Data validation across environments using HASH

Today i will discuss about data validation across environments using HASH function. There are times we need to validate the data of same table in different environments which is very monotonous and time consuming task while doing manually. Its better to automate the process. Here , I am considering the three environments Hive,IBM DB2,Snowflake Database.HIVE:md5(concatenated_columns)SNOWFLAKE:MD5_HEX (concatenated_columns)IBM DB2:HEX(HASH_MD5( concatenated_columns) Here, you need to take care of below things.1. Hexadecimal Output may in uppercase or lowercase, so handle with UPPER or LOWER function across environments.2. You need to take care of nulls…

Count the number of nulls using left join

Today, I will discuss about How to calculate the number of nulls that gets populated with left join or %age of matched data or count of not nulls using left join. CASE 1:Calculate the number of nulls that gets populated from right hand table using left join.Assume , I have two employee table EMP_TBL1 and EMP_TBL2. See the data for the same. EMP_TBL1 EMP_TBL2 below is the code used to get number of nulls that comes from right side table using left join. select count(*)-count(y_empid) from ( select x.emp_id ,y.emp_id…