demos/guru_scripts/tigergraph_notebook/gsql101.ipynb

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    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.7"
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      "title_cell": "Table of Contents",
      "title_sidebar": "Contents",
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      "toc_position": {},
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    },
    "colab": {
      "name": "gsql101.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/yaniv256/ecosys/blob/master/demos/guru_scripts/tigergraph_notebook/gsql101.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sIdweWQSk25O",
        "colab_type": "text"
      },
      "source": [
        "# GSQL101 - on a Colab Notebook"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LXpx_L7PqQgo",
        "colab_type": "text"
      },
      "source": [
        "## Establish a connection to a TigerGraph server"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "okWA1NYJqUVX",
        "colab_type": "text"
      },
      "source": [
        "### Start a [TigerGraph server](https://www.tigergraph.com/cloud/)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VZB-lMkPAqxK",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "outputId": "9800f1c8-0f39-4889-fe2d-fe2a247a9789"
      },
      "source": [
        "from IPython.display import YouTubeVideo\n",
        "\n",
        "YouTubeVideo(width=896, height=504, id='JARd9ULRP_I')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
              "        <iframe\n",
              "            width=\"896\"\n",
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              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7fecd6061400>"
            ],
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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "17LC4XRDBUCO",
        "colab_type": "text"
      },
      "source": [
        "## Enter your server's ip address and password into the input boxes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QU66klikk25P",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "b047ed8b-d5b7-44f7-97df-3a856497d57d"
      },
      "source": [
        "server_ip = input()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "yaniv.i.tgcloud.io\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "94CPhylck25Z",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "338cf808-13dc-4c70-a2b6-716b2ea706a5"
      },
      "source": [
        "import getpass\n",
        "\n",
        "password = getpass.getpass()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "··········\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3mNUgoBok25c",
        "colab_type": "text"
      },
      "source": [
        "### Download a certificate from the server"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ba82VIeAk25d",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "30a0a6db-1c8d-4d21-b4db-6cbcbd9ee349"
      },
      "source": [
        "!openssl s_client -connect $server_ip:14240 < /dev/null 2> /dev/null | openssl x509 -text > my-cert.txt\n",
        "!ls -l my-cert.txt"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "-rw-r--r-- 1 root root 8518 Jun 22 13:17 my-cert.txt\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AgNIHSNHk25g",
        "colab_type": "text"
      },
      "source": [
        "### Download the GSQL client java tar file"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fCyv554bk25g",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "049f6b65-81c6-455d-c074-af35cd18e5cd"
      },
      "source": [
        "import urllib.request\n",
        "\n",
        "client_version = '2.6.0'\n",
        "\n",
        "jar_url = ('https://bintray.com/api/ui/download/tigergraphecosys/tgjars/' \n",
        "           + 'com/tigergraph/client/gsql_client/' + client_version \n",
        "           + '/gsql_client-' + client_version + '.jar')\n",
        "           \n",
        "urllib.request.urlretrieve(jar_url, 'gsql_client.jar')\n",
        "\n",
        "!ls -l gsql_client.jar"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "-rw-r--r-- 1 root root 671144 Jun 22 13:17 gsql_client.jar\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jVNr4V5mCMkz",
        "colab_type": "text"
      },
      "source": [
        "If not running on Colab you need to have the Java JDK runtime installed. You can download it from Oracle's [download page](https://www.oracle.com/java/technologies/javase-downloads.html)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RrGuKsNxk25j",
        "colab_type": "text"
      },
      "source": [
        "### Define a function to handle input and output to the GSQL client "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SaMNELaok25j",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import subprocess, yaml, re\n",
