![]() ![]() Try It SQLite MAX function in the subquery example To get the largest track in bytes, you apply the MAX function to the bytes column as the following statement: SELECT MAX( bytes) FROM tracks Code language: SQL (Structured Query Language) ( sql ) We’ll use the tracks table in the sample database for the demonstration. Third, because a column can store mixed types of data e.g., integer, real, text, blob, and NULL in SQLite, when comparing values to find the maximum value, the MAX function uses the rules mentioned in the data types tutorial.Second, unlike the COUNT function, the DISTINCT clause is not relevant to the MAX function.First, the MAX function ignores NULL values.There are some important notes about MAX function: The expression can be a column of a table or an expression that consists of operands, which are the columns, and operators like +, *, etc. MAX( expression) Code language: SQL (Structured Query Language) ( sql ) The following illustrates the basic syntax of the MAX function. You can use the MAX function to accomplish a lot of things.įor example, you can use the MAX function to find the most expensive products, find the biggest item in its group, etc. ![]() The SQLite MAX function is an aggregate function that returns the maximum value of all values in a group. SQL Standard and Multiple Vendor “UPPERCASE” Types.Summary: in this tutorial, you will learn how to use SQLite MAX function to get the maximum value of all values in a group. Reference for the general set of “UPPERCASE” datatypes is below at SQL types that typically expect to be available on at least two backends The “UPPERCASE” datatypes that are part of sqlalchemy.types are common ![]() INTEGER, and TIMESTAMP, which inherit directlyįrom the previously mentioned “CamelCase” types Of UPPERCASE types include VARCHAR, NUMERIC, Of “UPPERCASE” types in a SQLAlchemy application indicates that specificĭatatypes are required, which then implies that the application would normally,īe limited to those backends which use the type exactly as given. Whether or not the current backend supports it. The name of the type is always rendered exactly as given, without regard for Theseĭatatypes are always inherited from a particular “CamelCase” datatype, andĪlways represent an exact datatype. In contrast to the “CamelCase” types are the “UPPERCASE” datatypes. Reference for the general set of “CamelCase” datatypes is below at “CamelCase” types in the general case, as they will generally provide the bestīasic behavior and be automatically portable to all backends. The typical SQLAlchemy application will likely wish to use primarily Interpreting Python numeric or boolean values. As data is sent and receivedįrom the database using this type, based on the dialect in use it may be May render BOOLEAN on a backend such as PostgreSQL, BIT on the Or BIT values 0 and 1, some have boolean literal constants true andįalse while others dont. Not every backend has a real “boolean” datatype some make use of integers Which represents a string datatype that all databases have, If arguments are needed, such as the lengthĪrgument of 60 in the "email_address" column above, the type may beĪnother “CamelCase” datatype that expresses more backend-specific behavior Table definition or in any SQL expression overall, if noĪrguments are required it may be passed as the class itself, that is, without When using a particular TypeEngine class in a
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