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sql-notes's Introduction

SQL Notes

Notes and references on SQL. Taken from various places on the internet.

Table of Contents

Overview

  • SQL syntax is different, but ANSI SQL is standard.
  • Not case sensitive.
  • Semi-optional: Use a semi-colon at the end of each statement.

Schemas

Star Schema

  • Not normalized.
  • Good for simple relationships.

Snowflake Schema

  • Normalized, no redundant information.
  • Fact tables contains business facts, and have foreign keys which refer to candidate keys in the dimension tables.
  • Dimension tables contain descriptive fields that are typically textual fields.

Terminology

Data Definiton Language (DDL)

DDL is used for creating and modifying database objects such as tables, indexes, and users.

Includes statements like:

CREATE, ALTER, DROP, TRUNCATE, COMMENT, RENAME

Data Manipulation Language (DML)

DML is used for adding (inserting), deleting, and modifying (updating) data in a database.

Includes statements like:

SELECT, INSERT, UPDATE, DELETE, MERGE, CALL, EXPLAIN PLAN, LOCK TABLE

Indexes

Indexes are used to find rows with specific column values quickly. Without an index, MySQL must begin with the first row and then read through the entire table to find the relevant rows. Usually implemented with b-trees.

Selecting

A select statement that selects the columns "col1" and "col2" from the table "table_name".

SELECT col1, col2
FROM table_name;

The statement below will only return distinct values from the "col1" columns. Alternatively, one could use a GROUP BY clause (recommend to use DISTINCT).

SELECT DISTINCT col1 
FROM table_name;

If multiple columns are used, the query uses a combination of all values. NULL counts as one distinct value only.

SELECT DISTINCT col1, col2, col3
FROM table_name;

You can also get a count of the distinct values:

SELECT COUNT(DISTINCT col1) 
FROM table_name;

In most databases, you can do:

SELECT TOP [number|percent] column_name(s)
FROM table_name
WHERE condition;

Example:

SELECT col1, col2
FROM table_name
WHERE (col2 + col1) = 4
LIMIT 3;

Filtering Data

The WHERE clause:

  • Is used to filter records.
  • Operators that can be used in WHERE clause: <>, BETWEEN, LIKE.
  • Can also do WHERE NOT .
SELECT col1
FROM table_name
WHERE col1 <> 'some_value';

SELECT col1_date
FROM table_name
WHERE col1_date BETWEEN '2020-12-01' AND '2020-12-03';

SELECT col2
FROM table_name
WHERE col2 NOT IN (1, 3, 4);

Operators

Operators include:

  • AND, OR, NOT
  • LIKE, ALL, ANY, ILIKE
  • >, >=, <, <=, =

Note: the equality operator is one single equal sign.

LIKE operator

  • %: The percent sign represents zero, one, or multiple characters.
  • _: The underscore represents a single character.
-- First name must start with A
SELECT first_name
FROM employees
WHERE first_name LIKE 'A%'

-- First name must start with A and be 2 or more characters in length
SELECT first_name
FROM employees
WHERE first_name LIKE 'A_%'

The ILIKE operator is case insenstive.

IN operator

SELECT column_name(s)
FROM table_name
WHERE column_name IN (value1, value2, ...);

ANY and ALL

NULL values

When checking for NULL values, you must use the IS keyword, not =.

  • Check using IS NULL or IS NOT NULL.
  • COALESCE() takes the first non-null value. Similar functions in other databases include NVL.
  • ANSI_NULLS operate differently, it is three-valued logic.
  • Generally, aggregate functions like AVG() dissmisses rows with NULL values.
SELECT col1
FROM table_name
WHERE col1 IS NULL;

Ordering

Put the ORDER BY statement at the end of your SQL query.

