{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lab 6 Reversed Lecture\n",
    "\n",
    "In this reverse lecture, we'll explore in more details a subset of the functionality of [dask](dask.org), a parallel data processing library for Python. We'll spend the majority of our time on dask's [`DataFrame`](https://docs.dask.org/en/latest/dataframe.html) API, as well as examine concepts such as lazy computation and its relationship with the different schedulers.\n",
    "\n",
    "We'll follow that by data processing using columnar binary data (Parquet), and end with a brief overview of dask's [`Bag`](https://docs.dask.org/en/latest/bag.html) API, using a JSON data \"scraper\" as working example.\n",
    "\n",
    "We close with a list of additional resources for you to learn more about dask, including examples on how to use it for ML tasks. Finally, for the take home portion of this lab, you'll solve three parallel programming assignments, which we detail on the [github repo](https://github.com/mitdbg/datascienceclass/blob/master/spring_2022/lab_6/README.md). \n",
    "\n",
    "## Running this notebook\n",
    "\n",
    "To execute code from a cell, you can either click `Run` at the top, or type `shift+Enter` after clicking a cell.  You can either run the entire notebook (`Restart & Run All` from the `Kernel` drop-down), or run each cell individually.  If you choose the latter, note that it is important that you run cells in order, as later cells depend on earlier ones. And to be able to `Run All` successfully, you'll have to write code for answering some of the questions in the notebook.\n",
    "\n",
    "Once you open your notebook on the browser, and check that the cells are rendering correctly (e.g., try running the \"Python packages\" cell below), we're good to go from there."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python packages we'll need\n",
    "\n",
    "First, import the python packages we'll be using for the lab:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "from time import perf_counter\n",
    "\n",
    "# Data processing.\n",
    "import json\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# Q6: For loading multiple CSVs into a single (pandas) dataframe.\n",
    "import glob\n",
    "import os\n",
    "\n",
    "# Plotting.\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "import seaborn as sns\n",
    "sns.set_style('whitegrid')\n",
    "\n",
    "# \"Vanilla\" python parallelism.\n",
    "import multiprocessing\n",
    "\n",
    "# Scalable data analytics: dask.\n",
    "import dask\n",
    "import dask.dataframe as dd\n",
    "from dask.distributed import Client, LocalCluster\n",
    "import graphviz\n",
    "\n",
    "# Unused: scalable data analytics using Spark.\n",
    "#from pyspark.sql import SparkSession\n",
    "\n",
    "# For GC large pandas dataframes after use.\n",
    "import gc\n",
    "\n",
    "# Ignore warnings.\n",
    "import warnings\n",
    "warnings.simplefilter(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Intro to `dask`\n",
    "\n",
    "Dask is a python library aimed at parallel computation. It comprises two main components: a task scheduler, and a collection of data structures suited for different parallel programming tasks. Take a look at the [main page of their documentation](https://docs.dask.org/en/latest/) for more details.\n",
    "\n",
    "In this part of the reverse lecture, we'll introduce you to a subset of these features, as well as cover example tasks using the two different categories of dask schedulers.\n",
    "\n",
    "Additionally, of special interest to our course is the fact that dask provides an interface that almost exactly matches that of numpy arrays and pandas dataframes. We'll see that this is useful when speeding up some of the data analysis tasks we've covered so far in our course.\n",
    "\n",
    "\n",
    "### Example pandas vs dask comparison: data loading\n",
    "\n",
    "Before getting into too many details about the different task schedulers, let's take a look at a simple example runtime comparison between pandas and dask. Specifically, let's load the same spotify dataset from lab 4 in both, and see how long each one takes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 981 ms, sys: 96.3 ms, total: 1.08 s\n",
      "Wall time: 1.35 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# load dataset using pandas:\n",
    "df = pd.read_csv('data/spotify_songs.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 23.2 ms, sys: 0 ns, total: 23.2 ms\n",
      "Wall time: 56.5 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# load dataset using dask:\n",
    "dd_df = dd.read_csv('data/spotify_songs.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we already see more than a 25x difference, which is impressive. However, this is also because dask does *lazy* computation.  That is, dask arrays have the required shape and data type, but they still point to data on disk. The loading is *lazy* in the sense that dask will load the array contents into memory (and in small chunks) only when necessary.\n",
    "\n",
    "We can observe this effect in action when we ask dask to compute an operation that requires inspecting the entire contents of the dataset.\n",
    "\n",
    "**Q1. Inspect the runtime each of the two dataframes (both pandas and dask) using `describe()`. How does the output in pandas compare to that of dask?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 146 ms, sys: 9.1 ms, total: 155 ms\n",
      "Wall time: 158 ms\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>popularity</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>danceability</th>\n",
       "      <th>duration_ms</th>\n",
       "      <th>energy</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>liveness</th>\n",
       "      <th>loudness</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>tempo</th>\n",
       "      <th>valence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>228159.000000</td>\n",
       "      <td>228159.000000</td>\n",
       "      <td>228159.000000</td>\n",
