I don’t like the ‘C’ word, it’s offensive to some people and gets used way too much. I mean “cloud” of course. Across all of I.T. it’s the current big trend that every PR department seems to feel the need to trump about and it’s what all Marketing people are trying to sell us. I’m not just talking Oracle here either, read any computing, technical or scientific magazine and there are the usual adds by big I.T. companies like IBM and they are all pushing clouds (and the best way to push a cloud is with hot air). And we’ve been here before so many times. It’s not so much the current technical trend that is the problem, it is the obsession with the one architecture as the solution to fit all requirements that is damaging.
There are some questions about Oracle that are like the mythical Hydra – you think you’ve killed it, but for every head you cut off another two grow. The claim that “the optimizer will switch between using an index and doing a tablescan when you access more than X% of the data” re-appeared on the OTN database forum a little while ago – it doesn’t really matter what the specific value of X was – and it’s a statement that needs to be refuted very firmly because it’s more likely to cause problems than it is to help anyone understand what’s going on.
I’ll be at Collaborate 16 next month and looking forward to seeing lots of good friends, learning some new things, and sharing a little experience too. For the last of those, I’ll present 3 sessions, er, more like 2.2 sessions:
The following is probably only relevant for customers that run Oracle on big servers with lots of cores in single instance mode (this specific problem here doesn't reproduce in a RAC environment, see below for an explanation why), like one of my clients that makes use of the Exadata Xn-8 servers, for example a X4-8 with 120 cores / 240 CPUs per node (but also reproduced on older and smaller boxes with 64 cores / 128 CPUs per node).
The intention of this blogpost is to show the Oracle wait time granularity and the Oracle database time measurement granularity. One of the reasons for doing this, is the Oracle database switched from using the function gettimeofday() up to version 11.2 to clock_gettime() to measure time.
This switch is understandable, as gettimeofday() is a best guess of the kernel of the wall clock time, while clock_gettime(CLOCK_MONOTONIC,…) is an monotonic increasing timer, which means it is more precise and does not have the option to drift backward, which gettimeofday() can do in certain circumstances, like time adjustments via NTP.
The first thing I wanted to proof, is the switch of the gettimeofday() call to the clock_gettime() call. This turned out not to be as simple as I thought.
This is the second blogpost on using PL/SQL inside SQL. If you landed on this page and have not read the first part, click this link and read that first. I gotten some reactions on the first article, of which one was: how does this look like with ‘pragma udf’ in the function?
Pragma udf is a way to speed up using PL/SQL functions in (user defined function), starting from version 12. If you want to know more about the use of pragma udf, and when it does help, and when it doesn’t, please google for it.
create or replace function add_one( value number ) return number is pragma udf; l_value number(10):= value; begin return l_value+1; end; / select sum(add_one(id)) from t2;
As you can see, really the only thing you have to do is add ‘pragma udf’ in the declaration section of PL/SQL.
Whenever you use PL/SQL in SQL statements, the Oracle engine needs to switch from doing SQL to doing PL/SQL, and switch back after it is done. Generally, this is called a “context switch”. This is an example of that:
-- A function that uses PL/SQL create or replace function add_one( value number ) return number is l_value number(10):= value; begin return l_value+1; end; / -- A SQL statement that uses the PL/SQL function select sum(add_one(id)) from t2;
Of course the functionality of the function is superfluous, it can easily be done in ‘pure’ SQL with ‘select sum(id+1) from t2’. But that is not the point.
Also, I added a sum() function, for the sake of preventing output to screen per row.
There’s been a lot of work in the area of profiling. One of the things I have recently fallen in love with is Brendan Gregg’s flamegraphs. I work mainly on Linux, which means I use perf for generating stack traces. Luca Canali put a lot of effort in generating extended stack profiling methods, including kernel (only) stack traces and CPU state, reading the wait interface via direct SGA reading and kernel stack traces and getting userspace stack traces using libunwind and ptrace plus kernel stack and CPU state. I was inspired by the last method, but wanted more information, like process CPU state including runqueue time.
This post is about manually calling and freeing a shared latch. Credits should go to Andrey Nikolaev, who has this covered in his presentation which was presented at UKOUG Tech 15. I am very sorry to see I did miss it.
Essentially, if you follow my Oracle 12 and shared latches part 2 blogpost, which is about shared latches, I showed how to get a shared latch:
SQL> oradebug setmypid Statement processed. SQL> oradebug call ksl_get_shared_latch 0x94af8768 1 0 2303 16 Function returned 1
Which works okay, but leaves a bit of a mess when freed:
In the last 14 months I delivered a dozen of presentations covering the In-Memory Column Store. During many of them, I spent most of the time showing the audience several demos. The aim of this post is to share with you the scripts and a recording (MP4) of those demos.
Warning about Demos
The recordings show the results of running the scripts on an Exadata system. The performance figures are intended only to explain and compare different kinds of processing and to give you a feel for their impact. Since every system and every application has its own characteristics, the relevance of using each technique might be very different, depending on where it’s applied. Simply put, the scripts were engineered to clearly show specific behaviors.
In case you want to run the scripts, to setup the environment run imcs_prepare_schema.sql.