10_sql/JOIN_adv.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a79a05df",
   "metadata": {},
   "source": [
    "# SQL other joins and subqueries"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb5f3ef2",
   "metadata": {},
   "source": [
    "## Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "867c5641",
   "metadata": {},
   "source": [
    "For this section you need `chinook.db` database file and working `%sql` magic.  \n",
    "If you don't have it, please go back to the [previous section](../09_sql/connect_to_database.ipynb) and follow the instructions.  \n",
    "The following code should not produce any errors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17a6f235",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext sql\n",
    "%sql sqlite:///chinook.db"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "022159e3",
   "metadata": {},
   "source": [
    "## `UNION` - merge two tables (right below left)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d80389f",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e06297bb",
   "metadata": {},
   "source": [
    "Both `UNION` and `UNION ALL` combine rows from two result sets into a single result set.    \n",
    "The `UNION` operator removes eliminate duplicate rows, whereas the `UNION ALL` operator does not."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12b3508c",
   "metadata": {},
   "source": [
    "The following are rules to union data:\n",
    "- The number of columns in both queries must be the same.\n",
    "- The corresponding columns must have compatible data types.\n",
    "- The column names of the first query determine the column names of the combined result set.\n",
    "- The `GROUP BY` and `HAVING` clauses are applied to each individual query, not the final result set.\n",
    "- The `ORDER BY` clause is applied to the combined result set, not within the individual result set."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1186660f",
   "metadata": {},
   "source": [
    "*Note:* `JOIN`s combine columns from multiple tables, while `UNION`s combine rows from multiple similar tables."
   ]
  },
  {
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"
    }
   },
   "cell_type": "markdown",
   "id": "23a677f1",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "2c2ee59a",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dd917e3",
   "metadata": {},
   "source": [
    "### Example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec8d311d",
   "metadata": {},
   "source": [
    "Let's combine persons from `employees` and `custormes` tables into one table:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e8c67e77",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "  SELECT FirstName, LastName, 'Employee' AS \"Group\" FROM employees\n",
    "UNION\n",
    "  SELECT FirstName, LastName, 'Customer' FROM customers\n",
    "ORDER BY LastName, FirstName\n",
    "LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75fd6d20",
   "metadata": {},
   "source": [
    "## EXCEPT - rows from the left but not the right table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcfa8d20",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d57b0acd",
   "metadata": {},
   "source": [
    "`EXCEPT` returns distinct rows from the left query that are not in the right query:\n",
    "- The number of columns in the select lists of both queries must be the same.\n",
    "- The order of the columns and their types must be comparable."
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "a6cbda01",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d71558c5",
   "metadata": {},
   "source": [
    "### Example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af7def22",
   "metadata": {},
   "source": [
    "Let's build a table with the `TrackId` column of all `tracks` which have never been sold (so they are not present among `invoice_items`).  \n",
    "This problem can be solved differently but for this demonstration we want to use the `EXCEPT` operator."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c0d1631",
   "metadata": {},
   "source": [
    "Let's build a table with all `TrackId`s from `tracks`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "99a94046",
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql SELECT TrackId FROM tracks LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c449cd63",
   "metadata": {},
   "source": [
    "And from the above table we will \"subtract\" a table of `TrackId`s from `invoice_tems`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4f58abbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql SELECT DISTINCT TrackId FROM invoice_items LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c053d4c",
   "metadata": {},
   "source": [
    "The table of never sold `TrackId`s can be generated as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fdb211bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "    SELECT TrackId FROM tracks\n",
    "EXCEPT\n",
    "    SELECT DISTINCT TrackId FROM invoice_items\n",
    "  LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "785d8e5a",
   "metadata": {},
   "source": [
    "## INERSECT - identical rows present in both tables"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "667a012a",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4156c20c",
   "metadata": {},
   "source": [
    "`INTERSECT` compares the result sets of two queries and returns distinct rows that are output by both queries.\n",
    "- The number and the order of the columns in both queries must be the same.\n",
    "- The data types must be comparable."