       "      <td>2.281590e+05</td>\n",
       "      <td>228159.000000</td>\n",
       "      <td>228159.000000</td>\n",
       "      <td>228159.000000</td>\n",
       "      <td>228159.000000</td>\n",
       "      <td>228159.000000</td>\n",
       "      <td>228159.000000</td>\n",
       "      <td>228159.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>44.209130</td>\n",
       "      <td>0.351200</td>\n",
       "      <td>0.554198</td>\n",
       "      <td>2.366092e+05</td>\n",
       "      <td>0.580967</td>\n",
       "      <td>0.137310</td>\n",
       "      <td>0.214638</td>\n",
       "      <td>-9.354658</td>\n",
       "      <td>0.122442</td>\n",
       "      <td>117.423062</td>\n",
       "      <td>0.444795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>17.276599</td>\n",
       "      <td>0.351385</td>\n",
       "      <td>0.183949</td>\n",
       "      <td>1.166787e+05</td>\n",
       "      <td>0.260577</td>\n",
       "      <td>0.292447</td>\n",
       "      <td>0.196977</td>\n",
       "      <td>5.940994</td>\n",
       "      <td>0.186264</td>\n",
       "      <td>30.712458</td>\n",
       "      <td>0.255397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.056900</td>\n",
       "      <td>1.550900e+04</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009670</td>\n",
       "      <td>-52.457000</td>\n",
       "      <td>0.022200</td>\n",
       "      <td>30.379000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>33.000000</td>\n",
       "      <td>0.030900</td>\n",
       "      <td>0.437000</td>\n",
       "      <td>1.862530e+05</td>\n",
       "      <td>0.405000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.097700</td>\n",
       "      <td>-11.287000</td>\n",
       "      <td>0.036800</td>\n",
       "      <td>92.734000</td>\n",
       "      <td>0.232000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>47.000000</td>\n",
       "      <td>0.205000</td>\n",
       "      <td>0.570000</td>\n",
       "      <td>2.211730e+05</td>\n",
       "      <td>0.618000</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>0.128000</td>\n",
       "      <td>-7.515000</td>\n",
       "      <td>0.050600</td>\n",
       "      <td>115.347000</td>\n",
       "      <td>0.430000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>57.000000</td>\n",
       "      <td>0.689000</td>\n",
       "      <td>0.690000</td>\n",
       "      <td>2.648400e+05</td>\n",
       "      <td>0.793000</td>\n",
       "      <td>0.023400</td>\n",
       "      <td>0.263000</td>\n",
       "      <td>-5.415000</td>\n",
       "      <td>0.109000</td>\n",
       "      <td>138.887000</td>\n",
       "      <td>0.643000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.996000</td>\n",
       "      <td>0.987000</td>\n",
       "      <td>5.552917e+06</td>\n",
       "      <td>0.999000</td>\n",
       "      <td>0.999000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.585000</td>\n",
       "      <td>0.967000</td>\n",
       "      <td>239.848000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          popularity   acousticness   danceability   duration_ms  \\\n",
       "count  228159.000000  228159.000000  228159.000000  2.281590e+05   \n",
       "mean       44.209130       0.351200       0.554198  2.366092e+05   \n",
       "std        17.276599       0.351385       0.183949  1.166787e+05   \n",
       "min         0.000000       0.000001       0.056900  1.550900e+04   \n",
       "25%        33.000000       0.030900       0.437000  1.862530e+05   \n",
       "50%        47.000000       0.205000       0.570000  2.211730e+05   \n",
       "75%        57.000000       0.689000       0.690000  2.648400e+05   \n",
       "max       100.000000       0.996000       0.987000  5.552917e+06   \n",
       "\n",
       "              energy  instrumentalness       liveness       loudness  \\\n",
       "count  228159.000000     228159.000000  228159.000000  228159.000000   \n",
       "mean        0.580967          0.137310       0.214638      -9.354658   \n",
       "std         0.260577          0.292447       0.196977       5.940994   \n",
       "min         0.000020          0.000000       0.009670     -52.457000   \n",
       "25%         0.405000          0.000000       0.097700     -11.287000   \n",
       "50%         0.618000          0.000037       0.128000      -7.515000   \n",
       "75%         0.793000          0.023400       0.263000      -5.415000   \n",
       "max         0.999000          0.999000       1.000000       1.585000   \n",
       "\n",
       "         speechiness          tempo        valence  \n",
       "count  228159.000000  228159.000000  228159.000000  \n",
       "mean        0.122442     117.423062       0.444795  \n",
       "std         0.186264      30.712458       0.255397  \n",
       "min         0.022200      30.379000       0.000000  \n",
       "25%         0.036800      92.734000       0.232000  \n",
       "50%         0.050600     115.347000       0.430000  \n",
       "75%         0.109000     138.887000       0.643000  \n",
       "max         0.967000     239.848000       1.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Q1: YOUR CODE GOES HERE (pandas)\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 125 ms, sys: 20.8 ms, total: 145 ms\n",
      "Wall time: 151 ms\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><strong>Dask DataFrame Structure:</strong></div>\n",
       "<div>\n",
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       "      <th>danceability</th>\n",
       "      <th>duration_ms</th>\n",
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       "      <td>float64</td>\n",
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       "      <td>float64</td>\n",
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       "</div>\n",
       "<div>Dask Name: describe-numeric, 64 tasks</div>"
      ],
      "text/plain": [
       "Dask DataFrame Structure:\n",
       "              popularity acousticness danceability duration_ms   energy instrumentalness liveness loudness speechiness    tempo  valence\n",