        "\n",
        "def gsql(query, options=['-g','social']):\n",
        "\n",
        "    cmd = ['java', '-DGSQL_CLIENT_VERSION=v2_6_0', '-jar', 'gsql_client.jar',\n",
        "       '-cacert', 'my-cert.txt', '-u', 'tigergraph', '-p', password, \n",
        "       '-ip', server_ip]\n",
        "\n",
        "    comp = subprocess.run(cmd + options + [query], \n",
        "                          stdout=subprocess.PIPE).stdout.decode()\n",
        "    \n",
        "    try:\n",
        "        json_string = re.search('(\\{|\\[).*$',comp.replace('\\n',''))[0]\n",
        "        json_object = yaml.safe_load(json_string)\n",
        "    except:\n",
        "        print(comp)\n",
        "        return\n",
        "    else:\n",
        "        return json_object"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FmFUHnDGk25n",
        "colab_type": "text"
      },
      "source": [
        "## Set up the graph"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sy6k9Sprk25V",
        "colab_type": "text"
      },
      "source": [
        "### Make sure your server is running properly by logging in to TigerStudio\n",
        "You will need this to upload your data files."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z501zEfNk25V",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "b2085c97-e07b-4ec9-813f-7d6edf420228"
      },
      "source": [
        "print('https://' + server_ip + ':14240') "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "https://yaniv.i.tgcloud.io:14240\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eiBosRXNk25n",
        "colab_type": "text"
      },
      "source": [
        "### Use TigerStudio to upload data files to server\n",
        "\n",
        "Run the these cells. If you're runing the notebook on Colab, download the csv files using the folder icon on the left. Go to GraphStudio and select `Map Data to Graph` and `Add data file`. Upload the csv files. After uploading you can hit `Cancel`, as the files are already on the server. You only need to do this once."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X_Nz-dVTk25o",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "1e6c24ad-57e6-4033-86f9-92737b5ded86"
      },
      "source": [
        "%%writefile person.csv\n",
        "name,gender,age,state\n",
        "Tom,male,40,ca\n",
        "Dan,male,34,ny\n",
        "Jenny,female,25,tx\n",
        "Kevin,male,28,az\n",
        "Amily,female,22,ca\n",
        "Nancy,female,20,ky\n",
        "Jack,male,26,fl"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Overwriting person.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qEiWKZEFk25q",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "cf8eed80-c9bd-4330-d1f6-67651631dd8e"
      },
      "source": [
        "%%writefile friendship.csv\n",
        "person1,person2,date\n",
        "Tom,Dan,2017-06-03\n",
        "Tom,Jenny,2015-01-01\n",
        "Dan,Jenny,2016-08-03\n",
        "Jenny,Amily,2015-06-08\n",
        "Dan,Nancy,2016-01-03\n",
        "Nancy,Jack,2017-03-02\n",
        "Dan,Kevin,2015-12-30"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Overwriting friendship.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rHsErjExk25u",
        "colab_type": "text"
      },
      "source": [
        "### Clear the graph"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KMWCtajBk25v",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 247
        },
        "outputId": "d2e7eb70-4271-42d0-a7c0-0248ba196b91"
      },
      "source": [
        "gsql('drop all', options=[])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "========================\n",
            "Trying version: v2_6_0\n",
            "Connecting to yaniv.i.tgcloud.io\n",
            "If there is any relative path, it is relative to tigergraph/dev/gdk/gsql\n",
            "Dropping all, about 1 minute ...\n",
            "Abort all active loading jobs\n",
            "Try to abort all loading jobs on graph social, it may take a while ...\n",
            "[ABORT_SUCCESS] No active Loading Job to abort.\n",
            "\n",
            "Shutdown restpp gse gpe ...\n",
            "Graph store /home/tigergraph/tigergraph/gstore/0/ has been cleared!\n",
            "Everything is dropped.\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FzBSHIjfk25x",
        "colab_type": "text"
      },
      "source": [
        "### Create the graph schema\n",
        "\n",
        "See [GSQL 101 - Module 1: Graph Schema](https://youtu.be/him2Uy3Nn7Y)\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nN05blvDk25x",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "outputId": "ca4031bc-7114-4750-9dd5-1ae475fc55e8"
      },
      "source": [
        "YouTubeVideo(width=896, height=504, id='him2Uy3Nn7Y')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"896\"\n",
