L1 E1 - Step 5.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# STEP 5: ETL the data from 3NF tables to Facts & Dimension Tables\n",
    "**IMPORTANT:** The following exercise depends on first having successing completed Exercise 1: Step 4. \n",
    "\n",
    "Start by running the code in the cell below to connect to the database. If you are coming back to this exercise, then uncomment and run the first cell to recreate the database. If you recently completed steps 1 through 4, then skip to the second cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " setval \r\n",
      "--------\r\n",
      "    200\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "    605\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "     16\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "    600\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "    109\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "    599\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "   1000\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "   4581\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "      6\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "  32098\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "  16049\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "      2\r\n",
      "(1 row)\r\n",
      "\r\n",
      " setval \r\n",
      "--------\r\n",
      "      2\r\n",
      "(1 row)\r\n",
      "\r\n"
     ]
    }
   ],
   "source": [
    " !PGPASSWORD=student createdb -h 127.0.0.1 -U student pagila\n",
    " !PGPASSWORD=student psql -q -h 127.0.0.1 -U student -d pagila -f Data/pagila-schema.sql\n",
    " !PGPASSWORD=student psql -q -h 127.0.0.1 -U student -d pagila -f Data/pagila-data.sql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "postgresql://student:student@127.0.0.1:5432/pagila\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'Connected: student@pagila'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%load_ext sql\n",
    "\n",
    "DB_ENDPOINT = \"127.0.0.1\"\n",
    "DB = 'pagila'\n",
    "DB_USER = 'student'\n",
    "DB_PASSWORD = 'student'\n",
    "DB_PORT = '5432'\n",
    "\n",
    "# postgresql://username:password@host:port/database\n",
    "conn_string = \"postgresql://{}:{}@{}:{}/{}\" \\\n",
    "                        .format(DB_USER, DB_PASSWORD, DB_ENDPOINT, DB_PORT, DB)\n",
    "\n",
    "print(conn_string)\n",
    "%sql $conn_string"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Introducing SQL to SQL ETL\n",
    "When writing SQL to SQL ETL, you first create a table then use the INSERT and SELECT statements together to populate the table. Here's a simple example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, you create a table called test_table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * postgresql://student:***@127.0.0.1:5432/pagila\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "CREATE TABLE test_table\n",
    "(\n",
    "  date timestamp,\n",
    "  revenue  decimal(5,2)\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then you use the INSERT and SELECT statements to populate the table. In this case, the SELECT statement extracts data from the `payment` table and INSERTs it INTO the `test_table`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * postgresql://student:***@127.0.0.1:5432/pagila\n",
      "16049 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "INSERT INTO test_table (date, revenue)\n",
    "SELECT payment_date AS date,\n",
    "       amount AS revenue\n",
    "FROM payment;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then you can use a SELECT statement to take a look at your new table."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you need to delete the table and start over, use the DROP TABLE command, like below."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great! Now you'll do the same thing below to create the dimension and fact tables for the Star Schema using the data in the 3NF database.\n",
    "\n",
    "## ETL from 3NF to Star Schema"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3NF - Entity Relationship Diagram\n",
    "\n",
    "<img src=\"./pagila-3nf.png\" width=\"50%\"/>\n",
    "\n",
    "### Star Schema - Entity Relationship Diagram\n",
    "\n",
    "<img src=\"pagila-star.png\" width=\"50%\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this section, you'll populate the tables in the Star schema. You'll `extract` data from the normalized database, `transform` it, and `load` it into the new tables. \n",
    "\n",
    "To serve as an example, below is the query that populates the `dimDate` table with data from the `payment` table.\n",
    "* NOTE 1: The EXTRACT function extracts date parts from the payment_date variable.\n",
    "* NOTE 2: If you get an error that says that the `dimDate` table doesn't exist, then go back to Exercise 1: Step 4 and recreate the tables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * postgresql://student:***@127.0.0.1:5432/pagila\n",
      "40 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "INSERT INTO dimDate (date_key, date, year, quarter, month, day, week, is_weekend)\n",
    "SELECT DISTINCT(TO_CHAR(payment_date :: DATE, 'yyyyMMDD')::integer) AS date_key,\n",
    "       date(payment_date)                                           AS date,\n",
    "       EXTRACT(year FROM payment_date)                              AS year,\n",
    "       EXTRACT(quarter FROM payment_date)                           AS quarter,\n",
    "       EXTRACT(month FROM payment_date)                             AS month,\n",
    "       EXTRACT(day FROM payment_date)                               AS day,\n",
    "       EXTRACT(week FROM payment_date)                              AS week,\n",
    "       CASE WHEN EXTRACT(ISODOW FROM payment_date) IN (6, 7) THEN true ELSE false END AS is_weekend\n",
    "FROM payment;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO: Now it's your turn. Populate the `dimCustomer` table with data from the `customer`, `address`, `city`, and `country` tables. Use the starter code as a guide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * postgresql://student:***@127.0.0.1:5432/pagila\n"
