Scaling Python with Dask by Holden Karau

Author:Holden Karau
Language: eng
Format: epub
Publisher: O'Reilly Media
Published: 2023-07-26T00:00:00+00:00

Tip

Dask DataFrame is not value-mutable in the way that pandas DataFrame users might be familiar with. Since in-memory modification of a particular value is not possible, the only way to change a value would be a map operation over the whole column of the entire DataFrame. If an in-memory value change is something you have to do often, it is better to use an external database.

Porting SQL to Dask

Dask does not natively offer a SQL engine, although it does natively offer options to read from a SQL database. There are a number of different libraries you can use to interact with an existing SQL database, and to treat Dask DataFrame as a SQL table and run SQL queries directly (see Example 9-4). Some allow you to even build and serve ML models directly using SQL ML syntax similar to that of Google’s BigQuery ML. In Examples 11-14 and 11-15, we will show the use of Dask’s native read_sql() function and running SQL ML using Dask-SQL.

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