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Spectre and Meltdown on Oracle Public Cloud UEK – LIO

In the last post I published the strange results I had when testing physical I/O with the latest Spectre and Meltdown patches. There is the logical I/O with SLOB cached reads.

Spectre/Meltdown on Oracle Public Cloud UEK – PIO

The Spectre and Meltdown is now in the latest Oracle UEK kernel, after updating it with ‘yum update':

[opc@PTI ~]$ rpm -q --changelog kernel-uek
| awk '/CVE-2017-5715|CVE-2017-5753|CVE-2017-5754/{print $NF}' | sort | uniq -c
43 {CVE-2017-5715}
16 {CVE-2017-5753}
71 {CVE-2017-5754}

As I did on the previous post on AWS, I’ve run quick tests on the Oracle Public Cloud.

Physical reads

I’ve run some SLOB I/O reads with the patches, as well sit KPTI disabled, and with KPTI, IBRS and IBPB disabled.

And I was quite surprised by the result:

Spectre and Meltdown, Oracle Database, AWS, SLOB

Last year, I measured the CPU performance for an Oracle Database on several types of AWS instances. Just by curiosity, I’ve run the same test (SLOB cached reads) now that Amazon has applied all Spectre and Meltdown mitigation patches.

I must admit that I wanted to test this on the Oracle Cloud first. I’ve updated a IaaS instance to the latest kernel but the Oracle Unbreakable Enterprise Kernel does not include the Meltdown fix yet, and booting on the Red Hat Compatible Kernel quickly goes to a kernel panic not finding the root LVM.

Google Cloud Platform instances and Oracle Database

When it comes to choose a cloud instance to run Oracle Database, you want to be able to run your workload on the minimum CPU cores. This is why in a previous post I measured how many logical reads per seconds can be achieved with a SLOB workload, on AWS which is often the first considered, and will probably do it on Azure in the future. I did the same on the Oracle Cloud which is the only one where Oracle make it easy to run an license the Oracle Database.

SLOB 2.3 Data Loading Failed? Here’s a Quick Diagnosis Tip.

The upcoming SLOB 2.4 release will bring improved data loading error handling. While still using SLOB 2.3, users can suffer data loading failures that may appear–on the surface–to be difficult to diagnose.

Before I continue, I should point out that the most common data loading failure with SLOB in pre-2.4 releases is the concurrent data loading phase suffering lack of sort space in TEMP. To that end, here is an example of a SLOB 2.3 data loading failure due to shortage of TEMP space. Please notice the grep command (in Figure 2 below) one should use to begin diagnosis of any SLOB data loading failure:

Is SLOB AWR Generation Really, Really, Really Slow on Oracle Database 11.2.0.4? Yes, Unless…

If you are testing SLOB against 11.2.0.4 and find that the AWR report generation phase of runit.sh is taking an inordinate amount of time (e.g., more than 10 seconds) then please be aware that, in the SLOB/awr subdirectory, there is a remedy script rightly called 11204-awr-stall-fix.sql.

Simply execute this script when connected to the instance with sysdba privilege and the problem will be solved. 

Announcing SLOB 2.2 : Think Time and Limited-Scope User-Data Modification

This is a hasty blog post to get SLOB 2.2 out to those who are interested.

Where To Get The Kit

Please visit kevinclosson.net/slob

About The New Kit

In addition to doing away with the cumbersome “seed” table and procedure.sql, this kit introduces 5 new slob.conf parameters. By default these parameters are disabled.

This SLOB distribution does not require re-executing setup.sh. One can simply adopt the kit and use it to test existing SLOB databases. The following explains the new slob.conf parameters:

DO_UPDATE_HOTSPOT=FALSE

When set to TRUE, modify SQL will no longer affect random rows spanning each session’s schema. Instead, each session will only modify HOTSPOT_PCT percent of their data.

SLOB Physical I/O Randomness. How Random Is Random? Random!

I recently read a blog post by Kyle Hailey regarding some lack of randomness he detected in the Orion I/O generator tool. Feel free to read Kyle’s post but in short he used dtrace to detect Orion was obliterating a very dense subset of the 96GB file Orion was accessing.

Interesting SLOB Use Cases – Part I. Studying ZFS Fragmentation. Introducing Bart Sjerps.

This is the first installment in a series of posts I’m launching to share interesting use cases for SLOB. I have several installments teed up but to put a spin on things I’m going to hit two birds with one stone in this installment. The first bird I’ll hit is to introduce a friend and colleague, Bart Sjerps, who I just added to my blogroll. The other bird in my cross-hairs is this interesting post Bart wrote some time back that covers a study of ZFS fragmentation using SLOB.

Bart Sjerps on ZFS Fragmentation. A SLOB study.

As always, please visit the SLOB Resources Page for SLOB kit and documentation.