This question came up recently when I was helping a customer migrate a large data warehouse to Oracle Database 11g. Prior to the upgrade, they were using an ESTIMATE_PERCENT of 0.000001, the smallest possible sample size allowed, when they gathering statistics on their larger tables. When I asked why they picked such a tiny sample size they said it was
because they needed statistics to be gathered extremely quickly after their daily load both at the partition and at the global level.
Since these large tables were partitioned, I thought they would be an excellent candidate for incremental statistics. However, in order to use incremental statistics gathering you have to let the ESTIMATE_PERCENT parameter default to AUTO_SAMPLE_SIZE. Although the customer saw the benefit of using incremental statistics they were not keen on changing the value of ESTIMATE_PERCENT. So I argued that with the new AUTO_SAMPLE_SIZE in Oracle Database 11g they would get statistics that were equivalent to a 100% sample but with the speed of a 10% sample. And since we would be using incremental statistics we would only have to gather statistics on the freshly loaded partition and the global statistics (table level statistics) would be automatically aggregated correctly.
So with much skepticism, they tried incremental statistics in their test system and they were pleasantly surprised at the elapse time. However, they didn’t trust the statistics that were gathered and asked me, “how
do I compare the statistics I got with AUTO_SAMPLE_SIZE to the statistics I normally get with an ESTIMATE_PERCENT of 0.000001?”
The answer to that was easy, ‘use DBMS_STAT.DIFF_TABLE_STATS