Category Archives: realApplicationClusters

OraChk Collection Manager

OraChk (Previously known as Raccheck) is a utility from oracle to perform configuration checks on Oracle database platforms, and report on configurations that do not match oracle’s best practices. OraChk has the ability to upload the results of its checks into an oracle database. Details about this utility can be found in Mos Note 1268927.1

Oracle has now released  OraChk Collection Manager which is a companion application to OraChk, which has an Oracle Application Express, Front End which can be used  as a dashboard, in which customers can track their ORAchk, RACcheck and Exachk collection data in one easy to use interface.

Details about downloading and using “OraChk Collection Manager” can be found in Mos Note 1602329.1

Managing Processes and Memory Consumption on Oracle Exadata database machines.

This post is equally applicable to Rac databases deployed, both on oracle database machines as well as traditional server/storage architectures, running RHEL5 or OEL5 (OEL6 has a new feature called transparent hugepages).

The Best practices for database consolidation on exadata database machine, White Paper outlines a lot of good guidelines. However the best practices seems to be getting occasionally overlooked, in some cases resulting in Node evictions/restarts in the cluster.

High amounts of memory and cpu consumption can result in some real bad things happening (Like for eg: Node evictions). So it is important to configure the operating system and the databases you deploy on the machine optimally, to use the available CPU and memory resources.

Let us first review what those available memory and cpu resources are on an Oracle Exadata Database Machine, on each database node.

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Anytime a workload is deployed on a database server, that exceeds the, operating systems ability to efficiently use the above mentioned, available cpu and memory resources, bad things can happen. (I know i am over simplifying in the prior comment, but you get the idea).

Managing Memory Resources.

Setting up HugePages

First we need to make sure that HugePages on each node, is setup correctly, for the databases you have deployed on the node.
Tanel Poder has explained the reasons for setting up HugePages on Exadata systems.
When the database machines are installed, the HugePages is configured to accomodate the one database that is pre-installed. So if you change the SGA setting for that database or deploy more databases you should now adjust the HugePages setting accordingly. It goes without saying that if you have already configured the hugepages to accomodate all the databases you have, and then you removed some databases from the node, or resized the SGA’s to be smaller, you should again resize your hugepages to free up the excess hugepages.

Once all the database instances are configured and started up you can run the script, hugepages_settings.sh from Mos Note 401749.1, which calculates the number of hugepages you need to setup. I usually recommend adding 10% to the value that hugepages_settings.sh suggests.

With 11.2.0.2 and 11.2.0.3 you should also be setting USE_LARGE_PAGES, preferably to ONLY, following the instructions in Mos Note 1392497.1.

You can then follow the instructions in MOS note 361323.1, under the section “Kernel version 2.6”, to set the value. You need to restart the databases so the SGA gets allocated with the hugepages.

You should also follow instructions from MOS note 1546861.1, and set the value of vm.min_free_kbytes = 524288, in /etc/sysctl.conf, to avoid page allocation failure messages when kernel memory is depleted.

Managing Memory Usage

Ideally for critical implementations, your SGA+PGA+Individual server processes, memory allocations should not exceed 75% of the physical memory on the database node.

The Exadata consolidation white paper above suggests that

For critical Hardware Pools, we recommend an even more conservative approach by not exceeding 75% physical memory per database node.
OLTP applications:
SUM of databases (SGA_TARGET +PGA_AGGREGATE_TARGET) + 4 MB * (Maximum PROCESSES) < Physical Memory per Database Node
DW/BI applications:
SUM of databases (SGA_TARGET + 3 * PGA_AGGREGATE_TARGET) < Physical Memory per Database Node

You can monitor the pga usage a few different ways.

1) SELECT s.inst_id, s.sid, s.serial#, p.spid, s.username, s.program, p.pga_used_mem FROM gv$session s JOIN gv$process p ON p.addr = s.paddr AND p.inst_id = s.inst_id WHERE s.type != ‘BACKGROUND’ and s.program not like ‘%(P%’ and p.pga_used_mem > <APPLICATION_MEMORY_THRESHOLD>
order by s.inst_id, s.sid, s.serial#;

The value you use for APPLICATION_MEMORY_THRESHOLD is dependent on your application and howmuch pga it needs to efficiently run your queries (Performing the sorts in memory using the space for PGA is usually faster than using the TEMP tablespace). However the white paper suggests using 1Gb for OLTP applications and 10Gb for DSS applications.

2) You can monitor the sysmetric “Total PGA Allocated” from dba_hist_sysmetric_summary, to see how much PGA is being allocated.

3) You can use the “PGA Memory Advisory” and “SGA Target Advisory” sections of the awr report, to guage, the impacts of increasing or decreasing the SGA and PGA Allocations.

