Archive for the 'Oracle 11g' Category

Oracle Exadata Database Machine I/O Bottleneck Revealed At… 157 MB/s! But At Least It Scales Linearly Within Datasheet-Specified Bounds!

It has been quite a while since my last Exadata-related post. Since I spend all my time, every working day, on Exadata performance work this blogging dry-spell should seem quite strange to readers of this blog. However, for a while it seemed to me as though I was saturating the websphere on the topic and Exadata is certainly more than a sort of  Kevin’s Dog and Pony Show. It was time to let other content filter up on the Google search results. Now, having said that, there have been times I’ve wished I had continued to saturate the namespace on the topic because of some of the totally erroneous content I’ve seen on the Web.

Most of the erroneous content is low-balling Exadata with FUD, but a surprisingly sad amount of content that over-hypes Exadata exists as well. Both types of erroneous content are disheartening to me given my profession. In actuality, the hype content is more disheartening to me than the FUD. I understand the motivation behind FUD, however, I cannot understand the need to make a good thing out to be better than it is with hype. Exadata is, after all, a machine with limits folks. All machines have limits. That’s why Exadata comes in different size configurations  for heaven’s sake! OK, enough of that.

FUD or Hype? Neither, Thank You Very Much!
Both the FUD-slinging folks and the folks spewing the ueber-light-speed, anti-matter-powered warp-drive throughput claims have something in common—they don’t understand the technology.  That is quickly changing though. Web content is popping up from sources I know and trust. Sources outside the walls of Oracle as well. In fact, two newly accepted co-members of the OakTable Network have started blogging about their Exadata systems. Kerry Osborne and Frits Hoogland have been posting about Exadata lately (e.g., Kerry Osborne on Exadata Storage Indexes).

I’d like to draw attention to Frits Hoogland’s investigation into Exadata. Frits is embarking on a series that starts with baseline table scan performance on a half-rack Exadata configuration that employs none of the performance features of Exadata (e.g., storage offload processing disabled). His approach is to then enable Exadata features and show the benefit while giving credit to which specific aspect of Exadata is responsible for the improved throughput. The baseline test in Frits’ series is achieved by disabling both Exadata cell offload processing and Parallel Query Option! To that end, the scan is being driven by a single foreground process executing on one of the 32 Intel Xeon 5500 (Nehalem EP) cores in his half-rack Database Machine.

Frits cited throughput numbers but left out what I believe is a critical detail about the baseline result—where was the bottleneck?

In Frits’ test, a single foreground process drives the non-offloaded scan at roughly 157MB/s. Why not 1,570MB/s (I’ve heard everything Exadata is supposed to be 10x)? A quick read of any Exadata datasheet will suggest that a half-rack Version 2 Exadata configuration offers up to 25GB/s scan throughput (when scanning both HDD and FLASH storage assets concurrently). So, why not 25 GB/s? The answer is that the flow of data has to go somewhere.

In Frits’ particular baseline case the data is flowing from cells via iDB (RDS IB) into heap-buffered PGA in a single foreground executing on a single core on a single Nehalem EP processor. Along with that data flow is the CPU cost paid by the foreground process in its marshalling all the I/O (communicating with Exadata via the intelligent storage layer) which means interacting with cells to request the ASM extents as per its mapping of the table segments to ASM extents (in the ASM extent map). Also, the particular query being tested by Frits performs a count(*) and predicates on a column. To that end, a single core in that single Nehalem EP socket is touching every row in every block for predicate evaluation. With all that going on, one should not expect more than 157MB/s to flow through a single Xeon 5500 core. That is a lot of code execution.

What Is My Point?
The point is that all systems have bottlenecks somewhere. In this case, Frits is creating a synthetic CPU bottleneck as a baseline in a series of tests. The only reason I’m blogging the point is that Frits didn’t identify the bottleneck in that particular test. I’d hate to see the FUD-slingers suggest that a half-rack Version 2 Exadata configuration bottlenecks at 157 MB/s for disk throughput related reasons about as badly as I’d hate to see the hype-spewing-light-speed-anti-matter-warp rah-rah folks suggest that this test could scale up without bounds. I mean to say that I would hate to see someone blindly project how Frits’ baseline test would scale with concurrent invocations. After all, there are 8 cores, 16 threads on each host in the Version 2 Database Machine and therefore 32/64 in a half rack (there are 4 hosts). Surely Frits could invoke 32 or 64 sessions each performing this query without exhibiting any bottlenecks, right? Indeed, 157 MB/s by 64 sessions is about 10 GB/s which fits within the datasheet claims. And, indeed, since the memory bandwidth in this configuration is about 19 GB/s into each Nehalem EP socket there must surely be no reason this query wouldn’t scale linearly, right? The answer is I don’t have the answer. I haven’t tested it. What I would not advise, however, is dividing maximum theoretical arbitrary bandwidth figures (e.g., the 25GB/s scan bandwidth offered by a half-rack) by a measured application throughput requirement  (e.g., Frits’ 157 MB/s) and claim victory just because the math happens to work out in your favor. That would be junk science.

