The Data Distribution Service (DDS) is a standard for efficient and ubiquitous data sharing built upon the concept of a, strongly typed, distributed data space. The ability to scale from resource constrained embedded systems to ultra-large scale distributed systems, has made DDS the technology of choice for applications, such as, Power Generation, Large Scale SCADA, Air Traffic Control and Management, Smart Cities, Smart Grids, Vehicles, Medical Devices, Simulation, Aerospace, Defense and Financial Trading. This two part webcast provides an in depth introduction to DDS – the universal data sharing technology. Specifically, we will introduce (1) the DDS conceptual model and data-centric design, (2) DDS data modeling fundamentals, (3) the complete set of C++ and Java API, (4) the most important programming, data modeling and QoS Idioms, and (5) the integration between DDS and web applications. After attending this webcast you will understand how to exploit DDS architectural features when designing your next system, how to write idiomatic DDS applications in C++ and Java and what are the fundamental patterns that you should adopt in your applications.

1. OpenSplice | DDS Tutorial
-- Part II -Angelo CORSARO, Ph.D.
Chief Technology Officer
OMG DDS Sig Co-Chair
PrismTech
angelo.corsaro@prismtech.com

2. Part I Recap

3. DDS is a standard technology for ubiquitous, interoperable,
secure, platform independent, and real-time data sharing
across network connected devices

4. Data Distribution Service (DDS)
•
DDS’ Global Data Space is fully
distributed, highly efficient and
scalable
Data
Writer
QoS
Data
Writer
TopicD
Data
Reader
QoS
TopicA
Data
Writer
QoS
QoS
TopicC
Data
Reader
TopicB
...
Data
Writer
Data
Reader
DDS Global Data Space
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•
DDS provides a Global Data Space
abstraction that allow applications to
autonomously, anonymously,
securely and efficiently share data
Data
Reader

5. DDS Entities
Domain (e.g. Domain 123)
Domain
Participant
Topic
Partition (e.g. “Telemetry”, “Shapes”, )
Topic Instances/Samples
Ta
•
•
•
•
Tb
Publisher
Subscriber
Tx
Ty
Tc
DataWrter
DataReader
DomainParticipant: Provides access to a data cloud -- called a domain in DDS
Topic: Domain-wide definition of a kind of Information
Publisher/Subscriber: Provide scope to data sharing through the concept of partitions
DataReader/DataWriter: Allow to read/write data for a given topic in the partitions their Subscriber/Publisher are associated with.
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T1
T1 T3

6. Part II

7. Quality of Service

8. QoS Model
•
QoS-Policies control local and endto-end properties of DDS entities
Type Matching
Local properties controlled by QoS
are related resource usage
QoS matching
QoS
QoS
QoS
•
•
Some QoS-Policies are matched
based on a Request vs. Offered
(RxO) Model
QoS
QoS
Topic
Name
Publisher
End-to-end properties controlled by
QoS are related to temporal and
spatial aspects of data distribution
QoS
QoS
...
DataWriter
writes
Type
reads
Subscriber
DataReader
...
...
DomainParticipant
DataWriter
writes
Type
reads
DataReader
DomainParticipant
Name
Topic
QoS
QoS
QoS
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9. QoS Policies
[T: Topic] [DR: DataReader] [DW: DataWriter] [P: Publisher]
[S: Subscriber]
Applicability
RxO
Modifiable
USER_DATA
DP, DR, DW
N
Y
TOPIC_DATA
T
N
Y
GROUP_DATA
P, S
N
Y
DURABILITY
T, DR, DW
Y
N
DURABILITY
SERVICE
T, DW
N
N
HISTORY
T, DR, DW
N
N
PRESENTATION
P, S
Y
N
RELIABILITY
T, DR, DW
Y
N
PARTITION
P, S
N
Y
DESTINATION
ORDER
T, DR, DW
Y
N
LIFESPAN
T, DW
N
Y
Configuration
Data Availability
Data Delivery
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QoS Policy
[DP: Domain Participant]

