Home > Articles > Networking > Storage

  • Print
  • + Share This
This chapter is from the book

This chapter is from the book

3.5 Simplified SAN Application I/O Models for Verification

Now that the performance assessment of the template applications and host systems has been completed, use the information gathered from the assessment to model the expected behaviors of the host systems. The verification model can be simple and should try to recreate the I/O behaviors of the system being modeled. Not all I/O behaviors need to be built into the model, because modeling everything is extremely complex and time-consuming. The verification model tries to emulate peak performance for the chosen I/O characteristics. The verification model can also test failure modes and evaluate SAN behaviors while working with specific features of the SAN.

Modeling the NAS Server Replacement

The I/O model for the NAS server replacement SAN in Figure 3.1 (page 59) should emulate the archival processes that the NAS server currently services. This application simultaneously transfers several large files to the NAS server, and the model for the file transfers can be quite simple. The tester places a set of test files on one client host system or more and then writes a simple set of scripts that transfers these files to and from the new SAN file server.

The tester then measures the transfers for bandwidth performance and checks for reliability. Performance should be evaluated and assessed from several places in the SAN. Ideally, the throughput of the NAS replacement SAN has been measured from the client, the server, and the fabric devices that make up the SAN.

Testing of the failure cases in the NAS replacement SAN includes these tasks:

  • Simulating device failures during data transfers

  • Powering off fabric devices

  • Rebooting host systems

  • Unplugging cables in a controlled manner to evaluate behaviors under failure or maintenance conditions

These tests provide a better understanding of the failure cases and may uncover problems in maintenance methods or the design.

Modeling the Data Warehouse ETL Consolidation SAN

A model for the storage consolidation SAN in Figure 3.4 (page 63) is more complex than the NAS replacement SAN test model. The systems in the storage consolidation SAN will use the fabric-attached storage for file creation in addition to reads and transfers, which differs from the dedicated data transfer use of the NAS replacement SAN. The I/O model must include file creation, reads, and writes. Modeling must also include an approximation of the timing of the processes.

The first step is the creation of a few simple scripts that create, read, and write files. These scripts can then be grouped together to simulate I/O behaviors of the systems being consolidated on the SAN. Example 3.3 shows a Perl script that randomly reads a file.

This simple script performs a specified number of random 1KB reads throughout a specified file. A similar script in Perl can randomly write updates to a file, as shown in Example 3.4.

The writer.pl script inserts an all-zero, 1KB update into a specified file at a random location. It is easy to modify the size and content of the update for customization.

Much simpler scripts can also create files. Because a new file will be sequentially written with the typical I/O size of the application in most cases, a file creation script can use the UNIX system tool dd. Example 3.5 shows a dd command to write an 800MB file in 8KB-size blocks.

In Example 3.5, the parameters are:

  • Input file (if)

  • Output file (of)

  • Block size (bs)

  • Number of IOPS (count)

To create a file of any size with any I/O size, change the block size and the count.

Use a wrapper script to run the scripts or file creation command numerous times. Simulate CPU processing time with delays in the wrapper. A wrapper script that simulates a load operation in a data warehouse is shown in Example 3.6.

EXAMPLE 3.3. A random file reader script (reader.pl)

#!/usr/local/bin/perl
#
# reader.pl
# Perform random reads of a file
#

# The first argument to the script is the file name
# The second argument to the script is the number
# of reads to perform
$file = $ARGV[0];
$count = $ARGV[1];

# open the file to be read and find its size
open(FH, $file) || die "Can't open $file\n";
seek(FH, 0, 2);
$filesize = tell(FH);
close(FH);

srand(time);

open(FH, $file) || die "Can't open $file\n";

# perform 1KB reads of the file at random offsets
# $count times
while ( $i <= $count) {
    $fpos = int(rand $filesize) + 1;
    read(FH, $dump, 1024);
    $i++;
    }

close(FH);
printf "Done reading file $file\n";

EXAMPLE 3.4. A random file updater script (writer.pl)

#!/usr/local/bin/perl
# writer.pl
# Perform random updates of a file
#
$LOCK_SH = 1;
$LOCK_EX = 2;
$LOCK_NB = 4;
$LOCK_UN = 8;
# The first argument to the script is the file name
# The second argument to the script is the number of writes to perform
$file = $ARGV[0];
$count = $ARGV[1];

# Make a 1KB buffer of zeros
$buf="0" x 1024;

# open the file to be read and find its size
open(FH, $file) || die "Can't open $file\n";
seek(FH, 0, 2);
$filesize = tell(FH);
close(FH);

srand(time);

# open and lock the file for writing
open(FH, "+<$file") || die "Can't open $file\n";
flock(FH, $LOCK_EX);

# perform 1KB writes to the file at random offsets $count times
while ( $i <= $count) {
    $fpos = int(rand $filesize) - 1;
    seek(FH, $fpos, 0);
    print FH $buf;
    $i++;
    }

flock(FH, $LOCK_UN);
close(FH);