Frits is not blogging junk science. I recommend following this fellow OakTable member to see where it goes.

Automatic Databases Automatically Detect Storage Capabilities, Don’t They?

Doug Burns has started an interesting blog thread about the Oracle Database 11g PARALLEL_IO_CAP_ENABLED parameter in his blog entry about Parallel Query and Oracle Database 11g. Doug is discussing Oracle’s new concept of built-in I/O subsystem calibration-a concept aimed at more auto-tuning database instances. The idea is that Oracle is trying to make PQ more aware of the down-wind I/O subsystem capability so that it doesn’t obliterate it with a flood of I/O. Yes, a kinder, gentler PQO.

I have to admit that I haven’t yet calibrated this calibration infrastructure. That is, I aim to measure the difference between what I know a given I/O subsystem is capable of and what DBMS_RESOURCE_MANAGER.CALIBRATE_IO thinks it is capable of. I’ll blog the findings of course.

In the meantime, I recommend you follow what Doug is up to.

A Really Boring Blog Entry
Nope, this is not just some look at that other cool blog over there post. At first glance I would hope that all the regular readers of my blog would wonder what value there is in throttling I/O all the way up in the database itself given the fact that there are several points at which I/O can/does get throttled downwind. For example, if the I/O is asynchronous, all operating systems have a maximum number of asynchronous I/O headers (the kernel structures used to track asynchronous I/Os) and other limiting factors on the number of outstanding asynchronous I/O requests. Likewise, SCSI kernel code is fit with queues of fixed depth and so forth. So why then is Oracle doing this up in the database? The answer is that Oracle can run on a wide variety of I/O subsystem architectures and not all of these are accessed via traditional I/O system calls. Consider Direct NFS for instance.

With Direct NFS you get disk I/O implemented via the remote procedure call interface (RPC). Basically, Oracle shoots the NFS commands directly at the NAS device as opposed to using the C library read/write routines on files in an NFS mount-which eventually filters down to the same thing anyway, but with more overhead. Indeed, there is throttling in the kernel for the servicing of RPC calls, as is the case with traditional disk I/O system calls, but I think you see the problem. Oracle is doing the heavy lifting that enables you to take advantage of a wide array of storage options-and not all of them are accessed with age-old traditional I/O libraries. And it’s not just DNFS. There is more coming down the pike, but I can’t talk about that stuff for several months given the gag order. If I could, it would be much easier for you to visualize the importance of DBMS_RESOURCE_MANAGER.CALIBRATE_IO. In the meantime, use your imagination. Think out of the box…way out of the box…

Databases are the Contents of Storage. Future Oracle DBAs Can Administer More. Why Would They Want To?

I’ve taken the following quote from this Oracle whitepaper about low cost storage:

A Database Storage Grid does not depend on flawless execution from its component storage arrays. Instead, it is designed to tolerate the failure of individual storage arrays.

In spite of the fact that the Resilient Low-Cost Storage Initiative program was decommissioned along with the Oracle Storage Compatability Program, the concepts discussed in that paper should be treated as a barometer of the future of storage for Oracle databases-with two exceptions: 1) Fibre Channel is not the future and 2) there’s more to “the database” than just the database. What do I mean by point 2? Well, with features like SecureFiles, we aren’t just talking rows and columns any more and I doubt (but I don’t know) that SecureFiles is the end of that trend.

Future Oracle DBAs
Oracle DBAs of the future become even more critical to the enterprise since the current “stove-pipe” style IT organization will invariably change. In today’s IT shop, the application team talks to the DBA team who talks to the Sys Admin team who tlks to the Storage Admin team. All this to get an application to store data on disk through a Oracle database. I think that will be the model that remains for lightly-featured products like MySQL and SQL Server, but Oracle aims for more. Yes, I’m only whetting your appetite but I will flesh out this topic over time. Here’s food for thought: Oracle DBAs should stop thinking their role in the model stops at the contents of the storage.

