The document discusses skeuomorphs and metaphors in architecture and databases. It explores how mobile applications can architect for performance by making the application smarter through profiling, threading, and caching, using the network intelligently through bundling and pipelining requests, and optimizing databases through stored procedures, queueing, denormalization, and managing result sets. The document considers whether describing the internet as a database is a skeuomorph or metaphor, and discusses lessons learned from prior database architectures that can help improve mobile performance.

1. Skeuomorphs,
Databases,
and Mobile Performance
Architecting for performance with devices & APIs
groups.google.com/group/api-craft
Sam Ramji @sramji
Apigee

2. SKEUOMORPHS

3. A brief history of architecture

4. Banister Fletcher
A History of Architecture

7. “ Greek columns and their entablatures were at
first entirely of timber, with terra-cotta
decorations in the upper trabeation, but were
converted into stone quite early in the
[Hellenic] period, about 600 BC. The translation
was quite direct, timber forms being imitated in
stonework with remarkable exactness. For this
reason, Greek architecture sometimes has been
called a ‘carpentry in marble’…
Banister Fletcher
A History of Architecture

13. Skeuomorphs and metaphors

14. Skeuomorph
A skeuomorph is a design feature found on an
imitation, pastiche or homage that was necessary
only to the original. Often used for the sake of
familiarity, they are details that have moved from
function to form.
Tom Petty
hipstercheerleaders.com

15. Metaphor
In cognitive linguistics, conceptual metaphor, or
cognitive metaphor, refers to the understanding
of one idea, or conceptual domain, in terms of
another, for example, understanding quantity in
terms of directionality (e.g. "prices are rising").
Wikipedia.org
Conceptual Metaphors

16. “ The concepts that govern our thought are not just
matters of the intellect. They also govern our everyday
functioning, down to the most mundane details. Our
concepts structure what we perceive, how we get
around in the world, and how we relate to other
people. Our conceptual system thus plays a central role
in defining our everyday realities. If we are right in
suggesting that our conceptual system is largely
metaphorical, then the way we thinks what we
experience, and what we do every day is very much a
matter of metaphor.
George Lakoff and Mark Johnson
Metaphors We Live By

17. DATABASES

18. A brief history of ^ architecture

19. Connected
Devices
Smartphone N-tier Web App
Personal DCOM CORBA
Computer Website
Minicomputer
Client/Server
Mainframe
Integrated Distributed
Computing Architectures

20. Domain-specific
Data APIs
Private
Cloud DBs
Caching DBs
Data API
Data
Warehousing
Mainframe
RDBMS
Flat file
Shared
Silos
Data Architectures

38. We’ve come back to client-server computing

39. From the perspective of the mobile client,
the Internet is a database.

40. Is that a skeuomorph or a metaphor?

41. If the Internet is a database,
what have we learned from prior eras about
architecting for performance?

42. MOBILE
PERFORMANCE

43. The classic client-server problem returns

44. If the database is slow, the app is slow.

45. Research shows that people will put up with
about 1.5 seconds between interactions.

46. More than 3 seconds on average
and they’ll stop using the app.

47. This is a problem.

48. Let’s dig into our client-server history
to break it down.

49. Make the application smarter
Use the network intelligently
Optimize the database aggressively

50. MAKE THE
APPLICATION
SMARTER

51. application
What makes the app feel fast to the user?

52. application
Time to first render
Time to first interaction
Time between interactions

53. application
Three mutually reinforcing techniques:
Code profiling for performance optimization
Threading/concurrency for user interactions
Client-side caching for everything else

54. application
Use the profiler to see where you’re slow
Write faster code where you see big gains
Run long operations in parallel
Keep local copies of everything you need

55. application
Concurrency

57. application
Anticipation

60. application
Caching

63. application
What should you be caching locally?
Security credentials or tokens
Last user session data
MRU (Most recently used)
MFU (Most frequently used)
LFC (Least frequently changed)
API write operations
Graceful fallbacks for failed API calls

64. application
Issues do remain
Can’t hit local cache on first use of app
Receiving the right shape of data

65. USE THE
NETWORK
INTELLIGENTLY

66. network
The radio network is a
high-latency,
limited-resource environment.

