![]() ![]() To allow DuckDB to fully integrate with these encoded structures, we implemented Enum Types. By lowering RAM usage, ENUMs also allow DuckDB to scale to significantly larger datasets. Pandas Categorical and R Factors are types that allow for columns of strings with many duplicate entries to be efficiently stored through dictionary encoding.ĭictionary encoding not only allows immense storage savings but also allows systems to operate on numbers instead of on strings, drastically boosting query performance. Environments like Pandas and R support these types more elegantly. In the old times, users would manually perform dictionary encoding by creating lookup tables and translating their ids back with join operations. ![]() The category stores the actual strings, and the values stores a reference to the strings. In dictionary encoding, the data is split into two parts: the category and the values. A better solution is to dictionary encode these columns. Storing a data type as a plain string causes a waste of storage and compromises query performance. For example, a country column will never have more than a few hundred unique entries. However, often string columns have a limited number of distinct values. String types are one of the most commonly used types. The Fellowship of the Categorical and Factors. Pedro Holanda DuckDB - The Lord of Enums:
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