Improving column compression

If you see slow performance or a large storage footprint with your FLOAT data, evaluate the data and your business needs to see if it can be contained in a NUMERIC column with a precision of 18 digits or less.

If you see slow performance or a large storage footprint with your FLOAT data, evaluate the data and your business needs to see if it can be contained in a NUMERIC column with a precision of 18 digits or less. Converting a FLOAT column to a NUMERIC column can improve data compression, reduce the on-disk size of your database, and improve performance of queries on that column.

When you define a NUMERIC data type, you specify the precision and the scale; NUMERIC data are exact representations of data. FLOAT data types represent variable precision and approximate values; they take up more space in the database.

Converting FLOAT columns to NUMERIC columns is most effective when:

  • NUMERIC precision is 18 digits or less. Performance of NUMERIC data is fine-tuned for the common case of 18 digits of precision. Vertica recommends converting FLOAT columns to NUMERIC columns only if they require precision of 18 digits or less.

  • FLOAT precision is bounded, and the values will all fall within a specified precision for a NUMERIC column. One example is monetary values like product prices or financial transaction amounts. For example, a column defined as NUMERIC(11,2) can accommodate prices from 0 to a few million dollars and can store cents, and compresses more efficiently than a FLOAT column.

If you try to load a value into a NUMERIC column that exceeds the specified precision, Vertica returns an error and does not load the data. If you assign a value with more decimal digits than the specified scale, the value is rounded to match the specified scale and stored in that column.

See also

Numeric data types