A single precision floating-point data type used in CREATE TABLE and ALTER
TABLE statements.
Syntax:
In the column definition of a CREATE TABLE statement:
column_name FLOATRange: 1.40129846432481707e-45 .. 3.40282346638528860e+38, positive or negative
Precision: 6 to 9 significant digits, depending on usage. The number of significant digits does not depend on the position of the decimal point.
Representation: The values are stored in 4 bytes, using IEEE 754 Single Precision Binary Floating Point format.
Conversions: Impala automatically converts FLOAT to more precise
DOUBLE values, but not the other way around. You can use CAST() to convert
FLOAT values to TINYINT, SMALLINT, INT,
BIGINT, STRING, TIMESTAMP, or BOOLEAN.
You can use exponential notation in FLOAT literals or when casting from
STRING, for example 1.0e6 to represent one million.
Casting an integer or floating-point value
N to TIMESTAMP produces a value that is
N seconds past the start of the epoch date (January 1, 1970). By
default, the result value represents a date and time in the UTC time zone. If the
setting ‑‑use_local_tz_for_unix_timestamp_conversions=true
is in effect, the resulting TIMESTAMP represents a date and time in the
local time zone.
Usage notes:
Impala does not evaluate NaN (not a number) as equal to any other numeric values,
including other NaN values. For example, the following statement, which evaluates
equality between two NaN values, returns false:
SELECT CAST('nan' AS FLOAT)=CAST('nan' AS FLOAT);
Examples:
CREATE TABLE t1 (x FLOAT);
SELECT CAST(1000.5 AS FLOAT);
Partitioning: Because fractional values of this type are not always represented
precisely, when this type is used for a partition key column, the underlying HDFS
directories might not be named exactly as you expect. Prefer to partition on a
DECIMAL column instead.
HBase considerations: This data type is fully compatible with HBase tables.
Parquet considerations: This type is fully compatible with Parquet tables.
Text table considerations: Values of this type are potentially larger in text tables than in tables using Parquet or other binary formats.
Internal details: Represented in memory as a 4-byte value.
Column statistics considerations: Because this type has a fixed size, the maximum
and average size fields are always filled in for column statistics, even before you run
the COMPUTE STATS statement.
Restrictions:
Due to the way arithmetic on FLOAT and DOUBLE columns
uses high-performance hardware instructions, and distributed queries can perform these
operations in different order for each query, results can vary slightly for aggregate
function calls such as SUM() and AVG() for
FLOAT and DOUBLE columns, particularly on large data
sets where millions or billions of values are summed or averaged. For perfect
consistency and repeatability, use the DECIMAL data type for such
operations instead of FLOAT or DOUBLE.
The inability to exactly represent certain floating-point values means that
DECIMAL is sometimes a better choice than DOUBLE or
FLOAT when precision is critical, particularly when transferring data
from other database systems that use different representations or file formats.
Kudu considerations:
Currently, the data types BOOLEAN, FLOAT, and
DOUBLE cannot be used for primary key columns in Kudu tables.
Related information:
Numeric Literals, Impala Mathematical Functions, DOUBLE Data Type