{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gkv0-iHdQR7N"
      },
      "source": [
        "# Simple table test\n",
        "[![View On GitHub](https://img.shields.io/badge/View_in_Github-grey?logo=github)](https://github.com/Qrlew/docs/blob/main/tutorials/postgres_simple_table.ipynb)\n",
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Qrlew/pyqrlew/blob/main/examples/postgres_simple_table.ipynb)\n",
        "\n",
        "In this notebook, we demonstrate the application of `qrlew` to an existing database, showcasing its capability to compile SQL queries into differential privacy.\n",
        "\n",
        "For the purpose of this demonstration, we focus on a single table, while more intricate use cases are explored in other notebooks."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZUq42jHlQR7P"
      },
      "source": [
        "## Install the database"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eO8s7I5KQR7Q"
      },
      "source": [
        "Initially, we establish a PostgreSQL database.\n",
        "\n",
        "This section maybe skipped if you have already access to a Postgres database."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "rdN3zDBeQR7Q"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "# Load the database\n",
        "# Inspired by https://colab.research.google.com/github/tensorflow/io/blob/master/docs/tutorials/postgresql.ipynb#scrollTo=YUj0878jPyz7\n",
        "!sudo apt-get -y -qq update\n",
        "!sudo apt-get -y -qq install postgresql-14 graphviz\n",
        "# Start postgresql server\n",
        "!sudo service postgresql start\n",
        "# Set password\n",
        "!sudo -u postgres psql -U postgres -c \"ALTER USER postgres PASSWORD 'pyqrlew-db'\"\n",
        "!sudo -u postgres psql -U postgres -c \"CREATE DATABASE my_database\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6HSIusfpQR7R"
      },
      "source": [
        "We create the `census_table` table with its synthetic version `synthetic census_table`.\n",
        "\n",
        "Note that the synthetic tables are not mandatory and can be used when `qrlew`` cannot compile into DP the query."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "DlPlTqPAQR7R"
      },
      "outputs": [],
      "source": [
        "import psycopg2\n",
        "\n",
        "connect_pars= {\n",
        "    'dbname':'my_database',\n",
        "    'user':'postgres',\n",
        "    'port':5432,\n",
        "    'password':'pyqrlew-db',\n",
        "    'host':'localhost',\n",
        "}\n",
        "conn = psycopg2.connect(**connect_pars)\n",
        "\n",
        "# Create a cursor\n",
        "cursor = conn.cursor()\n",
        "\n",
        "sql_script = \"\"\"\n",
        "CREATE SCHEMA census_schema;\n",
        "\n",
        "CREATE TABLE census_schema.census_table (\n",
        "    id SERIAL PRIMARY KEY,\n",
        "    first_name VARCHAR(50),\n",
        "    last_name VARCHAR(50),\n",
        "    age INT,\n",
        "    gender VARCHAR(10),\n",
        "    occupation VARCHAR(50),\n",
        "    city VARCHAR(50),\n",
        "    state VARCHAR(50)\n",
        ");\n",
        "\n",
        "-- Inserting sample data\n",
        "INSERT INTO census_schema.census_table (first_name, last_name, age, gender, occupation, city, state)\n",
        "VALUES\n",
        "    ('John', 'Doe', 30, 'Male', 'Engineer', 'New York', 'NY'),\n",
        "    ('Jane', 'Doe', 28, 'Female', 'Engineer', 'Los Angeles', 'CA'),\n",
        "    ('Bob', 'Smith', 45, 'Male', 'Analyst', 'Chicago', 'IL'),\n",
        "    ('Alice', 'Johnson', 35, 'Female', 'Data Scientist', 'San Francisco', 'CA'),\n",
        "    ('Tom', 'Brown', 50, 'Male', 'Lawyer', 'Miami', 'FL'),\n",
        "    ('Emily', 'Davis', 32, 'Female', 'Software Developer', 'Seattle', 'WA'),\n",
        "    ('Charlie', 'Miller', 40, 'Male', 'Accountant', 'Boston', 'MA'),\n",
        "    ('Eva', 'Williams', 29, 'Female', 'Marketing Manager', 'Austin', 'TX'),\n",
        "    ('Mike', 'Jones', 38, 'Male', 'Analyst', 'Denver', 'CO'),\n",
        "    ('Sophia', 'Taylor', 42, 'Female', 'Analyst', 'Atlanta', 'GA'),\n",
        "    ('John', 'Doe', 30, 'Male', 'Engineer', 'New York', 'NY'),\n",
        "    ('Jane', 'Doe', 28, 'Female', 'Engineer', 'Los Angeles', 'CA'),\n",
        "    ('Bob', 'Smith', 45, 'Male', 'Analyst', 'Chicago', 'IL'),\n",
        "    ('Alice', 'Johnson', 35, 'Female', 'Data Scientist', 'San Francisco', 'CA'),\n",
        "    ('Tom', 'Brown', 50, 'Male', 'Lawyer', 'Miami', 'FL'),\n",
        "    ('Emily', 'Davis', 32, 'Female', 'Software Developer', 'Seattle', 'WA'),\n",
        "    ('Charlie', 'Miller', 40, 'Male', 'Accountant', 'Boston', 'MA'),\n",
        "    ('Eva', 'Williams', 29, 'Female', 'Marketing Manager', 'Austin', 'TX'),\n",
        "    ('Mike', 'Jones', 38, 'Male', 'Analyst', 'Denver', 'CO'),\n",
        "    ('Sophia', 'Taylor', 42, 'Female', 'Analyst', 'Atlanta', 'GA'),\n",
        "    ('Alex', 'Johnson', 33, 'Male', 'Analyst', 'Portland', 'OR'),\n",
        "    ('Megan', 'White', 27, 'Female', 'Data Scientist', 'San Diego', 'CA'),\n",
        "    ('Daniel', 'Clark', 36, 'Male', 'Analyst', 'Houston', 'TX'),\n",
        "    ('Olivia', 'Martinez', 31, 'Female', 'Data Scientist', 'Phoenix', 'AZ'),\n",
        "    ('William', 'Lee', 48, 'Male', 'Professor', 'Philadelphia', 'PA'),\n",
        "    ('Emma', 'Garcia', 29, 'Female', 'Data Scientist', 'Minneapolis', 'MN'),\n",
        "    ('Ryan', 'Harris', 41, 'Male', 'Data Scientist', 'Dallas', 'TX'),\n",
        "    ('Ava', 'Taylor', 26, 'Female', 'Product Manager', 'San Jose', 'CA'),\n",
        "    ('Christopher', 'Anderson', 37, 'Male', 'Engineer', 'Detroit', 'MI'),\n",
        "    ('Sophie', 'Wilson', 34, 'Female', 'HR Specialist', 'Raleigh', 'NC'),\n",
        "    ('David', 'Miller', 29, 'Male', 'Engineer', 'New York', 'NY'),\n",
        "    ('Sophia', 'Taylor', 34, 'Female', 'Engineer', 'Los Angeles', 'CA'),\n",
        "    ('Bob', 'Smith', 42, 'Male', 'Analyst', 'Chicago', 'IL'),\n",
        "    ('Alice', 'Johnson', 39, 'Female', 'Data Scientist', 'San Francisco', 'CA'),\n",
        "    ('Tom', 'Brown', 37, 'Male', 'Lawyer', 'Miami', 'FL'),\n",
        "    ('Emily', 'Davis', 28, 'Female', 'Software Developer', 'Seattle', 'WA'),\n",
        "    ('Charlie', 'Miller', 45, 'Male', 'Accountant', 'Boston', 'MA'),\n",
        "    ('Eva', 'Williams', 31, 'Female', 'Marketing Manager', 'Austin', 'TX'),\n",
        "    ('Mike', 'Jones', 36, 'Male', 'Analyst', 'Denver', 'CO'),\n",
        "    ('Sophia', 'Taylor', 49, 'Female', 'Analyst', 'Atlanta', 'GA'),\n",
        "    ('Alex', 'Johnson', 37, 'Male', 'Analyst', 'Portland', 'OR'),\n",
        "    ('Megan', 'White', 27, 'Female', 'Data Scientist', 'San Diego', 'CA'),\n",
        "    ('Daniel', 'Clark', 41, 'Male', 'Analyst', 'Houston', 'TX'),\n",
        "    ('Olivia', 'Martinez', 32, 'Female', 'Data Scientist', 'Phoenix', 'AZ'),\n",
        "    ('William', 'Lee', 47, 'Male', 'Professor', 'Philadelphia', 'PA'),\n",
        "    ('Emma', 'Garcia', 30, 'Female', 'Data Scientist', 'Minneapolis', 'MN'),\n",
        "    ('Ryan', 'Harris', 40, 'Male', 'Entrepreneur', 'Dallas', 'TX'),\n",
        "    ('Ava', 'Taylor', 26, 'Female', 'Product Manager', 'San Jose', 'CA'),\n",
        "    ('Christopher', 'Anderson', 35, 'Male', 'Engineer', 'Detroit', 'MI'),\n",
        "    ('Sophie', 'Wilson', 33, 'Female', 'HR Specialist', 'Raleigh', 'NC'),\n",
        "    ('Grace', 'Brown', 55, 'Female', 'Analyst', 'New York', 'NY'),\n",
        "    ('Brian', 'Taylor', 50, 'Male', 'Professor', 'Los Angeles', 'CA'),\n",
        "    ('Lily', 'Harrison', 42, 'Female', 'Engineer', 'Chicago', 'IL'),\n",
        "    ('Kevin', 'Garcia', 55, 'Male', 'Analyst', 'San Francisco', 'CA'),\n",
        "    ('Sophie', 'Smithson', 48, 'Female', 'Lawyer', 'Miami', 'FL'),\n",
        "    ('John', 'Clarkston', 38, 'Male', 'Software Developer', 'Seattle', 'WA'),\n",
        "    ('Emma', 'Millerson', 40, 'Female', 'Accountant', 'Boston', 'MA'),\n",
        "    ('David', 'Williamson', 45, 'Male', 'Marketing Manager', 'Austin', 'TX'),\n",
        "    ('Ava', 'Johnsonson', 38, 'Female', 'Analyst', 'Denver', 'CO'),\n",
        "    ('Daniel', 'Anderson', 42, 'Male', 'Data Scientist', 'Atlanta', 'GA'),\n",
        "    ('Michael', 'Martinson', 33, 'Male', 'Engineer', 'Portland', 'OR'),\n",
        "    ('Sophia', 'Whiterson', 27, 'Female', 'Data Scientist', 'San Diego', 'CA'),\n",
        "    ('Robert', 'Davidson', 41, 'Male', 'Analyst', 'Houston', 'TX'),\n",
        "    ('Grace', 'Wilson', 45, 'Female', 'Data Scientist', 'Phoenix', 'AZ'),\n",
        "    ('Andrew', 'Leeson', 48, 'Male', 'Professor', 'Philadelphia', 'PA'),\n",
        "    ('Emily', 'Garcia', 39, 'Female', 'Data Scientist', 'Minneapolis', 'MN'),\n",
        "    ('Christopher', 'Sanders', 41, 'Male', 'Entrepreneur', 'Dallas', 'TX'),\n",
        "    ('Olivia', 'Martinez', 36, 'Female', 'Product Manager', 'San Jose', 'CA'),\n",
        "    ('Sophie', 'Brownson', 43, 'Female', 'Engineer', 'Detroit', 'MI'),\n",
        "    ('Matthew', 'Taylors', 46, 'Male', 'HR Specialist', 'Raleigh', 'NC');\n",
        "\n",
        "CREATE TABLE census_schema.synthetic_census_table (\n",
        "    id SERIAL PRIMARY KEY,\n",
        "    first_name VARCHAR(50),\n",
        "    last_name VARCHAR(50),\n",
        "    age INT,\n",
        "    gender VARCHAR(10),\n",
        "    occupation VARCHAR(50),\n",
        "    city VARCHAR(50),\n",
        "    state VARCHAR(50)\n",
        ");\n",
        "\n",
        "-- Inserting sample data\n",
        "INSERT INTO census_schema.synthetic_census_table (first_name, last_name, age, gender, occupation, city, state)\n",
        "VALUES\n",
        "    ('Adam', 'Johnson', 31, 'Male', 'Engineer', 'New York', 'NY'),\n",
        "    ('Sophie', 'Clark', 29, 'Female', 'Analyst', 'Los Angeles', 'CA'),\n",
        "    ('David', 'Smith', 46, 'Male', 'Data Scientist', 'Chicago', 'IL'),\n",
        "    ('Emma', 'Brown', 36, 'Female', 'Software Developer', 'San Francisco', 'CA'),\n",
        "    ('James', 'Taylor', 51, 'Male', 'Lawyer', 'Miami', 'FL'),\n",
        "    ('Olivia', 'Miller', 33, 'Female', 'Accountant', 'Seattle', 'WA'),\n",
        "    ('Lucas', 'Williams', 41, 'Male', 'Marketing Manager', 'Boston', 'MA'),\n",
        "    ('Ava', 'Davis', 30, 'Female', 'Analyst', 'Austin', 'TX'),\n",
        "    ('Adam', 'Jones', 39, 'Male', 'Engineer', 'Denver', 'CO'),\n",
        "    ('Sophie', 'Johnson', 43, 'Female', 'Analyst', 'Atlanta', 'GA'),\n",
        "    ('Alex', 'Smith', 34, 'Male', 'Software Developer', 'Portland', 'OR'),\n",
        "    ('Mia', 'White', 28, 'Female', 'Data Scientist', 'San Diego', 'CA'),\n",
        "    ('Daniel', 'Clarkson', 37, 'Male', 'Lawyer', 'Houston', 'TX'),\n",
        "    ('Oliver', 'Martinez', 32, 'Male', 'Data Scientist', 'Phoenix', 'AZ'),\n",
        "    ('Sophia', 'Lee', 49, 'Female', 'Professor', 'Philadelphia', 'PA'),\n",
        "    ('Lily', 'Garcia', 30, 'Female', 'Data Scientist', 'Minneapolis', 'MN'),\n",
        "    ('Matthew', 'Harris', 42, 'Male', 'Entrepreneur', 'Dallas', 'TX'),\n",
        "    ('Emily', 'Taylor', 27, 'Female', 'Product Manager', 'San Jose', 'CA'),\n",
        "    ('William', 'Anderson', 36, 'Male', 'Engineer', 'Detroit', 'MI'),\n",