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "2d1cef37",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ceb7b71",
   "metadata": {},
   "source": [
    "###  Example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d93552ad",
   "metadata": {},
   "source": [
    "Let's build a table with the `TrackId` column of all `tracks` which have been sold (so they are present among `invoice_items`).  \n",
    "This problem can be solved differently but for this demonstration we want to use the `INTERSECT` operator."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14804f05",
   "metadata": {},
   "source": [
    "Let's prepare a table of `TrackId`s from `invoice_tems`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b4256a60",
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql SELECT DISTINCT TrackId FROM invoice_items LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87877196",
   "metadata": {},
   "source": [
    "And as the second table let's use all `TrackId`s from `tracks`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1ac02de",
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql SELECT TrackId FROM tracks LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f01f7d6",
   "metadata": {},
   "source": [
    "To find the identical rows present in both tables use:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "416f0a07",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "    SELECT DISTINCT TrackId FROM invoice_items\n",
    "INTERSECT\n",
    "    SELECT TrackId FROM tracks\n",
    "  LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5ae1e27",
   "metadata": {},
   "source": [
    "## Self-joining (joining a table with itself)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac997eae",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb8bda5a",
   "metadata": {},
   "source": [
    "The self-join is a special kind of joins that allow you to join a table to itself.  \n",
    "Because you cannot refer to the same table more than one in a query, you need to use a table alias to assign the table a different name when you use self-join.  \n",
    "The self-join compares values of the same or different columns in the same table. Only one table is involved in the self-join."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b861725c",
   "metadata": {},
   "source": [
    "### Example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "343ae3c9",
   "metadata": {},
   "source": [
    "Each row of the `employee` table describes an emploee but also provides a self-foreign-key to an employee who is the boss.\n",
    "\n",
    "Let's build a table containing in a single row both the employee full name and the name of the employee's manager.\n",
    "\n",
    "We start with all rows of the `employees` table. Note, that `NULL` in `ReportsTo` denotes the CEO."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d9016b6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql SELECT EmployeeId, FirstName, LastName, ReportsTo FROM employees"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "927c20b2",
   "metadata": {},
   "source": [
    "Let's try `INNER JOIN` as follows. Because you use the same `employees` table twice, you need to introduce aliases (here: `e` and `m`) to distinguish the \"left\" table from the \"right\" table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8274f27",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT e.firstname, e.lastname,\n",
    "       m.firstname, m.lastname\n",
    "FROM employees e\n",
    "INNER JOIN employees m ON m.employeeid = e.reportsto"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c4e6d94",
   "metadata": {},
   "source": [
    "The above is suboptimal. Let's concatenate names and use `AS` to rename columns and clearly denote who is the employee and who the manager:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "72659824",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT e.firstname || ' ' || e.lastname AS \"Employee\",\n",
    "       m.firstname || ' ' || m.lastname AS \"Manager\"\n",
    "FROM employees e\n",
    "INNER JOIN employees m ON m.employeeid = e.reportsto"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad54248d",
   "metadata": {},
   "source": [
    "## `CROSS JOIN` - all row-row pairs (not really a join)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ba37131",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51c391e4",
   "metadata": {},
   "source": [
    "`CROSS JOIN` simply takes two tables and constructs all possible pairs of the rows from the left table with the rows of the right table."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c82cedbf",
   "metadata": {},
   "source": [
    "### Example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4effbcd3",
   "metadata": {},
   "source": [
    "Let's assume that there is a need that two `employees` always need to be present and there is a need to produce a table with all possible employee pairs.  \n",
    "Let's start with names of all `employees`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6949a75a",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT FirstName, LastName FROM employees"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b8f4823",
   "metadata": {},
   "source": [
    "Since here we use self-joining `CROSS JOIN` also needs to use table aliases `e1` and `e2`.  \n",
    "We use the concatenation `||` and aliasing with `AS` to produce two simple columns of names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "00194acf",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    e1.FirstName || ' ' || e1.LastName AS Name1, \n",
    "    e2.FirstName || ' ' || e2.LastName AS Name2\n",
    "  FROM employees e1\n",
    "  CROSS JOIN employees e2\n",
    "  LIMIT 10"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e6e1335",