EXAMPLE 3.5. Simple file creation using dd

dd if=/dev/zero of=/fs1/file01 bs=8192 count=100000 

EXAMPLE 3.6. Data warehouse load simulation wrapper

#!/bin/sh
# Data warehouse load I/O model

# create 10 2GB files sequentially
dd if=/dev/zero of=/fs1/file01 bs=8192 count=250000
dd if=/dev/zero of=/fs1/file02 bs=8192 count=250000
dd if=/dev/zero of=/fs1/file03 bs=8192 count=250000
dd if=/dev/zero of=/fs1/file04 bs=8192 count=250000
dd if=/dev/zero of=/fs1/file05 bs=8192 count=250000
dd if=/dev/zero of=/fs1/file06 bs=8192 count=250000
dd if=/dev/zero of=/fs1/file07 bs=8192 count=250000
dd if=/dev/zero of=/fs1/file08 bs=8192 count=250000
dd if=/dev/zero of=/fs1/file09 bs=8192 count=250000
dd if=/dev/zero of=/fs1/file10 bs=8192 count=250000

# read and write previously created
# simulated catalog file at random
# 250000 times simultaneously in
# 10000 I/O chunks with 30 seconds
# of simulated calculations between chunks
i=1
while [ $i -le 25 ]
do
    reader.pl /fs1/simucat 10000 &
    writer.pl /fs1/simucat 10000 &
    i=´expr $i + 1´
    sleep 30
done

These tools simulate the I/O workload of the ETL systems on the storage consolidation SAN. Use the same I/O workload simulation for failure mode and maintenance evaluation by simulating failures and performing maintenance tasks while the model runs.

Model the I/O behaviors of the systems on a capacity-planning SAN for midsize data warehouse applications using the same set of tools. In addition, use a nonrandom read command, because data warehouse systems tend to scan large tables sequentially. Example 3.7 shows a dd command that performs a simple sequential read.

This command reads 8KB blocks of the file created in Example 3.5. In this case the command simply reads and discards the data because the data is not needed for anything else.

The four simple I/O workload components just described can be assembled to simulate the I/O behavior of the data warehouse systems in almost any mode. Simulation of the staging, loading, and querying of the data warehouse system requires several wrapper scripts in order to combine these I/O workload driver tools. The wrapper scripts would be variations on Example 3.6 and can also be very simple.

In a capacity-planning SAN where zone changes can be frequent due to unknown initial system configurations, evaluation of zoning changes is particularly interesting. Make changes to the capacity-planning SAN configuration while running the I/O model to determine the exact behavior of the systems, fabric devices, and storage devices.

Create an experimental SAN I/O model out of the same components used for the capacity-planning SAN in order to exploit the SAN performance characteristic or behavior. Running several copies of the sequential reader at the same time will drive up bandwidth on the SAN. Multiple copies of the random reader and writer scripts will create high IOPS loads. Additional combinations of the I/O work-load components can simulate the interesting workloads found in most environments.

EXAMPLE 3.7. Simple sequential read using dd

dd if=/fs1/file01 of=/dev/null bs=8192 count=100000 

Model a SAN for a new project in the same fashion as an experimental SAN. The SAN for a new project has more clearly defined performance expectations that facilitate a more accurate model of the expected I/O workload. The SAN does not have to be intentionally stressed, but it can be evaluated with an I/O model that creates the expected performance level for the host systems and applications that will be using the SAN.

  • + Share This
  • 🔖 Save To Your Account

InformIT Promotional Mailings & Special Offers

I would like to receive exclusive offers and hear about products from InformIT and its family of brands. I can unsubscribe at any time.

Overview


Pearson Education, Inc., 221 River Street, Hoboken, New Jersey 07030, (Pearson) presents this site to provide information about products and services that can be purchased through this site.

This privacy notice provides an overview of our commitment to privacy and describes how we collect, protect, use and share personal information collected through this site. Please note that other Pearson websites and online products and services have their own separate privacy policies.

Collection and Use of Information


To conduct business and deliver products and services, Pearson collects and uses personal information in several ways in connection with this site, including:

Questions and Inquiries

For inquiries and questions, we collect the inquiry or question, together with name, contact details (email address, phone number and mailing address) and any other additional information voluntarily submitted to us through a Contact Us form or an email. We use this information to address the inquiry and respond to the question.

Online Store

For orders and purchases placed through our online store on this site, we collect order details, name, institution name and address (if applicable), email address, phone number, shipping and billing addresses, credit/debit card information, shipping options and any instructions. We use this information to complete transactions, fulfill orders, communicate with individuals placing orders or visiting the online store, and for related purposes.

Surveys

Pearson may offer opportunities to provide feedback or participate in surveys, including surveys evaluating Pearson products, services or sites. Participation is voluntary. Pearson collects information requested in the survey questions and uses the information to evaluate, support, maintain and improve products, services or sites, develop new products and services, conduct educational research and for other purposes specified in the survey.