              "            height=\"504\"\n",
              "            src=\"https://www.youtube.com/embed/him2Uy3Nn7Y\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7fecd53ec8d0>"
            ],
            "image/jpeg": 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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WnXp8Rk3k250",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 230
        },
        "outputId": "53211e04-2c5c-4bde-c839-a8c5fc234cb2"
      },
      "source": [
        "gsql('''\n",
        "create vertex person (primary_id name string, name string, age int, \n",
        "                      gender string, state string)\n",
        "                      \n",
        "create undirected edge friendship (from person, to person, \n",
        "                                   connect_day datetime)\n",
        "\n",
        "create graph social (person, friendship)\n",
        "''', options=[])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "========================\n",
            "Trying version: v2_6_0\n",
            "Connecting to yaniv.i.tgcloud.io\n",
            "If there is any relative path, it is relative to tigergraph/dev/gdk/gsql\n",
            "The vertex type person is created.\n",
            "The edge type friendship is created.\n",
            "\n",
            "Restarting gse gpe restpp ...\n",
            "\n",
            "Finish restarting services in 10.435 seconds!\n",
            "The graph social is created.\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "niTmtAZRk253",
        "colab_type": "text"
      },
      "source": [
        "### Create data loading job and run it\n",
        "\n",
        "See [GSQL 101 - Module 2: Data Loading](https://youtu.be/IFfR3tQNhoA)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CBTff_5Bk253",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "outputId": "5f69611c-cf2a-4f78-a5c8-d2e91c4df4bd"
      },
      "source": [
        "YouTubeVideo(width=896, height=504, id='IFfR3tQNhoA')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"896\"\n",
              "            height=\"504\"\n",
              "            src=\"https://www.youtube.com/embed/IFfR3tQNhoA\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7fecd5405b00>"
            ],
            "image/jpeg": 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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5R_BERhbk256",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 570
        },
        "outputId": "44f74d85-a6f4-4dd3-a322-beb9abc272af"
      },
      "source": [
        "gsql('''\n",
        "create loading job load_social for graph social {\n",
        "    define filename file1=\"~/tigergraph/loadingData/person.csv\";\n",
        "    define filename file2=\"~/tigergraph/loadingData/friendship.csv\";\n",
        "    \n",
        "    load file1 to vertex person values ($\"name\", $\"name\", $\"age\", $\"gender\", $\"state\") \n",
        "       using header=\"true\", separator=\",\";\n",
        "    \n",
        "    load file2 to edge friendship values ($\"person1\", $\"person2\", $\"date\") \n",
        "       using header=\"true\", separator=\",\";   \n",
        "}\n",
        "\n",
        "run loading job load_social\n",
        "''')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "========================\n",
            "Trying version: v2_6_0\n",
            "Connecting to yaniv.i.tgcloud.io\n",
            "If there is any relative path, it is relative to tigergraph/dev/gdk/gsql\n",
            "The job load_social is created.\n",
            "[Tip: Use \"CTRL + C\" to stop displaying the loading status update, then use \"SHOW LOADING STATUS jobid\" to track the loading progress again]\n",
            "[Tip: Manage loading jobs with \"ABORT/RESUME LOADING JOB jobid\"]\n",
            "Starting the following job, i.e.\n",
            "  JobName: load_social, jobid: social.load_social.file.m1.1592831968705\n",
            "  Loading log: '/home/tigergraph/tigergraph/logs/restpp/restpp_loader_logs/social/social.load_social.file.m1.1592831968705.log'\n",
            "\n",
            "Job \"social.load_social.file.m1.1592831968705\" loading status\n",
            "[RUNNING] m1 ( Finished: 0 / Total: 2 )\n",
            "\u001b[2A\u001b[2KJob \"social.load_social.file.m1.1592831968705\" loading status\n",
            "\u001b[2K[RUNNING] m1 ( Finished: 2 / Total: 2 )\n",
            "  [LOADED]\n",
            "  +--------------------------------------------------------------------------------------------------+\n",
            "  |                                              FILENAME |   LOADED LINES |   AVG SPEED |   DURATION|\n",
            "  |    /home/tigergraph/tigergraph/loadingData/person.csv |              8 |       7 l/s |     1.00 s|\n",