10. QoS Policies
[T: Topic] [DR: DataReader] [DW: DataWriter] [P: Publisher]
[S: Subscriber]
QoS Policy
Applicability
RxO
Modifiable
DEADLINE
T, DR, DW
Y
Y
LATENCY BUDGET
T, DR, DW
Y
[DP: Domain Participant]
Y
Temporal/
Importance
Characteristics
T, DW
N
Y
TIME BASED FILTER
DR
N
Y
OWNERSHIP
T, DR, DW
Y
N
OWNERSHIP
STRENGTH
DW
N
Y
Replication
LIVELINESS
T, DR, DW
Y
N
Fault-Detection
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TRANSPORT
PRIORITY

11. QoS DSL
•
•
The ISO C++ and Java 5 APIs provide DSL for dealing with QoS Policies configuration
•
Policies as well as Entity QoS are immutable — this allows for better safety and
object sharing
•
Policies are treated as algebraic data types and the DSL provide constructors of
each of the cases
•
A QoS Provider can now be used to retrieve QoS settings from external sources, e.g.
a file, an HTTP server, DDS durability
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The DSL uses language specific idioms, such as fluid interfaces, as well as specific
features of the languages

12. C++ QoS Policy DSL
//
==
ISO
C++
DDS
API
==
!
!
DataWriterQos
dwqos
=
pub.default_datawriter_qos()
!
<<
History.KeepLast(10)
<<
Durability.Transient();
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!

13. Java 5 QoS Policy DSL
//
==
Java
5
DDS
API
==
!
final
PolicyFactory
pf
=
...
!
DataWriterQos
dwqos
=
pub.getDefaultDataWriterQos()
!
.withPolicies
(
pf.History.withKeepLast(10),
pf.Durability.withTransient(),
);
!
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14. Data Delivery
Reliability
Data Delivery
Presentation
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Partition
Destination
Order

15. Reliability QoS Policy
The Reliability Policy controls the level of guarantee offered by the DDS
in delivering data to subscribers
•
Best Effort. Indicates that it is acceptable not to retry propagation
of samples
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•
Reliable. In steady-state, and with no data writer crashes, guarantees
that all samples in the DataWriter history will eventually be
delivered to all the DataReader
QoS Policy
Applicability
RxO
Modifiable
RELIABILITY
T, DR, DW
Y
N

16. Setting Reliability Policy
//
==
ISO
C++
DDS
API
==
!
//
Reliable
Reliability
DataWriterQos
dwqos
=
!
pub.default_datawriter_qos()
<<
Reliability.Reliable();
!
//
Best-­‐Effort
Reliability
DataWriterQos
dwqos
=
pub.default_datawriter_qos()
<<
Reliability.BestEffort();
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17. Setting Reliability Policy
//
==
Java
5
DDS
API
==
!
final
PolicyFactory
pf
=
...
!
//
Reliable
Reliability
DataWriterQos
dwqos
=
!
pub.getDefaultDataWriterQos()
!
.withPolicies(pf.Reliability.withReliable());
//
Best-­‐Effort
Reliability
DataWriterQos
dwqos
=
pub.getDefaultDataWriterQos()
.withPolicies(pf.Reliability.withBestEffort());
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18. Partitions
•
Partitions are the mechanism provided by DDS to
organise information within a domain
•
•
Access to partitions is controlled through QoS Policies
• “system:telemetry”
• “system:log”
• “data:row-­‐2:col-­‐3”
•
Partitions addressed by name or regular expressions:
•
• “data:row-­‐2:col-­‐*”
”system:telemetry”
Partitions
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Partitions are defined as strings:

