).data"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "8eb7e685",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:ylabel='None'>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x1080 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from collections import Counter\n",
"import msgpack\n",
"import pandas\n",
"from distributed.protocol.serialize import Serialized\n",
"\n",
"cnt = Counter()\n",
"for msg in msgs:\n",
" for msg_i in msg:\n",
" for k, v in msg_i.items():\n",
" if isinstance(v, Serialized):\n",
" for frame in v.frames:\n",
" cnt[k] += len(frame)\n",
" else:\n",
" cnt[k] += len(msgpack.dumps(v))\n",
"\n",
"ds = pandas.Series(cnt)\n",
"ds.plot(kind=\"pie\", figsize=(15, 15))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "21958dd8",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.15"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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