            "  |/home/tigergraph/tigergraph/loadingData/friendship.csv |              8 |       7 l/s |     1.00 s|\n",
            "  +--------------------------------------------------------------------------------------------------+\n",
            "\u001b[8A\u001b[2KJob \"social.load_social.file.m1.1592831968705\" loading status\n",
            "\u001b[2K[FINISHED] m1 ( Finished: 2 / Total: 2 )\n",
            "\u001b[2K  [LOADED]\n",
            "\u001b[2K  +--------------------------------------------------------------------------------------------------+\n",
            "\u001b[2K  |                                              FILENAME |   LOADED LINES |   AVG SPEED |   DURATION|\n",
            "\u001b[2K  |/home/tigergraph/tigergraph/loadingData/friendship.csv |              8 |       7 l/s |     1.00 s|\n",
            "\u001b[2K  |    /home/tigergraph/tigergraph/loadingData/person.csv |              8 |       7 l/s |     1.00 s|\n",
            "\u001b[2K  +--------------------------------------------------------------------------------------------------+\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mEeTnMuAk258",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 498
        },
        "outputId": "2b532535-9969-447a-e063-68600608aa62"
      },
      "source": [
        "gsql('ls')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "========================\n",
            "Trying version: v2_6_0\n",
            "Connecting to yaniv.i.tgcloud.io\n",
            "If there is any relative path, it is relative to tigergraph/dev/gdk/gsql\n",
            "---- Graph social\n",
            "Vertex Types: \n",
            "  - VERTEX person(PRIMARY_ID name STRING, name STRING, age INT, gender STRING, state STRING) WITH STATS=\"OUTDEGREE_BY_EDGETYPE\"\n",
            "Edge Types: \n",
            "  - UNDIRECTED EDGE friendship(FROM person, TO person, connect_day DATETIME)\n",
            "\n",
            "Graphs: \n",
            "  - Graph social(person:v, friendship:e)\n",
            "Jobs: \n",
            "  - CREATE LOADING JOB load_social FOR GRAPH social {\n",
            "      DEFINE FILENAME file2 = \"~/tigergraph/loadingData/friendship.csv\";\n",
            "      DEFINE FILENAME file1 = \"~/tigergraph/loadingData/person.csv\";\n",
            "      LOAD file1 TO VERTEX person VALUES($\"name\", $\"name\", $\"age\", $\"gender\", $\"state\") USING SEPARATOR=\",\", HEADER=\"true\", EOL=\"\\n\";\n",
            "      LOAD file2 TO EDGE friendship VALUES($\"person1\", $\"person2\", $\"date\") USING SEPARATOR=\",\", HEADER=\"true\", EOL=\"\\n\";\n",
            "    }\n",
            "\n",
            "Queries: \n",
            "\n",
            "\n",
            "\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qTGJn1rtk25-",
        "colab_type": "text"
      },
      "source": [
        "## Built-in `SELECT` queries\n",
        "\n",
        "See [GSQL 101 - Module 3: Graph Inspection Language](https://youtu.be/akGOSEWMC8I)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wjbvGcj6k25-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "outputId": "1a52db6a-d852-4ea8-edd6-31fb7fcc91e7"
      },
      "source": [
        "YouTubeVideo(width=896, height=504, id='akGOSEWMC8I')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"896\"\n",
              "            height=\"504\"\n",
              "            src=\"https://www.youtube.com/embed/akGOSEWMC8I\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7fecd53ec828>"
            ],
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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wx0MRs8Kk26B",
        "colab_type": "text"
      },
      "source": [
        "### `SELECT` queries return a native Python structure"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M__Kl68Zk26C",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "f1d07518-92cd-416c-d32f-5f7abe35c38d"
      },
      "source": [
        "q = gsql('select count(*) from person')\n",
        "q"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'count': 7, 'v_type': 'person'}]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R5iaq0gdk26E",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "d0fefef6-9c8f-477d-f404-11ba989101ec"
      },
      "source": [
        "q[0]['count']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "7"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Sh_2Onnnk26G",
        "colab_type": "text"
      },
      "source": [
        "### Since this is GSQL the `FROM` argument can be a pattern "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qkNRECjPk26G",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "a3869eef-b369-4c94-c7f8-e97d4c8eda78"
      },
      "source": [
        "gsql('select count() from person-(friendship)-person')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'count': 7, 'e_type': 'friendship'}]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0Wvn9K8gk26I",
