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 ---
 layout: global
 title: Data Types
 displayTitle: Data Types
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 ### Supported Data Types
 
 Spark SQL and DataFrames support the following data types:
 
 * Numeric types
   - `ByteType`: Represents 1-byte signed integer numbers.
   The range of numbers is from `-128` to `127`.
   - `ShortType`: Represents 2-byte signed integer numbers.
   The range of numbers is from `-32768` to `32767`.
   - `IntegerType`: Represents 4-byte signed integer numbers.
   The range of numbers is from `-2147483648` to `2147483647`.
   - `LongType`: Represents 8-byte signed integer numbers.
   The range of numbers is from `-9223372036854775808` to `9223372036854775807`.
   - `FloatType`: Represents 4-byte single-precision floating point numbers.
   - `DoubleType`: Represents 8-byte double-precision floating point numbers.
   - `DecimalType`: Represents arbitrary-precision signed decimal numbers. Backed internally by `java.math.BigDecimal`. A `BigDecimal` consists of an arbitrary precision integer unscaled value and a 32-bit integer scale.
 * String type
   - `StringType`: Represents character string values.
 * Binary type
   - `BinaryType`: Represents byte sequence values.
 * Boolean type
   - `BooleanType`: Represents boolean values.
 * Datetime type
   - `TimestampType`: Represents values comprising values of fields year, month, day,
   hour, minute, and second, with the session local time-zone. The timestamp value represents an
   absolute point in time.
   - `DateType`: Represents values comprising values of fields year, month and day, without a
   time-zone.
 * Complex types
   - `ArrayType(elementType, containsNull)`: Represents values comprising a sequence of
   elements with the type of `elementType`. `containsNull` is used to indicate if
   elements in a `ArrayType` value can have `null` values.
   - `MapType(keyType, valueType, valueContainsNull)`:
   Represents values comprising a set of key-value pairs. The data type of keys is
   described by `keyType` and the data type of values is described by `valueType`.
   For a `MapType` value, keys are not allowed to have `null` values. `valueContainsNull`
   is used to indicate if values of a `MapType` value can have `null` values.
   - `StructType(fields)`: Represents values with the structure described by
   a sequence of `StructField`s (`fields`).
     * `StructField(name, dataType, nullable)`: Represents a field in a `StructType`.
     The name of a field is indicated by `name`. The data type of a field is indicated
     by `dataType`. `nullable` is used to indicate if values of these fields can have
     `null` values.
 
 <div class="codetabs">
 <div data-lang="scala"  markdown="1">
 
 All data types of Spark SQL are located in the package `org.apache.spark.sql.types`.
 You can access them by doing
 
 {% include_example data_types scala/org/apache/spark/examples/sql/SparkSQLExample.scala %}
 
 |Data type|Value type in Scala|API to access or create a data type|
 |---------|-------------------|-----------------------------------|
 |**ByteType**|Byte|ByteType|
 |**ShortType**|Short|ShortType|
 |**IntegerType**|Int|IntegerType|
 |**LongType**|Long|LongType|
 |**FloatType**|Float|FloatType|
 |**DoubleType**|Double|DoubleType|
 |**DecimalType**|java.math.BigDecimal|DecimalType|
 |**StringType**|String|StringType|
 |**BinaryType**|Array[Byte]|BinaryType|
 |**BooleanType**|Boolean|BooleanType|
 |**TimestampType**|java.sql.Timestamp|TimestampType|
 |**DateType**|java.sql.Date|DateType|
 |**ArrayType**|scala.collection.Seq|ArrayType(*elementType*, [*containsNull]*)<br/>**Note:** The default value of *containsNull* is true.|
 |**MapType**|scala.collection.Map|MapType(*keyType*, *valueType*, [*valueContainsNull]*)<br/>**Note:** The default value of *valueContainsNull* is true.|
 |**StructType**|org.apache.spark.sql.Row|StructType(*fields*)<br/>**Note:** *fields* is a Seq of StructFields. Also, two fields with the same name are not allowed.|
 |**StructField**|The value type in Scala of the data type of this field(For example, Int for a StructField with the data type IntegerType)|StructField(*name*, *dataType*, [*nullable*])<br/>**Note:** The default value of *nullable* is true.|
 
