parallel-post-fit-scheduler-issues

parallel-post-fit-scheduler-issues.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "56adb93f",
   "metadata": {},
   "source": [
    "# Dask-ML ParallelPostFit issues with large model object\n",
    "\n",
    "TL;DR - getting scheduler failure with large model objects and ParallelPostFit. Workaround is use `map_partitions` with `client.scatter(model, brodacast=True)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0ebf20f6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-01T19:29:28.360886Z",
     "iopub.status.busy": "2021-07-01T19:29:28.360542Z",
     "iopub.status.idle": "2021-07-01T19:29:30.986716Z",
     "shell.execute_reply": "2021-07-01T19:29:30.985866Z",
     "shell.execute_reply.started": "2021-07-01T19:29:28.360803Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dask                      2021.5.1           pyhd8ed1ab_0    conda-forge\n",
      "dask-core                 2021.5.1           pyhd8ed1ab_0    conda-forge\n",
      "dask-glm                  0.2.0                      py_1    conda-forge\n",
      "dask-ml                   1.9.0              pyhd8ed1ab_0    conda-forge\n",
      "dask-saturn               0.2.3                    pypi_0    pypi\n",
      "distributed               2021.5.1         py38h578d9bd_0    conda-forge\n",
      "scikit-learn              0.24.2           py38hdc147b9_0    conda-forge\n"
     ]
    }
   ],
   "source": [
    "!conda list --name saturn | grep -e dask -e distributed -e scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a61b8f61",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-01T19:29:30.988439Z",
     "iopub.status.busy": "2021-07-01T19:29:30.988174Z",
     "iopub.status.idle": "2021-07-01T19:29:37.419150Z",
     "shell.execute_reply": "2021-07-01T19:29:37.418517Z",
     "shell.execute_reply.started": "2021-07-01T19:29:30.988403Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:dask-saturn:Cluster is ready\n",
      "INFO:dask-saturn:Registering default plugins\n",
      "INFO:dask-saturn:{'tcp://192.168.131.72:36159': {'status': 'repeat'}, 'tcp://192.168.193.73:38569': {'status': 'repeat'}, 'tcp://192.168.50.133:41839': {'status': 'repeat'}}\n"
     ]
    }
   ],
   "source": [
    "from dask_ml.datasets import make_classification_df\n",
    "from dask_ml.model_selection import train_test_split\n",
    "from dask_ml.wrappers import ParallelPostFit\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import cloudpickle\n",
    "from dask_saturn import SaturnCluster\n",
    "from dask.distributed import Client, wait\n",
    "\n",
    "cluster = SaturnCluster(\n",
    "    scheduler_size='large',  # 2 vCPUs, 16GB RAM\n",
    "    worker_size='large',  # 2 vCPUs, 16GB RAM\n",
    "    nprocs=1,\n",
    "    nthreads=2,\n",
    ")\n",
    "client = Client(cluster)\n",
    "seed = 42\n",
    "\n",
    "X, y = make_classification_df(\n",
    "    n_samples=50000,\n",
    "    chunks=1000,\n",
    "    random_state=seed,\n",
    ")\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, \n",
    "    test_size=0.5,\n",
    "    random_state=seed, \n",
    "    shuffle=True,\n",
    ")\n",
    "\n",
    "# compute to use scikit-learn for training\n",
    "X_train = X_train.compute()\n",
    "y_train = y_train.compute()\n",
    "\n",
    "# persist test set\n",
    "X_test = X_test.persist()\n",
    "y_test = y_test.persist()\n",
    "_ = wait(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "740871c0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-01T19:29:37.420724Z",
     "iopub.status.busy": "2021-07-01T19:29:37.420492Z",
     "iopub.status.idle": "2021-07-01T19:29:37.431414Z",
     "shell.execute_reply": "2021-07-01T19:29:37.430590Z",
     "shell.execute_reply.started": "2021-07-01T19:29:37.420693Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.npartitions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bb19afbc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-01T19:29:37.433104Z",
     "iopub.status.busy": "2021-07-01T19:29:37.432862Z",
     "iopub.status.idle": "2021-07-01T19:29:47.519711Z",
     "shell.execute_reply": "2021-07-01T19:29:47.519074Z",
     "shell.execute_reply.started": "2021-07-01T19:29:37.433074Z"
    }
   },
   "outputs": [],
   "source": [
    "rf = ParallelPostFit(\n",
    "    RandomForestClassifier(n_estimators=100, random_state=seed, n_jobs=-1)\n",
    ")\n",
    "_ = rf.fit(X_train, y_train)\n",
    "\n",
    "with open('/tmp/model.pkl', 'wb') as f:\n",
    "    cloudpickle.dump(rf, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0aaedaed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-01T19:29:47.525205Z",
     "iopub.status.busy": "2021-07-01T19:29:47.520886Z",