   "metadata": {},
   "source": [
    "Note, that `CROSS JOIN` gives all rows vs. all rows, so persons are paired with themselves.\n",
    "Also, each two persons are paired twice (i.e. X-Y and Y-X). Let's use the following `WHERE` condition to remove identical and repeated pairings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8869e96",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    e1.FirstName || ' ' || e1.LastName AS Name1, \n",
    "    e2.FirstName || ' ' || e2.LastName AS Name2\n",
    "  FROM employees e1\n",
    "  CROSS JOIN employees e2\n",
    "  WHERE Name1 < Name2\n",
    "  LIMIT 10"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47b39d74",
   "metadata": {},
   "source": [
    "## Subquery"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4938c15",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "178c8580",
   "metadata": {},
   "source": [
    "A subquery is a `SELECT` statement nested in another statement. See the following statement."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32d5a827",
   "metadata": {},
   "source": [
    "```sql\n",
    "SELECT column_1, ...\n",
    "FROM table_1\n",
    "WHERE column_1 = (\n",
    "   SELECT column_1 \n",
    "   FROM table_2\n",
    ")\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46b9c3bb",
   "metadata": {},
   "source": [
    "or:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c47c52dd",
   "metadata": {},
   "source": [
    "```sql\n",
    "SELECT column_1, ...\n",
    "FROM table_1\n",
    "WHERE column_1 IN (\n",
    "   SELECT column_1 \n",
    "   FROM table_2\n",
    ")\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "194a62dc",
   "metadata": {},
   "source": [
    "You can use a subquery in the `SELECT`, `FROM`, `WHERE`, and `JOIN` clauses."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53343cb7",
   "metadata": {},
   "source": [
    "### Example (suboptimal, assumes a single value from the subquery)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d2edc46",
   "metadata": {},
   "source": [
    "The following statement returns all the `tracks` which have `TrackIds` corresponding to the `albums` with the title equal to `Let There Be Rock`.\n",
    "\n",
    "The subquery is assumed to return a single `AlbumId` of the album with the title `Let There Be Rock`. For the single returned value, the query uses the equal operator (`=`) to compare `AlbumId` returned by the subquery with the `AlbumId` in the `tracks` table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e0a8fe5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT TrackId, Name, AlbumId\n",
    "  FROM tracks\n",
    "  WHERE AlbumId = (        -- note the equal operator here\n",
    "    SELECT AlbumId\n",
    "    FROM albums\n",
    "    WHERE Title = 'Let There Be Rock'\n",
    "  )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfee241b",
   "metadata": {},
   "source": [
    "### Example (usually better, multiple values can be returned from the subquery)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "fefc017f",
   "metadata": {},
   "source": [
    "If the subquery returns multiple values, you can use the `IN` operator to check for the existence of a single value against a set of values."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b372d458",
   "metadata": {},
   "source": [
    "Let's consider the task of finding the `tracks` whose genre contains the word `Rock`.   \n",
    "This are the (possibly multiple) `genres` to be considered:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0cd866f",
   "metadata": {},
   "outputs": [],
   "source": [
    "%sql SELECT * FROM genres WHERE Name LIKE \"%Rock%\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa4205fc",
   "metadata": {},
   "source": [
    "So, the `tracks` can be found as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0cd5b054",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT * FROM tracks \n",
    "  WHERE GenreId IN (      -- note the IN operator here\n",
    "    SELECT GenreId FROM genres WHERE Name LIKE \"%Rock%\"\n",
    "  )\n",
    "  LIMIT 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd9365fb",
   "metadata": {},
   "source": [
    "## Correlated subquery and `EXISTS` - check whether any row in subquery"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c41ac8a6",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "699a4529",
   "metadata": {},
   "source": [
    "The `EXISTS` operator is a logical operator that checks whether a subquery returns any row.  \n",
    "To negate the `EXISTS` operator, you use `NOT EXISTS`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1993e690",
   "metadata": {},
   "source": [
    "### Example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1710f2ef",
   "metadata": {},
   "source": [
    "Let's consider finding all `artists` which do not have any `albums`.  \n",
    "\n",
    "In other words: select all `artists` whose `ArtistId`s `NOT EXISTS` among `albums`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3907286",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT * FROM artists \n",
    "  WHERE NOT EXISTS (\n",
    "    SELECT * FROM albums WHERE ArtistId = artists.ArtistId\n",
    "  )\n",
    "  LIMIT 10"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3791bc0",
   "metadata": {},
   "source": [
    "*Note:* the columns of the table from the inner subquery are irrelevant, so to optimize you may return just a single column of `1`s whether any matching result is present:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68460501",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql\n",
    "SELECT * FROM artists \n",
    "  WHERE NOT EXISTS (\n",
    "    SELECT 1 FROM albums WHERE ArtistId = artists.ArtistId\n",
    "  )\n",
    "  LIMIT 10"
   ]
  }
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