       "npartitions=1                                                                                                                           \n",
       "                 float64      float64      float64     float64  float64          float64  float64  float64     float64  float64  float64\n",
       "                     ...          ...          ...         ...      ...              ...      ...      ...         ...      ...      ...\n",
       "Dask Name: describe-numeric, 64 tasks"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Q1: YOUR CODE GOES HERE (dask)   \n",
    "dd_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that just running `describe()` on dask *still* does not perform the whole computation. If you want dask to actually perform computations, you need to call `compute()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.32 s, sys: 189 ms, total: 1.51 s\n",
      "Wall time: 1.33 s\n"
     ]
    },
    {
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       "      <th>mean</th>\n",
       "      <td>44.209130</td>\n",
       "      <td>0.351200</td>\n",
       "      <td>0.554198</td>\n",
       "      <td>2.366092e+05</td>\n",
       "      <td>0.580967</td>\n",
       "      <td>0.137310</td>\n",
       "      <td>0.214638</td>\n",
       "      <td>-9.354658</td>\n",
       "      <td>0.122442</td>\n",
       "      <td>117.423062</td>\n",
       "      <td>0.444795</td>\n",
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       "      <th>std</th>\n",
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       "      <td>0.351385</td>\n",
       "      <td>0.183949</td>\n",
       "      <td>1.166787e+05</td>\n",
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       "      <td>0.255397</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
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       "      <td>-52.457000</td>\n",
       "      <td>0.022200</td>\n",
       "      <td>30.379000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>33.000000</td>\n",
       "      <td>0.030900</td>\n",
       "      <td>0.437000</td>\n",
       "      <td>1.862530e+05</td>\n",
       "      <td>0.405000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.097700</td>\n",
       "      <td>-11.287000</td>\n",
       "      <td>0.036800</td>\n",
       "      <td>92.734000</td>\n",
       "      <td>0.232000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>47.000000</td>\n",
       "      <td>0.205000</td>\n",
       "      <td>0.570000</td>\n",
       "      <td>2.211730e+05</td>\n",
       "      <td>0.618000</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>0.128000</td>\n",
       "      <td>-7.515000</td>\n",
       "      <td>0.050600</td>\n",
       "      <td>115.347000</td>\n",
       "      <td>0.430000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>57.000000</td>\n",
       "      <td>0.689000</td>\n",
       "      <td>0.690000</td>\n",
       "      <td>2.648400e+05</td>\n",
       "      <td>0.793000</td>\n",
       "      <td>0.023400</td>\n",
       "      <td>0.263000</td>\n",
       "      <td>-5.415000</td>\n",
       "      <td>0.109000</td>\n",
       "      <td>138.887000</td>\n",
       "      <td>0.643000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.996000</td>\n",
       "      <td>0.987000</td>\n",
       "      <td>5.552917e+06</td>\n",
       "      <td>0.999000</td>\n",
       "      <td>0.999000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.585000</td>\n",
       "      <td>0.967000</td>\n",
       "      <td>239.848000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          popularity   acousticness   danceability   duration_ms  \\\n",
       "count  228159.000000  228159.000000  228159.000000  2.281590e+05   \n",
       "mean       44.209130       0.351200       0.554198  2.366092e+05   \n",
       "std        17.276599       0.351385       0.183949  1.166787e+05   \n",
       "min         0.000000       0.000001       0.056900  1.550900e+04   \n",
       "25%        33.000000       0.030900       0.437000  1.862530e+05   \n",
       "50%        47.000000       0.205000       0.570000  2.211730e+05   \n",
       "75%        57.000000       0.689000       0.690000  2.648400e+05   \n",
       "max       100.000000       0.996000       0.987000  5.552917e+06   \n",
       "\n",
       "              energy  instrumentalness       liveness       loudness  \\\n",
       "count  228159.000000     228159.000000  228159.000000  228159.000000   \n",
       "mean        0.580967          0.137310       0.214638      -9.354658   \n",
       "std         0.260577          0.292447       0.196977       5.940994   \n",
       "min         0.000020          0.000000       0.009670     -52.457000   \n",
       "25%         0.405000          0.000000       0.097700     -11.287000   \n",
       "50%         0.618000          0.000037       0.128000      -7.515000   \n",
       "75%         0.793000          0.023400       0.263000      -5.415000   \n",
       "max         0.999000          0.999000       1.000000       1.585000   \n",
       "\n",
       "         speechiness          tempo        valence  \n",
       "count  228159.000000  228159.000000  228159.000000  \n",
       "mean        0.122442     117.423062       0.444795  \n",
       "std         0.186264      30.712458       0.255397  \n",
       "min         0.022200      30.379000       0.000000  \n",
       "25%         0.036800      92.734000       0.232000  \n",
       "50%         0.050600     115.347000       0.430000  \n",
       "75%         0.109000     138.887000       0.643000  \n",
       "max         0.967000     239.848000       1.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Q1: YOUR CODE GOES HERE (dask)   \n",
    "dd_df.describe().compute()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also inspect the task graph that dask assembles and executes for the computation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd_df.describe().visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see above, dask will try and perform as many block computations as possible, only merging and aggregating block results as needed.\n",
