--- id: sql-operators title: "Druid SQL Operators" sidebar_label: "Operators" --- :::info Apache Druid supports two query languages: Druid SQL and [native queries](querying.md). This document describes the SQL language. ::: Operators in [Druid SQL](./sql.md) typically operate on one or two values and return a result based on the values. Types of operators in Druid SQL include arithmetic, comparison, logical, and more, as described here. When performing math operations, Druid uses 64-bit integer (long) data type unless there are double or float values. If an operation uses float or double values, then the result is a double, which is a 64-bit float. The precision of float and double values is defined by [Java](https://docs.oracle.com/javase/specs/jls/se8/html/jls-5.html) and [the IEEE standard](https://en.wikipedia.org/wiki/IEEE_754). Keep the following guidelines in mind to help you manage precision issues: - Long values can store up to 2^63 accurately with an additional bit used for the sign. - Float values use 32 bits, and doubles use 64 bits. Both types are impacted by floating point precision. If you need exact decimal values, consider storing the number in a non-decimal format as a long value (up to the limit for longs). For example, if you need three decimal places, store the number multiplied by 1000 and then divide by 1000 when querying. ## Arithmetic operators |Operator|Description| |--------|-----------| |`x + y` |Add| |`x - y` |Subtract| |`x * y` |Multiply| |`x / y` |Divide| ## Datetime arithmetic operators For the datetime arithmetic operators, `interval_expr` can include interval literals like `INTERVAL '2' HOUR`. This operator treats days as uniformly 86400 seconds long, and does not take into account daylight savings time. To account for daylight savings time, use the [`TIME_SHIFT` function](sql-scalar.md#date-and-time-functions). Also see [`TIMESTAMPADD`](sql-scalar.md#date-and-time-functions) for datetime arithmetic. |Operator|Description| |--------|-----------| |`timestamp_expr + interval_expr`|Add an amount of time to a timestamp.| |`timestamp_expr - interval_expr`|Subtract an amount of time from a timestamp.| ## Concatenation operator Also see the [CONCAT function](sql-scalar.md#string-functions). |Operator|Description| |--------|-----------| |x || y|Concatenate strings `x` and `y`.| ## Comparison operators |Operator|Description| |--------|-----------| |`x = y` |Equal to| |`x IS NOT DISTINCT FROM y`|Equal to, considering `NULL` as a value. Never returns `NULL`.| |`x <> y`|Not equal to| |`x IS DISTINCT FROM y`|Not equal to, considering `NULL` as a value. Never returns `NULL`.| |`x > y` |Greater than| |`x >= y`|Greater than or equal to| |`x < y` |Less than| |`x <= y`|Less than or equal to| ## Logical operators |Operator|Description| |--------|-----------| |`x AND y`|Boolean AND| |`x OR y`|Boolean OR| |`NOT x`|Boolean NOT| |`x IS NULL`|True if _x_ is NULL or empty string| |`x IS NOT NULL`|True if _x_ is neither NULL nor empty string| |`x IS TRUE`|True if _x_ is true| |`x IS NOT TRUE`|True if _x_ is not true| |`x IS FALSE`|True if _x_ is false| |`x IS NOT FALSE`|True if _x_ is not false| |`x BETWEEN y AND z`|Equivalent to `x >= y AND x <= z`| |`x NOT BETWEEN y AND z`|Equivalent to `x < y OR x > z`| |`x LIKE pattern [ESCAPE esc]`|True if _x_ matches a SQL LIKE pattern (with an optional escape)| |`x NOT LIKE pattern [ESCAPE esc]`|True if _x_ does not match a SQL LIKE pattern (with an optional escape)| |`x IN (values)`|True if _x_ is one of the listed values| |`x NOT IN (values)`|True if _x_ is not one of the listed values| |`x IN (subquery)`|True if _x_ is returned by the subquery. This will be translated into a join; see [Query translation](sql-translation.md) for details.| |`x NOT IN (subquery)`|True if _x_ is not returned by the subquery. This will be translated into a join; see [Query translation](sql-translation.md) for details.| ## Other operators |Operator|Description| |--------|-----------| |`PIVOT (aggregation_function(column_to_aggregate) FOR column_with_values_to_pivot IN (pivoted_column1 [, pivoted_column2 ...]))`|Carries out an aggregation and transforms rows into columns in the output.| |`UNPIVOT (values_column FOR names_column IN (unpivoted_column1 [, unpivoted_column2 ... ]))`|Transforms existing column values into rows.|