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May 2015

I’m a Millionaire now!

At least regarding the hits on this Blog :-) Thank you all for visiting uhesse.com!

Log Buffer #422: A Carnival of the Vanities for DBAs

This Log Buffer Edition picks, choose and glean some of the top notch blog posts from Oracle, SQL Server and MySQL.

Oracle:

What happens to the Standby when you move a datafile on the Primary?

In 12c, we have introduced online datafile movement as a new feature. Now does that impact an existing standby database? I got asked that yesterday during an online webinar. My answer was that I expect no impact at all on the standby database since redo apply doesn’t care about the physical placement of the datafile on the primary. But I added also that this is just an educated guess because I didn’t test that yet. Now I did:

Cost

I’ve just been checking “Cost Based Oracle – Fundamentals” (Apress 2005) to see what I said on a particular topic, and I couldn’t resist quoting the following from the opening page of Chapter 1:

One of the commonest questions about the CBO on the Internet is: “What does the cost represent?” This is usually followed by comments like: “According to explain plan the cost of doing a hash join for this query is seven million and the cost of a nested loop is forty-two – but the hash join completes in three seconds and the nested loop takes 14 hours.”

The answer is simple: the cost represents (and has always represented) the optimizer’s best estimate of the time it will take to execute the statement. But how can this be true when people can see oddities like the hash join / nested loop join example above? The answer can usually be found in that good old acronym GIGO: Garbage In, Garbage Out.

Heuristic Temp Table Transformation - 2

Some time ago I've demonstrated the non-cost based decision for applying the temp table transformation when using CTEs (Common Table/Subquery Expressions). In this note I want to highlight another aspect of this behaviour.Consider the following data creating a table with delibrately wide columns:


create table a
as
select
rownum as id
, rownum as id2
, rpad('x', 4000) as large_vc1
, rpad('x', 4000) as large_vc2
, rpad('x', 4000) as large_vc3
from
dual
connect by
level <= 1000
;

exec dbms_stats.gather_table_stats(null, 'a')

Friday Philosophy – Know Your Audience

There are some things that are critical for businesses that can be hidden or of little concern to those of us doing a technical job. One of those is knowing who your customers are. It is vital to businesses to know who is buying their products or services. Knowing who is not and never will buy their products is also important (don’t target the uninterested) and knowing and who is not currently buying and might is often sold as the key to ever growing market share and profit. But fundamentally, they need to know who the current customers are, so they can be looked after {I know, some businesses are shocking to current customers, never understood that}.

This should also be a concern to me.

OpenTSDB and Google Cloud Bigtable

Data comes in different shapes. One of the these shapes is called a time series. Time series is basically a sequence of data points recorded over time. If, for example, you measure the height of the tide every hour for 24 hours, then you will end up with a time series of 24 data points. Each data point will consist of tide height in meters and the hour it was recorded at.