19. Partition QoS Policy
The Partition QoS Policy can be
used as subjects for organising the
flows of data
•
The Partition QoS Policy is used
to connect Publishers/Subscribers
to a Partitions’ List which might
also contain wildcards, e.g. tracks.*
•
Topics instances are published and
subscribed across one or more
Partitions
Partitions
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20. Setting Partition QoS Policy
//
==
ISO
C++
DDS
API
==
!
//
Setting
a
Partition
PublisherQos
pqos
=
!
dp.default_publisher_qos()
<<
Partition(“MyPartition”);
!
//
Setting
a
List
of
Partitions
PublisherQos
pqos
=
dp.default_publisher_qos()
<<
Partition(myPartitionList);
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21. Setting Partition QoS Policy
//
==
Java
5
DDS
API
==
!
final
PolicyFactory
pf
=
...
!
//
Setting
a
Partition
PublisherQos
pqos
=
!
dp.getDefaultPublisherQos()
!
.withPolicies(pf.Partition(“MyPartition”));
//
Setting
a
List
of
Partitions
PublisherQos
pqos
=
dp.getDefaultPublisherQos()
.withPolicies(pf.Partition(myPartitionList));
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22. Data Availability
History
Durability
Ownership
Ownership
Strength
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Lifespan
Data
Availability

23. History QoS Policy
3
time
2
time
3
4
e
ssur
Pre
KeepLast(3)
The DataWriter HISTORY QoS Policy controls
the amount of data that can be made available to
late joining DataReaders under
TRANSIENT_LOCAL Durability
The DataReader HISTORY QoS Policy controls
how many samples will be kept on the reader cache
•
Keep Last. DDS will keep the most recent
“depth” samples of each instance of data
identified by its key
•
Keep All. The DDS keep all the samples of
each instance of data identified by its key -- up
to reaching some configurable resource limits
time
KeepAll
QoS Policy
HISTORY
Applicability
T, DR, DW
RxO
N
Modifiable
N
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2
e
ssur
Pre
0
1
e
ssur
Pre
0
KeepLast(1)

24. Durability QoS Policy
The DURABILITY QoS controls the data availability w.r.t. late joiners,
specifically the DDS provides the following variants:
•
•
Volatile. No need to keep data instances for late joining data readers
•
•
Transient. Data instance availability outlives the data writer
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Transient Local. Data instance availability for late joining data reader is
tied to the data writer availability
Persistent. Data instance availability outlives system restarts
QoS Policy Applicability
DURABILITY T, DR, DW
RxO
Y
Modifiable
N

25. Volatile Durability
Data
Writer
QoS
TopicA
•
•
Data
Reader
No Time Decoupling
Readers get only data produced after they joined the Global Data Space
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26. Volatile Durability
Late Joiner
!
!
Data
Reader
Data
Writer
QoS
TopicA
Data
Reader
•
•
No Time Decoupling
Readers get only data produced after they joined the Global Data Space
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27. Volatile Durability
Late Joiner
!
!
Data
Reader
Data
Writer
2
QoS
TopicA
Data
Reader
•
•
No Time Decoupling
Readers get only data produced after they joined the Global Data Space
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28. Transient Local Durability
Data
Writer
QoS
TopicA
•
•
Data
Reader
Some Time Decoupling
Data availability is tied to the availability of the data writer and the history settings
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29. Transient Local Durability
Late Joiner
!
!
Data
Reader
Data
Writer
1
QoS
TopicA
Data
Reader
•
•
Some Time Decoupling
Data availability is tied to the availability of the data writer and the history settings
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30. Transient-Local Durability
Data
Reader
Data
Writer
1
2
1
QoS
TopicA
Data
Reader
•
•
Some Time Decoupling
Data availability is tied to the availability of the data writer and the history settings
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31. Transient Durability
Data
Writer
QoS
TopicA
1
•
•
Time Decoupling
Data availability is tied to the availability of the durability service
Data
Reader
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1

