getting_started_notebooks/basics/blazingsql/federated_query_demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "8AdUt3HiUrc3"
   },
   "source": [
    "# Querying Multiple Data Formats \n",
    "*By Winston Robson*\n",
    "\n",
    "In this notebook, we will cover: \n",
    "- How to create BlazingSQL tables from: \n",
    "    - Text file (CSV)\n",
    "    - Apache Parquet \n",
    "    - cuDF DataFrame (GDF)\n",
    "- How to `JOIN` multiple BlazingSQL tables into one cuDF DataFrame with a single query."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "aMwNKxePSwOp"
   },
   "source": [
    "#### BlazingSQL install check\n",
    "The next cell checks that you have BlazingSQL installed, and offers to install it if not (making sure the notebook will run as expected)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"You've got BlazingSQL set up perfectly! Let's get started with SQL in RAPIDS AI!\""
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sys \n",
    "# point import path notebooks-contrib/utils\n",
    "sys.path.append('../../../utils/')\n",
    "\n",
    "from sql_check import bsql_start\n",
    "# check that BlazingSQL is installed\n",
    "bsql_start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Download Data\n",
    "This cell will check if you have the data for this demo, and, if you don't, will download it for you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating blazingsql directory\n",
      "\n",
      "--2020-01-21 17:55:24--  https://raw.githubusercontent.com/BlazingDB/bsql-demos/master/data/cancer_data_00.csv\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.200.133\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.200.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 1233 (1.2K) [text/plain]\n",
      "Saving to: ‘../../../data/blazingsql/cancer_data_00.csv’\n",
      "\n",
      "cancer_data_00.csv  100%[===================>]   1.20K  --.-KB/s    in 0s      \n",
      "\n",
      "2020-01-21 17:55:24 (254 MB/s) - ‘../../../data/blazingsql/cancer_data_00.csv’ saved [1233/1233]\n",
      "\n",
      "--2020-01-21 17:55:24--  https://blazingsql-colab.s3.amazonaws.com/cancer_data/cancer_data_01.parquet\n",
      "Resolving blazingsql-colab.s3.amazonaws.com (blazingsql-colab.s3.amazonaws.com)... 52.217.9.156\n",
      "Connecting to blazingsql-colab.s3.amazonaws.com (blazingsql-colab.s3.amazonaws.com)|52.217.9.156|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 2364 (2.3K) [binary/octet-stream]\n",
      "Saving to: ‘../../../data/blazingsql/cancer_data_01.parquet’\n",
      "\n",
      "cancer_data_01.parq 100%[===================>]   2.31K  --.-KB/s    in 0s      \n",
      "\n",
      "2020-01-21 17:55:24 (197 MB/s) - ‘../../../data/blazingsql/cancer_data_01.parquet’ saved [2364/2364]\n",
      "\n",
      "--2020-01-21 17:55:24--  https://raw.githubusercontent.com/BlazingDB/bsql-demos/master/data/cancer_data_02.csv\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.200.133\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.200.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 1854 (1.8K) [text/plain]\n",
      "Saving to: ‘../../../data/blazingsql/cancer_data_02.csv’\n",
      "\n",
      "cancer_data_02.csv  100%[===================>]   1.81K  --.-KB/s    in 0s      \n",
      "\n",
      "2020-01-21 17:55:24 (448 MB/s) - ‘../../../data/blazingsql/cancer_data_02.csv’ saved [1854/1854]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "# relative path to data folder\n",
    "data_dir = '../../../data/blazingsql/'\n",
    "\n",
    "# does folder exist?\n",
    "if not os.path.exists(data_dir):\n",
    "    print('creating blazingsql directory\\n')\n",
    "    # create folder\n",
    "    os.system('mkdir ../../data/blazingsql')\n",
    "\n",
    "# do we have file 0?\n",
    "if not os.path.isfile(data_dir + 'cancer_data_00.csv'):\n",
    "    !wget -P ../../../data/blazingsql https://raw.githubusercontent.com/BlazingDB/bsql-demos/master/data/cancer_data_00.csv\n",
    "\n",
    "# do we have file 1?\n",
    "if not os.path.isfile(data_dir + 'cancer_data_01.parquet'):\n",
    "    !wget -P ../../../data/blazingsql https://blazingsql-colab.s3.amazonaws.com/cancer_data/cancer_data_01.parquet\n",
    "\n",
    "# do we have file 2?\n",
    "if not os.path.isfile(data_dir + 'cancer_data_02.csv'):\n",
    "    !wget -P ../../../data/blazingsql https://raw.githubusercontent.com/BlazingDB/bsql-demos/master/data/cancer_data_02.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create BlazingContext\n",
