Vertica Audit: Things To Know

The advancement of technology has provided end number of effective tools to the human race. Whatever complicated acts you perform in your work place, you are always getting the assistance of technology. Such an effective tool happens to be Vertica software that enables to keep a track of all the ongoing activities. The software includes large data storage allowance which comprises of data in columnar and flex tables. The audit function is one of the most important and effective activity that is being performed through this software. It enables the amount of raw data that are available in the columnar and flex tables.



It can also audit the size of tables, projections, schemas and databases that can be accessed by the user. Someone who does not have the access can only read the estimated size of the data. The software involves the permissions of two options namely the Select privilege on the table and Usage privilege on the Schema. The function works only in case of the Select option. The software also involves four major parameters which happen to be name, granularity, error tolerance and confidence level. The name parameter specifies the schema, projection or table to the Audit.



The granularity happens to be the same level as name. The audit reports the size of each table in the Schema. The Vertica Audit determines whether the size of the database complies with the license’s data allowance. Since the audit of a table has no effect, the granularity must be finer than the object. The error tolerance specifies the margin of error allowed in the audit estimate. The tolerance value has to be entered in the decimal number. The lower is the value; the more is the resources the audit uses since it performs more data sampling. The value of zero is very much resource intensive as all of the data in the database is analyzed.



The confidence level specifies the statistical confidence level percentage of the estimate. Here the default value is 99 which indicate a confidence level of 99%.  The higher the confidence value, the more resources the function uses since it performs more data sampling. Performing a full audit of the database significantly impacts the performance and it is not recommended to go for it when it comes to a production database. The size of the database is reported in bytes.