These types may be defined with parameters representing precision and scale, where precision is the number of significant digits that can be stored, and scale is the number of digits following the decimal point. The two defined types for SQL are NUMERIC and DECIMAL, which are synonyms of each other. These numbers are exact (unlike the floating point types described below) and permit exact mathematical operations where possible (addition, subtraction, and multiplication). Exact decimal numbers ¶ĭecimal number types allow for exact storage of numbers that have digits to the right of the decimal point, e.g., 1234.56789. Additional integer types may be available for your database system. Not all databases recognize all of these types, but INTEGER is recognized by all of the databases considered for this book.
Implementations of these types vary, but it is not uncommon for INTEGER (often abbreviated as INT) to store 32-bit integers, SMALLINT 16-bit integers, and BIGINT 64-bit integers. SQL defines three integer types: INTEGER, SMALLINT, and BIGINT.
SQLITE DATA TYPES FULL
However, actual implementation of the standard varies quite a bit see Appendix B - Number types for a full discussion of number types. SQL provides support for several different types of numbers, each with different applications and limitations.
In this section we survey the major data types, without discussion of database compatibility for more information, see Appendix B - Data types. For all of these reasons, you will want to consult your database system’s documentation to understand the types available to you. Unusually, SQLite is dynamically typed, and you can store values of any type in any column no matter how the column is defined. Most database systems define additional, non-standard types for various uses. While most of the basic types exist in all relational database systems, actual implementation of the types varies quite a bit. The SQL standard defines several basic data types with which columns can be associated. before any data is put into the table).This chapter will discuss basic table creation, starting with an explanation of SQL data types. I'm trying to confirm what internal data type affinity SQLite determined for the column from the TABLE CREATE statement (e.g. This is helpful, but is the answer to a different question. This shows the storage class SQLite used to actually save the data. How do you reliably access data types and the internal storage class affinity in SQLite using code? provided a useful comment: Run the query SELECT typeof(field_name) FROM table_name and process the rows. Also, why is the type fronk understood at all? The examples given in the SQLite documentation do not mention the "MEMO" or "BIT" types, though they appear to have been processed. (2) "DATA_TYPE" and "EDM_TYPE" values taken directly from the "Columns" schema TypeNameEntity = (string)row ĬOLUMN NAME CREATE ASSUMED AFFINITY(1) DATA_TYPE(2) EDM_TYPE(2)įloat_Decimal DECIMAL NUMERIC decimal decimalįloat_Currency CURRENCY NUMERIC currency decimalĭate_DateTime DATETIME NUMERIC datetime datetime ((DbConnection)connection).GetSchema("Columns", columnRestrictions) įoreach (DataRow row in schemaColumns.Rows)
SQLITE DATA TYPES CODE
Sample C# code using the wrapper in Visual Studio 2019 on this table: - SQL CREATE TABLE what SQLite interpreted as the data type hint from the CREATE TABLE statement). The recommendation is not a requirement as in other database systems, and the column can store data in any type.Īm looking for a programmatic way to access the affinity for a column (i.e. Rather a data type "affinity" is defined which is the recommended data type for the column. The SQLite3 documentation on data types makes it clear that SQLite does not enforce column data types.
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