The conditional functions available in the Apache Hive are as follows. The most of them are also available in Apache Impala. The behavior of the functions in both Apache Hive and Impala would not vary.
The use of conditional statements is very frequent when it comes to data interpretation. Often data manipulation, too, relies on conditional statements. Operators such as equal (=), greater than (>), less than (<) or a combination of any two operators shall produce a TRUE or FALSE value based on whether the comparison between the operands
Similar to relational database systems like SQL Server, Oracle, MySQL, the CASE statement in Apache Hive verifies the conditions against the values of the columns. This is equal to the IF-THEN-ELSE statement where, if one of the conditions is true, it avoids checking the other conditions and returns the value defined in the THEN clause.
Unlike in relational database systems like SQL Server, the ISNULL function works in a different way in Apache Hive. In SQL Server, ISNULL(col1, 0) returns 0 if the col1 value is null. Same implementation will return the below error in Apache Hive. This is because the Apache Hive ISNULL function is a conditional assertion that
An significant part is the treatment of NULL values during data processing and reports. Sometimes it ends up with arithmetic overflow errors or null values if not done properly. There are lots of conditional functions in the Apache Impala that manage NULL values. ISNULL NVL IFNULL ZEROIFNULL The above mentioned four functions does almost the
The NVL() function enables you to substitute null for a more relevant alternative in the query results. This function accepts two arguments. If the first argument is null, then it returns the second argument. If the first argument is not null, it returns the first one and will ignore the second argument. This function is