        "colab_type": "text"
      },
      "source": [
        "### The `WHERE` arument is a filter on the `FROM` pattern"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UaHPmzxnk26I",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "eb396707-68b4-4370-860f-d6974c8265e5"
      },
      "source": [
        "gsql('select * from person where primary_id==\"Tom\"')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'attributes': {'age': 40, 'gender': 'male', 'name': 'Tom', 'state': 'ca'},\n",
              "  'v_id': 'Tom',\n",
              "  'v_type': 'person'}]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lhamhuYZk26K",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        },
        "outputId": "1d16f97b-1b2c-41c0-f731-63294931c96e"
      },
      "source": [
        "q = gsql('select * from person where gender==\"female\"')\n",
        "q "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'attributes': {'age': 20,\n",
              "   'gender': 'female',\n",
              "   'name': 'Nancy',\n",
              "   'state': 'ky'},\n",
              "  'v_id': 'Nancy',\n",
              "  'v_type': 'person'},\n",
              " {'attributes': {'age': 25,\n",
              "   'gender': 'female',\n",
              "   'name': 'Jenny',\n",
              "   'state': 'tx'},\n",
              "  'v_id': 'Jenny',\n",
              "  'v_type': 'person'},\n",
              " {'attributes': {'age': 22,\n",
              "   'gender': 'female',\n",
              "   'name': 'Amily',\n",
              "   'state': 'ca'},\n",
              "  'v_id': 'Amily',\n",
              "  'v_type': 'person'}]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zfkvOYvvk26M",
        "colab_type": "text"
      },
      "source": [
        "### Use Python's list comprehension to access results"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TWhJgIsRk26N",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "99d90ad4-3761-417c-c102-2e19c260b7e1"
      },
      "source": [
        "[v['attributes']['age'] for v in q]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[20, 25, 22]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BcIhLr6Qk26P",
        "colab_type": "text"
      },
      "source": [
        "### Transform into a Pandas DataFrame"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HKbzxmVPk26P",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 137
        },
        "outputId": "14deeb94-64dc-413b-e062-11831bc58bf4"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "pd.DataFrame([v['attributes'] for v in q])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>gender</th>\n",
              "      <th>name</th>\n",
              "      <th>state</th>\n",
              "      <th>age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>female</td>\n",
              "      <td>Nancy</td>\n",
              "      <td>ky</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>female</td>\n",
              "      <td>Jenny</td>\n",
              "      <td>tx</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>female</td>\n",
              "      <td>Amily</td>\n",
              "      <td>ca</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   gender   name state  age\n",
              "0  female  Nancy    ky   20\n",
              "1  female  Jenny    tx   25\n",
              "2  female  Amily    ca   22"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dltnDFUsk26R",
        "colab_type": "text"
      },
      "source": [
        "## User defined queries\n",
        "\n",
        "See [GSQL 101 - Module 4: Basic GSQL](https://youtu.be/eK6f7qnylj0) "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5m_m_Xokk26S",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "outputId": "04fb5e71-928f-47a1-b739-4b03ed0fcf9f"
      },
      "source": [
        "YouTubeVideo(width=896, height=504, id='eK6f7qnylj0')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"896\"\n",
              "            height=\"504\"\n",
              "            src=\"https://www.youtube.com/embed/eK6f7qnylj0\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7fecd4f6c0b8>"
            ],
            "image/jpeg": 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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1Ar5YgeHk26U",
        "colab_type": "text"
      },
      "source": [
        "### Queries can saved and compiled"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b1O5KwW2k26U",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 214
        },
        "outputId": "86d8f381-e7eb-47c1-9f83-f3c0f7346df7"
      },
      "source": [
        "gsql('''\n",
        "create query hello(vertex<person> p) for graph social{\n",
        "    \n",