32. Transient Durability
Late Joiner
!
!
Data
Reader
Data
Writer
QoS
TopicA
Data
Reader
1
•
•
Time Decoupling
Data availability is tied to the availability of the durability service
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1

33. Transient Durability
Data
Reader
Data
Writer
1
2
QoS
TopicA
2
Data
Reader
1
•
•
Time Decoupling
Data availability is tied to the availability of the durability service
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1

34. Transient Durability
Data
Reader
2
1
QoS
TopicA
1
2
•
•
Time Decoupling
Data availability is tied to the availability of the durability service
1
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2
Data
Reader

35. Transient Durability
Data
Reader
2
1
QoS
TopicA
1
2
1
!
Data
Reader
!
•
•
Time Decoupling
Late Joiner
Data availability is tied to the availability of the durability service
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2
Data
Reader

36. Setting the Durability Policy
//
==
Java
5
DDS
API
==
!
final
PolicyFactory
pf
=
...
!
!
//
Setting
TransientLocalDurability
PublisherQos
pqos
=
dp.getDefaultPublisherQos()
.withPolicies(pf.Durability().withTransientLocal());
!
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37. Ownership QoS Policy
Availability of data producers can be controlled via two QoS Policies
•
•
•
OWNERSHIP (SHARED vs. EXCLUSIVE)
•
Writer strength is used to coordinate replicated writers
Instances of exclusively owned Topics can be modified (are owned)
by the higher strength writer
QoS Policy
OWNERSHIP
STRENGTH
Applicability
T, DR, DW
DW
RxO
Y
N
Modifiable
N
Y
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38. Temporal Properties
TimeBasedFilter
Deadline
[Inbound]
[Outbound]
LatencyBudget
Latency
TransportPriority
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Throughput

39. Latency Budget
•
The LATENCY_BUDGET QoS
policy specifies the maximum
acceptable delay from the time
the data is written until the
data is inserted in the
receiver's application-cache
QoS Policy Applicability
LATENCY
T, DR, DW
BUDGET
RxO
Y
Modifiable
Y
Latency = T1+T2+T3
A non-zero latency-budget
allows a DDS implementation
to batch samples and improve
CPU/Network utilisation
DataWriter
T3
T1
Batching
T2
DataReader
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40. Deadline QoS Policy
The DEADLINE QoS policy defines the
maximum inter-arrival time between data
samples
RxO
Y
Modifiable
Y
DataWriter indicates that the application
commits to write a new sample at least
once every deadline period
DataWriter
•
Applicability
T, DR, DW
DataReaders are notified when the
DEADLINE is violated
Deadline
Deadline
Deadline
Deadline Violation
Deadline
Deadline
DataReader
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QoS Policy
DEADLINE

41. Transport Priority QoS Policy
QoS Policy
Applicability
RxO
Modifiable
TRANSPORT
PRIORITY
T, DW
N
Y
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•
The TRANSPORT_PRIORITY QoS policy is a hint to the
infrastructure as to how to set the priority of the underlying
transport used to send the data.

42. Time-Based Filter QoS Policy
•
The Time Based Filter
allows to control the
throughput at which data is
received by a data reader
Samples produced more
often than the minimum
inter-arrival time are not
delivered to the data reader
QoS Policy
Applicability
RxO
Modifiable
TIME BASED FILTER
DR
N
Y
mit
Latency = T1+T2+T3
DataWriter
T3
DataReader
T2
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•
mit
mit
mit
mit = minimum inter-arrival time
produced sample
delivered sample
discarded sample

43. QoS Provider
This class allows to externally define policies and decouples the
mechanism used to define and access policy definition with policy
creation
//
QosProvider...
QosProvider
qos_provider(
!
"http://www.opensplice.org/demo/config/qos.xml",
"ishapes-­‐profile");
!
!
DataReader<ShapeType>
dr(sub,
topic,
qos_provider.datareader_qos());
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•
•
The new C++ and Java APIs introduce the concept of a QoS Provider