    "\n",
    "**Q2. Why do we have 11 \"pipelines\" in parallel for computing quantiles in the task graph above?**\n",
    "\n",
    "**a)** This is the number of workers dask is using for the computation.\n",
    "\n",
    "**b)** This is the number of categorical columns the dataframe has.\n",
    "\n",
    "**c)** This is the number of numerical columns the dataframe has.\n",
    "\n",
    "**d)** This is the number of threads dask is using for the computation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task scheduler\n",
    "\n",
    "Dask provides two categories of task schedulers: *single machine* and *distributed*. From the client setup [documentation](https://docs.dask.org/en/latest/setup.html?highlight=client#setup): \n",
    "\n",
    "> **Single machine scheduler:** This scheduler provides basic features on a local process or thread pool. This scheduler was made first and is the default. It is simple and cheap to use. It can only be used on a single machine and does not scale.\n",
    ">\n",
    "> **Distributed scheduler:** This scheduler is more sophisticated. It offers more features, but also requires a bit more effort to set up. It can run locally or distributed across a cluster.\n",
    "\n",
    "If you load data into a dask dataframe, and run some computation on it, when you call `compute()` to start the computation it will use the *single machine scheduler*. For example, the sum over `acousticness` below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.32 ms, sys: 543 µs, total: 3.86 ms\n",
      "Wall time: 2.51 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "80129.52932901"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# sum values for acousticness column using pandas\n",
    "df.acousticness.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 397 ms, sys: 38.8 ms, total: 435 ms\n",
      "Wall time: 556 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "80129.52932901"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# sum values for acousticness column using dask.\n",
    "# This computation uses the single machine scheduler:\n",
    "dd_df.acousticness.sum().compute()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To use the *distributed scheduler* (even if single node on the same machine), you need to explicitly create a dask [`Client`](https://docs.dask.org/en/latest/setup.html?highlight=client#setup).  Hence, starting a dask `Client` is optional. We'll go through this step, however, as it provides an example of how to setup a [`LocalCluster`](https://distributed.dask.org/en/latest/local-cluster.html). Creating a dask client will also provide a dashboard that we can use to monitor the dask workers while they're computing results for us.\n",
    "\n",
    "There are several ways to create a dask client that connects to a `LocalCluster`. We'll do each step explicitly, although if you create a `Client` without specifying which cluster to connect to, by default dask will create a task scheduler associated to a `LocalCluster` instance.\n",
    "\n",
    "First, we check how many cores we have in our machine:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of cores we have:  4\n"
     ]
    }
   ],
   "source": [
    "n_cores = multiprocessing.cpu_count()\n",
    "print('number of cores we have: ', n_cores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll use that to size the number of workers for our `LocalCluster` instance, and create a `Client` connected to it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
       "    <div style=\"margin-left: 48px;\">\n",
       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-dd6903a2-bb5e-11ec-818e-0242ac110002</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "\n",
       "        <tr>\n",
       "        \n",
       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
       "        \n",
       "        </tr>\n",
       "\n",
       "        \n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\"></td>\n",
       "            </tr>\n",
       "        \n",
       "\n",
       "        </table>\n",
       "\n",
       "        \n",
       "            <details>\n",
       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
       "    </div>\n",
       "    <div style=\"margin-left: 48px;\">\n",
       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">3c1a221b</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Workers:</strong> 4\n",
       "                </td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total threads:</strong> 4\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total memory:</strong> 4.00 GiB\n",
       "                </td>\n",
       "            </tr>\n",
       "            \n",
       "            <tr>\n",
       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
       "</tr>\n",
       "\n",
       "            \n",
       "        </table>\n",
       "\n",
       "        <details>\n",
       "            <summary style=\"margin-bottom: 20px;\">\n",
       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
       "            </summary>\n",
       "\n",
       "            <div style=\"\">\n",
       "    <div>\n",
       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
       "        <div style=\"margin-left: 48px;\">\n",
       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-997fa3b8-a2fb-443e-a4ba-a0ec472306b8</p>\n",
       "            <table style=\"width: 100%; text-align: left;\">\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Comm:</strong> tcp://127.0.0.1:40207\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Workers:</strong> 4\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total threads:</strong> 4\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Started:</strong> Just now\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total memory:</strong> 4.00 GiB\n",
       "                    </td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "\n",
       "    <details style=\"margin-left: 48px;\">\n",
