SQL | Snowflake | IFNULL vs NULLIF function

---

 DIFFERENCE BETWEEN IFNULL AND NULLIF FUNCTION

---

These SQL functions are compatible with mysql, SQL Server, Power BI, Big query.

IFNULL FUNCTION: If the in-parameter is NULL then it returns the default out-parameter.

Syntax : IFNULL (<in-parameter>,<out-parameter>)

SQL Snowflake IFNULL( ) function

NULLIF FUNCTION: If the first in-parameter is equal/same to the second in-parameter it returns NULL. If the first in-parameter is not equal/same to the second in-parameter it returns the first in-parameter.

Syntax : NULLIF (<in-parameter-1>,<in-parameter-2>)

SQLSnowflake NULLIF ( ) function

IFNULL( ) VS NULLIF( ) FUNCTION:

Features	IFNULL	NULLIF
Syntax	IFNULL (<in-parameter>, <out-parameter>)	NULLIF (<in-parameter-1>, <in-parameter-2>)
Example	[1] IFNULL(NULL,28) [2] IFNULL(100, 28)	[1] NULLIF(28,28) [2] NULLIF(100,28)
Number of IN parameter	1	2
Number of OUT parameter	1	0
If IN parameter is NULL	Returns out-parameter value O/p : [1] Returns 28	NA
If IN parameter is NOT NULL	Returns in-parameter value O/p : [2] Returns 100	NA
If IN parameter 1 is same/equal to IN parameter 2	NA	Returns NULL O/p :[1] Returns NULL
If IN parameter 1 is not same/equal to IN parameter 2	NA	Returns in-parameter-1 O/p :[2] Returns 100

SQL Snowflake NULLIF vs IFNULL function

---

Read More :

• Difference between WHERE and HAVING clause

---

• Difference between NVL and NVL2 function

---

Snowflake NVL vs NVL2 function | SQL

DIFFERENCE BETWEEN  NVL AND NVL2 FUNCTION

---

 This post explains the difference between NVL and NVL2 functions in Snowflake.

The NVL and NVL2 functions are also compatible with other databases like Teradata, Mysql, Postgresql, Oracle, PLSQL, Amazon Redshift.

---

NVL FUNCTION

The NVL function will return the default value if the in- parameter is NULL.

Syntax: NVL ( <in-param>,<out-param>)

• If the in-param is NULL then it will return the out-param value.
• If the in-param is NOT NULL then it will return the in-param value itself.

Difference between NVL and NVL2 function

NVL2 FUNCTION

The NVL2 function will return the first out-parameter if the in-parameter is NOT NULL and return the second parameter if the in-parameter is NULL.

Syntax: NVL2( <in-param>,<out-param-1>,<out-param-2>)

• If the in-param is NULL then it will return the out-param-1 value .
• If the in-param is NOT NULL then it will return the in-param-2 value itself.

Difference between NVL and NVL2 function

NVL VS NVL2 FUNCTION

Features	NVL	NVL2
Syntax	NVL ( <in-param>,<out-param>)	NVL2( <in-param> ,<out-param-1> ,<out-param-2>)
Example	[1] NVL(NULL,'It is NULL') [2] NVL('99','It is NULL')	[1] NVL2('99','It is Not NULL' ,'It is NULL')
Number of IN parameter	1	1
Number of OUT parameter	1	2
If IN parameter is NULL	Returns <out-param> i.e [1] 'It is NULL'	Returns <out-param-1>  i.e [1] 'It is Not NULL'
If IN parameter is NOT NULL	Returns  <in-param>  i.e [2] '99'	Returns <out-param-2>  i.e [1] 'It is NULL'

 

NVL vs NVL2 function | SQL

---

Read More :

• What does count 1 mean in SQL?

---

• How to include a single quote in a SQL query?

---

• Difference between WHERE and HAVING clause

---

• Create a table from an existing table

---

Difference between WHERE and HAVING clause | SQL

WHERE AND HAVING CLAUSE WITH EXAMPLE

This post explains the difference between WHERE and HAVING clauses and how to use them with example scenarios.

---

WHERE:

• WHERE clause is used to filter only the desired records in the table.
• Records that don't meet the condition are removed prior to the grouping operation.

HAVING:

• HAVING clause is used as a secondary filter. If the value is calculated in your query and the value is not readily available in your table then you need use the HAVING clause.
• This filter is applied after your aggregate functions are executed in order to meet the mentioned HAVING condition from your resultant.

For example, let's consider you have a data set with ticket sales details of a game by team.

Scenario 1 :

The resultant here will be each team’s sum of sales from every game that had sales greater than 50,000.

SELECT 
team, 
SUM(sales_amt ) 
FROM 
games 
WHERE 
sales_amt > 50000 
GROUP BY 
team;

Scenario 2 :

The resultant here will be only teams that have total sales of greater than 5,00,000.

SELECT 
team, 
SUM(sales_amt ) 
FROM 
games 
GROUP BY 
team
HAVING 
SUM(sales_amt ) > 500000;

Scenario 3 :

The resultant here will be only teams that have grossed more than 5,00,000 from games that did more than 50,000 in sales.

