Iceberg data types

References include Iceberg data types and a table of equivalent SQL data types by Impala SQL engine types.

Iceberg supported data types

Table 1.
Iceberg data type	SQL data type	Impala
binary		BINARY
boolean	BOOLEAN	BOOLEAN
date	DATE	DATE
decimal(P, S)	DECIMAL(P, S)	DECIMAL (P, S)
double	DOUBLE	DOUBLE
fixed(L)		Not supported
float	FLOAT	FLOAT
int	TINYINT, SMALLINT, INT	INTEGER
list	ARRAY	Read only
long	BIGINT	BIGINT
map	MAP	Read only
string	VARCHAR, CHAR	STRING
struct	STRUCT	Read only
time		Not supported
timestamp	TIMESTAMP	TIMESTAMP
timestamptz	TIMESTAMP WITH LOCAL TIME ZONE	Read timestamptz into TIMESTAMP values Writing not supported
uuid	none	Not supported

Data type limitations

An implicit conversion to an Iceberg type occurs only if there is an exact match; otherwise, a cast is needed. For example, to insert a VARCHAR(N) column into an Iceberg table you need a cast to the VARCHAR type as Iceberg does not support the VARCHAR(N) type. To insert a SMALLINT or TINYINT into an Iceberg table, you need a cast to the INT type as Iceberg does not support these types.

Iceberg supports two timestamp types:

timestamp (without timezone)
timestamptz ( with timezone)

In Spark 3.3 and earlier, Spark SQL supports a single TIMESTAMP type, which maps to the Iceberg timestamptz type. However, Impala is unable to write to Iceberg tables with timestamptz columns. To create Iceberg tables from Spark with timestamp rather than timestamptz columns, set the following configurations to true:

spark.sql.iceberg.handle-timestamp-without-timezone
spark.sql.iceberg.use-timestamp-without-timezone-in-new-tables

Configure these properties only on Spark 3.3 and earlier.

Spark still handles the timestamp column as a timestamp with local timezone. Inconsistent results occur unless Spark is running in UTC.

Unsupported data types

Impala does not support the following Iceberg data types:

TIMESTAMPTZ (only read support)
FIXED
UUID