  • Two options: ASC, DESC
    • Sorted by ascending order by default.
  • Can order by multiple columns.
SELECT column1, column2, ...
FROM table_name
ORDER BY column1, column2, ... [ASC|DESC];

Data Definiton Language (DDL) Commands

Creating Tables

CREATE TABLE table_name (
	col1_name TYPE [CONSTRAINTS] [KEY],
	...
);

Example:

CREATE TABLE employees
(
  employee_id int NOT NULL PRIMARY KEY,
  first_name varchar(50) NOT NULL,
  last_name varchar(50) NOT NULL,
  manager_id int NULL
);

Inserting Values

INSERT INTO table_name (column1, column2, column3, ...)
VALUES (value1, value2, value3, ...);

Updating Values

UPDATE table_name
SET column1 = value1, column2 = value2, ...
WHERE condition;

Aggregate Functions

MIN() and MAX() functions

  • MIN() returns the lowest value of the selected column.
  • Should use aliases for clarity.
SELECT MAX(Price) AS LargestPrice
FROM Products;

Note: The LEAST() and GREATEST() function may be of interest.

COUNT(), SUM(), and AVG() functions

SELECT col1, COUNT(col2) AS count_col2
FROM table_name
WHERE condition
GROUP BY col1

A COUNT(*) will count all NULL and NOT NULL values.

JOINS

SQL joins include:

  • INNER JOIN: Selects records that have matching join values in both tables.
  • LEFT (OUTER) JOIN: Returns all records from the left table (table1), and the matched records from the right table (table2). The result is NULL from the right side, if there is no match.
  • RIGHT (OUTER) JOIN: Same logic as LEFT JOIN.
  • FULL (OUTER) JOIN: Returns all records when there is a match in left (table1) or right (table2) table records.
  • CROSS JOIN: Does a cartesian product. The total number of rows will be (number of rows in table1)*(number of rows in table2).
-- INNER JOIN
SELECT DISTINCT c.name
FROM customers c
INNER JOIN orders o
ON c.id = o.cust_id;

-- LEFT JOIN
SELECT 
  c.name
  ,o.order_id
  ,o.order_date
FROM customers c
LEFT JOIN orders o
ON c.id = o.cust_id;

-- CROSS JOIN
SELECT * 
FROM table1 
CROSS JOIN table2;

Left Exclusive Join: If you don’t want any of the right table’s values and you just want the left table’s values.

-- LEFT EXCLUSIVE JOIN
SELECT column_name(s)
FROM table1
LEFT JOIN table2
ON table1.key = table2.key
WHERE table2.key IS NULL;

ON WHERE vs ON AND in JOINS

SELECT *
FROM Orders
LEFT JOIN OrderLines 
       ON OrderLines.OrderID = Orders.ID
    WHERE Orders.ID = 12345


SELECT *
FROM Orders
LEFT JOIN OrderLines
       ON OrderLines.OrderID = Orders.ID 
      AND Orders.ID = 12345

The first will return an order and its lines, if any, for order number 12345. The second will return all orders, but only order 12345 will have any lines associated with it.

With an INNER JOIN, the clauses are effectively equivalent.

Summary:

  • WHERE: Filtered after joining.
  • AND Filtered before joining.

Other Functions

Union

  • UNION ALL: Does not remove any rows.
  • UNION: Removes duplicate rows.
  • The number of columns from the queries must match. The datatype of each column must also match.
SELECT column_name(s) FROM table1
UNION
SELECT column_name(s) FROM table2;

Intersect

INTERSECT is used to combine two SELECT statements, but returns rows only from the first SELECT statement that are identical to a row in the second SELECT statement.

Except

EXCEPT combines two SELECT statements and returns rows from the first SELECT statement that are not returned by the second SELECT statement.

In set theory, this is equivalent to A - B = A ∩ Bc, where A is the first table and B is the second table.

Group Concat

GROUP_CONCAT / LISTAGG function is an aggregate function that concatenates strings from a group into a single string with various options.

GROUP_CONCAT(
    DISTINCT expression
    ORDER BY expression
    SEPARATOR sep
)

Grouping

The GROUP BY keyword is used to group values in a column and is usually used with aggregate functions such as SUM(), MAX(), COUNT().

