Tag Archives: SQL

How to Secure Your Azure SQL Database

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  1. Authentication and Authorization:
    • Use Azure Active Directory (Azure AD) authentication for better security.
    • Implement firewall rules to control access to your database.
    • Assign minimal permissions to users based on their roles (principle of least privilege).
  2. Encryption:
    • Enable Transparent Data Encryption (TDE) to protect data at rest.
    • Use Always Encrypted to secure sensitive data in transit.
    • Consider client-side encryption for additional protection.
  3. Auditing and Monitoring:
    • Enable Azure SQL Auditing to track database activity.
    • Set up Azure Monitor to receive alerts and insights.
    • Regularly review logs and audit trails.
  4. Network Security:
    • Isolate your database using Virtual Network Service Endpoints.
    • Restrict public access and use private endpoints.
  5. Patch Management:
    • Keep your database engine up to date with the latest security patches.
    • Regularly review vulnerability assessments.
  6. Backup and Recovery:
    • Implement automated backups and test recovery procedures (remember a backup is only theoretically there unless it has been tested and proven to work).
    • Store backups conforming to the 3-2-1 Backup Rule explained below (do not assume your backups are safe just because they are in the cloud).

The 3-2-1 Backup Rule: Ensuring Data Resilience

The 3-2-1 Rule is a robust strategy that emphasizes redundancy, resilience, and data availability. Here’s what it entails:

  1. Three Copies of Your Data:
    • Maintain the original data and create at least two additional copies.
  2. Two Different Types of Media for Storage:
    • Store your data on distinct forms of media (e.g., hard drives, tapes) to enhance redundancy.
  3. At Least One Copy Off-Site:
    • Safeguard one backup copy in an off-site location, separate from your primary data and on-site backups.

By adhering to this rule, you mitigate single points of failure, protect against corruption, and ensure data safety even in unexpected events or disasters

Comparing two tables for equality with Spark SQL

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The best way of comparing two tables to determine if they are the exact same is to calculate the hash sum of each table and then compare the sum of hash. The benefit of the technique below are that no matter how many fields there are and no matter what data types the fields may be, you can use following query to do the comparison:

SELECT SUM(HASH(*)) FROM t1;
SELECT SUM(HASH(*)) FROM t2;

Of course if the schemas of the two tables are different this will by default produce different hash values.

How to pick random numbers between two numbers with T-SQL

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Below is a T-SQL example that will pick a random number between 1 and 50. 

SELECT CAST(RAND() * (51 - 1) + 1 AS INT) AS Random#

That’s a bit boring though.
What about parameters?
What about a use case?
Where’s the familiar glamour of coding with T-SQL?

I hear ya.

Below is a T-SQL example that could make you a multimillionaire!

This T-SQL code will pick random numbers for the Euromillions lottery.

Good luck.

DECLARE @a INT;
DECLARE @b INT;
DECLARE @count INT;
DECLARE @pick INT;

DROP TABLE IF EXISTS #Num;

CREATE TABLE #Num (
	Number INT
	,NumberType VARCHAR(255)
	);

SET @a = 1
SET @b = 51
SET @count = 1

WHILE @count < 6
BEGIN
	SET @pick = CAST(RAND() * (@b - @a) + @a AS INT)

	IF (
			SELECT Number
			FROM #Num
			WHERE Number = @pick
			AND NumberType = 'Main'
			) IS NULL
	BEGIN
		INSERT INTO #Num (
			Number
			,NumberType
			)
		SELECT @pick
			,'Main';

		SET @count = @count + 1
	END
END

SET @a = 1
SET @b = 13
SET @count = 1

WHILE @count < 3
BEGIN
	SET @pick = CAST(RAND() * (@b - @a) + @a AS INT)

	IF (
			SELECT Number
			FROM #Num
			WHERE Number = @pick
			AND NumberType = 'Lucky'
			) IS NULL
	BEGIN
		INSERT INTO #Num (
			Number
			,NumberType
			)
		SELECT @pick
			,'Lucky';

		SET @count = @count + 1
	END
END

SELECT Number
	,NumberType
FROM #Num
ORDER BY NumberType DESC
,Number ASC;

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