     ]
    },
    {
     "ename": "IntegrityError",
     "evalue": "(psycopg2.IntegrityError) duplicate key value violates unique constraint \"dimcustomer_pkey\"\nDETAIL:  Key (customer_key)=(1) already exists.\n [SQL: 'INSERT INTO dimCustomer (customer_key, customer_id, first_name, last_name, email, address, address2, district, city, country, postal_code, phone, active, create_date, start_date, end_date)\\nSELECT c.customer_id AS customer_key,\\n       c.customer_id,\\n       c.first_name,\\n       c.last_name,\\n       c.email,\\n       a.address,\\n       a.address2,\\n       a.district,\\n       ci.city,\\n       co.country,\\n       a.postal_code,\\n       a.phone,\\n       CASE WHEN c.activebool THEN 1 ELSE 0 END AS active,\\n       now() AS create_date,\\n       now() AS start_date,\\n       now() AS end_date\\nFROM customer c\\nJOIN address a ON (c.address_id = a.address_id)\\nJOIN city ci ON (a.city_id = ci.city_id)\\nJOIN country co ON (ci.country_id = co.country_id);']",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIntegrityError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[0;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[1;32m   1181\u001b[0m                         \u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1182\u001b[0;31m                         context)\n\u001b[0m\u001b[1;32m   1183\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mBaseException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/engine/default.py\u001b[0m in \u001b[0;36mdo_execute\u001b[0;34m(self, cursor, statement, parameters, context)\u001b[0m\n\u001b[1;32m    469\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdo_execute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 470\u001b[0;31m         \u001b[0mcursor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    471\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mIntegrityError\u001b[0m: duplicate key value violates unique constraint \"dimcustomer_pkey\"\nDETAIL:  Key (customer_key)=(1) already exists.\n",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mIntegrityError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-10-b81ed046ab46>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_cell_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'sql'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m''\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'INSERT INTO dimCustomer (customer_key, customer_id, first_name, last_name, email, address, address2, district, city, country, postal_code, phone, active, create_date, start_date, end_date)\\nSELECT c.customer_id AS customer_key,\\n       c.customer_id,\\n       c.first_name,\\n       c.last_name,\\n       c.email,\\n       a.address,\\n       a.address2,\\n       a.district,\\n       ci.city,\\n       co.country,\\n       a.postal_code,\\n       a.phone,\\n       CASE WHEN c.activebool THEN 1 ELSE 0 END AS active,\\n       now() AS create_date,\\n       now() AS start_date,\\n       now() AS end_date\\nFROM customer c\\nJOIN address a ON (c.address_id = a.address_id)\\nJOIN city ci ON (a.city_id = ci.city_id)\\nJOIN country co ON (ci.country_id = co.country_id);'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_cell_magic\u001b[0;34m(self, magic_name, line, cell)\u001b[0m\n\u001b[1;32m   2165\u001b[0m             \u001b[0mmagic_arg_s\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvar_expand\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstack_depth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2166\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2167\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmagic_arg_s\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2168\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2169\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<decorator-gen-126>\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, line, cell, local_ns)\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/IPython/core/magic.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(f, *a, **k)\u001b[0m\n\u001b[1;32m    185\u001b[0m     \u001b[0;31m# but it's overkill for just that one bit of state.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    186\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mmagic_deco\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 187\u001b[0;31m         \u001b[0mcall\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    188\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    189\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcallable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<decorator-gen-125>\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, line, cell, local_ns)\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/IPython/core/magic.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(f, *a, **k)\u001b[0m\n\u001b[1;32m    185\u001b[0m     \u001b[0;31m# but it's overkill for just that one bit of state.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    186\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mmagic_deco\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 187\u001b[0;31m         \u001b[0mcall\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    188\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    189\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcallable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sql/magic.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, line, cell, local_ns)\u001b[0m\n\u001b[1;32m     93\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     94\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 95\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msql\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparsed\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'sql'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muser_ns\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     96\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     97\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumn_local_vars\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sql/run.