Contests and Drawings

Occasionally, we may sponsor a contest or drawing. Participation is optional. Pearson collects name, contact information and other information specified on the entry form for the contest or drawing to conduct the contest or drawing. Pearson may collect additional personal information from the winners of a contest or drawing in order to award the prize and for tax reporting purposes, as required by law.

Newsletters

If you have elected to receive email newsletters or promotional mailings and special offers but want to unsubscribe, simply email information@informit.com.

Service Announcements

On rare occasions it is necessary to send out a strictly service related announcement. For instance, if our service is temporarily suspended for maintenance we might send users an email. Generally, users may not opt-out of these communications, though they can deactivate their account information. However, these communications are not promotional in nature.

Customer Service

We communicate with users on a regular basis to provide requested services and in regard to issues relating to their account we reply via email or phone in accordance with the users' wishes when a user submits their information through our Contact Us form.

Other Collection and Use of Information


Application and System Logs

Pearson automatically collects log data to help ensure the delivery, availability and security of this site. Log data may include technical information about how a user or visitor connected to this site, such as browser type, type of computer/device, operating system, internet service provider and IP address. We use this information for support purposes and to monitor the health of the site, identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents and appropriately scale computing resources.

Web Analytics

Pearson may use third party web trend analytical services, including Google Analytics, to collect visitor information, such as IP addresses, browser types, referring pages, pages visited and time spent on a particular site. While these analytical services collect and report information on an anonymous basis, they may use cookies to gather web trend information. The information gathered may enable Pearson (but not the third party web trend services) to link information with application and system log data. Pearson uses this information for system administration and to identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents, appropriately scale computing resources and otherwise support and deliver this site and its services.

Cookies and Related Technologies

This site uses cookies and similar technologies to personalize content, measure traffic patterns, control security, track use and access of information on this site, and provide interest-based messages and advertising. Users can manage and block the use of cookies through their browser. Disabling or blocking certain cookies may limit the functionality of this site.

Do Not Track

This site currently does not respond to Do Not Track signals.

Security


Pearson uses appropriate physical, administrative and technical security measures to protect personal information from unauthorized access, use and disclosure.

Children


This site is not directed to children under the age of 13.

Marketing


Pearson may send or direct marketing communications to users, provided that

  • Pearson will not use personal information collected or processed as a K-12 school service provider for the purpose of directed or targeted advertising.
  • Such marketing is consistent with applicable law and Pearson's legal obligations.
  • Pearson will not knowingly direct or send marketing communications to an individual who has expressed a preference not to receive marketing.
  • Where required by applicable law, express or implied consent to marketing exists and has not been withdrawn.

Pearson may provide personal information to a third party service provider on a restricted basis to provide marketing solely on behalf of Pearson or an affiliate or customer for whom Pearson is a service provider. Marketing preferences may be changed at any time.

Correcting/Updating Personal Information


If a user's personally identifiable information changes (such as your postal address or email address), we provide a way to correct or update that user's personal data provided to us. This can be done on the Account page. If a user no longer desires our service and desires to delete his or her account, please contact us at customer-service@informit.com and we will process the deletion of a user's account.

Choice/Opt-out


Users can always make an informed choice as to whether they should proceed with certain services offered by InformIT. If you choose to remove yourself from our mailing list(s) simply visit the following page and uncheck any communication you no longer want to receive: www.informit.com/u.aspx.

Sale of Personal Information


Pearson does not rent or sell personal information in exchange for any payment of money.

While Pearson does not sell personal information, as defined in Nevada law, Nevada residents may email a request for no sale of their personal information to NevadaDesignatedRequest@pearson.com.

Supplemental Privacy Statement for California Residents


California residents should read our Supplemental privacy statement for California residents in conjunction with this Privacy Notice. The Supplemental privacy statement for California residents explains Pearson's commitment to comply with California law and applies to personal information of California residents collected in connection with this site and the Services.

Sharing and Disclosure


Pearson may disclose personal information, as follows:

  • As required by law.
  • With the consent of the individual (or their parent, if the individual is a minor)
  • In response to a subpoena, court order or legal process, to the extent permitted or required by law
  • To protect the security and safety of individuals, data, assets and systems, consistent with applicable law
  • In connection the sale, joint venture or other transfer of some or all of its company or assets, subject to the provisions of this Privacy Notice
  • To investigate or address actual or suspected fraud or other illegal activities
  • To exercise its legal rights, including enforcement of the Terms of Use for this site or another contract
  • To affiliated Pearson companies and other companies and organizations who perform work for Pearson and are obligated to protect the privacy of personal information consistent with this Privacy Notice
  • To a school, organization, company or government agency, where Pearson collects or processes the personal information in a school setting or on behalf of such organization, company or government agency.

Links


This web site contains links to other sites. Please be aware that we are not responsible for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every web site that collects Personal Information. This privacy statement applies solely to information collected by this web site.

Requests and Contact


Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice


We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020