So while Chen Shapira may be worried that DBAs will get obviated, I’d predict instead that Oracle technology will become more full-featured at the storage level. Unlike the stock market where past performance is no indicator of future performance, Oracle has consistently brought to market features that were once considered too “low-level” to be in the domain of a Database vendor.

The IT industry is going through consolidation. I think we’ll see Enterprise-level IT roles go through some consolidation over time as well. DBAs who can wear more than “one hat” will be more valuable to the enterprise. Instead of thinking about “encroachment” from the low-end database products, think about your increased value proposition with Oracle features that enable this consolidation of IT roles-that is, if I’m reading the tea leaves correctly.

How to Win Friends and Influence People
Believe me, my positions on Fibre Channel have prompted some fairly vile emails in my inbox-especially the posts in my Manly Man SAN series. Folks, I don’t “have it out”, as they say, for the role of Storage Administrators. I just believe that the Oracle DBAs of today are on the cusp of being in control of more of the stack. Like I said, it seems today’s DBA responsibilities stop at the contents of the storage-a role that fits the Fibre Channel paradigm quite well, but a role that makes little sense to me. I think Oracle DBAs are capable of more and will have more success when they have more control. Having said that, I encourage any of you DBAs who would love to be in more control of the storage to look at my my post about the recent SAN-free Oracle Data Warehouse. Read that post and give considerable thought to the model it discusses. And give even more consideration to the cost savings it yields.

The Voices in My Head
Now my alter ego (who is a DBA, whereas I’m not) is asking, “Why would I want more control at the storage level?” I’ll try to answer him in blog posts, but perhaps some of you DBAs can share experiences where performance or availability problems were further exacerbated by finger pointing between you and the Storage Administration group.

Note to Storage Administrators
Please, please, do not fill my email box with vitriolic messages about the harmony today’s typical stove-pipe IT organization creates. I’m not here to start battles.

Let me share a thought that might help this whole thread make more sense. Let’s recall the days when an Oracle DBA and a System Administrator together (yet alone) were able to provide Oracle Database connectivity and processing for thousands of users without ever talking to a “Storage Group.” Do you folks remember when that was? I do. It was the days of Direct Attach Storage (DAS). The problem with that model was that it only took until about the late 1990s to run out of connectivity-enter the Fibre Channel SAN. And since SANs are spokes attached to hubs of storage systems (SAN arrays), we wound up with a level of indirection between the Oracle server and its blocks on disk. Perhaps there are still some power DBAs that remember how life was with large numbers of DAS drives (hundreds). Perhaps they’ll recall the level of control they had back then. On the other hand, perhaps I’m going insane, but riddle me this (and feel free to quote me elsewhere):

Why is it that the industry needed SANs to get more than a few hundred disks attached to a high-end Oracle system in the late 1990s and yet today’s Oracle databases often reside on LUNs comprised of a handful of drives in a SAN?

The very though of that twist of fate makes me feel like a fish flopping around on a hot sidewalk. Do you remember my post about capacity versus spindles? Oh, right, SAN cache makes that all better. Uh huh.

Am I saying the future is DAS? No. Can I tell you now exactly what model I’m alluding to? Not yet, but I enjoy putting out a little food for thought.

Oracle Database 11g Initialization Parameters. A Digest.

Howard Rogers has a series of blog entries about Oracle11g initialization parameters. I recommend it. Here is a link:

New and obsolete Oracle11g initialization parameters.

Oracle11g Automatic Memory Management – Part I. Linux Hugepages Support.

I spent the majority of my time in the Oracle Database 11g Beta program testing storage-related aspects of the new release. To be honest, I didn’t even take a short peek at the new Automatic Memory Management feature. As I pointed out the other day, Tanel Poder has started blogging about the feature.

If you read Tanel’s post you’ll see that he points out AMM-style shared memory does not use hugepages. This is because AMM memory segments are memory mapped files in /dev/shm. At this time, the major Linux distributions do not implement backing memory mapped files with hugepages as they do with System V-style IPC shared memory. The latter supports the SHM_HUGETLB flag passed to the shmget(P) call. It appears as though there was an effort to get hugepages support for memory mapped pages by adding MAP_HUGETLB flag support for the mmap(P) call as suggested in this kernel developer email thread from 2004. I haven’t been able to find just how far that proposed patch went however. Nonetheless, I’m sure Wim’s group is more than aware of that proposed mmap(P) support and if it is really important for Oracle Database 11g Automatic Memory Management, it seem likely there would be a 2.6 Kernel patch for it someday. But that begs the question: just how important are hugepages? Is it blasphemy to even ask the question?