    "You can think of the BlazingContext much like a Spark Context (i.e. information such as FileSystems registered & Tables created will be stored)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "azZ7l2q7odYT",
    "outputId": "a5302d6e-307e-45c5-a682-c786cc999a40"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BlazingContext ready\n"
     ]
    }
   ],
   "source": [
    "from blazingsql import BlazingContext\n",
    "# start up BlazingSQL\n",
    "bc = BlazingContext()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Data Path\n",
    "BlazingSQL requires the full path to the data. This cell uses the `pwd` bash command to identify the path to this directory, then add it to the relative path to the notebooks-contrib `data` directory (i.e. what you'd type in Terminal to navigate to the data)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/jupyter-winston/notebooks-contrib/data/blazingsql/'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# bash command, returns SList w/ path (str) at 0th index\n",
    "path = !pwd\n",
    "\n",
    "# extract path to notebooks-contrib\n",
    "path = path[0].split('getting_started_notebooks')[0] \n",
    "\n",
    "# add path to blazingsql data\n",
    "path = path + 'data/blazingsql/'\n",
    "\n",
    "# what's it look like?\n",
    "path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "N2bqpDEnZyQf"
   },
   "source": [
    "### Create Table from CSV\n",
    "Here we create a BlazingSQL table directly from a comma-separated values (CSV) file. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "HhRhj-ZvZygH"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyblazing.apiv2.context.BlazingTable at 0x7fba380922b0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# define column names and types\n",
    "col_names = ['diagnosis_result', 'radius', 'texture', 'perimeter']\n",
    "col_types = ['float32', 'float32', 'float32', 'float32']\n",
    "\n",
    "# create table from CSV file\n",
    "bc.create_table('data_00', path+'cancer_data_00.csv', names=col_names, dtype=col_types)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "HJFz-mqZTJ5Z"
   },
   "source": [
    "### Create Table from Parquet\n",
    "Here we create a BlazingSQL table directly from an Apache Parquet file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "HJuvtJDYTMyb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "file /home/jupyter-winston/notebooks-contrib/data/blazingsql/cancer_data_01.parquet\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<pyblazing.apiv2.context.BlazingTable at 0x7fba38070ba8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create table from Parquet file\n",
    "bc.create_table('data_01', path+'cancer_data_01.parquet')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "98HJFrt5TRa0"
   },
   "source": [
    "### Create Table from GPU DataFrame\n",
    "Here we use cuDF to create a GPU DataFrame (GDF), then use BlazingSQL to create a table from that GDF.\n",
    "\n",
    "The GDF is the standard memory representation for the RAPIDS AI ecosystem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "14GwxmLsTV_p",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pyblazing.apiv2.context.BlazingTable at 0x7fba38092d30>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import cudf\n",
    "\n",
    "# define column names & types\n",
    "col_names = ['compactness', 'symmetry', 'fractal_dimension']\n",
    "col_types = ['float32', 'float32', 'float32', 'float32']\n",
    "\n",
    "# make GPU DataFrame from CSV w/ cuDF\n",
    "gdf_02 = cudf.read_csv(path+'cancer_data_02.csv', names=col_names, dtype=col_types)\n",
    "\n",
    "# create BlazingSQL table from cuDF DataFrame\n",
    "bc.create_table('data_02', gdf_02)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "9DAZShZ2y-Nx"
   },
   "source": [
    "# Join Tables Together \n",
    "\n",
    "Now we can use BlazingSQL to join all three data formats in a single federated query. BlazingSQL queries return results as a cuDF DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "HOYSFebvzGcX",
    "outputId": "ad133dfd-540e-4142-8f12-a4a70d803bb6",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25960\n"
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       "      <th>diagnosis_result</th>\n",
       "      <th>radius</th>\n",
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       "      <td>0.057</td>\n",
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       "      <td>78.0</td>\n",