        "    ('Sophia', 'Wilson', 34, 'Female', 'HR Specialist', 'Raleigh', 'NC'),\n",
        "    ('Ethan', 'Miller', 29, 'Male', 'Engineer', 'New York', 'NY'),\n",
        "    ('Mia', 'Clark', 35, 'Female', 'Software Developer', 'Los Angeles', 'CA'),\n",
        "    ('Jack', 'Smithson', 43, 'Male', 'Analyst', 'Chicago', 'IL'),\n",
        "    ('Ava', 'Johnsonson', 38, 'Female', 'Data Scientist', 'San Francisco', 'CA'),\n",
        "    ('Henry', 'Brown', 36, 'Male', 'Lawyer', 'Miami', 'FL'),\n",
        "    ('Sophie', 'Davis', 27, 'Female', 'Accountant', 'Seattle', 'WA'),\n",
        "    ('Noah', 'Williamson', 45, 'Male', 'Marketing Manager', 'Boston', 'MA'),\n",
        "    ('Mia', 'Williams', 29, 'Female', 'Analyst', 'Austin', 'TX'),\n",
        "    ('Ethan', 'Jones', 38, 'Male', 'Engineer', 'Denver', 'CO'),\n",
        "    ('Ava', 'Taylor', 42, 'Female', 'Analyst', 'Atlanta', 'GA'),\n",
        "    ('Alex', 'Johnson', 33, 'Male', 'Software Developer', 'Portland', 'OR'),\n",
        "    ('Mia', 'White', 27, 'Female', 'Data Scientist', 'San Diego', 'CA'),\n",
        "    ('Daniel', 'Clark', 41, 'Male', 'Lawyer', 'Houston', 'TX'),\n",
        "    ('Olivia', 'Martinez', 32, 'Female', 'Data Scientist', 'Phoenix', 'AZ'),\n",
        "    ('William', 'Lee', 47, 'Male', 'Professor', 'Philadelphia', 'PA'),\n",
        "    ('Emma', 'Garcia', 30, 'Female', 'Data Scientist', 'Minneapolis', 'MN'),\n",
        "    ('Ryan', 'Harris', 40, 'Male', 'Entrepreneur', 'Dallas', 'TX'),\n",
        "    ('Ava', 'Taylor', 26, 'Female', 'Product Manager', 'San Jose', 'CA'),\n",
        "    ('Christopher', 'Anderson', 35, 'Male', 'Engineer', 'Detroit', 'MI'),\n",
        "    ('Sophie', 'Wilson', 33, 'Female', 'HR Specialist', 'Raleigh', 'NC'),\n",
        "    ('Grace', 'Brown', 55, 'Female', 'Analyst', 'New York', 'NY'),\n",
        "    ('Brian', 'Taylor', 50, 'Male', 'Professor', 'Los Angeles', 'CA'),\n",
        "    ('Lily', 'Harrison', 42, 'Female', 'Engineer', 'Chicago', 'IL'),\n",
        "    ('Kevin', 'Garcia', 55, 'Male', 'Analyst', 'San Francisco', 'CA'),\n",
        "    ('Sophie', 'Smithson', 48, 'Female', 'Lawyer', 'Miami', 'FL'),\n",
        "    ('John', 'Clarkston', 38, 'Male', 'Software Developer', 'Seattle', 'WA'),\n",
        "    ('Emma', 'Millerson', 40, 'Female', 'Accountant', 'Boston', 'MA'),\n",
        "    ('David', 'Williamson', 45, 'Male', 'Marketing Manager', 'Austin', 'TX'),\n",
        "    ('Ava', 'Johnsonson', 38, 'Female', 'Analyst', 'Denver', 'CO'),\n",
        "    ('Daniel', 'Anderson', 42, 'Male', 'Data Scientist', 'Atlanta', 'GA'),\n",
        "    ('Michael', 'Martinson', 33, 'Male', 'Engineer', 'Portland', 'OR'),\n",
        "    ('Sophia', 'Whiterson', 27, 'Female', 'Data Scientist', 'San Diego', 'CA'),\n",
        "    ('Robert', 'Davidson', 41, 'Male', 'Analyst', 'Houston', 'TX'),\n",
        "    ('Grace', 'Wilson', 45, 'Female', 'Data Scientist', 'Phoenix', 'AZ'),\n",
        "    ('Andrew', 'Leeson', 48, 'Male', 'Professor', 'Philadelphia', 'PA'),\n",
        "    ('Emily', 'Garcia', 39, 'Female', 'Data Scientist', 'Minneapolis', 'MN'),\n",
        "    ('Christopher', 'Sanders', 41, 'Male', 'Entrepreneur', 'Dallas', 'TX'),\n",
        "    ('Olivia', 'Martinez', 36, 'Female', 'Product Manager', 'San Jose', 'CA'),\n",
        "    ('Sophie', 'Brownson', 43, 'Female', 'Engineer', 'Detroit', 'MI'),\n",
        "    ('Matthew', 'Taylors', 46, 'Male', 'HR Specialist', 'Raleigh', 'NC')\n",
        "\"\"\"\n",
        "cursor.execute(sql_script)\n",
        "\n",
        "# Commit the changes\n",
        "conn.commit()\n",
        "\n",
        "# Close the cursor and connection\n",
        "cursor.close()\n",
        "conn.close()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2XTYdjWhQR7S"
      },
      "source": [
        "# Use qrlew on the database"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Xs69AaXOQR7S"
      },
      "source": [
        "At this stage, we have a postgres dataset that can be connected with `qrlew`."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "j8RWjR4cQR7S"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "!pip install -U pyqrlew matplotlib graphviz"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E1S7u-GMQR7S"
      },
      "source": [
        "The `dataset_from_database` function, located in `pyqrlew.io.dataset`, enables the creation of a Dataset object from a SQLAlchemy engine.\n",
        "It takes the following parameters:\n",
        "- `name`: the dataset's name,\n",
        "- `engine`: the SQLAlchemy engine establishing a connection to the database,\n",
        "- `schema_name`: the optional name of the schema,\n",
        "- `ranges`: if set to True, we use the the minimum and maximum values of numeric and datetime columns for setting their bounds.\n",
        "    **This may violates differential privacy** and should be use if these values are public.\n",
        "    Otherwise, use `False`. In that case, the bounds have to be provided in the SQL query,\n",
        "- `possible_values_threshold`: an optional integer that serves as a threshold for identifying a column as categorical. If a column surpasses this threshold, its categories are published. Similar to the ranges parameter, exercising this option may compromise differential privacy."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "7-4WwTHAQR7T"
      },
      "outputs": [],
      "source": [
        "from pyqrlew.io.dataset import dataset_from_database\n",
        "from sqlalchemy import create_engine\n",
        "\n",
        "connect_pars= {\n",
        "    'dbname':'my_database',\n",
        "    'user':'postgres',\n",
        "    'port':5432,\n",
        "    'password':'pyqrlew-db',\n",
        "    'host':'localhost',\n",
        "}\n",
        "engine = create_engine(f'postgresql+psycopg2://{connect_pars[\"user\"]}:{connect_pars[\"password\"]}@{connect_pars[\"host\"]}:{connect_pars[\"port\"]}/{connect_pars[\"dbname\"]}')\n",
        "ds = dataset_from_database(\n",
        "    name=\"census\",\n",
        "    engine=engine,\n",
        "    schema_name=\"census_schema\",\n",
        "    ranges=True,\n",
        "    possible_values_threshold=5\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "20zBpJEmQR7T"
      },
      "source": [
        "`qrlew` connects to the database via the SQLAlchemy engine and fetch the tables."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9SvsAaZhQR7U"
      },
      "source": [
        "The table `\"census_schema\".\"census_table\"` is represented as a `Table` variant of a `Relation`.\n",
        "This specific representation encapsulates all columns, their respective types, and optionally includes information about bounds and possible values.\n",
        "\n",
        "In the provided example, we observe the bounds specification for the integer column `age` and the declaration of possible values for the string column `gender`."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 201
        },
        "id": "oUZ-hdwRQR7U",
        "outputId": "63a44077-b5e3-4833-ff4e-299aec48d5d3"
      },
      "outputs": [
        {
          "data": {
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              " -->\n",
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              "<!-- graph_px87 -->\n",
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              "<title>graph_px87</title>\n",
              "<path fill=\"#ff1744\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M299,-127C299,-127 12,-127 12,-127 6,-127 0,-121 0,-115 0,-115 0,-12 0,-12 0,-6 6,0 12,0 12,0 299,0 299,0 305,0 311,-6 311,-12 311,-12 311,-115 311,-115 311,-121 305,-127 299,-127\"/>\n",
              "<text text-anchor=\"start\" x=\"14\" y=\"-105.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">CENSUS_SCHEMA_CENSUS_TABLE size ∈ int{70}</text>\n",
              "<text text-anchor=\"start\" x=\"88\" y=\"-94.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">id = id ∈ int[1 70]</text>\n",
              "<text text-anchor=\"start\" x=\"54.5\" y=\"-83.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">first_name = first_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"61\" y=\"-72.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">last_name = last_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"78\" y=\"-61.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">age = age ∈ int[26 55]</text>\n",
              "<text text-anchor=\"start\" x=\"34\" y=\"-50.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">gender = gender ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"54.5\" y=\"-39.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">occupation = occupation ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"95\" y=\"-28.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">city = city ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"88\" y=\"-17.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">state = state ∈ str</text>\n",
              "</g>\n",
              "</g>\n",
              "</svg>\n"
            ],
            "text/plain": [
              "<graphviz.sources.Source at 0x7be2118fc9a0>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import graphviz\n",
        "display(graphviz.Source(ds.census_schema.census_table.relation().dot()))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QpW4KTS_QR7U"
      },
      "source": [
        "Any SQL query can be transformed into a `Relation`, a `qrlew` object that allow to more easily the compilation into differential privacy."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "BEETjOfYQR7U",
        "outputId": "2f989cfc-18c3-4365-e284-ab920dde1444"
      },
      "outputs": [
        {
          "data": {
            "image/svg+xml": [
              "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
              "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
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              " -->\n",
              "<!-- Title: graph_c_nh Pages: 1 -->\n",
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              " viewBox=\"0.00 0.00 326.00 315.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
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              "<title>graph_c_nh</title>\n",
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              "<!-- graph_c_nh -->\n",
              "<g id=\"node1\" class=\"node\">\n",
              "<title>graph_c_nh</title>\n",
              "<path fill=\"#00363a\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M306,-307C306,-307 12,-307 12,-307 6,-307 0,-301 0,-295 0,-295 0,-258 0,-258 0,-252 6,-246 12,-246 12,-246 306,-246 306,-246 312,-246 318,-252 318,-258 318,-258 318,-295 318,-295 318,-301 312,-307 306,-307\"/>\n",
              "<text text-anchor=\"start\" x=\"61\" y=\"-285.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">REDUCE_RTS_ size ∈ int[0 70]</text>\n",
              "<text text-anchor=\"start\" x=\"14\" y=\"-274.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">field_1wy3 = sum(field_z_jj) ∈ int[0 3850]</text>\n",
              "<text text-anchor=\"start\" x=\"88\" y=\"-263.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">GROUP BY (field_d4_o)</text>\n",