       "        <summary style=\"margin-bottom: 20px;\">\n",
       "            <h3 style=\"display: inline;\">Workers</h3>\n",
       "        </summary>\n",
       "\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:45621\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 1\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:33287/status\" target=\"_blank\">http://127.0.0.1:33287/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 1.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:40565\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /lab6/dask-worker-space/worker-snvej31k\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:37189\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 1\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:39913/status\" target=\"_blank\">http://127.0.0.1:39913/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 1.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:35815\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /lab6/dask-worker-space/worker-c486532k\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:41385\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 1\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:41233/status\" target=\"_blank\">http://127.0.0.1:41233/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 1.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:42763\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /lab6/dask-worker-space/worker-uyf8pey0\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:32815\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 1\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:44221/status\" target=\"_blank\">http://127.0.0.1:44221/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 1.00 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:36303\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /lab6/dask-worker-space/worker-yyyfj0k5\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "    </details>\n",
       "</div>\n",
       "\n",
       "        </details>\n",
       "    </div>\n",
       "</div>\n",
       "            </details>\n",
       "        \n",
       "\n",
       "    </div>\n",
       "</div>"
      ],
      "text/plain": [
       "<Client: 'tcp://127.0.0.1:40207' processes=4 threads=4, memory=4.00 GiB>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# multithreaded:\n",
    "# cluster = LocalCluster(n_workers=1, processes=False, threads_per_worker=4)\n",
    "# multiprocessing:\n",
    "# cluster = LocalCluster(n_workers=n_cores, processes=True)\n",
    "\n",
    "# If we start out the dask-scheduler from CLI on the Docker container using:\n",
    "# $ dask-scheduler --host 0.0.0.0 --dashboard-address 8787\n",
    "#\n",
    "# Then we specify the address for the client explicitly:\n",
    "# client = Client(address='0.0.0.0:8786')\n",
    "\n",
    "# If we start out the dask-scheduler from this jupyter notebook, then need\n",
    "# to set \"ip=None\" for the status dashboard to work correctly via Docker.\n",
    "# See:\n",
    "# https://github.com/dask/distributed/issues/1875#issuecomment-387519880\n",
    "cluster = LocalCluster(ip=None, n_workers=n_cores, processes=True)\n",
    "client = Client(cluster)\n",
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'tcp://127.0.0.1:32815': 1,\n",
       " 'tcp://127.0.0.1:37189': 1,\n",
       " 'tcp://127.0.0.1:41385': 1,\n",
       " 'tcp://127.0.0.1:45621': 1}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Info on each worker, together with how many threads per worker.\n",
    "client.ncores()\n",
    "\n",
    "# To restart the client and scheduler\n",
    "#client.restart()\n",
    "#\n",
    "# To shutdown the client and scheduler\n",
    "#client.shutdown()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can scale the cluster down:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scale cluster down: \n",
      "\n",
      "Wait a bit for scaling to take effect...\n",
      "\n",
      "Cluster workers:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'tcp://127.0.0.1:37189': 1, 'tcp://127.0.0.1:45621': 1}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_workers = n_cores / 2\n",
    "print('Scale cluster down: ')\n",
    "cluster.scale(n_workers)\n",
    "\n",
    "print('\\nWait a bit for scaling to take effect...')\n",
    "time.sleep(1)\n",
    "\n",
    "print('\\nCluster workers:')\n",
    "client.ncores()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And scale it back up again:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scale cluster up again: \n",
      "\n",
      "Wait a bit for scaling to take effect...\n",
      "\n",
      "Cluster workers:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'tcp://127.0.0.1:37189': 1,\n",
       " 'tcp://127.0.0.1:40709': 1,\n",
       " 'tcp://127.0.0.1:44993': 1,\n",
       " 'tcp://127.0.0.1:45621': 1}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_workers = n_cores\n",
    "print('Scale cluster up again: ')\n",
    "cluster.scale(n_workers)\n",
    "\n",
    "print('\\nWait a bit for scaling to take effect...')\n",
    "time.sleep(4)\n",
    "\n",
    "print('\\nCluster workers:')\n",
    "client.ncores()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Q3. Measure the time to compute the total sum of `acousticness` for `dd_df` on a local cluster with varying number of workers. Start with 1 core, and double number of cores all the way up to 8, or however many cores you have available (if less than 8). Take a look at our usage of `scale()` above for how to scale your cluster up or down, and at [`time.perf_counter`](https://docs.python.org/3/library/time.html#time.perf_counter) to measure elapsed time.** \n",
    "\n",
    "**Compare it against the time you get from using pandas. Was dask faster or slower than pandas?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using pandas:\n",
      "Pandas time (ms): 2.29849999959697\n",
      "\n",
      "Using dask:\n",
      "Resizing cluster to 1 worker(s)...\n",
      "dask time (ms): 1347.1630999993067\n",