4) You can monitor the memory usage at the o/s level using the top (Mem: free),free or vmstat (bo (page-out),bi (page-in)) commands.

Managing O/S Processes (And as a consequence CPU usage).

It is important to control the number of processes that are actively executing on each node. Each of these processes consume cpu and memory resources.

The following guidelines are important to follow.
– Use Application connection pooling to appropriately limit the number of sessions connected to the oracle database.

This is important for two reasons.
– Right-Size the resource consumption on each database node.
– Minimize the impact of connection storms.

– Configure the parallel query servers appropriately.
– For all the database’s deployed on a node the total setting for PARALLEL_MAX_SERVERS should be less than or equal to the following

X2-2 or X3-2, <= 240
X2-8 or X3-8, <= 1280

I often see implimentations where parallel_max_servers = 240 (or a high value) in each instance on the machine, which results in not so good consequences. I have occassionaly seen systems where there is sustained 100% cpu usage with load averages of > 300, resulting in node reboots.

– Use Instance Caging and Database Resource Manager to manage cpu allocation on the server.

It would be a good idea to always review the Best practices for database consolidation on exadata database machine, White Paper and follow the guidelines, to have a well performing and  stable database environment.

It would be a good idea to review the performance management screens from Enterprise Manager 12c every day to have a good understanding of the database and server workloads, and/or analyze the oswatcher data to understand the server workload profile.

Oracle Exadata Best Practices Tutorials

There is a set of recorded tutorials available from the oracle maximum availability architecture team, that cover a range of topics.

The tutorials can be accessed at  Oracle Exadata Best Practices Series

The topics include implementing Ebs, Siebel and Peoplesoft, resource manager, migration, DBFS, monitoring, backup and recovery, troubleshooting, patching and healthcheck.

Lots and Lots of great information.

Copying database files from one asm instance to another using asmcmd

Often one might have to copy datafiles from one database instance to another (And hence one ASM instance to another), for eg: when copying datafiles from prod to development.

You can use the cp command in asmcmd to accomplish this. cp can copy files from one instance to another. You can specify the username/password@connecstring for the target asm instance in the cp command.

ASMCMD [+] > cp +data/orcl/datafile/EXAMPLE.265.691577295 sys/password@myserver.+ASM:/scratch/backup/myexamples.bak

11.2.0.2 Grid infrastructure, private interconnect bonding new feature HAIP

I have been heads down on an Exadata Poc , and only now, got a chance to browse through the new features in 11.2.0.2. The out of place upgrade feature looks interesting.

This new feature in grid infrastructure installation had me really overjoyed (Anyone who has had the pleasure of configuring IPMP, Auto Port Aggregation, Etherchannel etc (based on the o/s) and setting it up correctly to work with Rac, will understand my Joy) . Starting with 11.2.0.2 you do not have to bond the interfaces (If you have redundant GigE nics you are going to use for your private interconnect) you are going to use as the private interconnect. If you have two different interface names to be used for the private interconnect you can provide both the interface names to the oracle grid infrastructure installer and oracle clusterware will create a Highly Available IP Address (HAIP).

Oracle Clusterware, Rac and ASM uses these  load balanced highly available interfaces for communication.

Details can be read at http://download.oracle.com/docs/cd/E11882_01/install.112/e17212/prelinux.htm#BABJHGBE for Linux.

HAIP info can also be found in the 11R2 Clusterware white paper.

Julian Dyke has a blog post that says that MULTICAST has to be enabled for the Network interfaces to enable this to work.

Enabling multicast on the interconnect network is a requirement with 11.2.0.2 Rac.My Oracle Support Notes 1228471.1,1212703.1 details how Multicast can be enabled and checked.

What makes the oracle database machine V2 incredibly awesome ?

Lots of hardware power for the database servers

– 8 Real Application Clusters, Database server nodes (aka compute nodes) (Sunfire X4170’s)
– 2 quad core, Intel Xeon, E5540 processors (2.53ghz) in each server (Total 64 cores across 8 nodes)
– 72gb of RAM on each node (Total 576gb of Ram on the database servers)
– 3, 36 port QDR Infiniband switches (40gbit infiniband)

Lots of hardware power for the storage servers

– 14 Exadata cells, (Sunfire X4275’s).
– Each cell has
– 2 quad core Intel Xeon, E5540 processors on each cell (Total 112 cpu cores on all 14 cells together)
– 24Gb RAM on each cell (Total 336gb of Ram on all 14 cells together)
– 384Gb of Flash Cache (PCI-E flash card) on each cell (5Tb on all 14 cells together)
– 12x600gb (SAS) disks (7.2Tb) or 12x1Tb (SATA) disks (12Tb) (Total 100Tb with SAS disks, or 168Tb with SATA disks on all 14 cells together)
The above hardware gives the database machine the ability to read data at the rate of 21GigaBytes a second or 1,000,000 Io’s per second.