              "</g>\n",
              "<!-- graph_sqxd -->\n",
              "<g id=\"node2\" class=\"node\">\n",
              "<title>graph_sqxd</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M296,-217C296,-217 22,-217 22,-217 16,-217 10,-211 10,-205 10,-205 10,-168 10,-168 10,-162 16,-156 22,-156 22,-156 296,-156 296,-156 302,-156 308,-162 308,-168 308,-168 308,-205 308,-205 308,-211 302,-217 296,-217\"/>\n",
              "<text text-anchor=\"start\" x=\"71.5\" y=\"-195.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_WTB7 size ∈ int[0 70]</text>\n",
              "<text text-anchor=\"start\" x=\"58\" y=\"-184.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_z_jj = age ∈ int[26 55]</text>\n",
              "<text text-anchor=\"start\" x=\"24\" y=\"-173.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = gender ∈ str{Female, Male}</text>\n",
              "</g>\n",
              "<!-- graph_c_nh&#45;&gt;graph_sqxd -->\n",
              "<g id=\"edge2\" class=\"edge\">\n",
              "<title>graph_c_nh&#45;&gt;graph_sqxd</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M159,-245.71C159,-239.83 159,-233.57 159,-227.42\"/>\n",
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              "</g>\n",
              "<!-- graph_px87 -->\n",
              "<g id=\"node3\" class=\"node\">\n",
              "<title>graph_px87</title>\n",
              "<path fill=\"#ff1744\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M302.5,-127C302.5,-127 15.5,-127 15.5,-127 9.5,-127 3.5,-121 3.5,-115 3.5,-115 3.5,-12 3.5,-12 3.5,-6 9.5,0 15.5,0 15.5,0 302.5,0 302.5,0 308.5,0 314.5,-6 314.5,-12 314.5,-12 314.5,-115 314.5,-115 314.5,-121 308.5,-127 302.5,-127\"/>\n",
              "<text text-anchor=\"start\" x=\"17.5\" y=\"-105.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">CENSUS_SCHEMA_CENSUS_TABLE size ∈ int{70}</text>\n",
              "<text text-anchor=\"start\" x=\"91.5\" y=\"-94.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">id = id ∈ int[1 70]</text>\n",
              "<text text-anchor=\"start\" x=\"58\" y=\"-83.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">first_name = first_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"64.5\" y=\"-72.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">last_name = last_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"81.5\" y=\"-61.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">age = age ∈ int[26 55]</text>\n",
              "<text text-anchor=\"start\" x=\"37.5\" y=\"-50.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">gender = gender ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"58\" y=\"-39.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">occupation = occupation ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"98.5\" y=\"-28.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">city = city ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"91.5\" y=\"-17.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">state = state ∈ str</text>\n",
              "</g>\n",
              "<!-- graph_sqxd&#45;&gt;graph_px87 -->\n",
              "<g id=\"edge1\" class=\"edge\">\n",
              "<title>graph_sqxd&#45;&gt;graph_px87</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M159,-155.9C159,-150.21 159,-144.01 159,-137.63\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"162.5,-137.47 159,-127.47 155.5,-137.47 162.5,-137.47\"/>\n",
              "</g>\n",
              "</g>\n",
              "</svg>\n"
            ],
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              "<graphviz.sources.Source at 0x7be1e1643dc0>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import pandas as pd\n",
        "query = \"SELECT sum(age) FROM census_schema.census_table GROUP BY gender\"\n",
        "relation = ds.relation(query)\n",
        "display(graphviz.Source(relation.dot()))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 590
        },
        "id": "NboNwp_pQR7U",
        "outputId": "672386f9-90b1-492d-a539-12f755e1ad4c"
      },
      "outputs": [
        {
          "data": {
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              "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
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              "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 423)\">\n",
              "<title>graph_lkbb</title>\n",
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              "<!-- graph_lkbb -->\n",
              "<g id=\"node1\" class=\"node\">\n",
              "<title>graph_lkbb</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M370,-419C370,-419 49,-419 49,-419 43,-419 37,-413 37,-407 37,-407 37,-370 37,-370 37,-364 43,-358 49,-358 49,-358 370,-358 370,-358 376,-358 382,-364 382,-370 382,-370 382,-407 382,-407 382,-413 376,-419 370,-419\"/>\n",
              "<text text-anchor=\"start\" x=\"122\" y=\"-397.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_VDVC size ∈ int[0 70]</text>\n",
              "<text text-anchor=\"start\" x=\"51\" y=\"-386.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">gender = field_d4_o ∈ str{Female, Male} UNIQUE</text>\n",
              "<text text-anchor=\"start\" x=\"91.5\" y=\"-375.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">count_all = field_i4xy ∈ int[0 70]</text>\n",
              "</g>\n",
              "<!-- graph_fz6f -->\n",
              "<g id=\"node2\" class=\"node\">\n",
              "<title>graph_fz6f</title>\n",
              "<path fill=\"#00363a\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M407,-329C407,-329 12,-329 12,-329 6,-329 0,-323 0,-317 0,-317 0,-269 0,-269 0,-263 6,-257 12,-257 12,-257 407,-257 407,-257 413,-257 419,-263 419,-269 419,-269 419,-317 419,-317 419,-323 413,-329 407,-329\"/>\n",
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              "<text text-anchor=\"start\" x=\"14\" y=\"-296.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">field_d4_o = first(field_d4_o) ∈ str{Female, Male} UNIQUE</text>\n",
              "<text text-anchor=\"start\" x=\"64.5\" y=\"-285.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">field_i4xy = count(field_n9r3) ∈ int[0 70]</text>\n",
              "<text text-anchor=\"start\" x=\"138.5\" y=\"-274.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">GROUP BY (field_d4_o)</text>\n",
              "</g>\n",
              "<!-- graph_lkbb&#45;&gt;graph_fz6f -->\n",
              "<g id=\"edge3\" class=\"edge\">\n",
              "<title>graph_lkbb&#45;&gt;graph_fz6f</title>\n",
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              "<g id=\"node3\" class=\"node\">\n",
              "<title>graph_gfjv</title>\n",
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              "<text text-anchor=\"start\" x=\"122\" y=\"-206.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_W7KV size ∈ int[0 70]</text>\n",
              "<text text-anchor=\"start\" x=\"128.5\" y=\"-195.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_n9r3 = 1 ∈ int{1}</text>\n",
              "<text text-anchor=\"start\" x=\"74.5\" y=\"-184.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = gender ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"155\" y=\"-173.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">WHERE (age = 10)</text>\n",
              "</g>\n",
              "<!-- graph_fz6f&#45;&gt;graph_gfjv -->\n",
              "<g id=\"edge2\" class=\"edge\">\n",
              "<title>graph_fz6f&#45;&gt;graph_gfjv</title>\n",
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              "<!-- graph_px87 -->\n",
              "<g id=\"node4\" class=\"node\">\n",
              "<title>graph_px87</title>\n",
              "<path fill=\"#ff1744\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M353,-127C353,-127 66,-127 66,-127 60,-127 54,-121 54,-115 54,-115 54,-12 54,-12 54,-6 60,0 66,0 66,0 353,0 353,0 359,0 365,-6 365,-12 365,-12 365,-115 365,-115 365,-121 359,-127 353,-127\"/>\n",
              "<text text-anchor=\"start\" x=\"68\" y=\"-105.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">CENSUS_SCHEMA_CENSUS_TABLE size ∈ int{70}</text>\n",
              "<text text-anchor=\"start\" x=\"142\" y=\"-94.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">id = id ∈ int[1 70]</text>\n",
              "<text text-anchor=\"start\" x=\"108.5\" y=\"-83.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">first_name = first_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"115\" y=\"-72.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">last_name = last_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"132\" y=\"-61.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">age = age ∈ int[26 55]</text>\n",
              "<text text-anchor=\"start\" x=\"88\" y=\"-50.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">gender = gender ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"108.5\" y=\"-39.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">occupation = occupation ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"149\" y=\"-28.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">city = city ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"142\" y=\"-17.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">state = state ∈ str</text>\n",
              "</g>\n",
              "<!-- graph_gfjv&#45;&gt;graph_px87 -->\n",
              "<g id=\"edge1\" class=\"edge\">\n",
              "<title>graph_gfjv&#45;&gt;graph_px87</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M209.5,-155.76C209.5,-149.91 209.5,-143.66 209.5,-137.27\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"213,-137.16 209.5,-127.16 206,-137.16 213,-137.16\"/>\n",
              "</g>\n",
              "</g>\n",
              "</svg>\n"
            ],
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              "<graphviz.sources.Source at 0x7be212756980>"
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          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "query = \"SELECT gender as gender, COUNT(*)  AS count_all FROM census_schema.census_table WHERE age = 10 GROUP BY gender\"\n",
        "relation = ds.relation(query)\n",
        "display(graphviz.Source(relation.dot()))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vsKdOqcJQR7U"
      },
      "source": [
        "Let's convert this `Relation` into differential privacy with the `rewrite_with_differential_privacy` method that outputs:\n",
        "- `privacy_unit`: the privacy unit may be defined as a column within the current table or even another table. Alternatively, each row can be protected.\n",
        "- `synthetic_data`: this optional list associates each original table to its synthetic version. If these tables are provided, any queries that can't be compiled into DP will be executed on the synthetic data\n",
        "- `epsilon_delta`: a dictionnary with the $\\varepsilon$ and $\\delta$ privacy parameters."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "mRTKmSDfQR7U"
      },
      "outputs": [],
      "source": [
        "privacy_unit = [\n",
        "    (\"census_table\", [], \"_PRIVACY_UNIT_ROW_\"), # each row is protected\n",
        "]\n",
        "synthetic_data = None\n",
        "\n",
        "dp_relation = relation.rewrite_with_differential_privacy(\n",