SELECT 
team, 
SUM(sales_amt ) 
FROM 
games 
WHERE 
sales_amt > 50000 
GROUP BY 
team
HAVING 
SUM(sales_amt ) > 500000;

WHERE VS HAVING:

Features	WHERE	HAVING
Syntax	WHERE condition;	GROUP BY columns HAVING condition;
Example	WHERE sales_amt > 50000;	GROUP BY team HAVING SUM(sales_amt ) > 500000;
What value can be used condition	Direct value from table	Derived  aggregate value from table
When to use WHERE/HAVING clause	To filter data based on values available in the table.	To filter data based on aggregate values derived from values available in the table

---

Read More:

• What does count 1 mean in SQL?

---

• How to include a single quote in a SQL query?

---

• Create a table from an existing table

---

• Snowflake NVL vs NVL2

---

Convert SQL query output into HTML table | Python

FORMAT SQL QUERY OUTPUT INTO AN HTML TABLE 

From my own experience with python SQL connector. I think this is one of the easiest way to format the output SQL query output into HTML  table code.

Steps to convert SQL query output  into HTML table code:

• Connect to the database using SQL connector
• Create a cursor to execute your SQL query and fetch the resultant 
• Execute the SQL query and use the below code to convert the output into an HTML table.

Convert  SQL query output into HTML table | Python

For example, I want to convert the above SQL query output into HTML code and I am using Snowflake Connector.

snowflake = snowflake.connector.connect(
  user=SF_USER,
  password=SF_PASSWORD,
  account=SF_ACCOUNT,
  warehouse=SF_WAREHOUSE,
  database=SF_DATABASE,
  schema=SF_SCHEMA
)    
snowflake_cur = snowflake.cursor()	

 sHtml=""
    
sql = """ 
            SELECT CustomerID, CustomerName FROM Customers ORDER BY CustomerName ASC;
          """
snowflake_cur.execute(sql)

sHtml=sHtml+"""</br><table order="1"><tr><th>CustomerID</th><th>CustomerName</th></tr>"""

for row in snowflake_cur.fetchall():
    sHtml=sHtml+"<tr><td>"+str(row[0])+"</td><td style=""text-align:center"" >"+str( "{:,}".format(row[1]))+"</td></tr>"

sHtml=sHtml+"</table></br>"

---

Read More :

• Connect to Postgres database using AWS Secrets Manager and psycopg2

---

Create a table from an existing table | SQL

CREATE A NEW TABLE FROM THE EXISTING TABLE  WITH DATA OR WITHOUT DATA ALONG WITH FEW COLUMNS OR ALL THE COLUMNS USING ONE TABLE OR MULTIPLE TABLES

These SQL queries will create the basic table and its fields but not indexes, constraints, or triggers as it is in the existing table.

---

CREATE AN EMPTY TABLE FROM AN EXISTING TABLE:

Syntax:

CREATE TABLE new_table 
  AS (SELECT * 
      FROM old_table WHERE 1=2); 

Example:

CREATE TABLE suppliers 
AS (SELECT * 
 FROM companies 
 WHERE 1=2);

---

CREATE A TABLE FROM AN EXISTING TABLE WITH DATA:

Syntax:

CREATE TABLE new_table 
  AS (SELECT * 
      FROM old_table); 

Example:

CREATE TABLE suppliers 
AS (SELECT * 
 FROM companies 
 WHERE id > 1000);

---

CREATE A TABLE WITH ONLY A FEW COLUMNS FROM AN EXISTING TABLE WITH DATA:

Syntax:

CREATE TABLE new_table 
AS (SELECT column_1, column2, ... column_n 
FROM old_table); 

Example:

CREATE TABLE suppliers 
AS (SELECT id, address, city, state, zip 
FROM companies 
WHERE id > 1000); 

---

CREATE A TABLE WITH ONLY A FEW COLUMNS FROM AN EXISTING MULTIPLE TABLES WITH DATA:

Syntax:

CREATE TABLE new_table 
  AS (SELECT column_1, column2, ... column_n 
      FROM old_table_1, old_table_2, ... old_table_n); 

Example:

CREATE TABLE suppliers 
AS (SELECT companies.id, companies.address, categories.cat_type 
FROM companies, categories 

WHERE companies.id = categories.id 
AND companies.id > 1000); 

---

Read More:

What does count 1 mean in SQL?

How to include a single quote in a SQL query?

---

How to include a single quote in a SQL query

INSERT SINGLE QUOTE IN SQL

---

This post explains how to insert a single quote in data/text/string.

It can be inserted by placing the single quotes in between a pair of single quotes.

This is compatible with all the databases like Snowflake, Teradata, Mysql, Postgresql, Oracle, PLSQL, Amazon Redshift.

Below is an example of how to include/ insert a single quote in SQL.

Insert a single quote in a SQL

---

Read More :

• What does count 1 mean in SQL?

---

• Difference between WHERE and HAVING clause

---

• Create a table from an existing table

---

• Snowflake NVL vs NVL2

---

What does count 1 mean in SQL?

 There is a common misunderstanding that it interprets the ordinal of the column.

COUNT(*) takes all columns to count rows which is equivalent to select * from tablename.

COUNT(1) counts using the first column which is the Primary Key which is equivalent to select 1 from tablename, which returns all the records with the value “1” instead of fetching the actual value.

So count(1) little efficient than count(*).