      "Resizing cluster to 2 worker(s)...\n",
      "dask time (ms): 1014.922000000297\n",
      "Resizing cluster to 4 worker(s)...\n",
      "dask time (ms): 805.3055000000313\n"
     ]
    }
   ],
   "source": [
    "# Q3: YOUR CODE GOES HERE.\n",
    "print('Using pandas:')\n",
    "t1_start = perf_counter()\n",
    "df.acousticness.sum()\n",
    "t1_stop = perf_counter()\n",
    "print('Pandas time (ms): %s' % ((t1_stop - t1_start)*1000))\n",
    "\n",
    "print('\\nUsing dask:')\n",
    "w=1;\n",
    "while w <= n_cores:\n",
    "    print('Resizing cluster to %s worker(s)...' % w)\n",
    "    cluster.scale(w)\n",
    "    time.sleep(2)\n",
    "    \n",
    "    t1_start = perf_counter()\n",
    "    dd_df.acousticness.sum().compute()\n",
    "    t1_stop = perf_counter()\n",
    "    \n",
    "    print('dask time (ms): %s' % ((t1_stop - t1_start)*1000))\n",
    "    w*=2;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see above, the Spotify 218k songs dataset is not large enough to justify the additional scheduler overhead from dask. Specifically, on datasets that comfortably fit within available memory, pandas is expected to be faster than dask for most operations other than loading from disk. Take a look at [\"Best Practices\"](https://docs.dask.org/en/latest/dataframe-best-practices.html) section of dask documentation for more details.\n",
    "\n",
    "So let's use a larger dataset instead. We can use dask's `demo` package to create a synthetic timeseries dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><strong>Dask DataFrame Structure:</strong></div>\n",
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=364</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-01</th>\n",
       "      <td>int64</td>\n",
       "      <td>float64</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-02</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-30</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "<div>Dask Name: make-timeseries, 364 tasks</div>"
      ],
      "text/plain": [
       "Dask DataFrame Structure:\n",
       "                    id        x        y\n",
       "npartitions=364                         \n",
       "2021-01-01       int64  float64  float64\n",
       "2021-01-02         ...      ...      ...\n",
       "...                ...      ...      ...\n",
       "2021-12-30         ...      ...      ...\n",
       "2021-12-31         ...      ...      ...\n",
       "Dask Name: make-timeseries, 364 tasks"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This lazily creates a timeseries dataset for us.\n",
    "dd_df = dd.demo.make_timeseries(start='2021-01-01',\n",
    "                                end='2021-12-31',\n",
    "                                dtypes={'x': float, 'y': float, 'id': int},\n",
    "                                freq='1s',\n",
    "                                partition_freq='24h')\n",
    "\n",
    "dd_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we've learned so far, dask computations are lazy up until we either explicitly call `compute()`, or call computations that themselves call `compute()`.\n",
    "\n",
    "This is why creating a large dataset above is almost instant. When we call `make_timeseries()`, calculates the number of partitions required for the parallel computation (we asked for one partition every 24h on that date range). It will only perform the actual computation required to create the dataset or brings required data chunks into memory once we actually need it to.\n",
    "\n",
    "We can see below that dask uses lazy computations even for the shape attribute:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pandas shape:  (228159, 18)\n",
      "dask shape:  (Delayed('int-c2a41040-d74b-4a6c-9dbc-a8b85e2958fe'), 3)\n"
     ]
    }
   ],
   "source": [
    "print('pandas shape: ', df.shape)\n",
    "print('dask shape: ', dd_df.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can retrieve the actual shape by again calling `compute()`, or by calling `len()`, which itself calls `compute()` behind the scenes: "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Q4. Compare the runtimes of running `head()` and `len(dd_df.index)` on the dask dataframe. Which one was faster? Why do you think that was the case?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dd_df.head() runtime (ms): 161.38259999934235\n",
      "len(dd_df.index) runtime (ms): 12815.530700001545\n"
     ]
    }
   ],
   "source": [
    "# Q4: YOUR CODE GOES HERE.\n",
    "t1_start = perf_counter()\n",
    "dd_df.head()\n",
    "t1_stop = perf_counter()\n",
    "print('dd_df.head() runtime (ms): %s' % ((t1_stop - t1_start)*1000))\n",
    "\n",
    "t1_start = perf_counter()\n",
    "len(dd_df.index)\n",
    "t1_stop = perf_counter()\n",
    "print('len(dd_df.index) runtime (ms): %s' % ((t1_stop - t1_start)*1000))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Operations over the index is where dask usually does a lot better than pandas (see [\"Best Practices\"](https://docs.dask.org/en/latest/dataframe-best-practices.html)):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.14 s, sys: 455 ms, total: 1.59 s\n",
      "Wall time: 4.3 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Timestamp('2021-01-01 00:00:01')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Dask: rolling standard deviation of 'x' column on 1m windows over the Datetime index.\n",
    "# Return index of first occurrence of max value out of those rolling 1m stddev.\n",
    "dd_df.x.rolling('1min').std().loc['2021-01-01':'2021-02-15'].idxmax().compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 5.49 s, sys: 3.62 s, total: 9.11 s\n",
      "Wall time: 18.8 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# Get a Pandas dataframe out of dask.\n",
    "df = dd_df.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.16 s, sys: 873 ms, total: 3.03 s\n",
      "Wall time: 2.94 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Timestamp('2021-01-01 00:00:01', freq='S')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# Same operation in Pandas\n",