        "    dataset=ds,\n",
        "    synthetic_data=synthetic_data,\n",
        "    privacy_unit=privacy_unit,\n",
        "    epsilon_delta={\"epsilon\": 1.0, \"delta\": 1e-3}\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZksZxGQqQR7V"
      },
      "source": [
        "The result of `rewrite_with_differential_privacy` is an object that holds both the differentially private `Relation` and a `PrivateQuery` containing the invoked mechanisms during the compilation."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "zN_4fJt2QR7V",
        "outputId": "c82d26d7-bcce-4531-b906-445b69dc72b4"
      },
      "outputs": [
        {
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              "<text text-anchor=\"start\" x=\"405\" y=\"-2367.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">gender = field_d4_o ∈ str{Female, Male} UNIQUE</text>\n",
              "<text text-anchor=\"start\" x=\"442\" y=\"-2356.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">count_all = field_i4xy ∈ int[0 140]</text>\n",
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              "<g id=\"node2\" class=\"node\">\n",
              "<title>graph_i4m8</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M737.5,-2310C737.5,-2310 389.5,-2310 389.5,-2310 383.5,-2310 377.5,-2304 377.5,-2298 377.5,-2298 377.5,-2261 377.5,-2261 377.5,-2255 383.5,-2249 389.5,-2249 389.5,-2249 737.5,-2249 737.5,-2249 743.5,-2249 749.5,-2255 749.5,-2261 749.5,-2261 749.5,-2298 749.5,-2298 749.5,-2304 743.5,-2310 737.5,-2310\"/>\n",
              "<text text-anchor=\"start\" x=\"472.5\" y=\"-2288.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_09T5 size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"391.5\" y=\"-2277.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = field_d4_o ∈ str{Female, Male} UNIQUE</text>\n",
              "<text text-anchor=\"start\" x=\"438.5\" y=\"-2266.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_i4xy = field_i4xy ∈ int[0 140]</text>\n",
              "</g>\n",
              "<!-- graph_rhz9&#45;&gt;graph_i4m8 -->\n",
              "<g id=\"edge22\" class=\"edge\">\n",
              "<title>graph_rhz9&#45;&gt;graph_i4m8</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M563.5,-2338.71C563.5,-2332.83 563.5,-2326.57 563.5,-2320.42\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"567,-2320.26 563.5,-2310.26 560,-2320.26 567,-2320.26\"/>\n",
              "</g>\n",
              "<!-- graph_a1i4 -->\n",
              "<g id=\"node3\" class=\"node\">\n",
              "<title>graph_a1i4</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M771.5,-2220C771.5,-2220 355.5,-2220 355.5,-2220 349.5,-2220 343.5,-2214 343.5,-2208 343.5,-2208 343.5,-2171 343.5,-2171 343.5,-2165 349.5,-2159 355.5,-2159 355.5,-2159 771.5,-2159 771.5,-2159 777.5,-2159 783.5,-2165 783.5,-2171 783.5,-2171 783.5,-2208 783.5,-2208 783.5,-2214 777.5,-2220 771.5,-2220\"/>\n",
              "<text text-anchor=\"start\" x=\"472.5\" y=\"-2198.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_ITYA size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"357.5\" y=\"-2187.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_i4xy = cast_as_integer(_COUNT_field_n9r3) ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"391.5\" y=\"-2176.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = field_d4_o ∈ str{Female, Male} UNIQUE</text>\n",
              "</g>\n",
              "<!-- graph_i4m8&#45;&gt;graph_a1i4 -->\n",
              "<g id=\"edge21\" class=\"edge\">\n",
              "<title>graph_i4m8&#45;&gt;graph_a1i4</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M563.5,-2248.71C563.5,-2242.83 563.5,-2236.57 563.5,-2230.42\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"567,-2230.26 563.5,-2220.26 560,-2230.26 567,-2230.26\"/>\n",
              "</g>\n",
              "<!-- graph_rteh -->\n",
              "<g id=\"node4\" class=\"node\">\n",
              "<title>graph_rteh</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M998,-2130C998,-2130 129,-2130 129,-2130 123,-2130 117,-2124 117,-2118 117,-2118 117,-2081 117,-2081 117,-2075 123,-2069 129,-2069 129,-2069 998,-2069 998,-2069 1004,-2069 1010,-2075 1010,-2081 1010,-2081 1010,-2118 1010,-2118 1010,-2124 1004,-2130 998,-2130\"/>\n",
              "<text text-anchor=\"start\" x=\"472.5\" y=\"-2108.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_M6IS size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"391.5\" y=\"-2097.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = field_d4_o ∈ str{Female, Male} UNIQUE</text>\n",
              "<text text-anchor=\"start\" x=\"131\" y=\"-2086.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_COUNT_field_n9r3 = least(140, greatest(0, (coalesce(_COUNT_field_n9r3, 0) + (3.776479532659047 * (sqrt((&#45;2 * ln(random()))) ...</text>\n",
              "</g>\n",
              "<!-- graph_a1i4&#45;&gt;graph_rteh -->\n",
              "<g id=\"edge20\" class=\"edge\">\n",
              "<title>graph_a1i4&#45;&gt;graph_rteh</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M563.5,-2158.71C563.5,-2152.83 563.5,-2146.57 563.5,-2140.42\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"567,-2140.26 563.5,-2130.26 560,-2140.26 567,-2140.26\"/>\n",
              "</g>\n",
              "<!-- graph_aluv -->\n",
              "<g id=\"node5\" class=\"node\">\n",
              "<title>graph_aluv</title>\n",
              "<path fill=\"#00363a\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M764.5,-2040C764.5,-2040 362.5,-2040 362.5,-2040 356.5,-2040 350.5,-2034 350.5,-2028 350.5,-2028 350.5,-1980 350.5,-1980 350.5,-1974 356.5,-1968 362.5,-1968 362.5,-1968 764.5,-1968 764.5,-1968 770.5,-1968 776.5,-1974 776.5,-1980 776.5,-1980 776.5,-2028 776.5,-2028 776.5,-2034 770.5,-2040 764.5,-2040\"/>\n",
              "<text text-anchor=\"start\" x=\"462.5\" y=\"-2018.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">REDUCE_TDCW size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"368\" y=\"-2007.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">field_d4_o = first(field_zyse) ∈ str{Female, Male} UNIQUE</text>\n",
              "<text text-anchor=\"start\" x=\"364.5\" y=\"-1996.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">_COUNT_field_n9r3 = sum(field_8d51) ∈ option(float[0 140])</text>\n",
              "<text text-anchor=\"start\" x=\"492.5\" y=\"-1985.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">GROUP BY (field_zyse)</text>\n",
              "</g>\n",
              "<!-- graph_rteh&#45;&gt;graph_aluv -->\n",
              "<g id=\"edge19\" class=\"edge\">\n",
              "<title>graph_rteh&#45;&gt;graph_aluv</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M563.5,-2068.92C563.5,-2063.09 563.5,-2056.85 563.5,-2050.64\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"567,-2050.28 563.5,-2040.28 560,-2050.28 567,-2050.28\"/>\n",
              "</g>\n",
              "<!-- graph_j9ct -->\n",
              "<g id=\"node6\" class=\"node\">\n",
              "<title>graph_j9ct</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M828.5,-1939C828.5,-1939 298.5,-1939 298.5,-1939 292.5,-1939 286.5,-1933 286.5,-1927 286.5,-1927 286.5,-1890 286.5,-1890 286.5,-1884 292.5,-1878 298.5,-1878 298.5,-1878 828.5,-1878 828.5,-1878 834.5,-1878 840.5,-1884 840.5,-1890 840.5,-1890 840.5,-1927 840.5,-1927 840.5,-1933 834.5,-1939 828.5,-1939\"/>\n",
              "<text text-anchor=\"start\" x=\"472.5\" y=\"-1917.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_ORR7 size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"300.5\" y=\"-1906.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_8d51 = _CLIPPED__ONE_field_n9r3 ∈ option(float[0.000603681610520369 1])</text>\n",
              "<text text-anchor=\"start\" x=\"415\" y=\"-1895.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_zyse = field_d4_o ∈ str{Female, Male}</text>\n",
              "</g>\n",
              "<!-- graph_aluv&#45;&gt;graph_j9ct -->\n",
              "<g id=\"edge18\" class=\"edge\">\n",
              "<title>graph_aluv&#45;&gt;graph_j9ct</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M563.5,-1967.92C563.5,-1961.88 563.5,-1955.56 563.5,-1949.4\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"567,-1949.27 563.5,-1939.27 560,-1949.27 567,-1949.27\"/>\n",
              "</g>\n",
              "<!-- graph_ms3c -->\n",
              "<g id=\"node7\" class=\"node\">\n",
              "<title>graph_ms3c</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M960.5,-1849C960.5,-1849 166.5,-1849 166.5,-1849 160.5,-1849 154.5,-1843 154.5,-1837 154.5,-1837 154.5,-1745 154.5,-1745 154.5,-1739 160.5,-1733 166.5,-1733 166.5,-1733 960.5,-1733 960.5,-1733 966.5,-1733 972.5,-1739 972.5,-1745 972.5,-1745 972.5,-1837 972.5,-1837 972.5,-1843 966.5,-1849 960.5,-1849\"/>\n",
              "<text text-anchor=\"start\" x=\"472.5\" y=\"-1827.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_M3CM size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"435.5\" y=\"-1816.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = _PRIVACY_UNIT_ ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"361\" y=\"-1805.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_WEIGHT_ = _PRIVACY_UNIT_WEIGHT_ ∈ float{0, 1}</text>\n",
              "<text text-anchor=\"start\" x=\"415\" y=\"-1794.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = field_d4_o ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"384.5\" y=\"-1783.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_ONE_field_n9r3 = _ONE_field_n9r3 ∈ option(float{1})</text>\n",
              "<text text-anchor=\"start\" x=\"341\" y=\"-1772.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_SCALE_FACTOR__PRIVACY_UNIT_ = _SCALE_FACTOR__PRIVACY_UNIT_ ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"219.5\" y=\"-1761.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_SCALE_FACTOR__ONE_field_n9r3 = _SCALE_FACTOR__ONE_field_n9r3 ∈ option(float[0.000603681610520369 1])</text>\n",
              "<text text-anchor=\"start\" x=\"168.5\" y=\"-1750.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_CLIPPED__ONE_field_n9r3 = (_ONE_field_n9r3 * _SCALE_FACTOR__ONE_field_n9r3) ∈ option(float[0.000603681610520369 1])</text>\n",
              "</g>\n",
              "<!-- graph_j9ct&#45;&gt;graph_ms3c -->\n",
              "<g id=\"edge17\" class=\"edge\">\n",
              "<title>graph_j9ct&#45;&gt;graph_ms3c</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M563.5,-1877.76C563.5,-1871.97 563.5,-1865.68 563.5,-1859.23\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"567,-1859.02 563.5,-1849.02 560,-1859.02 567,-1859.02\"/>\n",
              "</g>\n",
              "<!-- graph_n6pl -->\n",
              "<g id=\"node8\" class=\"node\">\n",
              "<title>graph_n6pl</title>\n",
              "<path fill=\"#ff616f\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M889.5,-1704C889.5,-1704 237.5,-1704 237.5,-1704 231.5,-1704 225.5,-1698 225.5,-1692 225.5,-1692 225.5,-1600 225.5,-1600 225.5,-1594 231.5,-1588 237.5,-1588 237.5,-1588 889.5,-1588 889.5,-1588 895.5,-1588 901.5,-1594 901.5,-1600 901.5,-1600 901.5,-1692 901.5,-1692 901.5,-1698 895.5,-1704 889.5,-1704\"/>\n",