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(conn, sql, config, user_namespace)\u001b[0m\n\u001b[1;32m    338\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    339\u001b[0m                 \u001b[0mtxt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msqlalchemy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msql\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 340\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msession\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtxt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muser_namespace\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    341\u001b[0m             \u001b[0m_commit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    342\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfeedback\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, object, *multiparams, **params)\u001b[0m\n\u001b[1;32m    943\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mObjectNotExecutableError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    944\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 945\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mmeth\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    946\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    947\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_execute_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/sql/elements.py\u001b[0m in \u001b[0;36m_execute_on_connection\u001b[0;34m(self, connection, multiparams, params)\u001b[0m\n\u001b[1;32m    261\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_execute_on_connection\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconnection\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    262\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msupports_execution\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 263\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mconnection\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_execute_clauseelement\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    264\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    265\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mObjectNotExecutableError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36m_execute_clauseelement\u001b[0;34m(self, elem, multiparams, params)\u001b[0m\n\u001b[1;32m   1051\u001b[0m             \u001b[0mcompiled_sql\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1052\u001b[0m             \u001b[0mdistilled_params\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1053\u001b[0;31m             \u001b[0mcompiled_sql\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdistilled_params\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1054\u001b[0m         )\n\u001b[1;32m   1055\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_events\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_events\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[0;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[1;32m   1187\u001b[0m                 \u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1188\u001b[0m                 \u001b[0mcursor\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1189\u001b[0;31m                 context)\n\u001b[0m\u001b[1;32m   1190\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1191\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_events\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_events\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36m_handle_dbapi_exception\u001b[0;34m(self, e, statement, parameters, cursor, context)\u001b[0m\n\u001b[1;32m   1400\u001b[0m                 util.raise_from_cause(\n\u001b[1;32m   1401\u001b[0m                     \u001b[0msqlalchemy_exception\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1402\u001b[0;31m                     \u001b[0mexc_info\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1403\u001b[0m                 )\n\u001b[1;32m   1404\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/util/compat.py\u001b[0m in \u001b[0;36mraise_from_cause\u001b[0;34m(exception, exc_info)\u001b[0m\n\u001b[1;32m    201\u001b[0m     \u001b[0mexc_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexc_value\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexc_tb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    202\u001b[0m     \u001b[0mcause\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mexc_value\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mexc_value\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mexception\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 203\u001b[0;31m     \u001b[0mreraise\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexception\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexception\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mexc_tb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcause\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcause\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    204\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    205\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mpy3k\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/util/compat.py\u001b[0m in \u001b[0;36mreraise\u001b[0;34m(tp, value, tb, cause)\u001b[0m\n\u001b[1;32m    184\u001b[0m             \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__cause__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcause\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    185\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__traceback__\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 186\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    187\u001b[0m         \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    188\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/engine/base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[0;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[1;32m   1180\u001b[0m                         \u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1181\u001b[0m                         \u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1182\u001b[0;31m                         context)\n\u001b[0m\u001b[1;32m   