    "df.x.rolling('1min').std().loc['2021-01-01':'2021-02-15'].idxmax()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "353"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# GC pandas df\n",
    "del df\n",
    "gc.collect()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Writing and loading data\n",
    "\n",
    "Let's take a look at processing data in column-oriented binary format using [`Parquet`](https://en.wikipedia.org/wiki/Apache_Parquet). As we've seen in class, Parquet is an open-source column-oriented data storage format. In addition to allowing us to store our dataframe data in a column-wise fashion, it also supports a number of compression techniques (e.g., dictionary encoding, RLE, and bit packing, as we've seen in class).\n",
    "\n",
    "In this part of the lab, we'll briefly look at how to store and read data written in Parquet format, and compare it to loading the same dataset from CSV.\n",
    "\n",
    "First, we can save the timeseries dataset as both Parquet and CSV format. We'll do this for a smaller subset of the data, as it takes a really long time to save the entire dataset as CSV."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "to_parquet() (ms): 4149.844100000337\n",
      "to_csv() (ms): 51727.89890000058\n"
     ]
    }
   ],
   "source": [
    "subset_df = dd_df.loc['2021-01-01':'2021-1-31']\n",
    "\n",
    "# Measure time for saving as Parquet files.\n",
    "t1_start = perf_counter()\n",
    "subset_df.to_parquet('data/parquet/')\n",
    "t1_stop = perf_counter()\n",
    "print('to_parquet() (ms): %s' % ((t1_stop - t1_start)*1000))\n",
    "\n",
    "# Measure time for saving as CSV files.\n",
    "t1_start = perf_counter()\n",
    "subset_df.to_csv('data/csv/timeseries-*.csv')\n",
    "t1_stop = perf_counter()\n",
    "print('to_csv() (ms): %s' % ((t1_stop - t1_start)*1000))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even though we used dask to write to Parquet, both pandas and dask support writing to / reading from Parquet files. The method interface is the same: [pandas's `read_parquet`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_parquet.html) vs [dask's `read_parquet`](https://docs.dask.org/en/latest/dataframe-api.html#dask.dataframe.read_parquet).\n",
    "\n",
    "**Q5. Measure the runtime of reading a dataframe from the same Parquet and CSV data we saved above using `dask`. Compare to reading the Parquet file using `pandas`.**\n",
    "\n",
    "**NOTE: Pandas does not support reading csv with a file pattern. While you could use the `pd.concat` function, you do not need to benchmark `pd.read_csv`**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dask + parquet (ms): 1395.5055000005814\n",
      "dask + csv (ms): 10111.803300000247\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "42"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Q5: YOUR CODE GOES HERE.\n",
    "expt_name = \"dask + parquet\"\n",
    "t1_start = perf_counter()\n",
    "df = dd.read_parquet(\"data/parquet/\").compute()\n",
    "t1_stop = perf_counter()\n",
    "print(f'{expt_name} (ms): {((t1_stop - t1_start)*1000)}')\n",
    "del df\n",
    "gc.collect()\n",
    "\n",
    "expt_name = \"dask + csv\"\n",
    "t1_start = perf_counter()\n",
    "df = dd.read_csv(\"data/csv/timeseries-*.csv\").compute()\n",
    "t1_stop = perf_counter()\n",
    "print(f'{expt_name} (ms): {((t1_stop - t1_start)*1000)}')\n",
    "del df\n",
    "gc.collect()\n",
    "\n",
    "expt_name = \"pandas + parquet\"\n",
    "t1_start = perf_counter()\n",
    "df = pd.read_parquet(\"data/parquet/\")\n",
    "t1_stop = perf_counter()\n",
    "print(f'{expt_name} (ms): {((t1_stop - t1_start)*1000)}')\n",
    "del df\n",
    "gc.collect()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dask bag\n",
    "\n",
    "Finally, we'll look at processing JSON data hosted on the web using the dask [`Bag`](https://docs.dask.org/en/latest/bag.html) data structure ([full API](https://docs.dask.org/en/latest/bag-api.html)). \n",
    "\n",
    "There is some overlap between what you can do with bags and dataframes, as we'll see below. However, bags are useful when the data you're analyzing is more naturally represented as Python objects (e.g., dicts) than as tabular data (dataframe). That's often the case with JSON data, which has an almost 1:1 mapping with Python dicts.\n",
    "\n",
    "From the official documentation:\n",
    "\n",
    ">Dask Bag implements operations like `map`, `filter`, `groupby` and `aggregations` on collections of Python objects. It does this in parallel and in small memory using Python iterators.\n",
    "\n",
    "\n",
    "### Example: using Bag to process JSON data\n",
    "\n",
    "Below we'll use events JSON data from a web service that runs Jupyter notebooks called [mybinder.org](http://mybinder.org). Every time a user launches a notebook on platforms such as GitHub or GitLab, mybinder publishes an event and stores it in publicly accessible JSON files (one per day).\n",
    "\n",
    "Let's go through a step by step example of bags. Suppose we want to get information about notebooks published in 2022."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dask.bag as db"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[`mybinder.org`](mybinder.org) publishes an index containing the JSON files that they're currently hosting. To read it, we will use the `read_text` function which lazily returns a bag containing the list of lines of text. The `take(n)` function will return `n` elements of the bag."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('{\"name\": \"events-2018-11-03.jsonl\", \"date\": \"2018-11-03\", \"count\": \"7057\"}\\n',\n",
       " '{\"name\": \"events-2018-11-04.jsonl\", \"date\": \"2018-11-04\", \"count\": \"7489\"}\\n',\n",
       " '{\"name\": \"events-2018-11-05.jsonl\", \"date\": \"2018-11-05\", \"count\": \"13590\"}\\n',\n",
       " '{\"name\": \"events-2018-11-06.jsonl\", \"date\": \"2018-11-06\", \"count\": \"13920\"}\\n',\n",
       " '{\"name\": \"events-2018-11-07.jsonl\", \"date\": \"2018-11-07\", \"count\": \"12766\"}\\n')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load index file, inspect its contents.\n",