              "<text text-anchor=\"start\" x=\"469\" y=\"-1682.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">JOIN_0GI9 size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"411.5\" y=\"-1671.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = _LEFT_._PRIVACY_UNIT_ ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"337.5\" y=\"-1660.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_WEIGHT_ = _LEFT_._PRIVACY_UNIT_WEIGHT_ ∈ float{0, 1}</text>\n",
              "<text text-anchor=\"start\" x=\"391.5\" y=\"-1649.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = _LEFT_.field_d4_o ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"361\" y=\"-1638.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_ONE_field_n9r3 = _LEFT_._ONE_field_n9r3 ∈ option(float{1})</text>\n",
              "<text text-anchor=\"start\" x=\"361\" y=\"-1627.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_SCALE_FACTOR__PRIVACY_UNIT_ = _RIGHT_._PRIVACY_UNIT_ ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"239.5\" y=\"-1616.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_SCALE_FACTOR__ONE_field_n9r3 = _RIGHT_._ONE_field_n9r3 ∈ option(float[0.000603681610520369 1])</text>\n",
              "<text text-anchor=\"start\" x=\"371\" y=\"-1605.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">INNER ON (_LEFT_._PRIVACY_UNIT_ = _RIGHT_._PRIVACY_UNIT_)</text>\n",
              "</g>\n",
              "<!-- graph_ms3c&#45;&gt;graph_n6pl -->\n",
              "<g id=\"edge16\" class=\"edge\">\n",
              "<title>graph_ms3c&#45;&gt;graph_n6pl</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M563.5,-1732.66C563.5,-1726.69 563.5,-1720.58 563.5,-1714.5\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"567,-1714.35 563.5,-1704.35 560,-1714.35 567,-1714.35\"/>\n",
              "</g>\n",
              "<!-- graph_0uw9 -->\n",
              "<g id=\"node9\" class=\"node\">\n",
              "<title>graph_0uw9</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M725,-1559C725,-1559 12,-1559 12,-1559 6,-1559 0,-1553 0,-1547 0,-1547 0,-1510 0,-1510 0,-1504 6,-1498 12,-1498 12,-1498 725,-1498 725,-1498 731,-1498 737,-1504 737,-1510 737,-1510 737,-1547 737,-1547 737,-1553 731,-1559 725,-1559\"/>\n",
              "<text text-anchor=\"start\" x=\"277.5\" y=\"-1537.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_FRO8 size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"216.5\" y=\"-1526.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = _PRIVACY_UNIT_ ∈ str UNIQUE</text>\n",
              "<text text-anchor=\"start\" x=\"14\" y=\"-1515.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_ONE_field_n9r3 = (1 / greatest(1, (sqrt(_ONE_field_n9r3) / 1))) ∈ option(float[0.000603681610520369 1])</text>\n",
              "</g>\n",
              "<!-- graph_n6pl&#45;&gt;graph_0uw9 -->\n",
              "<g id=\"edge15\" class=\"edge\">\n",
              "<title>graph_n6pl&#45;&gt;graph_0uw9</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M467.14,-1587.93C453.42,-1579.8 439.67,-1571.65 426.98,-1564.14\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"428.76,-1561.12 418.37,-1559.04 425.19,-1567.15 428.76,-1561.12\"/>\n",
              "</g>\n",
              "<!-- graph_v35s -->\n",
              "<g id=\"node15\" class=\"node\">\n",
              "<title>graph_v35s</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M896.5,-964C896.5,-964 312.5,-964 312.5,-964 306.5,-964 300.5,-958 300.5,-952 300.5,-952 300.5,-893 300.5,-893 300.5,-887 306.5,-881 312.5,-881 312.5,-881 896.5,-881 896.5,-881 902.5,-881 908.5,-887 908.5,-893 908.5,-893 908.5,-952 908.5,-952 908.5,-958 902.5,-964 896.5,-964\"/>\n",
              "<text text-anchor=\"start\" x=\"513.5\" y=\"-942.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_66HX size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"314.5\" y=\"-931.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = coalesce(cast_as_text(_PRIVACY_UNIT_), _PRIVACY_UNIT_DEFAULT_) ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"358\" y=\"-920.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_WEIGHT_ = coalesce(_PRIVACY_UNIT_WEIGHT_, 0) ∈ float{0, 1}</text>\n",
              "<text text-anchor=\"start\" x=\"456\" y=\"-909.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = field_d4_o ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"371.5\" y=\"-898.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_ONE_field_n9r3 = case(is_null(field_n9r3), 0, 1) ∈ option(float{1})</text>\n",
              "</g>\n",
              "<!-- graph_n6pl&#45;&gt;graph_v35s -->\n",
              "<g id=\"edge14\" class=\"edge\">\n",
              "<title>graph_n6pl&#45;&gt;graph_v35s</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M715.18,-1587.97C725.9,-1579.55 735.58,-1569.94 743.5,-1559 776.32,-1513.62 759.5,-1490.01 759.5,-1434 759.5,-1434 759.5,-1434 759.5,-1134.5 759.5,-1068.68 709.91,-1009.81 666.82,-971.09\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"668.97,-968.31 659.15,-964.34 664.34,-973.57 668.97,-968.31\"/>\n",
              "</g>\n",
              "<!-- graph_sfnz -->\n",
              "<g id=\"node10\" class=\"node\">\n",
              "<title>graph_sfnz</title>\n",
              "<path fill=\"#00363a\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M579.5,-1469C579.5,-1469 163.5,-1469 163.5,-1469 157.5,-1469 151.5,-1463 151.5,-1457 151.5,-1457 151.5,-1409 151.5,-1409 151.5,-1403 157.5,-1397 163.5,-1397 163.5,-1397 579.5,-1397 579.5,-1397 585.5,-1397 591.5,-1403 591.5,-1409 591.5,-1409 591.5,-1457 591.5,-1457 591.5,-1463 585.5,-1469 579.5,-1469\"/>\n",
              "<text text-anchor=\"start\" x=\"270.5\" y=\"-1447.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">REDUCE_SMED size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"209.5\" y=\"-1436.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = first(field_grep) ∈ str UNIQUE</text>\n",
              "<text text-anchor=\"start\" x=\"165.5\" y=\"-1425.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">_ONE_field_n9r3 = sum(field_7ra5) ∈ option(float[0 2744000])</text>\n",
              "<text text-anchor=\"start\" x=\"300.5\" y=\"-1414.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">GROUP BY (field_grep)</text>\n",
              "</g>\n",
              "<!-- graph_0uw9&#45;&gt;graph_sfnz -->\n",
              "<g id=\"edge13\" class=\"edge\">\n",
              "<title>graph_0uw9&#45;&gt;graph_sfnz</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M369.45,-1497.92C369.64,-1492.09 369.84,-1485.85 370.04,-1479.64\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"373.55,-1479.39 370.37,-1469.28 366.55,-1479.16 373.55,-1479.39\"/>\n",
              "</g>\n",
              "<!-- graph_z5mx -->\n",
              "<g id=\"node11\" class=\"node\">\n",
              "<title>graph_z5mx</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M581,-1368C581,-1368 172,-1368 172,-1368 166,-1368 160,-1362 160,-1356 160,-1356 160,-1319 160,-1319 160,-1313 166,-1307 172,-1307 172,-1307 581,-1307 581,-1307 587,-1307 593,-1313 593,-1319 593,-1319 593,-1356 593,-1356 593,-1362 587,-1368 581,-1368\"/>\n",
              "<text text-anchor=\"start\" x=\"285.5\" y=\"-1346.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_HFZQ size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"174\" y=\"-1335.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_7ra5 = _NORM__ONE_field_n9r3 ∈ option(float[0 19600])</text>\n",
              "<text text-anchor=\"start\" x=\"262\" y=\"-1324.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_grep = _PRIVACY_UNIT_ ∈ str</text>\n",
              "</g>\n",
              "<!-- graph_sfnz&#45;&gt;graph_z5mx -->\n",
              "<g id=\"edge12\" class=\"edge\">\n",
              "<title>graph_sfnz&#45;&gt;graph_z5mx</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M373.38,-1396.92C373.7,-1390.88 374.04,-1384.56 374.37,-1378.4\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"377.87,-1378.44 374.91,-1368.27 370.88,-1378.07 377.87,-1378.44\"/>\n",
              "</g>\n",
              "<!-- graph_248a -->\n",
              "<g id=\"node12\" class=\"node\">\n",
              "<title>graph_248a</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M724.5,-1278C724.5,-1278 32.5,-1278 32.5,-1278 26.5,-1278 20.5,-1272 20.5,-1266 20.5,-1266 20.5,-1218 20.5,-1218 20.5,-1212 26.5,-1206 32.5,-1206 32.5,-1206 724.5,-1206 724.5,-1206 730.5,-1206 736.5,-1212 736.5,-1218 736.5,-1218 736.5,-1266 736.5,-1266 736.5,-1272 730.5,-1278 724.5,-1278\"/>\n",
              "<text text-anchor=\"start\" x=\"287.5\" y=\"-1256.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_2N4O size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"250.5\" y=\"-1245.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = _PRIVACY_UNIT_ ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"230\" y=\"-1234.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = field_d4_o ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"34.5\" y=\"-1223.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_NORM__ONE_field_n9r3 = abs((_NORM__ONE_field_n9r3 * _NORM__ONE_field_n9r3)) ∈ option(float[0 19600])</text>\n",
              "</g>\n",
              "<!-- graph_z5mx&#45;&gt;graph_248a -->\n",
              "<g id=\"edge11\" class=\"edge\">\n",
              "<title>graph_z5mx&#45;&gt;graph_248a</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M377.13,-1306.92C377.26,-1301.09 377.39,-1294.85 377.52,-1288.64\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"381.03,-1288.35 377.75,-1278.28 374.03,-1288.2 381.03,-1288.35\"/>\n",
              "</g>\n",
              "<!-- graph_k4sy -->\n",
              "<g id=\"node13\" class=\"node\">\n",
              "<title>graph_k4sy</title>\n",
              "<path fill=\"#00363a\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M656.5,-1177C656.5,-1177 240.5,-1177 240.5,-1177 234.5,-1177 228.5,-1171 228.5,-1165 228.5,-1165 228.5,-1106 228.5,-1106 228.5,-1100 234.5,-1094 240.5,-1094 240.5,-1094 656.5,-1094 656.5,-1094 662.5,-1094 668.5,-1100 668.5,-1106 668.5,-1106 668.5,-1165 668.5,-1165 668.5,-1171 662.5,-1177 656.5,-1177\"/>\n",
              "<text text-anchor=\"start\" x=\"347.5\" y=\"-1155.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">REDUCE_3SQD size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"310\" y=\"-1144.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = first(field_grep) ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"276.5\" y=\"-1133.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">field_d4_o = first(field_zyse) ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"242.5\" y=\"-1122.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">_NORM__ONE_field_n9r3 = sum(field_1iro) ∈ option(int[0 140])</text>\n",
              "<text text-anchor=\"start\" x=\"337\" y=\"-1111.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">GROUP BY (field_grep, field_zyse)</text>\n",
              "</g>\n",
              "<!-- graph_248a&#45;&gt;graph_k4sy -->\n",
              "<g id=\"edge10\" class=\"edge\">\n",
              "<title>graph_248a&#45;&gt;graph_k4sy</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M402,-1205.91C406.36,-1199.41 410.98,-1192.51 415.56,-1185.67\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"418.65,-1187.35 421.31,-1177.09 412.84,-1183.45 418.65,-1187.35\"/>\n",
              "</g>\n",
