# Data Type Conversions

When saving a DataFrame to SingleStore, the DataFrame column is converted to the following SingleStore type:

| Spark Type    | SingleStoreType |
| ------------- | --------------- |
| LongType      | BIGINT          |
| IntegerType   | TINYINT         |
| ShortType     | SMALLINT        |
| FloatType     | FLOAT           |
| DoubleType    | DOUBLE          |
| ByteType      | TINYINT         |
| StringType    | TEXT            |
| BinaryType    | BLOB            |
| DecimalType   | DECIMAL         |
| BooleanType   | TINYINT         |
| TimeStampType | TIMESTAMP(6)    |
| DateType      | DATE            |

When reading a SingleStore table as a Spark DataFrame, the SingleStore column type is converted to the following Spark type:

| SingleStoreType | SparkType     |
| --------------- | ------------- |
| TINYINT         | ShortType     |
| SMALLINT        | ShortType     |
| INT             | IntegerType   |
| BIGINT          | LongType      |
| DOUBLE          | DoubleType    |
| FLOAT           | FloatType     |
| DECIMAL         | DecimalType   |
| TIMESTAMP       | TimeStampType |
| TIMESTAMP(6)    | TimeStampType |
| DATE            | DateType      |
| TEXT            | StringType    |
| JSON            | StringType    |
| TIME            | TimeStampType |
| BIT             | BinaryType    |
| BLOB            | BinaryType    |

## Data Type Conversion Remarks

* When using the `onDuplicateKeySQL` option, the connector will error when writing a null-terminated StringType (i.e., *\0*).
* `DECIMAL` in SingleStore and `DecimalType` in Spark have different maximum scales and precisions. An error will occur if you perform a read or write from a table or DataFrame with unsupported precision or scale. SingleStore’s maximum scale for the `DECIMAL` data type is 30, while Spark’s maximum scale for `DecimalType` is 38. Similarly, SingleStore’s maximum precision is 65, while Spark’s maximum precision is 38.
* `TIMESTAMP` in SingleStore supports values from 1000 to 2147483647999. SingleStore treats a null value in the `TIMESTAMP` column as the current time.
* The Avro format does not support writing `TIMESTAMP` and `DATE` types. As a result, the SingleStore Spark Connector currently does not support these types with Avro serialization.

***

Modified at: July 28, 2022

Source: [/db/v9.1/load-data/integrate-with-singlestore/load-data-from-spark/data-type-conversions/](https://docs.singlestore.com/db/v9.1/load-data/integrate-with-singlestore/load-data-from-spark/data-type-conversions/)

(An index of the documentation is available at /llms.txt)