 </div>
 
 <div data-lang="java" markdown="1">
 
 All data types of Spark SQL are located in the package of
 `org.apache.spark.sql.types`. To access or create a data type,
 please use factory methods provided in
 `org.apache.spark.sql.types.DataTypes`.
 
 |Data type|Value type in Java|API to access or create a data type|
 |---------|------------------|-----------------------------------|
 |**ByteType**|byte or Byte|DataTypes.ByteType|
 |**ShortType**|short or Short|DataTypes.ShortType|
 |**IntegerType**|int or Integer|DataTypes.IntegerType|
 |**LongType**|long or Long|DataTypes.LongType|
 |**FloatType**|float or Float|DataTypes.FloatType|
 |**DoubleType**|double or Double|DataTypes.DoubleType|
 |**DecimalType**|java.math.BigDecimal|DataTypes.createDecimalType()<br/>DataTypes.createDecimalType(*precision*, *scale*).|
 |**StringType**|String|DataTypes.StringType|
 |**BinaryType**|byte[]|DataTypes.BinaryType|
 |**BooleanType**|boolean or Boolean|DataTypes.BooleanType|
 |**TimestampType**|java.sql.Timestamp|DataTypes.TimestampType|
 |**DateType**|java.sql.Date|DataTypes.DateType|
 |**ArrayType**|java.util.List|DataTypes.createArrayType(*elementType*)<br/>**Note:** The value of *containsNull* will be true.<br/>DataTypes.createArrayType(*elementType*, *containsNull*).|
 |**MapType**|java.util.Map|DataTypes.createMapType(*keyType*, *valueType*)<br/>**Note:** The value of *valueContainsNull* will be true.<br/>DataTypes.createMapType(*keyType*, *valueType*, *valueContainsNull*)|
 |**StructType**|org.apache.spark.sql.Row|DataTypes.createStructType(*fields*)<br/>**Note:** *fields* is a List or an array of StructFields.Also, two fields with the same name are not allowed.|
 |**StructField**|The value type in Java of the data type of this field (For example, int for a StructField with the data type IntegerType)|DataTypes.createStructField(*name*, *dataType*, *nullable*)| 
 
 </div>
 
 <div data-lang="python"  markdown="1">
 
 All data types of Spark SQL are located in the package of `pyspark.sql.types`.
 You can access them by doing
 {% highlight python %}
 from pyspark.sql.types import *
 {% endhighlight %}
 
 |Data type|Value type in Python|API to access or create a data type|
 |---------|--------------------|-----------------------------------|
 |**ByteType**|int or long<br/>**Note:** Numbers will be converted to 1-byte signed integer numbers at runtime. Please make sure that numbers are within the range of -128 to 127.|ByteType()|
 |**ShortType**|int or long<br/>**Note:** Numbers will be converted to 2-byte signed integer numbers at runtime. Please make sure that numbers are within the range of -32768 to 32767.|ShortType()|
 |**IntegerType**|int or long|IntegerType()|
 |**LongType**|long<br/>**Note:** Numbers will be converted to 8-byte signed integer numbers at runtime. Please make sure that numbers are within the range of -9223372036854775808 to 9223372036854775807.Otherwise, please convert data to decimal.Decimal and use DecimalType.|LongType()|
 |**FloatType**|float<br/>**Note:** Numbers will be converted to 4-byte single-precision floating point numbers at runtime.|FloatType()|
 |**DoubleType**|float|DoubleType()|
 |**DecimalType**|decimal.Decimal|DecimalType()|
 |**StringType**|string|StringType()|
 |**BinaryType**|bytearray|BinaryType()|
 |**BooleanType**|bool|BooleanType()|
 |**TimestampType**|datetime.datetime|TimestampType()|
 |**DateType**|datetime.date|DateType()|
 |**ArrayType**|list, tuple, or array|ArrayType(*elementType*, [*containsNull*])<br/>**Note:**The default value of *containsNull* is True.|
 |**MapType**|dict|MapType(*keyType*, *valueType*, [*valueContainsNull]*)<br/>**Note:**The default value of *valueContainsNull* is True.|
 |**StructType**|list or tuple|StructType(*fields*)<br/>**Note:** *fields* is a Seq of StructFields. Also, two fields with the same name are not allowed.|
 |**StructField**|The value type in Python of the data type of this field<br/>(For example, Int for a StructField with the data type IntegerType)|StructField(*name*, *dataType*, [*nullable*])<br/>**Note:** The default value of *nullable* is True.|
 