     "iopub.status.idle": "2021-07-01T19:29:48.311007Z",
     "shell.execute_reply": "2021-07-01T19:29:48.310020Z",
     "shell.execute_reply.started": "2021-07-01T19:29:47.525178Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-r--r-- 1 jovyan users 56M Jul  1 19:29 /tmp/model.pkl\n"
     ]
    }
   ],
   "source": [
    "!ls -alh /tmp/model.pkl"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9c26099",
   "metadata": {},
   "source": [
    "The following cell will eventually error after ~40 minutes and take down the cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a95c5770",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-01T19:17:15.951034Z",
     "iopub.status.busy": "2021-07-01T19:17:15.950809Z"
    }
   },
   "outputs": [],
   "source": [
    "%%time\n",
    "preds = rf.predict(X_test)\n",
    "_ = preds.compute()"
   ]
  },
  {
   "attachments": {
    "5dc5efca-0dbd-4643-b753-1b681f9baff7.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "67941e65",
   "metadata": {},
   "source": [
    "The scheduler memory tops out and holds at 2.86GB, which is approximately 50 times the size of the model object.\n",
    "\n",
    "This makes me think that the scheduler memory use = npartitions * model size. \n",
    "\n",
    "![image.png](attachment:5dc5efca-0dbd-4643-b753-1b681f9baff7.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8655b805",
   "metadata": {},
   "source": [
    "Error message:\n",
    "\n",
    "```\n",
    "CancelledError: ('_predict-00c7f0ef1863f3f75149cc7cef02e658', 43)\n",
    "\n",
    "distributed.client - ERROR - Failed to reconnect to scheduler after 10.00 seconds, closing client\n",
    "ERROR:asyncio:_GatheringFuture exception was never retrieved\n",
    "future: <_GatheringFuture finished exception=CancelledError()>\n",
    "asyncio.exceptions.CancelledError\n",
    "```\n",
    "\n",
    "\n",
    "\n",
    "<details>\n",
    "    <summary>Full stack trace</summary>\n",
    "\n",
    "```\n",
    "---------------------------------------------------------------------------\n",
    "CancelledError                            Traceback (most recent call last)\n",
    "<timed exec> in <module>\n",
    "\n",
    "/srv/conda/envs/saturn/lib/python3.8/site-packages/dask/base.py in compute(self, **kwargs)\n",
    "    283         dask.base.compute\n",
    "    284         \"\"\"\n",
    "--> 285         (result,) = compute(self, traverse=False, **kwargs)\n",
    "    286         return result\n",
    "    287 \n",
    "\n",
    "/srv/conda/envs/saturn/lib/python3.8/site-packages/dask/base.py in compute(*args, **kwargs)\n",
    "    565         postcomputes.append(x.__dask_postcompute__())\n",
    "    566 \n",
    "--> 567     results = schedule(dsk, keys, **kwargs)\n",
    "    568     return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])\n",
    "    569 \n",
    "\n",
    "/srv/conda/envs/saturn/lib/python3.8/site-packages/distributed/client.py in get(self, dsk, keys, workers, allow_other_workers, resources, sync, asynchronous, direct, retries, priority, fifo_timeout, actors, **kwargs)\n",
    "   2670                     should_rejoin = False\n",
    "   2671             try:\n",
    "-> 2672                 results = self.gather(packed, asynchronous=asynchronous, direct=direct)\n",
    "   2673             finally:\n",
    "   2674                 for f in futures.values():\n",
    "\n",
    "/srv/conda/envs/saturn/lib/python3.8/site-packages/distributed/client.py in gather(self, futures, errors, direct, asynchronous)\n",
    "   1979             else:\n",
    "   1980                 local_worker = None\n",
    "-> 1981             return self.sync(\n",
    "   1982                 self._gather,\n",
    "   1983                 futures,\n",
    "\n",
    "/srv/conda/envs/saturn/lib/python3.8/site-packages/distributed/client.py in sync(self, func, asynchronous, callback_timeout, *args, **kwargs)\n",
    "    850             return future\n",
    "    851         else:\n",
    "--> 852             return sync(\n",
    "    853                 self.loop, func, *args, callback_timeout=callback_timeout, **kwargs\n",
    "    854             )\n",
    "\n",
    "/srv/conda/envs/saturn/lib/python3.8/site-packages/distributed/utils.py in sync(loop, func, callback_timeout, *args, **kwargs)\n",
    "    352     if error[0]:\n",
    "    353         typ, exc, tb = error[0]\n",
    "--> 354         raise exc.with_traceback(tb)\n",
    "    355     else:\n",
    "    356         return result[0]\n",
    "\n",
    "/srv/conda/envs/saturn/lib/python3.8/site-packages/distributed/utils.py in f()\n",
    "    335             if callback_timeout is not None:\n",
    "    336                 future = asyncio.wait_for(future, callback_timeout)\n",