SELECT column_name(s)
FROM table_name
WHERE condition
GROUP BY column_name(s)
ORDER BY column_name(s);

Having

  • The HAVING clause was added to SQL because the WHERE keyword could not be used with aggregate functions.
  • When GROUP BY and WHERE is in the same query, WHERE clause is used to filter records from a result. The filtering occurs before any groupings are made. The HAVING clause is used to filter values from a group.
SELECT column_name(s)
FROM table_name
WHERE condition
GROUP BY column_name(s)
HAVING aggregate_condition
ORDER BY column_name(s);

Example:

SELECT titles.pub_id, AVG(titles.price) AS avg_price
FROM titles 
INNER JOIN publishers  
  ON titles.pub_id = publishers.pub_id  
WHERE publishers.state = 'CA'  
GROUP BY titles.pub_id  
HAVING AVG(titles.price) > 10

Case Statements

The CASE statement goes through conditions and returns a value when the first condition is met (like an IF-THEN-ELSE statement). So, once a condition is true, it will stop reading and return the result. If no conditions are true, it returns the value in the ELSE clause. If there is no ELSE part and no conditions are true, it returns NULL.

CASE
    WHEN condition1 THEN result1
    WHEN condition2 THEN result2
    ...
    WHEN conditionN THEN resultN
    ELSE result
END;
CASE 
  WHEN condition THEN return_val ELSE some_other_val
END

or sum the values

SUM(CASE WHEN condition THEN 1 ELSE 0 END) AS col_name

Common Table Expresions (CTEs) / WITH Clauses

  • Why? An alternative to creating a view.
  • Increased readability and simplification.
  • Named columns must match selected columns in CTE definition.
WITH CTE_expression_name([named_col_1, ...]) AS (
  CTE_definition
)
SQL_statement using above CTE;

You can write multiple CTEs in one query

WITH send_timespent AS (
    SELECT age_breakdown.age_bucket, SUM(activities.time_spent) AS send_timespent 
    FROM age_breakdown
  LEFT JOIN activities on age_breakdown.user_id = activities.user_id
    WHERE activities.type = 'send'
    GROUP BY 1
),
open_timespent AS (
    SELECT age_breakdown.age_bucket, SUM(activities.time_spent) AS open_timespent 
    FROM age_breakdown
  LEFT JOIN activities on age_breakdown.user_id = activities.user_id
    WHERE activities.type = 'open'
    GROUP BY 1
),
SELECT a.age_bucket, 
    s.send_timespent / (s.send_timespent + o.open_timespent) AS pct_send,
    o.open_timespent / (s.send_timespent + o.open_timespent) AS pct_open,
FROM age_breakdown a 
LEFT JOIN send_timespent s ON a.age_bucket = s.age_bucket
LEFT JOIN open_timespent o ON a.age_bucket = o.age_bucket
GROUP BY 1;

Can be used for recursive statements

WITH RECURSIVE factorial(n, fact) AS ( 
  SELECT 0, 1 
  UNION ALL  
  SELECT n + 1, fact * (n+1)  
  FROM factorial 
  WHERE n < 20
) 
SELECT * from factorial;

--Output
+------+---------------------+
| n    | fact                |
+------+---------------------+
|    0 |                   1 |
|    1 |                   1 |
|    2 |                   2 |
|    3 |                   6 |
|    4 |                  24 |
|    5 |                 120 |
|    6 |                 720 |
|    7 |                5040 |
|    8 |               40320 |
|    9 |              362880 |
|   10 |             3628800 |
|   11 |            39916800 |
|   12 |           479001600 |
|   13 |          6227020800 |
|   14 |         87178291200 |
|   15 |       1307674368000 |
|   16 |      20922789888000 |
|   17 |     355687428096000 |
|   18 |    6402373705728000 |
|   19 |  121645100408832000 |
|   20 | 2432902008176640000 |
+------+---------------------+

Derived Tables

  • A subquery nested within a FROM clause, this result must be named.
    • Usually writing a CTE is cleaner.
SELECT 
  named_table.col1
  ,named_table.col2
FROM 
  (
  SELECT col1, col2
  FROM table1
  ) named_tabled
WHERE named_tabled.col1 > 0;

