internalize_keys.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3a111273",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-12-12 12:10:48,387 - distributed.diskutils - INFO - Found stale lock file and directory '/tmp/dask-worker-space/worker-08vdd8bn', purging\n"
     ]
    }
   ],
   "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": "95408cb4",
   "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": [
       "2149.161"
      ]
     },
     "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": "9ad90020",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2273"
      ]
     },
     "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": "da9af256",
   "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": "93a8d556",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5481"
      ]
     },
     "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": "db7de818",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19051783"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(len(frame) for frame in frames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1bec5c5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19131999"
      ]
     },
     "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": 12,
   "id": "e7a498dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from typing import Any\n",
    "from collections import defaultdict\n",
    "\n",
    "internalized = {}\n",
    "\n",
    "def internalize(addr: str, msg: dict[str, Any]) -> dict[int, Any]:\n",
    "    intmap = internalized.setdefault(addr, {})\n",
    "    out = {}\n",
    "    new_keys = {}\n",
    "    for k, v in msg.items():\n",
    "        assert isinstance(k, str)\n",
    "\n",
    "        try:\n",
    "            ki = intmap[k]\n",
    "        except KeyError:\n",
    "            ki = intmap[k] = len(intmap) - 31\n",
    "            new_keys[ki] = k\n",
    "\n",
    "        if k == \"op\":\n",
    "            assert isinstance(v, str)\n",
    "            try:\n",
    "                vi = intmap[v]\n",
    "            except KeyError:\n",
    "                vi = intmap[v] = len(intmap) - 31\n",
    "                new_keys[vi] = v\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": 13,
   "id": "dd880f07",
   "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": 14,
   "id": "2e3ffc0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17090404"
      ]
     },
     "execution_count": 14,
     "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": 15,
   "id": "3e0137f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8970501081184895"
      ]
     },
     "execution_count": 15,
     "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": 16,
   "id": "8eb76664",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " -29: \"('random_sample-ea441a278d9d09ac7b03c574ddf4897d', 0, 2)\",\n",
       " -28: (0, 1, 6),\n",
       " -27: 0.5,\n",
       " -26: 'compute-task-1670847052.353606',\n",
       " -25: {},\n",
       " -24: {},\n",
       " -23: None,\n",
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       " -20: None,\n",
       " -19: {},\n",
       " -18: False,\n",
       " -17: {},\n",
       " -32: {-31: 'op',\n",
       "  -30: 'compute-task',\n",
       "  -29: 'key',\n",
       "  -28: 'priority',\n",
       "  -27: 'duration',\n",
       "  -26: 'stimulus_id',\n",
       "  -25: 'who_has',\n",
       "  -24: 'nbytes',\n",
       "  -23: 'run_spec',\n",
       "  -22: 'function',\n",
       "  -21: 'args',\n",
       "  -20: 'kwargs',\n",
       "  -19: 'resource_restrictions',\n",
       "  -18: 'actor',\n",
       "  -17: 'annotations'}}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "msgs2[0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e55fec79",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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