              "<!-- graph_1cob -->\n",
              "<g id=\"node14\" class=\"node\">\n",
              "<title>graph_1cob</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M669.5,-1065C669.5,-1065 341.5,-1065 341.5,-1065 335.5,-1065 329.5,-1059 329.5,-1053 329.5,-1053 329.5,-1005 329.5,-1005 329.5,-999 335.5,-993 341.5,-993 341.5,-993 669.5,-993 669.5,-993 675.5,-993 681.5,-999 681.5,-1005 681.5,-1005 681.5,-1053 681.5,-1053 681.5,-1059 675.5,-1065 669.5,-1065\"/>\n",
              "<text text-anchor=\"start\" x=\"414.5\" y=\"-1043.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_2PCL size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"343.5\" y=\"-1032.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_1iro = _ONE_field_n9r3 ∈ option(float{1})</text>\n",
              "<text text-anchor=\"start\" x=\"391\" y=\"-1021.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_grep = _PRIVACY_UNIT_ ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"357\" y=\"-1010.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_zyse = field_d4_o ∈ str{Female, Male}</text>\n",
              "</g>\n",
              "<!-- graph_k4sy&#45;&gt;graph_1cob -->\n",
              "<g id=\"edge9\" class=\"edge\">\n",
              "<title>graph_k4sy&#45;&gt;graph_1cob</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M470.7,-1093.8C474.15,-1087.48 477.72,-1080.93 481.21,-1074.54\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"484.51,-1075.78 486.23,-1065.33 478.37,-1072.43 484.51,-1075.78\"/>\n",
              "</g>\n",
              "<!-- graph_1cob&#45;&gt;graph_v35s -->\n",
              "<g id=\"edge8\" class=\"edge\">\n",
              "<title>graph_1cob&#45;&gt;graph_v35s</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M538.74,-992.91C545.18,-986.12 552.02,-978.89 558.78,-971.76\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"561.71,-973.76 566.04,-964.09 556.63,-968.94 561.71,-973.76\"/>\n",
              "</g>\n",
              "<!-- graph_c6wu -->\n",
              "<g id=\"node16\" class=\"node\">\n",
              "<title>graph_c6wu</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M819,-852C819,-852 390,-852 390,-852 384,-852 378,-846 378,-840 378,-840 378,-781 378,-781 378,-775 384,-769 390,-769 390,-769 819,-769 819,-769 825,-769 831,-775 831,-781 831,-781 831,-840 831,-840 831,-846 825,-852 819,-852\"/>\n",
              "<text text-anchor=\"start\" x=\"513.5\" y=\"-830.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_LPGC size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"456\" y=\"-819.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = field_d4_o ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"449.5\" y=\"-808.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = _PRIVACY_UNIT_ ∈ option(str)</text>\n",
              "<text text-anchor=\"start\" x=\"392\" y=\"-797.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_WEIGHT_ = _PRIVACY_UNIT_WEIGHT_ ∈ option(int{1})</text>\n",
              "<text text-anchor=\"start\" x=\"466\" y=\"-786.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_n9r3 = field_n9r3 ∈ option(int{1})</text>\n",
              "</g>\n",
              "<!-- graph_v35s&#45;&gt;graph_c6wu -->\n",
              "<g id=\"edge7\" class=\"edge\">\n",
              "<title>graph_v35s&#45;&gt;graph_c6wu</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M604.5,-880.85C604.5,-874.89 604.5,-868.69 604.5,-862.56\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"608,-862.35 604.5,-852.35 601,-862.35 608,-862.35\"/>\n",
              "</g>\n",
              "<!-- graph_nr52 -->\n",
              "<g id=\"node17\" class=\"node\">\n",
              "<title>graph_nr52</title>\n",
              "<path fill=\"#ff616f\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M846,-740C846,-740 363,-740 363,-740 357,-740 351,-734 351,-728 351,-728 351,-647 351,-647 351,-641 357,-635 363,-635 363,-635 846,-635 846,-635 852,-635 858,-641 858,-647 858,-647 858,-728 858,-728 858,-734 852,-740 846,-740\"/>\n",
              "<text text-anchor=\"start\" x=\"510\" y=\"-718.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">JOIN_FD1M size ∈ int[0 140]</text>\n",
              "<text text-anchor=\"start\" x=\"432.5\" y=\"-707.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = _LEFT_.field_d4_o ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"422.5\" y=\"-696.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = _RIGHT_._PRIVACY_UNIT_ ∈ option(str)</text>\n",
              "<text text-anchor=\"start\" x=\"365\" y=\"-685.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_WEIGHT_ = _RIGHT_._PRIVACY_UNIT_WEIGHT_ ∈ option(int{1})</text>\n",
              "<text text-anchor=\"start\" x=\"439\" y=\"-674.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_n9r3 = _RIGHT_.field_n9r3 ∈ option(int{1})</text>\n",
              "<text text-anchor=\"start\" x=\"402\" y=\"-663.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">left__kq_o = _RIGHT_.field_d4_o ∈ option(str{Female, Male})</text>\n",
              "<text text-anchor=\"start\" x=\"442\" y=\"-652.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">LEFT ON (_LEFT_.field_d4_o = _RIGHT_.field_d4_o)</text>\n",
              "</g>\n",
              "<!-- graph_c6wu&#45;&gt;graph_nr52 -->\n",
              "<g id=\"edge6\" class=\"edge\">\n",
              "<title>graph_c6wu&#45;&gt;graph_nr52</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M604.5,-768.87C604.5,-762.98 604.5,-756.8 604.5,-750.6\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"608,-750.19 604.5,-740.19 601,-750.19 608,-750.19\"/>\n",
              "</g>\n",
              "<!-- graph_s4t9 -->\n",
              "<g id=\"node18\" class=\"node\">\n",
              "<title>graph_s4t9</title>\n",
              "<path fill=\"#006064\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M535,-584C535,-584 362,-584 362,-584 356,-584 350,-578 350,-572 350,-572 350,-546 350,-546 350,-540 356,-534 362,-534 362,-534 535,-534 535,-534 541,-534 547,-540 547,-546 547,-546 547,-572 547,-572 547,-578 541,-584 535,-584\"/>\n",
              "<text text-anchor=\"start\" x=\"364\" y=\"-562.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">FIELD_D4_O size ∈ int{2}</text>\n",
              "<text text-anchor=\"start\" x=\"401\" y=\"-551.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">[Female, Male]</text>\n",
              "</g>\n",
              "<!-- graph_nr52&#45;&gt;graph_s4t9 -->\n",
              "<g id=\"edge4\" class=\"edge\">\n",
              "<title>graph_nr52&#45;&gt;graph_s4t9</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M540.6,-634.68C522.26,-619.81 502.84,-604.06 486.58,-590.88\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"488.37,-587.82 478.39,-584.24 483.96,-593.26 488.37,-587.82\"/>\n",
              "</g>\n",
              "<!-- graph_v4pl -->\n",
              "<g id=\"node19\" class=\"node\">\n",
              "<title>graph_v4pl</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M948,-606C948,-606 573,-606 573,-606 567,-606 561,-600 561,-594 561,-594 561,-524 561,-524 561,-518 567,-512 573,-512 573,-512 948,-512 948,-512 954,-512 960,-518 960,-524 960,-524 960,-594 960,-594 960,-600 954,-606 948,-606\"/>\n",
              "<text text-anchor=\"start\" x=\"673\" y=\"-584.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_W7KV size ∈ int[0 70]</text>\n",
              "<text text-anchor=\"start\" x=\"632.5\" y=\"-573.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = _PRIVACY_UNIT_ ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"575\" y=\"-562.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_WEIGHT_ = _PRIVACY_UNIT_WEIGHT_ ∈ int{1}</text>\n",
              "<text text-anchor=\"start\" x=\"679.5\" y=\"-551.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_n9r3 = 1 ∈ int{1}</text>\n",
              "<text text-anchor=\"start\" x=\"625.5\" y=\"-540.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">field_d4_o = gender ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"706\" y=\"-529.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">WHERE (age = 10)</text>\n",
              "</g>\n",
              "<!-- graph_nr52&#45;&gt;graph_v4pl -->\n",
              "<g id=\"edge5\" class=\"edge\">\n",
              "<title>graph_nr52&#45;&gt;graph_v4pl</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M668.4,-634.68C677.38,-627.4 686.62,-619.91 695.62,-612.61\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"697.89,-615.28 703.45,-606.26 693.48,-609.84 697.89,-615.28\"/>\n",
              "</g>\n",
              "<!-- graph_e7tl -->\n",
              "<g id=\"node20\" class=\"node\">\n",
              "<title>graph_e7tl</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M968.5,-483C968.5,-483 552.5,-483 552.5,-483 546.5,-483 540.5,-477 540.5,-471 540.5,-471 540.5,-335 540.5,-335 540.5,-329 546.5,-323 552.5,-323 552.5,-323 968.5,-323 968.5,-323 974.5,-323 980.5,-329 980.5,-335 980.5,-335 980.5,-471 980.5,-471 980.5,-477 974.5,-483 968.5,-483\"/>\n",
              "<text text-anchor=\"start\" x=\"673\" y=\"-461.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_LG9F size ∈ int[0 70]</text>\n",
              "<text text-anchor=\"start\" x=\"554.5\" y=\"-450.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ = md5(cast_as_text(_PRIVACY_UNIT_ROW_)) ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"642.5\" y=\"-439.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_WEIGHT_ = 1 ∈ int{1}</text>\n",
              "<text text-anchor=\"start\" x=\"581.5\" y=\"-428.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ROW_ = _PRIVACY_UNIT_ROW_ ∈ float[0 1]</text>\n",
              "<text text-anchor=\"start\" x=\"693\" y=\"-417.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">id = id ∈ int[1 70]</text>\n",
              "<text text-anchor=\"start\" x=\"659.5\" y=\"-406.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">first_name = first_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"666\" y=\"-395.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">last_name = last_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"683\" y=\"-384.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">age = age ∈ int[26 55]</text>\n",
              "<text text-anchor=\"start\" x=\"639\" y=\"-373.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">gender = gender ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"659.5\" y=\"-362.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">occupation = occupation ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"700\" y=\"-351.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">city = city ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"693\" y=\"-340.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">state = state ∈ str</text>\n",
              "</g>\n",
              "<!-- graph_v4pl&#45;&gt;graph_e7tl -->\n",
              "<g id=\"edge3\" class=\"edge\">\n",
              "<title>graph_v4pl&#45;&gt;graph_e7tl</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M760.5,-511.79C760.5,-505.86 760.5,-499.64 760.5,-493.31\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"764,-493.28 760.5,-483.28 757,-493.28 764,-493.28\"/>\n",
              "</g>\n",
              "<!-- graph_zcpn -->\n",
              "<g id=\"node21\" class=\"node\">\n",