Memory Mapped Files and Oracle Ports
The concept of large page tables is a bit of a porting nightmare. It will be interesting to see how the other ports deal with OS-level support for the dynamic nature of Automatic Memory Management. Will the other ports also use memory mapped files instead of IPC Shared Memory? If so, they too will have spotty large page table support for memory mapped files. For instance, Solaris 9 supported large page tables for mmap(2) pages, but only if it was an anonymous mmap (e.g., a map without a file) or a map of /dev/zero-neither of which would work for AMM. I understand that Solaris 10 supports large page tables for mmap(2) regions that are MAP_SHARED mmap(2)s of files-which is most likely how AMM will look on Solaris, but I’m only guessing. Other OSes, like Tru64-and I’m quite sure most others-don’t support large page tables for mmap(2)ed files. This will be interesting to watch.

Performance, Large Page Table, Etc
I remember back in the mid-90s when Sequent implemented shared large page tables for IPC Shared memory on our Unix variant-DYNIX/ptx. It was a very significant performance enhancement. For instance, 1024 shadow processes attached to a 1GB SGA required 1GB of physical memory-for the page tables alone! That was significant on systems that had very small L2 caches and only supported 4GB physical memory. Fast forwarding to today. I know people with Oracle 10g workloads that absolutely seize up their Linux (2.6. Kernel) system unless they use hugepages. Now I should point out that these sites I know of have a significant mix of structured and unstructured data. That is, they call out to LOBs in the filesystem (give me SecureFiles please). So the pathology they generally suffered without hugepages was memory thrashing between Oracle and the OS page cache (filesystem buffer cache). The salve for those wounds was hugepages since that essentially carves out and locks down the memory at boot time. Hugepages memory can never be nibbled up for page cache. To that end, benefiting from hugepages in this way is actually a by-product. The true point behind hugepages not the fact that it is reserved at boot time, but the fact that CPUs don’t have to thrash to maintain the physical to virtual translations (tlb). In general, hugepages are a lot more polite on processor caches and they reduce RAM overhead for page tables. Compared to the mid 1990s, however, RAM is about the least of our worries these days. Manageability is the most important and AMM aims to help on that front.

Confusion
Of all things Oracle and Linux, I think one of the topics that gets mangled the most is hugepages. The terms and nobs to twist run the gamut. There’s hugepages, hugetlb, hugetlbfs, hugetlbpool and so on. Then there are the differences from one Linux distro and Linux kernel to the other. For instance, you can’t use hugepages on SuSE unless you turn off vm.disable_cap_mlock (need a few double negatives?). Then there is the question of boot-time versus /proc or sysctl(8) to reserve the pages. Finally, there is the fact that if you don’t have enough hugepages when you boot Oracle, Oracle will not complain-you just don’t get hugepages. I think Metalink 361323.1 does a decent job explaining hugepages with old and recent Linux in mind, but I never see it explained as succinctly as follows:

  1. Use OEL 4 or RHEL 4 with Oracle Database 10g or 11g
  2. Set oracle hard memlock N in /etc/security/limits.conf where N is a value large enough to cover your SGA needs
  3. Set vm.nr_hugepages in /etc/sysctl.conf to a value large enough to cover your SGA.

Further Confusion
Audited TPC results don’t help. For instance, on page 125 of this Full disclosure report from a recent Oracle10g TPC-C, there are listings of sysctl.conf and lilo showing the setting of the hugetlbpool parameter. That would be just fine if this was a RHEL3 benchmark since vm.hugetlbpool doesn’t exist in RHEL4.

Performance
I admit I haven’t done a great deal of testing with AMM, but generally a quick I/O-intensive OLTP test on a system with 4 processor cores utilized at 100% speak volumes to me. So I did just such a test.

Using an order-entry workload accessing the schema detailed in this Oracle Whitepaper about Direct NFS, I tested two configurations:

Automatic Memory Management (AMM). Just like it says, I configured the simplest set of initialization parameters I could:

UNDO_TABLESPACE=rb1
UNDO_MANAGEMENT = AUTO
compatible = 10.1.0.0
control_files                  = ( /u01/app/oracle/product/11/db_1/rw/DATA/cntlbench_1 )
db_block_size                   = 4096
MEMORY_TARGET=1500M
db_files                        = 100
db_writer_processes = 1
db_name                         = bench
processes                       = 200
sessions                        = 400
cursor_space_for_time           = TRUE  # pin the sql in cache
filesystemio_options=setall

Manual Memory Management(MMM). I did my best to tailor the important SGA regions to match what AMM produced. In my mind, for an OLTP workload the most important SGA regions are the block buffers and the shared pool.

