In a WHERE clause, compares an expression to both a lower and upper bound. The comparison is successful is the expression is greater than or equal to the lower bound, and less than or equal to the upper bound. If the bound values are switched, so the lower bound is greater than the upper bound, does not match any values.

Syntax: expression BETWEEN lower_bound AND upper_bound

Data types: Typically used with numeric data types. Works with any data type, although not very practical for BOOLEAN values. (BETWEEN false AND true will match all BOOLEAN values.) Use CAST() if necessary to ensure the lower and upper bound values are compatible types. Call string or date/time functions if necessary to extract or transform the relevant portion to compare, especially if the value can be transformed into a number.

Usage notes: Be careful when using short string operands. A longer string that starts with the upper bound value will not be included, because it is considered greater than the upper bound. For example, BETWEEN 'A' and 'M' would not match the string value 'Midway'. Use functions such as upper(), lower(), substr(), trim(), and so on if necessary to ensure the comparison works as expected.

Examples:

-- Retrieve data for January through June, inclusive.
select c1 from t1 where month between 1 and 6;

-- Retrieve data for names beginning with 'A' through 'M' inclusive.
-- Only test the first letter to ensure all the values starting with 'M' are matched.
-- Do a case-insensitive comparison to match names with various capitalization conventions.
select last_name from customers where upper(substr(last_name,1,1)) between 'A' and 'M';

-- Retrieve data for only the first week of each month.
select count(distinct visitor_id)) from web_traffic where dayofmonth(when_viewed) between 1 and 7;

Impala supports the familiar comparison operators for checking equality and sort order for the column data types:

• =, !=, <>: apply to all types.
• <, <=, >, >=: apply to all types; for BOOLEAN, TRUE is considered greater than FALSE.

Alternatives:

The IN and BETWEEN operators provide shorthand notation for expressing combinations of equality, less than, and greater than comparisons with a single operator.

Because comparing any value to NULL produces NULL rather than TRUE or FALSE, use the IS NULL and IS NOT NULL operators to check if a value is NULL or not.

The IN operator compares an argument value to a set of values, and returns TRUE if the argument matches any value in the set. The argument and the set of comparison values must be of compatible types.

Any expression using the IN operator could be rewritten as a series of equality tests connected with OR, but the IN syntax is often clearer, more concise, and easier for Impala to optimize. For example, with partitioned tables, queries frequently use IN clauses to filter data by comparing the partition key columns to specific values.

Examples:

-- Using IN is concise and self-documenting.
SELECT * FROM t1 WHERE c1 IN (1,2,10);
-- Equivalent to series of = comparisons ORed together.
SELECT * FROM t1 WHERE c1 = 1 OR c1 = 2 OR c1 = 10;

SELECT c1 AS "starts with vowel" FROM t2 WHERE upper(substr(c1,1,1)) IN ('A','E','I','O','U');

SELECT COUNT(DISTINCT(visitor_id)) FROM web_traffic WHERE month IN ('January','June','July');

The IS NULL operator, and its converse the IS NOT NULL operator, test whether a specified value is NULL. Because using NULL with any of the other comparison operators such as = or != also returns NULL rather than TRUE or FALSE, you use a special-purpose comparison operator to check for this special condition.

Usage notes:

In many cases, NULL values indicate some incorrect or incomplete processing during data ingestion or conversion. You might check whether any values in a column are NULL, and if so take some followup action to fill them in.

With sparse data, often represented in "wide" tables, it is common for most values to be NULL with only an occasional non-NULL value. In those cases, you can use the IS NOT NULL operator to identify the rows containing any data at all for a particular column, regardless of the actual value.

With a well-designed database schema, effective use of NULL values and IS NULL and IS NOT NULL operators can save having to design custom logic around special values such as 0, -1, 'N/A', empty string, and so on. NULL lets you distinguish between a value that is known to be 0, false, or empty, and a truly unknown value.

Examples:

-- If this value is non-zero, something is wrong.
select count(*) from employees where employee_id is null;

-- With data from disparate sources, some fields might be blank.
-- Not necessarily an error condition.
select count(*) from census where household_income is null;

-- Sometimes we expect fields to be null, and followup action
-- is needed when they are not.
select count(*) from web_traffic where weird_http_code is not null;

A comparison operator for STRING data, with basic wildcard capability using _ to match a single character and % to match multiple characters. The argument expression must match the entire string value. Typically, it is more efficient to put any % wildcard match at the end of the string.

Examples:

select distinct c_last_name from customer where c_last_name like 'Mc%' or c_last_name like 'Mac%';
select count(c_last_name) from customer where c_last_name like 'M%';
select c_email_address from customer where c_email_address like '%.edu';

-- We can find 4-letter names beginning with 'M' by calling functions...
select distinct c_last_name from customer where length(c_last_name) = 4 and substr(c_last_name,1,1) = 'M';
-- ...or in a more readable way by matching M followed by exactly 3 characters.
select distinct c_last_name from customer where c_last_name like 'M___';

For a more general kind of search operator using regular expressions, see REGEXP Operator.

Tests whether a value matches a regular expression. Uses the POSIX regular expression syntax where ^ and $ match the beginning and end of the string, . represents any single character, * represents a sequence of zero or more items, + represents a sequence of one or more items, ? produces a non-greedy match, and so on.

The regular expression must match the entire value, not just occur somewhere inside it. Use .* at the beginning and/or the end if you only need to match characters anywhere in the middle. Thus, the ^ and $ atoms are often redundant, although you might already have them in your expression strings that you reuse from elsewhere.

The RLIKE operator is a synonym for REGEXP.

The | symbol is the alternation operator, typically used within () to match different sequences. The () groups do not allow backreferences. To retrieve the part of a value matched within a () section, use the regexp_extract() built-in function.

Examples:

-- Find all customers whose first name starts with 'J', followed by 0 or more of any character.
select c_first_name, c_last_name from customer where c_first_name regexp '^J.*';

-- Find 'Macdonald', where the first 'a' is optional and the 'D' can be upper- or lowercase.
-- The ^...$ are required, to match the start and end of the value.
select c_first_name, c_last_name from customer where c_last_name regexp '^Ma?c[Dd]onald$';

-- Match multiple character sequences, either 'Mac' or 'Mc'.
select c_first_name, c_last_name from customer where c_last_name regexp '^(Mac|Mc)donald$';

-- Find names starting with 'S', then one or more vowels, then 'r', then any other characters.
-- Matches 'Searcy', 'Sorenson', 'Sauer'.
select c_first_name, c_last_name from customer where c_last_name regexp '^S[aeiou]+r.*$';

-- Find names that end with 2 or more vowels: letters from the set a,e,i,o,u.
select c_first_name, c_last_name from customer where c_last_name regexp '.*[aeiou]{2,}$';

-- You can use letter ranges in the [] blocks, for example to find names starting with A, B, or C.
select c_first_name, c_last_name from customer where c_last_name regexp '^[A-C].*';

-- If you are not sure about case, leading/trailing spaces, and so on, you can process the
-- column using string functions first.
select c_first_name, c_last_name from customer where lower(trim(c_last_name)) regexp '^de.*';

Synonym for the REGEXP operator.