 </div>
 
 <div data-lang="r"  markdown="1">
 
 |Data type|Value type in R|API to access or create a data type|
 |---------|---------------|-----------------------------------|
 |**ByteType**|integer <br/>**Note:** Numbers will be converted to 1-byte signed integer numbers at runtime.  Please make sure that numbers are within the range of -128 to 127.|"byte"|
 |**ShortType**|integer <br/>**Note:** Numbers will be converted to 2-byte signed integer numbers at runtime.  Please make sure that numbers are within the range of -32768 to 32767.|"short"|
 |**IntegerType**|integer|"integer"|
 |**LongType**|integer <br/>**Note:** Numbers will be converted to 8-byte signed integer numbers at runtime.  Please make sure that numbers are within the range of -9223372036854775808 to 9223372036854775807.  Otherwise, please convert data to decimal.Decimal and use DecimalType.|"long"|
 |**FloatType**|numeric <br/>**Note:** Numbers will be converted to 4-byte single-precision floating point numbers at runtime.|"float"|
 |**DoubleType**|numeric|"double"|
 |**DecimalType**|Not supported|Not supported|
 |**StringType**|character|"string"|
 |**BinaryType**|raw|"binary"|
 |**BooleanType**|logical|"bool"|
 |**TimestampType**|POSIXct|"timestamp"|
 |**DateType**|Date|"date"|
 |**ArrayType**|vector or list|list(type="array", elementType=*elementType*, containsNull=[*containsNull*])<br/>**Note:** The default value of *containsNull* is TRUE.|
 |**MapType**|environment|list(type="map", keyType=*keyType*, valueType=*valueType*, valueContainsNull=[*valueContainsNull*])<br/> **Note:** The default value of *valueContainsNull* is TRUE.|
 |**StructType**|named list|list(type="struct", fields=*fields*)<br/> **Note:** *fields* is a Seq of StructFields. Also, two fields with the same name are not allowed.|
 |**StructField**|The value type in R of the data type of this field (For example, integer for a StructField with the data type IntegerType)|list(name=*name*, type=*dataType*, nullable=[*nullable*])<br/> **Note:** The default value of *nullable* is TRUE.|
 
 </div>
 
 <div data-lang="SQL"  markdown="1">
 
 The following table shows the type names as well as aliases used in Spark SQL parser for each data type.
 
 |Data type|SQL name|
 |---------|--------|
 |**BooleanType**|BOOLEAN|
 |**ByteType**|BYTE, TINYINT|
 |**ShortType**|SHORT, SMALLINT|
 |**IntegerType**|INT, INTEGER|
 |**LongType**|LONG, BIGINT|
 |**FloatType**|FLOAT, REAL|
 |**DoubleType**|DOUBLE|
 |**DateType**|DATE|
 |**TimestampType**|TIMESTAMP|
 |**StringType**|STRING|
 |**BinaryType**|BINARY|
 |**DecimalType**|DECIMAL, DEC, NUMERIC|
 |**CalendarIntervalType**|INTERVAL|
 |**ArrayType**|ARRAY<element_type>|
 |**StructType**|STRUCT<field1_name: field1_type, field2_name: field2_type, ...>|
 |**MapType**|MAP<key_type, value_type>|
 