1183\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mBaseException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1184\u001b[0m             self._handle_dbapi_exception(\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sqlalchemy/engine/default.py\u001b[0m in \u001b[0;36mdo_execute\u001b[0;34m(self, cursor, statement, parameters, context)\u001b[0m\n\u001b[1;32m    468\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    469\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdo_execute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 470\u001b[0;31m         \u001b[0mcursor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    471\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    472\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdo_execute_no_params\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mIntegrityError\u001b[0m: (psycopg2.IntegrityError) duplicate key value violates unique constraint \"dimcustomer_pkey\"\nDETAIL:  Key (customer_key)=(1) already exists.\n [SQL: 'INSERT INTO dimCustomer (customer_key, customer_id, first_name, last_name, email, address, address2, district, city, country, postal_code, phone, active, create_date, start_date, end_date)\\nSELECT c.customer_id AS customer_key,\\n       c.customer_id,\\n       c.first_name,\\n       c.last_name,\\n       c.email,\\n       a.address,\\n       a.address2,\\n       a.district,\\n       ci.city,\\n       co.country,\\n       a.postal_code,\\n       a.phone,\\n       CASE WHEN c.activebool THEN 1 ELSE 0 END AS active,\\n       now() AS create_date,\\n       now() AS start_date,\\n       now() AS end_date\\nFROM customer c\\nJOIN address a ON (c.address_id = a.address_id)\\nJOIN city ci ON (a.city_id = ci.city_id)\\nJOIN country co ON (ci.country_id = co.country_id);']"
     ]
    }
   ],
   "source": [
    "%%sql\n",
    "INSERT INTO dimCustomer (customer_key, customer_id, first_name, last_name, email, address, address2, district, city, country, postal_code, phone, active, create_date, start_date, end_date)\n",
    "SELECT c.customer_id AS customer_key,\n",
    "       c.customer_id,\n",
    "       c.first_name,\n",
    "       c.last_name,\n",
    "       c.email,\n",
    "       a.address,\n",
    "       a.address2,\n",
    "       a.district,\n",
    "       ci.city,\n",
    "       co.country,\n",
    "       a.postal_code,\n",
    "       a.phone,\n",
    "       CASE WHEN c.activebool THEN 1 ELSE 0 END AS active,\n",
    "       now() AS create_date,\n",
    "       now() AS start_date,\n",
    "       now() AS end_date\n",
    "FROM customer c\n",
    "JOIN address a ON (c.address_id = a.address_id)\n",
    "JOIN city ci ON (a.city_id = ci.city_id)\n",
    "JOIN country co ON (ci.country_id = co.country_id);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO: Populate the `dimMovie` table with data from the `film` and `language` tables. Use the starter code as a guide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * postgresql://student:***@127.0.0.1:5432/pagila\n",
      "1000 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "INSERT INTO dimMovie (movie_key, film_id, title, description, release_year, language, original_language, rental_duration, length, rating, special_features)\n",
    "SELECT  f.film_id AS movie_key,\n",
    "        f.film_id,\n",
    "        f.title,\n",
    "        f.description,\n",
    "        f.release_year,\n",
    "        l.name,\n",
    "        orig_lang.name AS original_language,\n",
    "        f.rental_duration,\n",
    "        f.length,\n",
    "        f.rating,\n",
    "        f.special_features\n",
    "FROM film f\n",
    "JOIN language l              ON (f.language_id=l.language_id)\n",
    "LEFT JOIN language orig_lang ON (f.original_language_id = orig_lang.language_id);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO: Populate the `dimStore` table with data from the `store`, `staff`, `address`, `city`, and `country` tables. This time, there's no guide. You should write the query from scratch. Use the previous queries as a reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * postgresql://student:***@127.0.0.1:5432/pagila\n",
      "2 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "INSERT INTO dimStore(store_key, store_id, address, address2, district, city, country, postal_code, manager_first_name, manager_last_name, start_date, end_date)\n",
    "SELECT s.store_id as store_key,\n",
    "        s.store_id,\n",
    "        a.address,\n",
    "        a.address2,\n",
    "        a.district,\n",
    "        ci.city,\n",
    "        c.country,\n",
    "        a.postal_code,\n",
    "        staff.first_name,\n",
    "        staff.last_name,\n",
    "        now() AS start_date,\n",
    "        now() AS end_date\n",
    "FROM store s\n",
    "JOIN address a ON (s.address_id = a.address_id)\n",
    "JOIN city ci ON (a.city_id = ci.city_id)\n",
    "JOIN country c ON (ci.country_id = c.country_id)\n",
    "LEFT JOIN staff ON(s.manager_staff_id = staff.staff_id);\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO: Populate the `factSales` table with data from the `payment`, `rental`, and `inventory` tables. This time, there's no guide. You should write the query from scratch. Use the previous queries as a reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * postgresql://student:***@127.0.0.1:5432/pagila\n",
      "16049 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "\n",
    "INSERT INTO factSales (sales_key, date_key, customer_key, movie_key, store_key, sales_amount)\n",
    "SELECT p.payment_id as sales_key,\n",
    "        TO_CHAR(p.payment_date :: DATE, 'yyyyMMDD')::integer AS date_key ,\n",
    "        p.customer_id                                        AS customer_key,\n",
    "        i.film_id                                            AS movie_key,\n",
    "        i.store_id                                           AS store_key,\n",
    "        p.amount                                             AS sales_amount\n",
    "FROM payment p\n",
    "JOIN rental r    ON ( p.rental_id = r.rental_id )\n",
    "JOIN inventory i ON ( r.inventory_id = i.inventory_id );"
   ]
  }
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