This is the second part of a series of blogpost on Oracle database PGA usage. See the first part here. The first part described SGA and PGA usage, their distinction (SGA being static, PGA being variable), the problem (no limitation for PGA allocations outside of sort, hash and bitmap memory), a resolution for Oracle 12 (PGA_AGGREGATE_LIMIT), and some specifics about that (it doesn’t look like a very hard limit).
But this leaves out Oracle version 11.2. In reality, the vast majority of the database that I deal with at the time of writing is at version 11.2, and my guess is that this is not just the databases I deal with, but a general tendency. This could change in the coming time with the desupport of Oracle 11.2, however I suspect the installed base of Oracle version 12 to increase gradually and smoothly instead of in a big bang.
This post is about memory management on the operating system level of an Oracle database. The first question that might pop in your head is: isn’t this a solved problem? The answer is: yes, if you use Oracle’s AMM (Automatic Memory Management) feature, which let’s you set a limit for the Oracle datababase’s two main memory area’s: SGA and PGA. But in my opinion any serious, real life, usage of an Oracle database on Linux will be (severely) constrained in performance because of the lack of huge pages with AMM, and I personally witnessed very strange behaviour and process deaths with the AMM feature and high demand for memory.
One of the many interesting things I heard at the conference this time around was that Oracle’s future direction includes the use of database files on ACFS. When ACFS came out this was strictly ruled out, but has been possible for a little while now, I believe with 22.214.171.124.0. With the Oracle Database Appliance (ODA) using this deployment option and hearing about it at the conference, a little further investigation was in order. During one of the presentation @OracleRACPM Markus Michalewicz had a reference to a script that I didn’t know on his slides. The script is called gDBClone, and I wanted to see how it works. The idea is that the script can be used to create a snap-clone of a database if the source is on ACFS and in archivelog mode.
As it turned out there were a few hurdles along the way and I will point them out so you don’t run into the same issues.
This is a little note, primarily to myself I guess, about the creation of the order entry schema (part of Swingbench, written by Dominic Giles) when no VNC sessions are available (although you can almost always use port-forwarding :). Instead, you can create the schema on the command line. I always execute commands on remote systems in screen for increased peace of mind. Should the network drop, the order entry generation will continue as if nothing ever happened.
Like many others I use Swingbench during trainings and presentations to have some activity on a system. Very useful for demonstrating ASH and OEM, and many other things too!
I posted a fair amount of stuff on how Oracle is generating IOs, and especially large IOs, meaning more than one Oracle block, so > 8KB. This is typically what is happening when the Oracle database is executing a row source which does a full segment scan. Let’s start off with a quiz: what you think Oracle is the maximum IO size the Oracle engine is capable of requesting of the Operating System (so the IO size as can be seen at the SCI (system call interface) layer? If you made up your answer, remember it, and read on!
The real intention of this blogpost is to describe what is going on in the Oracle database kernel, but also what is being done in the Linux kernel. Being a performance specialised Oracle DBA means you have to understand what the operating system does. I often see that it’s of the utmost importance to understand how an IO ends up as a request at the NAS or SAN head, so you understand what a storage admin is talking about.
Prompted by an actual task at hand I spent some time investigating an 126.96.36.199 feature – concurrent statistics gathering. It has been on my to-do list for quite some time but so far I didn’t have a use case, and use cases make it so much easier. The question was-how can I gather statistics on a really large, partitioned table? Previously, you could revert to the degree in dbms_stats.gather_table_stats to ensure that statistics were gathered in parallel. This is all good, but sometimes you need more umph. Some DBAs wrote scripts to execute individual statistic gathering jobs against partitions in parallel, using the tabname and partname arguments in dbms_stats.gather_table_stats(). But that requires manual effort – and the not-quite-so-new concurrent option is so much nicer. Let me take you along the ride… Actually I have to tell the story starting with the happy ending as I had a few snags along the way. This is 188.8.131.52.1 on Oracle Linux 6.5.
If you ever wanted to know how Clusterware works with registered database resources, read on! It takes a little while to get your head around the concepts of the ORACLE_SID, the instance_name and the database name as well. And how Clusterware deals with all of them. Although this post has been written on 184.108.40.206.0 on Linux, it should be applicable to 11.2 Clusterware as well. Oh and by Clusterware I mean Grid Infrastructure of course ;)
Why would you want to care?
Most deployments I have seen use the simple formula: ORACLE_SID = instance_name = db_name, especially in single instance deployments. RAC One Node and RAC databases are slightly different as their instances are usually named db_name where is the n-th instance in the cluster. What however, if you want to have separate SID, instance name and database names? I keep things simple for now and don’t throw in a different db_unique_name…
My lab server has 2 SSDs, one is connected using SATA 2 and another is connected using SATA 3. I’d expect the SATA 3 connected device to be equally well equipped or even better to do work than the “old” interface. I ran SLOB on these devices to find out if there was a difference. To my great surprise the SATA2 – connected SSD performed a lot better than the SATA 3 device, as shown in the AWR report! Initially I was not entirely sure why, since the FIO results on both devices are roughly equal. You will see why though when reading this post. In summary: use XFS for any concurrent writes. Or maybe ASM.
Let’s do a little I/O investigation because a) it’s cool and b) you can.
This is a quick post on using git on a server. I use my Synology NAS as a fileserver, but also as a git repository server. The default git package for Synology enables git usage on the command line, which means via ssh, or via web-DAV. Both require a logon to do anything with the repository. That is not very handy if you want to clone and pull from the repository in an automated way. Of course there are ways around that (basically setting up password-less authentication, probably via certificates), but I wanted simple, read-only access without authentication. If you installed git on a linux or unix server you get the binaries, but no daemon, which means you can only use ssh if you want to use that server for central git repositories.
Some of you might have followed the discussion around the number of standby redo logs on twitter, but since 140 characters are woefully short for the complete story here’s the writeup that prompted the question. This is a test with 220.127.116.11 on virtualised Linux, repeated on a proper platform with physical hardware.
First of all here’s my setup. I have a dbca-based database (CDB, but doesn’t matter) that features 3 groups for its online redo logs. They are all 50 MB in size-important for this test, but not realistic :) Following the Oracle documentation I created n + 1 groups (per thread) on the standby to stop Data Guard broker from complaining about missing standby redo logs (SRL).
The end result was positive, here’s what the broker thinks: