Oracle RAC Administration – Part 13: Cache Coherency

Brief intro

In our last article,
we took a deeper and closer look at the OIFCFG command line utility. As a DBA,
the performance of our RAC is crucial. Just like any other application, we need
to make sure that our Oracle Database, whether a single node or a multi-node
RAC, runs efficiently.

Although we are still into the administration part of the series,
we will throw some special attention to the performance of our RAC. After all,
when the installation is done, all the manuals and workbooks have been
delivered and the consultants have gone home, it’s time to watch how the
workload of the database is going to affect the performance of the RAC. It is almost
always a forgotten area. Not to a professional DBA obviously, but surely to the
ones who think, "Oracle 11g will be self-managing so I really don’t
need a professional DBA."

Some Performance metrics specific to the RAC environment

Cache Coherency

What exactly do we mean by Cache Coherency? Our Oracle RAC environment
needs some added sets of metrics rather than a regular Oracle RAC installation,
which I sometimes refer to as a “Single-Node RAC”. I call it a Single-Node RAC
because someday that Oracle application will also grow and need a ticket to “RACdom”.
A typical production DBA, responsible for uptime and upkeep of his RAC Database
needs more that just some statspack runs; he will need to measure the health of
his HSI (High Speed Interconnects) Network interfaces, he will have to monitor
and diagnose the traffic volume across the nodes and response times. A typical
high intensive OLTP environment can keep you pretty busy. To measure the
traffic we will concentrate on two categories:

  • GCS (Global Cache Services)

  • GES (Global Enqueue Services)

So what are they?

Global Cache Service

According to the manual:

Process that implement Cache Fusion. It
maintains the block mode for blocks in the global role. It is responsible for
block transfers between instances. The Global Cache Service employs various
background processes such as the Global Cache Service Processes (LMSn) and
Global Enqueue Service Daemon (LMD).

It actually is more or less like your buffer cache, but
here it acts globally across the nodes. This process is an integral part to the
cache-fusion concepts. So what does a buffer have, data blocks obviously. Simply
said, the coherency in the Global Buffer Cache is maintained by making sure
that whenever an attempt to modify the database block is made, a global lock is
acquired. . Now this “asking instance” will have both the past copy of the
block (for redo purposes) as well as the current version of the block
containing both committed and uncommitted transactions. Should another node
come asking for that block, then it is the GCS’s responsibility to do a “Block
Version Lookup” at the node, which is currently holding the global lock to the
block. The LMSn processes are crucial for a successful operation of GCS and do
the block version lookup, block mode etc.

Global Enqueue Service

According to the manual:

A service that coordinates enqueues that
are shared globally.

The blocks in your RAC
environment do most of the work themselves, but there is a crucial area when GES
or the Global Enqueue Services come in. A seamless coordination across the
nodes is crucial for RAC’s operation. The GES is primarily responsible for maintaining
coherency in the dictionary and library caches. The dictionary cache consists
of the data dictionary master information for each node in its SGA (System
Global Area) primarily for quicker lookup and access. Any DDL committed from a
requesting node needs to be sync’ed and written across all data dictionaries in
all nodes of the RAC environment. The GES makes sure that the changes remain
consistent across the nodes and that there are no discrepancies. Moreover, with
the same directive, the locks must be created and maintained across the nodes
and GES must ensure that there are no deadlocks across requesting nodes over
access to the same objects. LMON, LCK and LMD processes work in tandem to make
the GES operate in a smooth and seamless fashion.

GV$ Views

Obviously, the meat part of the whole equation is, “Where
are my RAC views?” RAC environment has additional views known as Global Views.
A typical view for a Single Node installation is V$ but for RAC you have GV$
views. In addition, all these views have additional columns like INST_ID to
identify nodes across the RAC environment. So a typical 4 node RAC (like that
of our VMware ESX 3.0 nodes) will give you four nodes in our 4-node RAC with
their own data when querying the GV$ view. Obviously, you can query individual
nodes from any node. To get started try doing this:

SQL> select * from gv$sysstat where name like '%gcs %';

This will give you a result set with specific attention to
GCS messages sent across the nodes. If this value is inconsistent across nodes
or if huge differences are apparent then it might be time to investigate.

Finding which NIC was used for block transfer

Try to do the following to find out which NIC (private
obviously) was used for Cache Fusion:


SQL> oradebug setmypid
Statement processed.
SQL> oradebug ipc
Information written to trace file.
SQL> oradebug tracefile_name
/oracle/app/oracle/product/10.2.0.1/admin/…/10gr2_ora_12443.trc
SQL>

The trace file will contain the details of the IPC
information along with the interconnect details:


SKGXPCTX: 0xad95d70 ctx
admono 0xbcfc2b9 admport:
SSKGXPT 0xad95e58 flags info for network 0
socket no 8 IP 10.0.0.25 UDP 38206
sflags SSKGXPT_UP
info for network 1
socket no 0 IP 0.0.0.0 UDP 0
sflags SSKGXPT_DOWN
active 0 actcnt 1
context timestamp 0

It is clear that it is our node 1 using private port
10.0.0.25 via UDP.

What networks do various Oss use?

OS

Network

Linux (RHEL/Centos 4.4)

Gigabit Ethernet

Windows 2003 R2

Gigabit Ethernet

AIX

UDP High-Perf Switch, UDP

HP-True64

RDG (Reliable Data Gram) Memory Channel

Sun

RSM (Remote Shared Memory Firelink)

Several vendors, like Veritas (Symantec now), have their own
protocols to enable a fast and efficient cache fusion operation.

Conclusion

In our next article, we will carefully start moving towards
Workload Management. (AWR, FAN, etc.) I will try to keep the articles more fun
and examples oriented. Although I must stress on the fact that it is not all examples
and we must keep coming back to fundamentals.

»


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Tarry Singh

Tarry Singh
Tarry Singh
I have been active in several industries since 1991. While working in the maritime industry I have worked for several Fortune 500 firms such as NYK, A.P. Møller-Mærsk Group. I made a career switch, emigrated, learned a new language and moved into the IT industry starting 2000. Since then I have been a Sr. DBA, (Technical) Project Manager, Sr. Consultant, Infrastructure Specialist (Clustering, Load Balancing, Networks, Databases) and (currently) Virtualization/Cloud Computing Expert and Global Sourcing in the IT industry. My deep understanding of multi-cultural issues (having worked across the globe) and international exposure has not only helped me successfully relaunch my career in a new industry but also helped me stay successful in what I do. I believe in "worknets" and "collective or swarm intelligence". As a trainer (technical as well as non-technical) I have trained staff both on national and international level. I am very devoted, perspicacious and hard working.

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