Data Connectivity Best Practices

Report
PUG Challenge Americas
– 2012 Remove
Click toPerformance
edit MasterBottlenecks
title style in Your SQL Connections Data Connectivity Performance Best Practices
Steve Pittman, Architect
OpenEdge SQL
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© 2012 Progress Software Corporation. All rights reserved.
Disclaimer
The future features described in this presentation
are under consideration by Progress Software and
are not commitments for future products,
technologies, or services.
Any forward looking statements represent our
estimates only as of today and should not be relied
upon as representing our estimates as of any
subsequent date. While we may elect to update
forward looking statements at some point in the
future, we specifically disclaim any obligation to do
so, even if our estimates change.
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© 2012 Progress Software Corporation. All rights reserved.
Agenda
 Where did all that data come from?
 What can we do?
 A systematic approach to performance
 An OpenEdge perspective
 Questions?
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© 2012 Progress Software Corporation. All rights reserved.
A Brief Audience Survey
 # using ODBC
– Tools – Crystal?
 # using JDBC
– Tools – DbVis?
 # using Java
 Java appservers
– WebLogic?
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© 2012 Progress Software Corporation. All rights reserved.
Humans are information machines
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
Humans are now storing over 988 Exabytes
of information (at the end of 2010)

15 petabytes of information generated every
day

Scientific, Engineering, Financial, Social – all
areas of our lives continue to generate and
store the world’s data at an increasing rate.
© 2012 Progress Software Corporation. All rights reserved.
Making this data useable
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© 2012 Progress Software Corporation. All rights reserved.

Performance trends in 2010-11 were
centered around making this data
more quickly accessible (and more
useful).

Sorting, cataloging, querying,
inserting…all these are required for
making the data mean something –
and it has to be fast!
Performance trends in 2012

Virtualization made efficiency a way of life

Concurrency will gain steam in 2012
– Research on multi-core has been building
– New tools by chip makers will help
– Additional Language constructs and
compiler directives will come
– Java application development frameworks
– Application servers – WebLogic, JBoss

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Larger buffers and algorithm changes will
take place to fully utilize 64 bit processors.
© 2012 Progress Software Corporation. All rights reserved.
How did we get here?
Multi-tenant db
2012
1982
The advance of information technology (hardware and
software) gives you a dizzying array of choices on
how to store your data….
…and not everyone has the same opinion.
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A typical Enterprise App Architecture
Application UI
Buffers, I/O, etc..
Business Logic &
Data Access Code
Driver
Network efficiency
Database
Database Settings
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© 2012 Progress Software Corporation. All rights reserved.
Time is of the essence
 Large amounts of data
require long processing
times – small percentage
gains result in large time
savings
 Performance tuning steps
remain the same
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So, what can we do to keep up?
Aggressively analyze all pieces of your
application architecture.
Just follow the PANDDa.
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Where Performance Bottlenecks Lie
P.A.N.D.Da
Platform
Application Code
Network
Driver
Database
Which element will give the most
payback?
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© 2012 Progress Software Corporation. All rights reserved.
Platform

Consider native calls into the Platform and
whether you can do them more efficiently.