Balanced Configuration

Each disk drive (SAS) in the Sunfire X4275 server are, 3.5 inch, 15k Rpm, SAS 2.0, 600Gb drives. Each drive has an average read capacity of atleast 125MegaBytes per second for sequential scans. 168 disk drives, can together scan at the rate off (And return) 21,000 MegaBytes per second.
The Infiniband connections between the storage cells and the compute nodes have enough network bandwidth to transport data at the rate of 21GigaBytes per second.
The 64 cpu cores can issue i/o requests at the approx rate of 300megabytes per core, hence requesting about 21GigaBytes of data per second.
So the system is architect ed to optimally read (enough cpu’s to request the i/o, network bandwidth to ship the i/o and enough disk capacity to service that i/o requests). This is why the oracle database machine is a well balanced system.
At the read rate of 21GigaBytes a second, 1Terabyte of data can be read by the database servers in less than 1 minute.

Infiniband

Each database Node and Exadata Cell, has dual port, Quad data rate (QDR) Infiniband connectivity.
Infiniband is used for the database node to exadata cell connectivity and also for the Rac high speed interconnect (Cache fusion network)
Infiniband has the flexibility of a LAN network with the Speed of a SAN.
Oracle’s interconnect protocol uses DMA, to move data from the wire directly to the Memory without any additional copies made.

Exadata Cells

The exadata cells provide a highly redundant, high performance hardware with very intelligent software to efficiently process database i/o requests.
The hardware capability was discussed in the section “Lots of hardware power for the storage servers”.
The Intelligence in the Exadata cells include “Smart flash cache”, “Smart Scan’s”, “Storage Indexes” and “Exadata column compression”.
Oracle Automatic Storage Management (ASM) ensures that all oracle database files are evenly spread across all the 168 disks available in the database machine.
Oracle Database uses  the protocol iDB (Built by oracle, aptly called the Intelligent Database protocol) to communicate with the exadata cells. iDB is built on the Zero Data Loss, Zero Copy implementation (ZDP) of the industry standard protocol RDSv3 (Reliable datagram socket)

Flash cache

Random read operations are cached on the 5Tb of flash cache available in the database machine, significantly improving oltp performance.
The exadata smart flash cache, working with the database server, keeps track of data access patterns and intelligently manages the caching of blocks from the oracle datafiles.

Smart Scans

The oracle database server uses the iDB protocol to push query predicates (That limit data retrieved by the query using filters and join conditions) to the exadata cell.
This enables the cell to do three things
– Identify rows that are needed by the query and ship only those rows back to the database server (Not entire blocks)
– Identify the columns needed by the query and ship only the required columns in the rows back to the database server
– Use Bloom filters and process join conditions and ship only matching rows in queries with joins back to the database server
This drastically reduces the amount of data send back to the database server (Reducing the network usage)
Transferring file blocks from disks inside a cell to the physical memory of the cell can happen relatively fast. If a lot of the data that is not needed by the database server, can be eliminated at the cell, then the amount of data that needs to go over a network to the database server is significantly reduced. So the network i/o usage between the database servers and exadata cells is reduced by smart scans.

Storage Indexes

Smart scans however do not reduce the disk i/o within the cell (ie transfer from disk to cell physical memory).
Oracle creates an in memory array of structures, that keep track off min and max values of columns (columns used in the where clause that benefit by storage indexes), that let oracle identify if specific 1mb regions are needed based on the filtering conditions applied to the tables.
So storage indexes is a filter oracle applies to prune away 1mb chunks that do not have to be read.
This reduces the i/o within the exadata cell.

Exadata Hybrid Columnar Compression

Traditional relational databases store data in database blocks in a “Row” format. This type of storage limits the amount of compression that can be achieved
Column store databases, organizes and stores data by column. Storing column data together, with the same datatype and similar charachteristics , results in significant compression that can be achieved. However if the query refers to more than a couple of columns in the table, or does more than modest updates and inserts , those queries and dml tend to have slower performance.
Exadata hybrid columnar compression takes a blended approach. Oracle takes rows that fit into multiple blocks (Called a compression unit), converts the rows into columns and stores the data in a columnar format within a compression unit.
Oracle uses 3 different compression format’s and different transformations, depending on the compression level you have chosen
There are 4 levels of compression (Each level is a tradeoff between compression ratio and compression speeds)
– Query Low
– Query High (Default when you say compress for query)
– Archive Low
– Archive High
With Exadata Hybrid columnar compression
1) The amount of storage required to store massive amounts of data could be potentially decreased by a factor of 10.
2) The amount of i/o to be issued (For queries that scan very very large tables) is significantly reduced.
The above features together make’s the Oracle Database Machine, rock database performance.