        "    start = {p};\n",
        "    tgt = select t from start:s-(friendship:e)-person:t ;\n",
        "    print tgt;\n",
        "}\n",
        "\n",
        "install query hello\n",
        "''')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "========================\n",
            "Trying version: v2_6_0\n",
            "Connecting to yaniv.i.tgcloud.io\n",
            "If there is any relative path, it is relative to tigergraph/dev/gdk/gsql\n",
            "The query hello has been added!\n",
            "Start installing queries, about 1 minute ...\n",
            "hello query: curl -X GET 'https://127.0.0.1:9000/query/social/hello?p=VALUE'. Add -H \"Authorization: Bearer TOKEN\" if authentication is enabled.\n",
            "\n",
            "\r[                                                                 ] 0% (0/1)   \r[                                                                 ] 0% (0/1)   \r[=====                                                            ] 7% (0/1)   \r[==========                                                       ] 14% (0/1)  \r[==============                                                   ] 21% (0/1)  \r[===================                                              ] 29% (0/1)  \r[========================                                         ] 36% (0/1)  \r[============================                                     ] 43% (0/1)  \r[==================================                               ] 51% (0/1)  \r[======================================                           ] 58% (0/1)  \r[===========================================                      ] 65% (0/1)  \r[================================================                 ] 73% (0/1)  \r[====================================================             ] 80% (0/1)  \r[=========================================================        ] 87% (0/1)  \r[==============================================================   ] 95% (0/1)  \r[=================================================================] 100% (1/1) \n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VrsdwA0Dk26W",
        "colab_type": "text"
      },
      "source": [
        "### Run the installed query and process the output"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uyirQnElk26X",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "outputId": "ee2db73f-dea9-4856-a2d3-6fc1cf5a2d67"
      },
      "source": [
        "q = gsql('run query hello(\"Tom\")')\n",
        "q"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'error': False,\n",
              " 'message': '',\n",
              " 'results': [{'tgt': [{'attributes': {'age': 34,\n",
              "      'gender': 'male',\n",
              "      'name': 'Dan',\n",
              "      'state': 'ny'},\n",
              "     'v_id': 'Dan',\n",
              "     'v_type': 'person'},\n",
              "    {'attributes': {'age': 25,\n",
              "      'gender': 'female',\n",
              "      'name': 'Jenny',\n",
              "      'state': 'tx'},\n",
              "     'v_id': 'Jenny',\n",
              "     'v_type': 'person'}]}],\n",
              " 'version': {'api': 'v2', 'edition': 'enterprise', 'schema': 0}}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S8tErLGJk26Z",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "06d7b33f-5e22-412a-8aa9-43525f237d8a"
      },
      "source": [
        "[v['attributes']['age'] for v in q['results'][0]['tgt']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[34, 25]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UjDxbelBk26a",
        "colab_type": "text"
      },
      "source": [
        "## Accumulators\n",
        "\n",
        "See [GSQL 101 - Module 5: Advanced GSQL (Accumulators)](https://youtu.be/ysrm9OjVoqg)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "caiDj6zak26b",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "outputId": "1f8ab16e-a519-48dd-e0c3-10a0ddd16ce2"
      },
      "source": [
        "YouTubeVideo(width=896, height=504, id='ysrm9OjVoqg')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"896\"\n",
              "            height=\"504\"\n",
              "            src=\"https://www.youtube.com/embed/ysrm9OjVoqg\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7fecd4f20fd0>"
            ],
            "image/jpeg": 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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RVlq42Mqk26d",
        "colab_type": "text"
      },
      "source": [
        "### Measuring hop distance\n",
        "\n",
        "Measuring hop distance requires that we flag every vertex we visit using a local accumulator `@visited`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Apiirk4Ek26e",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 214
        },