       "      <td>451.0</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.071000002</td>\n",
       "      <td>0.162</td>\n",
       "      <td>0.057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>244.0</td>\n",
       "      <td>0.098</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>648.0</td>\n",
       "      <td>0.094</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>506.0</td>\n",
       "      <td>0.099</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>506.0</td>\n",
       "      <td>0.099</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>572.0</td>\n",
       "      <td>0.077</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>441.0</td>\n",
       "      <td>0.111</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>572.0</td>\n",
       "      <td>0.077</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>572.0</td>\n",
       "      <td>0.077</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>652.0</td>\n",
       "      <td>0.113</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>0.102</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>0.102</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>0.102</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286</th>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>559.0</td>\n",
       "      <td>0.102</td>\n",
       "      <td>0.126000002</td>\n",
       "      <td>0.172000006</td>\n",
       "      <td>0.063999996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287</th>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>563.0</td>\n",
       "      <td>0.082</td>\n",
       "      <td>0.059999999</td>\n",
       "      <td>0.178000003</td>\n",
       "      <td>0.056000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>288</th>\n",
       "      <td>1.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>563.0</td>\n",
       "      <td>0.082</td>\n",
       "      <td>0.059999999</td>\n",
       "      <td>0.178000003</td>\n",
       "      <td>0.056000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>289</th>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>1033.0</td>\n",
       "      <td>0.115</td>\n",
       "      <td>0.149000004</td>\n",
       "      <td>0.209000006</td>\n",
       "      <td>0.063000001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290</th>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>645.0</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.187000006</td>\n",
       "      <td>0.224999994</td>\n",
       "      <td>0.068999998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291</th>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>657.0</td>\n",
       "      <td>0.114</td>\n",
       "      <td>0.136999995</td>\n",
       "      <td>0.203000009</td>\n",
       "      <td>0.067999996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>292</th>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>657.0</td>\n",
       "      <td>0.114</td>\n",
       "      <td>0.136999995</td>\n",
       "      <td>0.203000009</td>\n",
       "      <td>0.067999996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>293</th>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>251.0</td>\n",
       "      <td>0.107</td>\n",
       "      <td>0.141000003</td>\n",
       "      <td>0.21100001</td>\n",
       "      <td>0.079999998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294</th>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>643.0</td>\n",
       "      <td>0.098</td>\n",
       "      <td>0.114</td>\n",
       "      <td>0.188000008</td>\n",
       "      <td>0.063999996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295</th>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>524.0</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.037999999</td>\n",
       "      <td>0.147</td>\n",
       "      <td>0.059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>1.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>0.116</td>\n",
       "      <td>0.123000003</td>\n",
       "      <td>0.213000014</td>\n",
       "      <td>0.067999996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>545.0</td>\n",
       "      <td>0.104</td>\n",
       "      <td>0.143999994</td>\n",
       "      <td>0.196999997</td>\n",
       "      <td>0.067999996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>552.0</td>\n",
       "      <td>0.074</td>\n",
       "      <td>0.050999999</td>\n",
       "      <td>0.157000005</td>\n",