 </div>
 </div>
 
 ### Floating Point Special Values
 
 Spark SQL supports several special floating point values in a case-insensitive manner:
 
  * Inf/+Inf/Infinity/+Infinity: positive infinity
    * ```FloatType```: equivalent to Scala <code>Float.PositiveInfinity</code>.
    * ```DoubleType```: equivalent to Scala <code>Double.PositiveInfinity</code>.
  * -Inf/-Infinity: negative infinity
    * ```FloatType```: equivalent to Scala <code>Float.NegativeInfinity</code>.
    * ```DoubleType```: equivalent to Scala <code>Double.NegativeInfinity</code>.
  * NaN: not a number
    * ```FloatType```: equivalent to Scala <code>Float.NaN</code>.
    * ```DoubleType```:  equivalent to Scala <code>Double.NaN</code>.
 
 #### Positive/Negative Infinity Semantics
 
 There is special handling for positive and negative infinity. They have the following semantics:
 
  * Positive infinity multiplied by any positive value returns positive infinity.
  * Negative infinity multiplied by any positive value returns negative infinity.
  * Positive infinity multiplied by any negative value returns negative infinity.
  * Negative infinity multiplied by any negative value returns positive infinity.
  * Positive/negative infinity multiplied by 0 returns NaN.
  * Positive/negative infinity is equal to itself.
  * In aggregations, all positive infinity values are grouped together. Similarly, all negative infinity values are grouped together.
  * Positive infinity and negative infinity are treated as normal values in join keys.
  * Positive infinity sorts lower than NaN and higher than any other values.
  * Negative infinity sorts lower than any other values.
 
 #### NaN Semantics
 
 There is special handling for not-a-number (NaN) when dealing with `float` or `double` types that
 do not exactly match standard floating point semantics.
 Specifically:
 
  * NaN = NaN returns true.
  * In aggregations, all NaN values are grouped together.
  * NaN is treated as a normal value in join keys.
  * NaN values go last when in ascending order, larger than any other numeric value.
 
 #### Examples
 
 ```sql
 SELECT double('infinity') AS col;
 +--------+
 |     col|
 +--------+
 |Infinity|
 +--------+
 
 SELECT float('-inf') AS col;
 +---------+
 |      col|
 +---------+
 |-Infinity|
 +---------+
 
 SELECT float('NaN') AS col;
 +---+
 |col|
 +---+
 |NaN|
 +---+
 
 SELECT double('infinity') * 0 AS col;
 +---+
 |col|
 +---+
 |NaN|
 +---+
 
 SELECT double('-infinity') * (-1234567) AS col;
 +--------+
 |     col|
 +--------+
 |Infinity|
 +--------+
 
 SELECT double('infinity') < double('NaN') AS col;
 +----+
 | col|
 +----+
 |true|
 +----+
 
 SELECT double('NaN') = double('NaN') AS col;
 +----+
 | col|
 +----+
 |true|
 +----+
 
 SELECT double('inf') = double('infinity') AS col;
 +----+
 | col|
 +----+
 |true|
 +----+
 
 CREATE TABLE test (c1 int, c2 double);
 INSERT INTO test VALUES (1, double('infinity'));
 INSERT INTO test VALUES (2, double('infinity'));
 INSERT INTO test VALUES (3, double('inf'));
 INSERT INTO test VALUES (4, double('-inf'));
 INSERT INTO test VALUES (5, double('NaN'));
 INSERT INTO test VALUES (6, double('NaN'));
 INSERT INTO test VALUES (7, double('-infinity'));
 SELECT COUNT(*), c2 FROM test GROUP BY c2;
 +---------+---------+
 | count(1)|       c2|
 +---------+---------+
 |        2|      NaN|
 |        2|-Infinity|
 |        3| Infinity|
 +---------+---------+
 ```

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