              "<title>graph_zcpn</title>\n",
              "<path fill=\"#428e92\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M907.5,-294C907.5,-294 613.5,-294 613.5,-294 607.5,-294 601.5,-288 601.5,-282 601.5,-282 601.5,-168 601.5,-168 601.5,-162 607.5,-156 613.5,-156 613.5,-156 907.5,-156 907.5,-156 913.5,-156 919.5,-162 919.5,-168 919.5,-168 919.5,-282 919.5,-282 919.5,-288 913.5,-294 907.5,-294\"/>\n",
              "<text text-anchor=\"start\" x=\"673\" y=\"-272.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">MAP_XT3G size ∈ int[0 70]</text>\n",
              "<text text-anchor=\"start\" x=\"615.5\" y=\"-261.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">_PRIVACY_UNIT_ROW_ = random() ∈ float[0 1]</text>\n",
              "<text text-anchor=\"start\" x=\"693\" y=\"-250.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">id = id ∈ int[1 70]</text>\n",
              "<text text-anchor=\"start\" x=\"659.5\" y=\"-239.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">first_name = first_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"666\" y=\"-228.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">last_name = last_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"683\" y=\"-217.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">age = age ∈ int[26 55]</text>\n",
              "<text text-anchor=\"start\" x=\"639\" y=\"-206.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">gender = gender ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"659.5\" y=\"-195.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">occupation = occupation ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"700\" y=\"-184.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">city = city ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"693\" y=\"-173.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#000000\" fill-opacity=\"0.733333\">state = state ∈ str</text>\n",
              "</g>\n",
              "<!-- graph_e7tl&#45;&gt;graph_zcpn -->\n",
              "<g id=\"edge2\" class=\"edge\">\n",
              "<title>graph_e7tl&#45;&gt;graph_zcpn</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M760.5,-322.75C760.5,-316.62 760.5,-310.42 760.5,-304.29\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"764,-304.05 760.5,-294.05 757,-304.05 764,-304.05\"/>\n",
              "</g>\n",
              "<!-- graph_px87 -->\n",
              "<g id=\"node22\" class=\"node\">\n",
              "<title>graph_px87</title>\n",
              "<path fill=\"#ff1744\" stroke=\"#000000\" stroke-opacity=\"0.333333\" d=\"M904,-127C904,-127 617,-127 617,-127 611,-127 605,-121 605,-115 605,-115 605,-12 605,-12 605,-6 611,0 617,0 617,0 904,0 904,0 910,0 916,-6 916,-12 916,-12 916,-115 916,-115 916,-121 910,-127 904,-127\"/>\n",
              "<text text-anchor=\"start\" x=\"619\" y=\"-105.2\" font-family=\"Red Hat Display,sans-serif\" font-weight=\"bold\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">CENSUS_SCHEMA_CENSUS_TABLE size ∈ int{70}</text>\n",
              "<text text-anchor=\"start\" x=\"693\" y=\"-94.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">id = id ∈ int[1 70]</text>\n",
              "<text text-anchor=\"start\" x=\"659.5\" y=\"-83.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">first_name = first_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"666\" y=\"-72.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">last_name = last_name ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"683\" y=\"-61.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">age = age ∈ int[26 55]</text>\n",
              "<text text-anchor=\"start\" x=\"639\" y=\"-50.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">gender = gender ∈ str{Female, Male}</text>\n",
              "<text text-anchor=\"start\" x=\"659.5\" y=\"-39.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">occupation = occupation ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"700\" y=\"-28.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">city = city ∈ str</text>\n",
              "<text text-anchor=\"start\" x=\"693\" y=\"-17.2\" font-family=\"Red Hat Display,sans-serif\" font-size=\"11.00\" fill=\"#ffffff\" fill-opacity=\"0.733333\">state = state ∈ str</text>\n",
              "</g>\n",
              "<!-- graph_zcpn&#45;&gt;graph_px87 -->\n",
              "<g id=\"edge1\" class=\"edge\">\n",
              "<title>graph_zcpn&#45;&gt;graph_px87</title>\n",
              "<path fill=\"none\" stroke=\"#2b303a\" d=\"M760.5,-155.89C760.5,-149.77 760.5,-143.54 760.5,-137.37\"/>\n",
              "<polygon fill=\"#2b303a\" stroke=\"#2b303a\" points=\"764,-137.07 760.5,-127.07 757,-137.07 764,-137.07\"/>\n",
              "</g>\n",
              "</g>\n",
              "</svg>\n"
            ],
            "text/plain": [
              "<graphviz.sources.Source at 0x7be1e1643b50>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "display(graphviz.Source(dp_relation.relation().dot()))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wskO1NjaQR7V"
      },
      "source": [
        "In this example, the only invocked mechanism is a gaussain mechanism for adding noise to the count."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sV2b9HpOQR7V",
        "outputId": "9aead7c1-e28b-4485-86a7-2ff8bd3bf874"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "{'module_name': 'dp_accounting.dp_event', 'class_name': 'GaussianDpEvent', 'noise_multiplier': 3.776479532659047, '_fields': ['module_name', 'class_name', 'noise_multiplier']}\n"
          ]
        }
      ],
      "source": [
        "print(dp_relation.dp_event().to_dict())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fU4CPTtnQR7V"
      },
      "source": [
        "Any `Relation` can be transformed into an SQL query:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "hbQCKX5HQR7V",
        "outputId": "b7107ded-52b2-416d-83fb-41c0b5ae5aec"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "\"WITH field_d4_o (field_d4_o) AS (SELECT * FROM (VALUES ('Female'), ('Male')) AS field_d4_o (field_d4_o)), map_xt3g (_PRIVACY_UNIT_ROW_, id, first_name, last_name, age, gender, occupation, city, state) AS (SELECT RANDOM() AS _PRIVACY_UNIT_ROW_, id AS id, first_name AS first_name, last_name AS last_name, age AS age, gender AS gender, occupation AS occupation, city AS city, state AS state FROM census_schema.census_table), map_lg9f (_PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_, _PRIVACY_UNIT_ROW_, id, first_name, last_name, age, gender, occupation, city, state) AS (SELECT MD5(CAST(_PRIVACY_UNIT_ROW_ AS TEXT)) AS _PRIVACY_UNIT_, 1 AS _PRIVACY_UNIT_WEIGHT_, _PRIVACY_UNIT_ROW_ AS _PRIVACY_UNIT_ROW_, id AS id, first_name AS first_name, last_name AS last_name, age AS age, gender AS gender, occupation AS occupation, city AS city, state AS state FROM map_xt3g), map_w7kv (_PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_, field_n9r3, field_d4_o) AS (SELECT _PRIVACY_UNIT_ AS _PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_ AS _PRIVACY_UNIT_WEIGHT_, 1 AS field_n9r3, gender AS field_d4_o FROM map_lg9f WHERE (age) = (10)), join_fd1m (field_d4_o, _PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_, field_n9r3, left__kq_o) AS (SELECT * FROM field_d4_o AS _LEFT_ LEFT JOIN map_w7kv AS _RIGHT_ ON (_LEFT_.field_d4_o) = (_RIGHT_.field_d4_o)), map_lpgc (field_d4_o, _PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_, field_n9r3) AS (SELECT field_d4_o AS field_d4_o, _PRIVACY_UNIT_ AS _PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_ AS _PRIVACY_UNIT_WEIGHT_, field_n9r3 AS field_n9r3 FROM join_fd1m), map_66hx (_PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_, field_d4_o, _ONE_field_n9r3) AS (SELECT COALESCE(CAST(_PRIVACY_UNIT_ AS TEXT), '_PRIVACY_UNIT_DEFAULT_') AS _PRIVACY_UNIT_, COALESCE(_PRIVACY_UNIT_WEIGHT_, 0) AS _PRIVACY_UNIT_WEIGHT_, field_d4_o AS field_d4_o, CASE WHEN field_n9r3 IS NULL THEN 0 ELSE 1 END AS _ONE_field_n9r3 FROM map_lpgc), map_2pcl (field_1iro, field_grep, field_zyse) AS (SELECT _ONE_field_n9r3 AS field_1iro, _PRIVACY_UNIT_ AS field_grep, field_d4_o AS field_zyse FROM map_66hx), reduce_3sqd (_PRIVACY_UNIT_, field_d4_o, _NORM__ONE_field_n9r3) AS (SELECT field_grep AS _PRIVACY_UNIT_, field_zyse AS field_d4_o, SUM(field_1iro) AS _NORM__ONE_field_n9r3 FROM map_2pcl GROUP BY field_grep, field_zyse), map_2n4o (_PRIVACY_UNIT_, field_d4_o, _NORM__ONE_field_n9r3) AS (SELECT _PRIVACY_UNIT_ AS _PRIVACY_UNIT_, field_d4_o AS field_d4_o, ABS((_NORM__ONE_field_n9r3) * (_NORM__ONE_field_n9r3)) AS _NORM__ONE_field_n9r3 FROM reduce_3sqd), map_hfzq (field_7ra5, field_grep) AS (SELECT _NORM__ONE_field_n9r3 AS field_7ra5, _PRIVACY_UNIT_ AS field_grep FROM map_2n4o), reduce_smed (_PRIVACY_UNIT_, _ONE_field_n9r3) AS (SELECT field_grep AS _PRIVACY_UNIT_, SUM(field_7ra5) AS _ONE_field_n9r3 FROM map_hfzq GROUP BY field_grep), map_fro8 (_PRIVACY_UNIT_, _ONE_field_n9r3) AS (SELECT _PRIVACY_UNIT_ AS _PRIVACY_UNIT_, (1) / (GREATEST(1, (SQRT(_ONE_field_n9r3)) / (1))) AS _ONE_field_n9r3 FROM reduce_smed), join_0gi9 (_PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_, field_d4_o, _ONE_field_n9r3, _SCALE_FACTOR__PRIVACY_UNIT_, _SCALE_FACTOR__ONE_field_n9r3) AS (SELECT * FROM map_66hx AS _LEFT_ JOIN map_fro8 AS _RIGHT_ ON (_LEFT_._PRIVACY_UNIT_) = (_RIGHT_._PRIVACY_UNIT_)), map_m3cm (_PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_, field_d4_o, _ONE_field_n9r3, _SCALE_FACTOR__PRIVACY_UNIT_, _SCALE_FACTOR__ONE_field_n9r3, _CLIPPED__ONE_field_n9r3) AS (SELECT _PRIVACY_UNIT_ AS _PRIVACY_UNIT_, _PRIVACY_UNIT_WEIGHT_ AS _PRIVACY_UNIT_WEIGHT_, field_d4_o AS field_d4_o, _ONE_field_n9r3 AS _ONE_field_n9r3, _SCALE_FACTOR__PRIVACY_UNIT_ AS _SCALE_FACTOR__PRIVACY_UNIT_, _SCALE_FACTOR__ONE_field_n9r3 AS _SCALE_FACTOR__ONE_field_n9r3, (_ONE_field_n9r3) * (_SCALE_FACTOR__ONE_field_n9r3) AS _CLIPPED__ONE_field_n9r3 FROM join_0gi9), map_orr7 (field_8d51, field_zyse) AS (SELECT _CLIPPED__ONE_field_n9r3 AS field_8d51, field_d4_o AS field_zyse FROM map_m3cm), reduce_tdcw (field_d4_o, _COUNT_field_n9r3) AS (SELECT field_zyse AS field_d4_o, SUM(field_8d51) AS _COUNT_field_n9r3 FROM map_orr7 GROUP BY field_zyse), map_m6is (field_d4_o, _COUNT_field_n9r3) AS (SELECT field_d4_o AS field_d4_o, LEAST(140, GREATEST(0, (COALESCE(_COUNT_field_n9r3, 0)) + ((3.776479532659047) * ((SQRT((-2) * (LN(RANDOM())))) * (COS((6.283185307179586) * (RANDOM()))))))) AS _COUNT_field_n9r3 FROM reduce_tdcw), map_itya (field_i4xy, field_d4_o) AS (SELECT CAST(_COUNT_field_n9r3 AS INTEGER) AS field_i4xy, field_d4_o AS field_d4_o FROM map_m6is), map_09t5 (field_d4_o, field_i4xy) AS (SELECT field_d4_o AS field_d4_o, field_i4xy AS field_i4xy FROM map_itya), map_vdvc (gender, count_all) AS (SELECT field_d4_o AS gender, field_i4xy AS count_all FROM map_09t5) SELECT * FROM map_vdvc\""
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dp_sql_query = dp_relation.relation().to_query()\n",
        "dp_sql_query"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gbS3OMG7QR7V"
      },
      "source": [
        "The DP query can then be sent to the database:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "NzEc4hjmQR7V",
        "outputId": "711723cd-6def-40d4-cde6-b3384ab97c63"
      },
      "outputs": [
        {
          "data": {