UNDO_TABLESPACE=rb1
UNDO_MANAGEMENT = AUTO
compatible = 10.1.0.0
control_files                  = ( /u01/app/oracle/product/11/db_1/rw/DATA/cntlbench_1 )
db_block_size                   = 4096
#MEMORY_TARGET=1500M
db_cache_size = 624M
shared_pool_size=224M
db_files                        = 100
db_writer_processes = 1
db_name                         = bench
processes                       = 200
sessions                        = 400
cursor_space_for_time           = TRUE  # pin the sql in cache
filesystemio_options=setall

The following v$sgainfo output justifies just how closely configured the AMM and MMM cases were.

AMM:

SQL> select * from v$sgainfo ;

NAME                                  BYTES RES
-------------------------------- ---------- ---
Fixed SGA Size                      1298916 No
Redo Buffers                       11943936 No
Buffer Cache Size                 654311424 Yes
Shared Pool Size                  234881024 Yes
Large Pool Size                    16777216 Yes
Java Pool Size                     16777216 Yes
Streams Pool Size                         0 Yes
Shared IO Pool Size                33554432 Yes
Granule Size                       16777216 No
Maximum SGA Size                 1573527552 No
Startup overhead in Shared Pool    83886080 No

NAME                                  BYTES RES
-------------------------------- ---------- ---
Free SGA Memory Available                 0

MMM:

SQL> select * from v$sgainfo ;
NAME                                  BYTES RES
-------------------------------- ---------- ---
Fixed SGA Size                      1302592 No
Redo Buffers                        4964352 No
Buffer Cache Size                 654311424 Yes
Shared Pool Size                  234881024 Yes
Large Pool Size                           0 Yes
Java Pool Size                     25165824 Yes
Streams Pool Size                         0 Yes
Shared IO Pool Size                29360128 Yes
Granule Size                        4194304 No
Maximum SGA Size                  949989376 No
Startup overhead in Shared Pool    75497472 No

NAME                                  BYTES RES
-------------------------------- ---------- ---
Free SGA Memory Available                 0

The server was a HP DL380 with 4 processor cores and the storage was an HP EFS Clustered Gateway NAS. Before each test I did the following:

  1. Restore Database
  2. Reboot Server
  3. Mount NFS filesystems
  4. Boot Oracle

Before the MMM case I set vm.nr_hugepages=600 and after the database was booted, hugepages utilization looked like this:

$ grep Huge /proc/meminfo
HugePages_Total:   600
HugePages_Free:    145
Hugepagesize:     2048 kB

So, given all these conditions, I believe I am making an apples-apples comparison of AMM to MMM where AMM does not get hugepages support but MMM does. I think this is a pretty stressful workload since I am maxing out the processors and performing a significant amount of I/O-given the size of the server.

Test Results
OK, so this is a very contained case and Oracle Database 11g is still only available on x86 Linux. I hope I can have the time to do a similar test with more substantial gear. For the time being, what I know is that losing hugepages support for the sake of gaining AMM should not make you lose sleep. The results measured in throughput (transactions per second) and server statistics are in:

Configuration OLTP Transactions/sec Logical IO/sec Block Changes/sec Physical Read/sec Physical Write/sec
AMM 905 36,742 10,195 4,287 2,817
MMM 872 36,411 10,101 4,864 2,928

Looks like 4% in the favor of AMM to me and that is likely attributed to the 13% more physical I/O per transaction the MMM case had to perform. That part of the results has me baffled for the moment since they both have the same buffering as the v$sgainfo output above shows. Well, yes, there is a significant difference in the amount of Large Pool in the MMM case, but this workload really shouldn’t have any demand on Large Pool. I’m going to investigate that further. Perhaps an interesting test would be to reduce the amount buffering the AMM case gets to force more physical I/O. That could bring it more in line. We’ll see.

Summary
I’m not saying hugepages is no help across the board. What I am saying is that I would weigh heavily the benefits AMM offers because losing hugepages might not make any difference for you at all. If it is, in fact, a huge problem across the board then it looks like there has been work done in this area for the 2.6 Kernel and it seems reasonable that such a feature (hugepages support for mmap(P)) could be implemented. We’ll see.

Another Thought About Oracle Database 11g SecureFiles.