        "outputId": "e9aff89b-ff9a-4a1b-b67f-fdece75dd428"
      },
      "source": [
        "gsql('''\n",
        "create query hello2(vertex<person> p) for graph social {\n",
        "    \n",
        "    OrAccum @visited = false;\n",
        "    AvgAccum @@aveAge;\n",
        "    \n",
        "    start = {p};\n",
        "    \n",
        "    firstHop = select t from start:s-(friendship:e)-person:t\n",
        "               accum t.@visited += true, s.@visited += true;\n",
        "    \n",
        "    secondHop = select t from firstHop:s-(friendship:e)-person:t\n",
        "                where t.@visited == false\n",
        "                post_accum @@aveAge += t.age;\n",
        "    \n",
        "    print secondHop;\n",
        "    print @@aveAge;\n",
        "            \n",
        "}\n",
        "\n",
        "install query hello2\n",
        "''')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "========================\n",
            "Trying version: v2_6_0\n",
            "Connecting to yaniv.i.tgcloud.io\n",
            "If there is any relative path, it is relative to tigergraph/dev/gdk/gsql\n",
            "The query hello2 has been added!\n",
            "Start installing queries, about 1 minute ...\n",
            "hello2 query: curl -X GET 'https://127.0.0.1:9000/query/social/hello2?p=VALUE'. Add -H \"Authorization: Bearer TOKEN\" if authentication is enabled.\n",
            "\n",
            "\r[                                                                 ] 0% (0/1)   \r[                                                                 ] 0% (0/1)   \r[===============================                                  ] 47% (0/1)  \r[==============================================================   ] 95% (0/1)  \r[=================================================================] 100% (1/1) \n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J40rT1E8k26g",
        "colab_type": "text"
      },
      "source": [
        "### Excluding visited verticies\n",
        "Results exclude Jenny and Dan even though they are a friend of a friend of Tom because they are also direct friends of Tom"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sVADKVwHk26g",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "outputId": "9aca81ef-620d-40aa-ea90-070415cd8b4e"
      },
      "source": [
        "q = gsql('run query hello2(\"Tom\")')\n",
        "q"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'error': False,\n",
              " 'message': '',\n",
              " 'results': [{'secondHop': [{'attributes': {'@visited': False,\n",
              "      'age': 22,\n",
              "      'gender': 'female',\n",
              "      'name': 'Amily',\n",
              "      'state': 'ca'},\n",
              "     'v_id': 'Amily',\n",
              "     'v_type': 'person'},\n",
              "    {'attributes': {'@visited': False,\n",
              "      'age': 28,\n",
              "      'gender': 'male',\n",
              "      'name': 'Kevin',\n",
              "      'state': 'az'},\n",
              "     'v_id': 'Kevin',\n",
              "     'v_type': 'person'},\n",
              "    {'attributes': {'@visited': False,\n",
              "      'age': 20,\n",
              "      'gender': 'female',\n",
              "      'name': 'Nancy',\n",
              "      'state': 'ky'},\n",
              "     'v_id': 'Nancy',\n",
              "     'v_type': 'person'}]},\n",
              "  {'@@aveAge': 23.33333}],\n",
              " 'version': {'api': 'v2', 'edition': 'enterprise', 'schema': 0}}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x7QSMNEZk26i",
        "colab_type": "text"
      },
      "source": [
        "### Global accumulators \n",
        "We can verify that the global accumulator `@@aveAge` did its job correctly."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e3oNJyK_k26i",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "5b747b34-696a-4e55-9721-352f3228b3d6"
      },
      "source": [
        "q['results'][1]['@@aveAge']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "23.33333"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sLP--BHdk26k",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "1b5ff007-e086-41a0-bd8d-bca12adb8fd3"
      },
      "source": [
        "ages = [v['attributes']['age'] for v in q['results'][0]['secondHop']]\n",
        "ages"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[22, 28, 20]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uIL7cBgjk26n",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "7c827340-7175-44cf-a94a-c62e6d259e79"
      },
      "source": [
        "sum(ages)/len(ages)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "23.333333333333332"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K7mdfbb-k26p",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}