    "--> 337             result[0] = yield future\n",
    "    338         except Exception as exc:\n",
    "    339             error[0] = sys.exc_info()\n",
    "\n",
    "/srv/conda/envs/saturn/lib/python3.8/site-packages/tornado/gen.py in run(self)\n",
    "    760 \n",
    "    761                     try:\n",
    "--> 762                         value = future.result()\n",
    "    763                     except Exception:\n",
    "    764                         exc_info = sys.exc_info()\n",
    "\n",
    "/srv/conda/envs/saturn/lib/python3.8/site-packages/distributed/client.py in _gather(self, futures, errors, direct, local_worker)\n",
    "   1845                         else:\n",
    "   1846                             raise exception.with_traceback(traceback)\n",
    "-> 1847                         raise exc\n",
    "   1848                     if errors == \"skip\":\n",
    "   1849                         bad_keys.add(key)\n",
    "\n",
    "CancelledError: ('_predict-00c7f0ef1863f3f75149cc7cef02e658', 43)\n",
    "\n",
    "distributed.client - ERROR - Failed to reconnect to scheduler after 10.00 seconds, closing client\n",
    "ERROR:asyncio:_GatheringFuture exception was never retrieved\n",
    "future: <_GatheringFuture finished exception=CancelledError()>\n",
    "asyncio.exceptions.CancelledError\n",
    "```\n",
    "    \n",
    "<details>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b08f705",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-01T19:19:12.152738Z",
     "iopub.status.busy": "2021-07-01T19:19:12.152493Z",
     "iopub.status.idle": "2021-07-01T19:19:21.997347Z",
     "shell.execute_reply": "2021-07-01T19:19:21.996717Z",
     "shell.execute_reply.started": "2021-07-01T19:19:12.152714Z"
    }
   },
   "source": [
    "## Try without ParallelPostFit\n",
    "\n",
    "We can use `map_partitions` with the scikit-learn model directly and avoid `ParallelPostFit`. The following cell has the same error behavior because it's doing exactly what `ParallelPostFit` does under the hood."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d41289b",
   "metadata": {},
   "outputs": [],
   "source": [
    "rf = RandomForestClassifier(n_estimators=100, random_state=seed, n_jobs=-1)\n",
    "_ = rf.fit(X_train, y_train)\n",
    "\n",
    "def dask_predict(df):\n",
    "    return rf.predict(df)\n",
    "\n",
    "preds = X_test.map_partitions(dask_predict, meta=np.array([1]))\n",
    "_ = preds.compute()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed08a32a",
   "metadata": {},
   "source": [
    "## Workaround\n",
    "\n",
    "By scattering the model with `broadcast=True` and then giving the future to the `map_partitions` call, we bypass the scheduler and don't clog up the memory. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f70979e9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-01T19:30:51.741422Z",
     "iopub.status.busy": "2021-07-01T19:30:51.741184Z",
     "iopub.status.idle": "2021-07-01T19:32:49.503177Z",
     "shell.execute_reply": "2021-07-01T19:32:49.502440Z",
     "shell.execute_reply.started": "2021-07-01T19:30:51.741398Z"
    }
   },
   "outputs": [],
   "source": [
    "rf = RandomForestClassifier(n_estimators=100, random_state=seed, n_jobs=-1)\n",
    "_ = rf.fit(X_train, y_train)\n",
    "\n",
    "rf_fut = client.scatter(rf, broadcast=True)\n",
    "\n",
    "def dask_predict(df, model):\n",
    "    return model.predict(df)\n",
    "\n",
    "preds = X_test.map_partitions(\n",
    "    dask_predict,\n",
    "    model=rf_fut,\n",
    "    meta=np.array([1])\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcc99587",
   "metadata": {},
   "source": [
    "The following cell completes in less than a second and doesn't impact the scheduler memory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6092173e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-01T19:33:00.484948Z",
     "iopub.status.busy": "2021-07-01T19:33:00.484706Z",
     "iopub.status.idle": "2021-07-01T19:33:01.347346Z",
     "shell.execute_reply": "2021-07-01T19:33:01.346652Z",
     "shell.execute_reply.started": "2021-07-01T19:33:00.484923Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 37 ms, sys: 3.62 ms, total: 40.7 ms\n",
      "Wall time: 858 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "_ = preds.compute()"
   ]
  },
  {
   "attachments": {
    "390f7ee4-d460-4543-908f-d1c2aeec1d86.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "4c53f12d",
   "metadata": {},
   "source": [
    "![image.png](attachment:390f7ee4-d460-4543-908f-d1c2aeec1d86.png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "saturn (Python 3)",
   "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}