68. network
Speed and battery usage
are both important dimensions of
mobile performance

70. network
Intermittent usage of the radio for
pingbacks
keep-alives
analytics
screen rotations
will slow you down and burn battery.

72. network
A better approach:
Bundling, piggybacking, and pipelining

73. network
Connection Tail
setup time
2 sec n sec 15 sec
Data
Idle transfer
Battery cost of a series of small API requests
90 sec of radio use and battery burn
Bundling a set of API requests
19 sec

74. network
Intermittent analytics and keep-alives
90 sec of radio use and battery burn
Piggybacking on a set of user API requests
19 sec

75. network
API calls in series
200 ms 200 ms 200 ms 200 ms 200 ms
1000 ms
API pipelining

76. Bundling loosely-related requests together
Piggybacking secondary intermittent traffic
Pipelining requests to maximize throughput

77. OPTIMIZE THE
DATABASE
AGGRESSIVELY

78. database
What were our old
database optimization tricks
that we can apply to Internet data?

79. database
Stored Procedures
Queueing
Denormalization
Result Sets

80. database
What is a Stored Procedure in this world?
Server-side code that executes complex operations
Ones that should happen right next to the data
Where you need high compute and low latency
Could be written in node.js, ruby, java, python, c#

81. database
Where does a Stored Procedure run in this world?

82. database
Where does a Stored Procedure run in this world?
Probably in a cloud

83. database
Once you’ve built this architectural layer
you gain a lot of control

84. database
You can deal with queueing, denormalization,
and manage result sets properly.

85. database
Queueing enables you to break the
request/response pair into separate pieces
You may even be able to tell the client when to call
you back for the result
Making your requests to this queueing layer also lets
you serve from a cloud-side cache if you have one

86. database
Denormalization refers to writing multiple indexes
in order to optimize query performance
Where your app relies on your own data, don’t
make it wait for slow queries
Remember, in the cloud, storage is cheap and easy
to obtain – write data as often as needed to improve
query speeds.

87. database
Managing result sets to save bandwidth and
response time means limiting cursor size by default
This can be complementary to the caches you keep
around, since a massive API result is cheap to
manage in the cloud
and can be trickled back to the app in bite-size
chunks.

88. database
Managing result sets to save processor time for the
client is an option as well.
What would happen if you could focus on
app-shaped data?

89. XML in Javascript
var parseXml;
if (typeof window.DOMParser != "undefined")
{
parseXml = function(xmlStr) {
return (new window.DOMParser()).parseFromString(xmlStr,"text/xml");
};
}
else if (typeof window.ActiveXObject != "undefined" &&
new window.ActiveXObject("Microsoft.XMLDOM"))
{
parseXml = function(xmlStr) {
var xmlDoc = new window.ActiveXObject("Microsoft.XMLDOM");
xmlDoc.async = "false";
xmlDoc.loadXML(xmlStr);
return xmlDoc;
};
}
else { throw new Error("No XML parser found"); }
var xml = parseXml("<result>true</result><count>1</count>");
alert(xml.documentElement.nodeName);

90. JSON in Javascript
var json = '{"result":true,"count":1}',
obj = JSON.parse(json);
alert(obj.count);

91. IN
CLOSING

92. There are a few things we can
borrow from the past
to help us right now

93. Make the application smarter
Use the network intelligently
Optimize the database aggressively

94. What did you decide about the statement
“The internet is a database”?

95. Carpentry in marble?
or cognitive tool?

96. Skeuomorph?
or metaphor?

97. groups.google.com/group/api-craft

98. THANK YOU
Questions and ideas to:
@sramji
groups.google.com/group/api-craft