Incremental statistics reduce the time to gather global statistics for a partitioned table. Really? In some situations it may happen that incremental statistics slow down statistics calculation dramatically. An example of a real project in Oracle 12.1 and how it can be improved with Oracle 12.2.
For the first time, I had the chance to attend and speak at the UKOUG Technology Conference. In these three days at UKOUG Tech17 in Birmingham, I attended some very good sessions, had many interesting discussions about Oracle databases, data warehousing and performance tuning, met nice people and tasted a lot of chocolate.
This year, I had the opportunity to present three sessions at the DOAG conference in Nuremberg – one on each conference day. Here a short summary of the sessions and links to the downloads.
Hash keys are often used as primary keys in Data Vault environments. When loading dimensional data marts from a Data Vault schema, it seems to be obvious to use them as dimension keys, too. At least in combination with Oracle Database In-Memory, this is not a good idea.
With Oracle Database In-Memory, it is possible to populate individual columns of a table into the In-Memory Column Store. This is very useful for large tables, if only the frequently used columns should be populated to safe memory. The SQL syntax to define this seems to be straight-forward, but does not always work as expected.
Analytic Views, in combination with Attribute Dimensions and Hierarchies, are very useful for ad-hoc queries in a Star Schema. But how about the performance of this Oracle 12.2 feature? I wanted to know it and analyzed the execution plans of some simple queries.
In summer time, the nights are very short. For some Data Warehouses, this is the case all year round, but not because of late sunset and early sunrise. The night is not long enough to finish all the ETL jobs. Long-running load jobs that run for several hours are not a seldom situation. Here some tips how this can be avoided.