       "      <td>0.055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>1.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>0.116</td>\n",
       "      <td>0.123000003</td>\n",
       "      <td>0.213000014</td>\n",
       "      <td>0.067999996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>545.0</td>\n",
       "      <td>0.104</td>\n",
       "      <td>0.143999994</td>\n",
       "      <td>0.196999997</td>\n",
       "      <td>0.067999996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>1040.0</td>\n",
       "      <td>0.095</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>1104.0</td>\n",
       "      <td>0.091</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>303</th>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>870.0</td>\n",
       "      <td>0.096</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>1104.0</td>\n",
       "      <td>0.091</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>559.0</td>\n",
       "      <td>0.129</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "      <td>null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306</th>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>659.0</td>\n",
       "      <td>0.114</td>\n",
       "      <td>0.159999996</td>\n",
       "      <td>0.230000004</td>\n",
       "      <td>0.071000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>477.0</td>\n",
       "      <td>0.128</td>\n",
       "      <td>0.170000002</td>\n",
       "      <td>0.193000004</td>\n",
       "      <td>0.064999998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>524.0</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.037999999</td>\n",
       "      <td>0.182000011</td>\n",
       "      <td>0.055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>699.0</td>\n",
       "      <td>0.094</td>\n",
       "      <td>0.050999999</td>\n",
       "      <td>0.138999999</td>\n",
       "      <td>0.052999999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>0.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>0.098</td>\n",
       "      <td>0.052999999</td>\n",
       "      <td>0.13499999</td>\n",
       "      <td>0.068999998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>312.0</td>\n",
       "      <td>0.113</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.274000019</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>699.0</td>\n",
       "      <td>0.094</td>\n",
       "      <td>0.050999999</td>\n",
       "      <td>0.138999999</td>\n",
       "      <td>0.052999999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>552.0</td>\n",
       "      <td>0.074</td>\n",
       "      <td>0.050999999</td>\n",
       "      <td>0.138999999</td>\n",
       "      <td>0.052999999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>1152.0</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.127000004</td>\n",
       "      <td>0.192000002</td>\n",
       "      <td>0.059999999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>559.0</td>\n",
       "      <td>0.102</td>\n",
       "      <td>0.126000002</td>\n",
       "      <td>0.191</td>\n",
       "      <td>0.066</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>316 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     diagnosis_result  radius  texture  perimeter    area  smoothness  \\\n",
       "0                 0.0    19.0     22.0       87.0   545.0       0.104   \n",
       "1                 1.0    14.0     26.0      120.0  1006.0       0.107   \n",
       "2                 1.0    18.0     25.0       97.0   713.0       0.091   \n",
       "3                 0.0    22.0     15.0       83.0   524.0       0.090   \n",
       "4                 0.0    21.0     11.0       83.0   527.0       0.081   \n",
       "5                 1.0    15.0     21.0       87.0   561.0       0.088   \n",
       "6                 0.0    25.0     11.0       87.0   561.0       0.088   \n",
       "7                 0.0    19.0     22.0       87.0   561.0       0.088   \n",
       "8                 0.0    22.0     15.0       83.0   527.0       0.081   \n",
       "9                 0.0    21.0     11.0       83.0   499.0       0.112   \n",
       "10                1.0    24.0     16.0       86.0   520.0       0.108   \n",
       "11                1.0    18.0     11.0      124.0  1130.0       0.090   \n",
       "12                1.0    20.0     14.0       86.0   520.0       0.108   \n",
       "13                0.0    22.0     15.0       83.0   499.0       0.112   \n",
       "14                1.0    11.0     15.0       96.0   646.0       0.105   \n",