    "events = db.read_text('https://archive.analytics.mybinder.org/index.jsonl')\n",
    "events.take(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, each line represents json text about daily events. We want to convert json text to python dictionaries. We will use the `map()` function. `map(f)` applies the `f` function to every element in the bag. We should thus call `map(json.loads)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "({'name': 'events-2018-11-03.jsonl', 'date': '2018-11-03', 'count': '7057'},\n",
       " {'name': 'events-2018-11-04.jsonl', 'date': '2018-11-04', 'count': '7489'},\n",
       " {'name': 'events-2018-11-05.jsonl', 'date': '2018-11-05', 'count': '13590'},\n",
       " {'name': 'events-2018-11-06.jsonl', 'date': '2018-11-06', 'count': '13920'},\n",
       " {'name': 'events-2018-11-07.jsonl', 'date': '2018-11-07', 'count': '12766'})"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Turn lines text to python dicts.\n",
    "events = events.map(json.loads)\n",
    "events.take(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's now filter by date. We will use the `filter(p)` function which apply the `p` predicate to every item, and returns only the items that satisfy the predicate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "({'name': 'events-2022-01-01.jsonl', 'date': '2022-01-01', 'count': '11020'},\n",
       " {'name': 'events-2022-01-02.jsonl', 'date': '2022-01-02', 'count': '14363'},\n",
       " {'name': 'events-2022-01-03.jsonl', 'date': '2022-01-03', 'count': '22912'},\n",
       " {'name': 'events-2022-01-04.jsonl', 'date': '2022-01-04', 'count': '27393'},\n",
       " {'name': 'events-2022-01-05.jsonl', 'date': '2022-01-05', 'count': '27602'})"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter by year.\n",
    "events = events.filter(lambda entry: '2022' in entry['date'])\n",
    "events.take(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's extract the filename. We will use the `pluck(key)` function, which will extract the `key` from the dictionary. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('events-2022-01-01.jsonl',\n",
       " 'events-2022-01-02.jsonl',\n",
       " 'events-2022-01-03.jsonl',\n",
       " 'events-2022-01-04.jsonl',\n",
       " 'events-2022-01-05.jsonl')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the names.\n",
    "events = events.pluck(\"name\")\n",
    "events.take(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using a bag on the list of urls, we can automatically parse the JSON data into Python dict:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "({'timestamp': '2022-01-01T00:00:00+00:00',\n",
       "  'schema': 'binderhub.jupyter.org/launch',\n",
       "  'version': 5,\n",
       "  'provider': 'Git',\n",
       "  'spec': 'https%3A%2F%2Fcodeberg.org%2Fforgiagether%2Fr/HEAD',\n",
       "  'ref': 'b71c00c41c771a2d7f4230a7ac7da677217e7a12',\n",
       "  'status': 'success',\n",
       "  'build_token': True,\n",
       "  'origin': 'ovh.mybinder.org'},\n",
       " {'timestamp': '2022-01-01T00:00:00+00:00',\n",
       "  'schema': 'binderhub.jupyter.org/launch',\n",
       "  'version': 5,\n",
       "  'provider': 'GitHub',\n",
       "  'spec': 'ipython/ipython-in-depth/HEAD',\n",
       "  'ref': 'b2f9442aa52118dec44ccb0ee749ea63ac578bba',\n",
       "  'status': 'success',\n",
       "  'build_token': True,\n",
       "  'origin': 'turing.mybinder.org'})"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fetch the urls.\n",
    "urls = events.map(lambda name: f\"https://archive.analytics.mybinder.org/{name}\")\n",
    "notebook_runs = db.read_text(urls.compute()).map(json.loads)\n",
    "notebook_runs.take(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Q6. Using the Python dict data we just saved above in `notebook_runs`, filter it for runs whose provider was \"GitHub\", and that happened in March 2022. What were the top-3 most run notebooks in that month, and how many times were they run?**\n",
    "\n",
    "**To answer this question, you should use only `Bag` functions, such as [`filter`](https://docs.dask.org/en/latest/bag-api.html#dask.bag.Bag.filter) and [`frequencies`](https://docs.dask.org/en/latest/bag-api.html#dask.bag.Bag.frequencies) (take a look at some [usage examples here](https://examples.dask.org/bag.html)).**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Q6: YOUR CODE GOES HERE.\n",
    "github_march = notebook_runs.filter(lambda n: n['provider']=='GitHub' and n['timestamp'].startswith('2022-03'))\n",
    "specs = github_march.pluck(\"spec\")\n",
    "specs = specs.frequencies(sort=True)\n",
    "specs.take(3)\n",
    "\n",
    "# Getting top-3: dask dataframe.\n",
    "t1_start = perf_counter()\n",
    "dd_df = notebook_runs.to_dataframe()\n",
    "dd_df = dd_df[(dd_df['provider'] == 'GitHub') & (dd_df['timestamp'].str.startswith('2022-03'))]\n",
    "top_runs = (dd_df.spec.value_counts()\n",
    "                 .nlargest(3)\n",
    "                 .compute())\n",
    "t1_stop = perf_counter()\n",
    "print('\\nTop-3 using dask dataframe (ms): %s\\n' % ((t1_stop - t1_start)*1000))\n",
    "print('results:')\n",
    "print(top_runs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Naturally, the top 3 are all jupyter tutorials."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Additional Resources\n",
    "\n",
    "## Dask examples and tutorials\n",
    "\n",
    "* Dask examples: https://examples.dask.org/\n",
    "* Dask for ML tasks (e.g., incremental learning and hyperparameter tuning): https://ml.dask.org/examples.html\n",
    "* YouTube playlist with introductory Dask concepts: https://www.youtube.com/playlist?list=PLTgRMOcmRb3OlkfAdqJWyGGrQM7eU-mi7\n",
    "\n",
    "## Dask benchmark codes\n",
    "* On a 512 core server: https://matthewrocklin.com/blog/work/2017/07/03/scaling\n",
    "* On GCS: https://gist.github.com/mrocklin/4c198b13e92f881161ef175810c7f6bc#file-scaling-gcs-ipynb\n"
   ]
  }
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