Varying client platform performance levels
–
–
–
–

Windows
Linux: 32bit, 64bit
Unix
Scale up, scale out
What are your optimization options? Are
tools available? Ex. Intel Parallel Studio
Consider Resource Usage when the
Platform is Virtualized!
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Platform – Virtualization
On a machine that has much less available Memory
and/or CPU, this graph will look different.
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Memory Usage Scalability – from the Lab
Still consumes
less Memory!!
Application #5
Application #4
Application #3
Application #2
Application #1
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© 2012 Progress Software Corporation. All rights reserved.
Virtualization Update
 Updated Performance Lab to scale Virtual
machines to measure VM Impact.
VM1
DD
1
3559.7
2
3
VM2
Comp
DD
VM3
Comp
Total
VM3
Total
2305
11741.8
7394.9
41.60%
49.40%
88.00%
58.80%
4155.9
7006
3162.7
18982.7
11347.6
48.30%
44.40% 121.50%
67.30%
4846.4
8117.6
3631.4
24172.8
13285.4
61.80%
70.80% 123.50%
82.00%
9809.8
5191
8593.5
3699
28048.8
14219.6
81.00%
89.00% 132.30%
97.30%
11031.7
5678.6
9163.5
3832.2
31061.4
15078.7
95.20%
94.30% 139.10% 106.00%
4493.3
11259.7
4146.8
35218.3
13066.2
169.30% 167.90% 171.50% 169.50%
12986.4
6312
12401.2
4451.7
38185.9
16399.9
127.10% 105.70% 178.60% 132.80%
13851.1
5820.3
13224.6
3259.7
40794.1
15397.8
117.10% 138.00% 305.70% 164.90%
6230.1
14601.7
6489
14135.6
3905.4
43167
16624.5
131.60% 125.00% 262.00% 159.70%
6294.1
15316.7
6277
14648.6
3329.3
45194
15900.4
142.00% 144.00% 340.00% 184.20%
3848.1
2575.2
5974.4
4029
6002.3
7778.9
4807.6
8276.3
4
9645.5
5329.6
5
10866.2
5567.9
6
11921.4
4426.1
12037.2
7
12798.3
5636.2
8
13718.4
6317.8
9
14429.7
10
15228.7
+
+
Comp
DD
Comparison
4334
2514.7
DD
=
Comp
VM1
VM2
The Competition needs 3 virtual machines to achieve the same
performance as 1 of our virtual machines!
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© 2012 Progress Software Corporation. All rights reserved.
Virtualized Optimizations give you options!
Increase throughput
Add Progress | DataDirect
6277rps
6294rps
3329rps
Total = 15900 rps
15229rps
15317rps
14649rps
Total = 45194 rps
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© 2012 Progress Software Corporation. All rights reserved.
Machine Consolidation
Application Code & Infrastructure

Faster communication
– Caching & Object Reuse
(avoiding comm!)

Increase Parallelism
– Threading, Concurrency
– Network async streams
– Not for basic reporting!

Minimize Slow operations
– Disk I/O, blocking operations

Re-architect when ?
– Reference architectures

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Tools
– latest versions
© 2012 Progress Software Corporation. All rights reserved.
It’s like the Tower of Babel; we have
great infrastructure… but we still can’t
communicate
Network
Physical Location
Co-locate, Same country,
City, etc..
Security is expensive
How many Hops?
At what speed?
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The Network has much to tune…
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The Driver is the network
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Database

Utilize OpenEdge Tools if available
–

E.g., promon statement cache options
Data Layout
– Tune your SQL queries
– Eliminate unnecessary calls and scans
– Save MetaData

Memory tuning
– Buffer sizes, pre-fetch, etc.

Disk Usage
– Striping, storing more data in memory

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Logging and health monitors – look in
the OpenEdge documentation
© 2012 Progress Software Corporation. All rights reserved.
OpenEdge sql techniques – better connectivity

Quick ordering
– “SELECT TOP”

Minimize round trips
– Stored procedures

Capturing preferred query form
– Views

Managing variable sized data
– dbtool for column width
– Network buffer memory impact
– Rows per network message

Managing concurrency effects
– Lockwait timeout
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SELECT TOP – Order and Time
db
TOP
ordering
App
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ORDER
BY
Sorting
machine
Optimized
ordering
Java Stored Procedure – logic on the server
App
Stored
Proc
SQL
db
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Push network
traffic
to server
Pushing best query elements into sql views

Views can be a toolbox of nicely working query components
– Pre-fab join relationships for naturally related tables
• The right tables with the right join predicates
• The right WHERE clause predicates to choose correct data
• Avoid those queries missing a vital WHERE predicate

Views can be a storehouse of totally built queries
– End users pick the view vs. end users built query from scratch

Accelerate those ad-hoc reports with views as building blocks

Views can provide security
– Expose only “need to know” tables, columns
– Screen out data which must be private or secured away