11gr2 new awr reports for Real Application Clusters

There are two new awr reports in 11gr2, which will be helpful to dba’s in Real Application Clusters Environments (RAC).

awrgrpt.sql

This is a cluster wide awr report, so you can see a lot of the information from all the nodes in the same section, and you can also see aggregated statistics from all the instances at the same time (You can see totals, averages and standard deviations).

awrgdrpt.sql

This is a cluster wide stats diff report (like you had awrddrpt.sql in 11gr1), comparing the stats differences between two different snapshot intervals, across all nodes in the cluster.

These are huge additions to the awr reports, that enable understanding the database performance in real application clusters environments.

Cloud computing definition.

The National Institute of Standards and technology has a good, concise  definition of cloud computing. Sushil kumar of Oracle, was using the same language to define cloud computing in an article the current release of the oracle magazine.

Essential Charachteristics

  • On Demand Self-Service
  • Broad Network Access
  • Resource Pooling
  • Rapid Elasticity
  • Measured Service

Service Models

  • Cloud Software as a Service (SaaS)
  • Cloud Platform as a Service (PaaS)
  • Cloud Infrastructure as a Service (IaaS)

Deployment Models

  • Private Cloud
  • Community Cloud
  • Public Cloud
  • Hybrid Cloud

Grid computing sessions at Oracle Openworld 2009

If you are attending Oracle Openworld 2009, and are interested in learning a lot about oracle Rac and Grid computing, you can find a full list of Oracle Rac and Grid computing events Here (Starting at page 2 of the pdf doc).

In preparation for the event, you could read the following new 11gR2 white papers from Oracle, to understand the latest developments and arm yourself with questions.

Oracle Real Application Clusters 11g Release 2 Technical Overview

Oracle Real Application Clusters 11g Release 2 Overview of SCAN

Oracle Real Application Clusters One Node 11g Release 2 Technical Overview

11gR2 rac installation on 64 bit Linux step by step

Yesterday i completed a 11g Release 2 real application clusters installation on 64 bit Oracle Enterprise Linux 4. The installation process is very similar to the 10g and 11gr1 installations, but much simpler. This was a two node cluster. There are some new concepts that are introduced in 11gR2 real application clusters. Below are some of my notes on 11gr2 new features for Rac and detailed steps that i followed to complete the installation.

Some new concepts in 11gR2 Rac


Oracle clusterware and ASM now are installed into the Same Oracle Home, and is now called the grid infrastructure install.

Raw devices are no longer supported for use for anything (Read oracle cluster registry, voting disk, asm disks), for new installs.

OCR and Voting disk can now be stored in ASM, or a certified cluster file system.

The redundancy level of your ASM diskgroup (That you choose to place voting disk on) determines the number of voting disks you can have.
You can place

  • Only One voting disk on an ASM diskgroup configured as external redundancy
  • Only Three voting disks on an ASM diskgroup configured as normal redundancy
  • Only Five voting disks on an ASM diskgroup configured as high redundancy


The contents of the voting disks are automatically backed up into the OCR

ACFS (Asm cluster file system) is only supported on Oracle Enterprise Linux 5 (And RHEL5), not on OEL4.

There is a new service called cluster time synchronization service that can keep the clocks on all the servers in the cluster synchronized (In case you dont have network time protocol (ntp) configured)

Single Client Access Name (SCAN), is a hostname in the DNS server that will resolve to 3 (or at least one) ip addresses in your public network. This hostname is to be used by client applications to connect to the database (As opposed to the vip hostnames you were using in 10g and 11gr1). SCAN provides location independence to the client connections connecting to the database. SCAN makes node additions and removals transparent to the client application (meaning you dont have to edit your tnsnames.ora entries every time you add or remove a node from the cluster).

Oracle Grid Naming Service (GNS), provides a mechanism to make the allocation and removal of VIP addresses a dynamic process (Using dynamic Ip addresses).

Intelligent Platform Management Interface (IPMI) integration, provides a new mechanism to fence server’s in the cluster, when the server is not responding.

The installer can now check the O/S requirements, report on the requirements that are not met, and give you fixup scripts to fix some of them (like setting kernel parameters).

The installer can also help you setup SSH between the cluster nodes.

There is a new deinstall utility that cleans up a existing or failed install.

And the list goes on an on.

I have broken up the installation process into 3 distinct documents, which can be found below

Installing 11gr2 grid infrastructure

Installing 11gr2 Real Application Clusters

Creating the 11gr2 Clustered database