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              "      <th>gender</th>\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-db72bc4e-9a49-406a-b92f-9627f3970ba3');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
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              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "</div>\n",
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              "  </div>\n"
            ],
            "text/plain": [
              "   gender  count_all\n",
              "0  Female          1\n",
              "1    Male          3"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dp_results = pd.read_sql(dp_sql_query, engine)\n",
        "dp_results"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2ZykqVBrQR7V"
      },
      "source": [
        "This can be compared to the result of the original query:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
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        },
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        "outputId": "6d0b465d-ae50-4691-a1b6-b37fcb70fbd2"
      },
      "outputs": [
        {
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              "      <th></th>\n",
              "      <th>gender</th>\n",
              "      <th>count_all</th>\n",
              "    </tr>\n",
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              "\n",
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              "      async function convertToInteractive(key) {\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
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              "  </div>\n"
            ],
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [gender, count_all]\n",
              "Index: []"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "exact_results = pd.read_sql(query, engine)\n",
        "exact_results"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9WhEScfWQR7V"
      },
      "source": [
        "## Queries with `GROUP BY` clause\n",
        "\n",
        "f the grouping keys are not public, we utilize the $\\tau$-thresholding mechanism, which filters out keys with noisy counts below a specific threshold determined by the privacy parameters."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6JGVFIZ6QR7V",
        "outputId": "7bdfcb5d-9a07-426d-9691-38e3ffa839c0"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "{'module_name': 'dp_accounting.dp_event', 'class_name': 'ComposedDpEvent', 'events': [{'module_name': 'dp_accounting.dp_event', 'class_name': 'EpsilonDeltaDpEvent', 'epsilon': 2.5, 'delta': 0.00025, '_fields': ['module_name', 'class_name', 'epsilon', 'delta']}, {'module_name': 'dp_accounting.dp_event', 'class_name': 'GaussianDpEvent', 'noise_multiplier': 5.2624632808831, '_fields': ['module_name', 'class_name', 'noise_multiplier']}, {'module_name': 'dp_accounting.dp_event', 'class_name': 'GaussianDpEvent', 'noise_multiplier': 5.2624632808831, '_fields': ['module_name', 'class_name', 'noise_multiplier']}, {'module_name': 'dp_accounting.dp_event', 'class_name': 'GaussianDpEvent', 'noise_multiplier': 289.4354804485705, '_fields': ['module_name', 'class_name', 'noise_multiplier']}], '_fields': ['module_name', 'class_name', 'events']}\n"
          ]
        }
      ],
      "source": [
        "query = \"\"\"\n",
        "    SELECT occupation as occupation, COUNT(*) AS count_occ, AVG(age) AS avg_age\n",
        "    FROM census_schema.census_table\n",
        "    GROUP BY occupation\n",
        "\"\"\"\n",
        "relation = ds.relation(query)\n",
        "privacy_unit = [\n",
        "    (\"census_table\", [], \"_PRIVACY_UNIT_ROW_\"),\n",
        "]\n",
        "synthetic_data = None\n",
        "\n",
        "dp_relation = relation.rewrite_with_differential_privacy(\n",
        "    dataset=ds,\n",
        "    synthetic_data=synthetic_data,\n",
        "    privacy_unit=privacy_unit,\n",
        "    epsilon_delta={\"epsilon\": 5.0, \"delta\": 5e-4}\n",
        ")\n",
        "print(dp_relation.dp_event().to_dict())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mJe8uSbYQR7W"
      },
      "source": [
        "In that case, 3 gaussian mechanisms have been used for adding noise to the aggregations (1 for the count, 2 for the average) and a $(\\varepsilon, \\delta)$ mechanism for the $\\tau$-thresholding.\n",
        "\n",
        "If you execute the next cell multiple times, you will notice that the grouping keys may vary due to the randomness introduced by the $\\tau$-thresholding mechanism."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "HfuMVURhQR7W",
        "outputId": "955c8a1e-e372-4c29-9194-106027ec74e0"
      },
      "outputs": [
        {
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
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              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
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              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-eb81da9c-9871-40ce-8f68-fde59d74f62c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "       occupation  count_occ    avg_age\n",
              "0         Analyst         17  74.085976\n",
              "1        Engineer         21  22.989924\n",
              "2  Data Scientist         19  31.201097"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dp_results = pd.read_sql(dp_relation.relation().to_query(), engine)\n",
        "dp_results"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WxsBKBH0QR7W"
      },
      "source": [
        "We can also include the grouping keys in the query's `WHERE` clause. In this case, the grouping keys are treated as public, and they all appear in the result and the $\\tau$-thresholding mechnaism is not used."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W9nia6LUQR7W",
        "outputId": "8c7890f3-3da0-4420-b4fb-747742e60dfe"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "{'module_name': 'dp_accounting.dp_event', 'class_name': 'ComposedDpEvent', 'events': [{'module_name': 'dp_accounting.dp_event', 'class_name': 'GaussianDpEvent', 'noise_multiplier': 2.5346230440950324, '_fields': ['module_name', 'class_name', 'noise_multiplier']}, {'module_name': 'dp_accounting.dp_event', 'class_name': 'GaussianDpEvent', 'noise_multiplier': 2.5346230440950324, '_fields': ['module_name', 'class_name', 'noise_multiplier']}, {'module_name': 'dp_accounting.dp_event', 'class_name': 'GaussianDpEvent', 'noise_multiplier': 139.40426742522678, '_fields': ['module_name', 'class_name', 'noise_multiplier']}], '_fields': ['module_name', 'class_name', 'events']}\n"
          ]
        }
      ],
      "source": [
        "query = \"\"\"\n",
        "    SELECT occupation as occupation, COUNT(*) AS count_occ, AVG(age) AS avg_age\n",
        "    FROM census_schema.census_table\n",
        "    WHERE occupation in ('Analyst', 'Professor')\n",
        "    GROUP BY occupation\n",
        "\"\"\"\n",
        "relation = ds.relation(query)\n",
        "privacy_unit = [\n",
        "    (\"census_table\", [], \"_PRIVACY_UNIT_ROW_\"),\n",
        "]\n",
        "synthetic_data = None\n",
        "\n",
        "dp_relation = relation.rewrite_with_differential_privacy(\n",
        "    dataset=ds,\n",
        "    synthetic_data=synthetic_data,\n",
        "    privacy_unit=privacy_unit,\n",
        "    epsilon_delta={\"epsilon\": 5.0, \"delta\": 5e-4}\n",
        ")\n",
        "print(dp_relation.dp_event().to_dict())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "wjBMd8Y3QR7W",
        "outputId": "17d335d1-c646-421b-8ddb-d70a74c10056"
      },
      "outputs": [
        {
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              "\n",
              "  @keyframes spin {\n",
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              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7f7fd8ec-7381-43f1-948d-e170b002e13e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "  occupation  count_occ    avg_age\n",
              "0  Professor          0  38.499150\n",
              "1    Analyst         18  36.381657"
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dp_results = pd.read_sql(dp_relation.relation().to_query(), engine)\n",
        "dp_results"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RsjAEzRSQR7W"
      },
      "source": [
        "## Not DP-compilable queries\n",
        "\n",
        "If the query cannot by DP-compiled by `qrlew` and no synthetic data have been provided, then `qrlew` returns an error."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qxv3WYxsQR7W",
        "outputId": "93f2f2df-a7a5-448c-c5b7-86ed547e6176"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The error is: UnreachableProperty: differential_privacy is unreachable\n",
            "\n"
          ]
        }
      ],
      "source": [
        "query = \"\"\"\n",
        "    SELECT occupation as occupation, MAX(age) AS max_age\n",
        "    FROM census_schema.census_table\n",
        "    GROUP BY occupation\n",
        "\"\"\"\n",
        "relation = ds.relation(query)\n",
        "privacy_unit = [\n",
        "    (\"census_table\", [], \"_PRIVACY_UNIT_ROW_\"),\n",
        "]\n",
        "synthetic_data = None\n",
        "try:\n",
        "    dp_relation = relation.rewrite_with_differential_privacy(\n",
        "        dataset=ds,\n",
        "        synthetic_data=synthetic_data,\n",
        "        privacy_unit=privacy_unit,\n",
        "        epsilon_delta={\"epsilon\": 5.0, \"delta\": 5e-4}\n",
        "    ).relation()\n",
        "    dp_results = pd.read_sql(dp_relation.to_query(), engine)\n",
        "    dp_results\n",
        "except RuntimeError as e:\n",
        "    print(f\"The error is: {e}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QgALx6T4QR7j"
      },
      "source": [
        "If the user provides the list of the original and synthetic tables, then the query is sent to the synthetic tables and no budget has been spent."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HuHyYsvAQR7j",
        "outputId": "880087de-6aa9-43b5-bebf-90f91f427b38"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "{'module_name': 'dp_accounting.dp_event', 'class_name': 'NoOpDpEvent', '_fields': ['module_name', 'class_name']}\n"
          ]
        }
      ],
      "source": [
        "query = \"\"\"\n",
        "    SELECT occupation as occupation, MAX(age) AS max_age\n",
        "    FROM census_schema.census_table\n",
        "    GROUP BY occupation\n",
        "\"\"\"\n",
        "relation = ds.relation(query)\n",
        "privacy_unit = [(\"census_table\", [], \"_PRIVACY_UNIT_ROW_\")]\n",
        "synthetic_data = [\n",
        "    ([\"census_schema\", \"census_table\"], [\"census_schema\", \"synthetic_census_table\"])\n",
        "]\n",
        "\n",
        "dp_relation = relation.rewrite_with_differential_privacy(\n",
        "    dataset=ds,\n",
        "    synthetic_data=synthetic_data,\n",
        "    privacy_unit=privacy_unit,\n",
        "    epsilon_delta={\"epsilon\": 5.0, \"delta\": 5e-4}\n",
        ")\n",
        "print(dp_relation.dp_event().to_dict())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "RRcXF2qrQR7j"
      },
      "outputs": [],
      "source": []
    }
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