       "15                1.0    17.0     20.0       96.0   646.0       0.105   \n",
       "16                1.0    12.0     22.0       96.0   646.0       0.105   \n",
       "17                0.0    20.0     21.0       78.0   451.0       0.105   \n",
       "18                0.0    24.0     17.0       59.0   244.0       0.098   \n",
       "19                1.0    18.0     12.0       94.0   648.0       0.094   \n",
       "20                0.0    21.0     11.0       83.0   506.0       0.099   \n",
       "21                0.0    22.0     15.0       83.0   506.0       0.099   \n",
       "22                1.0    15.0     21.0       87.0   572.0       0.077   \n",
       "23                0.0    20.0     21.0       78.0   441.0       0.111   \n",
       "24                0.0    25.0     11.0       87.0   572.0       0.077   \n",
       "25                0.0    19.0     22.0       87.0   572.0       0.077   \n",
       "26                1.0    11.0     15.0       96.0   652.0       0.113   \n",
       "27                1.0    15.0     21.0       87.0   555.0       0.102   \n",
       "28                0.0    25.0     11.0       87.0   555.0       0.102   \n",
       "29                0.0    19.0     22.0       87.0   555.0       0.102   \n",
       "..                ...     ...      ...        ...     ...         ...   \n",
       "286               1.0    10.0     14.0       88.0   559.0       0.102   \n",
       "287               1.0    24.0     16.0       86.0   563.0       0.082   \n",
       "288               1.0    20.0     14.0       86.0   563.0       0.082   \n",
       "289               1.0    14.0     26.0      120.0  1033.0       0.115   \n",
       "290               1.0    18.0     25.0       97.0   645.0       0.105   \n",
       "291               1.0    17.0     20.0       96.0   657.0       0.114   \n",
       "292               1.0    12.0     22.0       96.0   657.0       0.114   \n",
       "293               0.0    24.0     17.0       59.0   251.0       0.107   \n",
       "294               1.0    18.0     12.0       94.0   643.0       0.098   \n",
       "295               0.0    21.0     11.0       83.0   524.0       0.090   \n",
       "296               1.0    24.0     16.0       86.0   535.0       0.116   \n",
       "297               1.0    15.0     21.0       87.0   545.0       0.104   \n",
       "298               1.0    10.0     15.0       85.0   552.0       0.074   \n",
       "299               1.0    20.0     14.0       86.0   535.0       0.116   \n",
       "300               0.0    25.0     11.0       87.0   545.0       0.104   \n",
       "301               1.0    14.0     26.0      120.0  1040.0       0.095   \n",
       "302               1.0    11.0     21.0      128.0  1104.0       0.091   \n",
       "303               1.0    10.0     13.0      110.0   870.0       0.096   \n",
       "304               1.0    11.0     11.0      128.0  1104.0       0.091   \n",
       "305               1.0    10.0     14.0       88.0   559.0       0.129   \n",
       "306               1.0    18.0     25.0       97.0   659.0       0.114   \n",
       "307               0.0    22.0     15.0       83.0   477.0       0.128   \n",
       "308               0.0    21.0     11.0       83.0   524.0       0.090   \n",
       "309               1.0    17.0     20.0       96.0   699.0       0.094   \n",
       "310               0.0    23.0     26.0       54.0   225.0       0.098   \n",
       "311               0.0    15.0     18.0       65.0   312.0       0.113   \n",
       "312               1.0    12.0     22.0       96.0   699.0       0.094   \n",
       "313               1.0    10.0     15.0       85.0   552.0       0.074   \n",
       "314               1.0    10.0     19.0      126.0  1152.0       0.105   \n",
       "315               1.0    10.0     14.0       88.0   559.0       0.102   \n",
       "\n",
       "     compactness     symmetry fractal_dimension  \n",
       "0    0.143999994  0.196999997       0.067999996  \n",
       "1    0.215000004  0.215000004       0.067000002  \n",
       "2    0.071000002        0.162             0.057  \n",
       "3    0.037999999        0.147             0.059  \n",
       "4    0.037999999        0.147             0.059  \n",
       "5          0.077  0.181000009             0.057  \n",
       "6          0.077  0.181000009             0.057  \n",
       "7          0.077  0.181000009             0.057  \n",
       "8    0.037999999        0.147             0.059  \n",