JOINS with derived tables

SELECT * FROM
(SELECT * from table1) t1 INNER JOIN
(SELECT * from table2) t2 ON
t1.id = t2.id

Window Functions

  • Act after the result of the query.
  • Window functions operate on a set of rows and return a single value for each row from the underlying query.
  • PARTITION BY col, and ORDER BY col are optional; i.e if no partiton, taken over whole table
    • ORDER BY is not optional for ROW_NUMBER()
  • The ORDER BY clause defines the logical order of the rows within each partition of the result set.
  • Function can be AVG(), SUM(), ROW_NUMBER(), etc.
  • For ranking functions, make sure to get the correct ordering.
  • Note: The ROW_NUMBER() function does not reset if it sees a different partition value that switches back (i.e XXYX)
FUNCTION() OVER([PARTITION BY col1,...] 
                [ORDER BY col1, ...[NULLS {FIRST|LAST}]
                [FRAME CLAUSE]) AS calc_col

Example:

--- 3 Day Moving Average
SELECT
  Ticker
  ,Date
  ,Price
  ,AVG(Price) OVER(ORDER BY Date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS moving_average
FROM stock_prices;

Frame Clauses

The FRAME CLAUSE is by default:

[ROWS|RANGE] BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW

RANGE will include those rows in the window frame which have the same ORDER BY values as the current row.

The FRAME CLAUSE can be either:

  • {RANGE|ROWS} frame_start
  • {RANGE|ROWS} BETWEEN frame_start and frame_end

Where frame_start is:

  • UNBOUNDED PRECEDING or CURRENT ROW

And frame_end is:

  • CURRENT ROW or UNBOUNDED FOLLOWING

Example:

SELECT
AVG(price) OVER(ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING) as avg_3D_price
...

Lag and Lead

  • LAG and LEAD gets the previous or following value of a particular column.

The syntax is:

SELECT
LAG(col, offset, [default_if_no_value]) OVER()
...

Example:

SELECT
LAG(sale_value, 1) OVER(ORDER BY date_updated) AS previous_sale_price
FROM sales

Ranking Functions

  • ROW_NUMBER() attributes a unique value to each row.
  • RANK() attributes the same row number to the same value, leaving "holes".
  • DENSE_RANK() attributes the same row number to the same value, leaving no "holes".

Here is a good explanation of the differences.

CREATE TABLE t AS
SELECT 'a' v FROM dual UNION ALL
SELECT 'a'   FROM dual UNION ALL
SELECT 'a'   FROM dual UNION ALL
SELECT 'b'   FROM dual UNION ALL
SELECT 'c'   FROM dual UNION ALL
SELECT 'c'   FROM dual UNION ALL
SELECT 'd'   FROM dual UNION ALL
SELECT 'e'   FROM dual;

SELECT
  v,
  ROW_NUMBER() OVER (ORDER BY v) row_number,
  RANK()       OVER (ORDER BY v) rank,
  DENSE_RANK() OVER (ORDER BY v) dense_rank
FROM t
ORDER BY v;

+---+------------+------+------------+
| V | ROW_NUMBER | RANK | DENSE_RANK |
+---+------------+------+------------+
| a |          1 |    1 |          1 |
| a |          2 |    1 |          1 |
| a |          3 |    1 |          1 |
| b |          4 |    4 |          2 |
| c |          5 |    5 |          3 |
| c |          6 |    5 |          3 |
| d |          7 |    7 |          4 |
| e |          8 |    8 |          5 |
+---+------------+------+------------+

Built-In Functions

  • concat is ||

Date Functions

DATEDIFF(date1, date2) calculate the number of days between (date1 - date2)

SELECT DATEDIFF("2017-06-25", "2017-06-15");
-- 10

Other

  • Division: SQL automically does integer division if both the numerator and denominator are integers. Explicit cast to floats is needed. You can also force the numerator or denominator into a float by multiplying by 1.0

References

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