Simple to setup and use
–
–
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CREATE VIEW myview AS <regular SELECT statement>
SELECT * FROM myview WHERE myview.region = ‘NW’
© 2012 Progress Software Corporation. All rights reserved.
Failing transactions – the problem
SELECT *
FROM customer
WHERE custnum
BETWEEN 10000 AND 20000
UPDATE customer
SET city = ‘Northboro’
WHERE custnum = 12345
12345,Smith Trucking, Westford,MA,02423,…..
Customer table
lockWaitTimeout expires
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© 2012 Progress Software Corporation. All rights reserved.
Failing transactions – some help

Global lockwait timeout
– Environment variable PROSQL_LOCKWAIT_TIMEOUT
• export PROSQL_LOCKWAIT_TIMEOUT=30
• Significant shortcomings

JDBC Connection property
– “lockWaitTimeout”
– As of 10.2B04
String
url = "jdbc:datadirect:openedge://localhost:9878;" +
"databaseName=mys2k;lockWaitTimeout=60";
Connection conn = DriverManager.getConnection(url, ….. );

FUTURE: ODBC Connection property
– “lockWaitTimeout”, same format
– Target delivery in OE 11.2
– In ODBC Data Admin “Advanced” Tab
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© 2012 Progress Software Corporation. All rights reserved.
Coping with column sizes

Power of the ABL
– ABL: size unlimited – TEXT
– Sql: size limited
– VARCHAR (61)

Result: “over-stuffed” columns
• OE sql error: “Column XXX has value exceeding it’s max length”

Server side fixes
– Data Dictionary
• Options - SQL Properties - Adjust Field Width
– OE SQL as DBA
• ALTER TABLE ALTER COL SET PRO_SQL_WIDTH …..
– dbtool
• High performance, multi-threaded db maintenance
• Menu choice: SQL Width Scan w/Fix Option
• Online schema updater
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© 2012 Progress Software Corporation. All rights reserved.
Coping with column sizes - more
 Client side fixes
– Find column which has size problem from error text
• “Column Name in table PUB.Customer has value
exceeding its max length or precision.”
– Change sql statement column reference to “substring()”
• SELECT Name, city, state, country FROM pub.customer ……
• SELECT SUBSTR( Name, 1, 84) AS ‘Name’, city, state,
country, ……
– OR, truncate over-stuffed value to column defined size
• SELECT SUBSTR( Name, 1) AS ‘Name’, city, state, country,
……
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© 2012 Progress Software Corporation. All rights reserved.
Coping with column sizes – maxing out
App
Table1 Table2 Table3
result set result result
set
set
rows
rows
rows
Query
network buffers
32K * 100 cols * 50 rows = 160M
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© 2012 Progress Software Corporation. All rights reserved.
db
New Challenges & Research in 2012

More 2012 Enterprise Performance Research
– Caching, Concurrency, Cloud deployment

Mobile devices
– 3g to 4g to wiMax
– Hardware upgrades coming fast

Services still the norm – what’s next?
–
–

SaaS
PaaS
SQL vs NoSQL
“Cloud”
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© 2012 Progress Software Corporation. All rights reserved.
In Summary
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
Humans continue to create
copious amounts of data at
breakneck speed. This data
must be cataloged, sorted, and
queried – the latest
improvements in data access
middleware will ensure this
remains scalable for your
applications in the enterprise!

R&D trends in 2011 give way to
actionable development
changes in 2012. Follow the
P.A.N.D.Da model to keep your
application up to date!
© 2012 Progress Software Corporation. All rights reserved.
For More Information

Progress|DataDirect Website: www.datadirect.com

More than a Driver: http://web.datadirect.com/products/feature-overview/data-connectivity/anatomy/index.html

Progress|DataDirect Performance Data: http://web.datadirect.com/products/feature-overview/data-connectivity/performance.html

Progress|DataDirect Virtualization: http://web.datadirect.com/solutions/virtualization/virtualization.html

Documentation: http://www.datadirect.com/support/product_info/proddoc_product/index.ssp
Contact Us: http://web.datadirect.com/contact-us/request_information.html
NA Tel Number: +1-800-876-3101
Intl Tel Number: +44 (0) 1753-218 930
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© 2012 Progress Software Corporation. All rights reserved.

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