Well, you can close your eyes or just not read the blog, but you are about to start hearing me harp more and more about the Oracle11g SecureFiles feature. I’m about to start some high-end testing with an eye on the performance delta between storing unstructured data in Oracle Database 11g with the SecureFiles feature versus storing them in a traditional filesystem.

I was reading StorageMojo.com today where Robin was discussing the state of commodity filesystems and their (in)ability to properly deal with certain storage failures. The story seems even more grim than I was aware. I recommend you read the IRON paper and think about those LOBs. Oracle can do this stuff so much better.

Simply put, Oracle is not going to corrupt your data-structured or unstructured. Oracle offers features and options ranging from from block check summing to HARD and DataGuard and a myriad of other features and tools to help ensure that this claim is true.

It’s worth thinking about. Besides, if you put your unstructured data in the filesystem it is “owned” by the system administrators. If you use SecureFiles, it’s yours!

Worth thinking about?

Oracle11g: Oracle Inventory On Shared Storage. Don’t Bother Trying To Install 11g RAC That Way.

A few days ago there was a thread on the oracle-l email list about adding nodes in an Oracle Database 10g Real Application Clusters environment. The original post showed a problem that Alex Gorbachev reports he’s only seen with shared Oracle Home installs. I found that odd because I’ve done dozens, upon dozens of RAC installs on shared Oracle Homes with both CFS and NFS and haven’t seen this error:

Remote 'UpdateNodeList' failed on node: 'af-xxx2'. Refer to
'/apps/oracle/oraInventory/logs/addNodeActions2007-07-08_09-36-12PM.log'
for details.
You can manually re-run the following command on the failed nodes after the
installation:
/apps/oracle/product/10.2/oui/bin/runInstaller -updateNodeList -noClusterEnabled
ORACLE_HOME=/apps/oracle/product/10.2 CLUSTER_NODES=af-xxx1,af-xxx2,af-xxx6
CRS=false "INVENTORY_LOCATION=/apps/oracle/oraInventory" LOCAL_NODE=
<node on which command is to be run>

I never have any problems with shared Oracle Home and I blog about the topic a lot as can be seen in in this list of posts. Nonetheless, Alex pointed out that the error has to do with the Oracle Inventory being on a shared filesystem. Another list participant followed up with the following comment about placing the inventory on a shared drive:

Sharing the oraInventory across nodes is not a good practice in my opinion. It runs counter to the whole concept of redundancy in an HA configuration and RAC was not written to support it.

Well, the Oracle Inventory is not a RAC concept, it is an Oracle Universal Installer concept, but I think I know what this poster was saying. However, the topic at hand is shared Oracle Home. When people use the term shared Oracle Home, they don’t mean shared ORACLE_BASE, they mean shared Oracle Home. Nonetheless, I have routinely shared the 10g inventory without problems, but then my software environments might not be as complex as those maintained by the poster of this comment.

Shared Inventory with Oracle Database 11g
No can do! Well, sort of. Today I was installing 11g RAC on one of my RHEL 4 x86 clusters. In the fine form of not practicing what I preach, I mistakenly pointed Oracle Universal Installer to a shared location (NFS) for the inventory when I was installing CRS. I got CRS installed just fine on 2 nodes and proceeded to install the database with the RAC option. It didn’t take long for OUI to complain as follows:

shared_home_11g.jpg

Ugh. This is just a test cluster that I need to set up quick and dirty. So I figured I’d just change the contents of /etc/oraInst.loc to point to some new non-shared location-aren’t I crafty. Well, that got me past the error, but without an inventory with CRS in it, Oracle11g OUI does not detect the cluster during the database install! No node selection screen, no RAC.

I proceeded to blow away all the CRS stuff (ORA_CRS_HOME, inittab entries, /etc/oracle/* and /etc/oraInst.loc) and reinstalled CRS using a non-shared locale for the inventory. The CRS install went fine and subsequently OUI detected the cluster when I went to install the database.

This is a significant change from 10g where the inventory content regarding CRS was not needed for anything. With 10g, the cluster is detected based on what /etc/oracle/ocr.loc tells OUI.

Summary
Shared Oracle Home is an option, shared Oracle Home means shared Oracle Home not shared Oracle Inventory. Oracle11g enforces this best practice nicely!


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All content is © Kevin Closson and "Kevin Closson's Blog: Platforms, Databases, and Storage", 2006-2013. Unauthorized use and/or duplication of this material without express and written permission from this blog’s author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Kevin Closson and Kevin Closson's Blog: Platforms, Databases, and Storage with appropriate and specific direction to the original content.

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