       "9    0.126000002  0.172000006       0.063999996  \n",
       "10   0.153999999  0.193999991       0.068999998  \n",
       "11         0.103  0.158000007       0.054000001  \n",
       "12   0.153999999  0.193999991       0.068999998  \n",
       "13   0.126000002  0.172000006       0.063999996  \n",
       "14   0.201000005  0.194999993       0.072999999  \n",
       "15   0.201000005  0.194999993       0.072999999  \n",
       "16   0.201000005  0.194999993       0.072999999  \n",
       "17   0.071000002        0.162             0.057  \n",
       "18          null         null              null  \n",
       "19          null         null              null  \n",
       "20          null         null              null  \n",
       "21          null         null              null  \n",
       "22          null         null              null  \n",
       "23          null         null              null  \n",
       "24          null         null              null  \n",
       "25          null         null              null  \n",
       "26          null         null              null  \n",
       "27          null         null              null  \n",
       "28          null         null              null  \n",
       "29          null         null              null  \n",
       "..           ...          ...               ...  \n",
       "286  0.126000002  0.172000006       0.063999996  \n",
       "287  0.059999999  0.178000003       0.056000002  \n",
       "288  0.059999999  0.178000003       0.056000002  \n",
       "289  0.149000004  0.209000006       0.063000001  \n",
       "290  0.187000006  0.224999994       0.068999998  \n",
       "291  0.136999995  0.203000009       0.067999996  \n",
       "292  0.136999995  0.203000009       0.067999996  \n",
       "293  0.141000003   0.21100001       0.079999998  \n",
       "294        0.114  0.188000008       0.063999996  \n",
       "295  0.037999999        0.147             0.059  \n",
       "296  0.123000003  0.213000014       0.067999996  \n",
       "297  0.143999994  0.196999997       0.067999996  \n",
       "298  0.050999999  0.157000005             0.055  \n",
       "299  0.123000003  0.213000014       0.067999996  \n",
       "300  0.143999994  0.196999997       0.067999996  \n",
       "301         null         null              null  \n",
       "302         null         null              null  \n",
       "303         null         null              null  \n",
       "304         null         null              null  \n",
       "305         null         null              null  \n",
       "306  0.159999996  0.230000004       0.071000002  \n",
       "307  0.170000002  0.193000004       0.064999998  \n",
       "308  0.037999999  0.182000011             0.055  \n",
       "309  0.050999999  0.138999999       0.052999999  \n",
       "310  0.052999999   0.13499999       0.068999998  \n",
       "311        0.081  0.274000019              0.07  \n",
       "312  0.050999999  0.138999999       0.052999999  \n",
       "313  0.050999999  0.138999999       0.052999999  \n",
       "314  0.127000004  0.192000002       0.059999999  \n",
       "315  0.126000002        0.191             0.066  \n",
       "\n",
       "[316 rows x 9 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# grab everything from data_00 & data_01 and area & smoothness from data_01\n",
    "query = '''\n",
    "        SELECT \n",
    "            a.*, \n",
    "            b.area, b.smoothness, \n",
    "            c.* \n",
    "        FROM \n",
    "            data_00 AS a\n",
    "        LEFT JOIN data_01 AS b\n",
    "            ON (a.perimeter = b.perimeter)\n",
    "        LEFT JOIN data_02 AS c\n",
    "            ON (b.compactness = c.compactness)\n",
    "            '''\n",
    "\n",
    "# join the tables together\n",
    "join = bc.sql(query)\n",
    "\n",
    "# display results (type(join)==cudf.core.dataframe.DataFrame)\n",
    "join"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "wygAeTIFTm2X"
   },
   "source": [
    "# You're Ready to Rock\n",
    "And... thats it! You are now live with BlazingSQL.\n",
    "\n",
    "Check out our [docs](https://docs.blazingdb.com) or [Twitter](https://twitter.com/blazingsql) to get fancy or to learn more about how BlazingSQL works with the rest of [RAPIDS AI](https://rapids.ai/)."
   ]
  }
 ],
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   "provenance": [],
   "toc_visible": true
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