44. Demo: QoS in Action

45. Shapes Application
•
The iShapes application is used by DDS
vendors to demonstrate some of the
basic mechanism as well as product
interoperability
•
Three Topics
•
One Type
struct ShapeType {
string color;
long x;
long y;
long shapesize;
};
#pragma keylist ShapeType color
Spotted shapes represent subscriptions
Pierced shapes represent publications
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Circle, Square, Triangle

46. QoS Idioms

47. Soft State
In distributed systems you often need to model soft-state -- a state that
is periodically updated
•
Examples are the reading of a sensor (e.g. Temperature Sensor), the
position of a vehicle, etc.
•
The QoS combination to model Soft-State is the following:
Reliability
=>
BestEffort
Durability
=>
Volatile
History
=>
KeepLast(n)
[with
n
=
1
in
most
of
the
cases]
Deadline
=>
updatePeriod
LatencyBudget
=>
updatePeriod/3
[rule
of
thumb]
DestinationOrder
=>
SourceTimestamp
[if
multiple
writers
per
instance]
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48. Hard State
•
In distributed systems you often need to model hard-state -- a state that
is sporadically updated and that often has temporal persistence
requirements
•
•
Examples are system configuration, a price estimate, etc.
Reliability
=>
Reliable
Durability
=>
Transient
|
Persistent
History
=>
KeepLast(n)
[with
n
=
1
in
most
of
the
cases]
DestinationOrder
=>
SourceTimestamp
[if
multiple
writers
per
instance]
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The QoS combination to model Hard-State is the following:

49. Events
In distributed systems you often need to model events -- the occurrence
of something noteworthy for our system
•
Examples are a collision alert, the temperature beyond a given threshold,
etc.
•
The QoS combination to model Events is the following:
Reliability
=>
Reliable
Durability
=>
any
[depends
on
system
requirements]
History
=>
KeepAll
[on
both
DataWriter
and
DataReader!]
DestinationOrder
=>
SourceTimestamp
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50. Accessing the Reader Cache

51. Reading Samples
Samples can be read from the Data Reader History Cache
The action of reading a sample is non-destructive. Samples are not
removed from the cache
DataReader
DataReader
...
DataReader Cache
read
...
DataReader Cache
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•
•

52. Taking Samples
Samples can be taken from the Data Reader History Cache
The action of taking a sample is destructive. Samples are removed
from the cache
DataReader
DataReader
...
DataReader Cache
take
...
DataReader Cache
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•
•

53. Sample Selectors
DDS provides some very flexible mechanisms for selecting the
samples to be read/take:
•
•
•
Content
Status
These mechanisms are composable
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54. Content-Based Selection

55. Filters and Queries
•
DDS Filters allow to control what gets
into a DataReader cache
•
DDS Queries allow to control what
gets out of a DataReader cache
Application
Query
DataReader
Filters are defined by means of
ContentFilteredTopics
•
Filters and Queries are expressed as
SQL where clauses
DataReader Cache
Filter
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Queries operate in conjunction with
read operations
...
•
...
...
...
•

56. // == ISO C++ DDS API
!
// Create a Topic
auto topic = Topic<ShapeType>(dp, “Circle”);
!
// Define filter expression and parameters
!
auto filter = Filter(“x < 100 AND y < 200”);
!
!
// Define content filtered topic
auto cftopic =
ContentFilteredTopic<ShapeType>(“CFCircle”, topic,
filter)
!
// Create a DataReader for the content-filtered Topic
auto dr = DataReader<ShapeType>(sub,cftopic)
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Filters
struct ShapeType {
string color;
long x;
long y;
long shapesize;
};
#pragma keylist ShapeType color

57. Filters
struct ShapeType {
string color;
long x;
long y;
long shapesize;
};
#pragma keylist ShapeType color
!
final
PolicyFactory
pf
=
runtime.policyFactory();
final
DataReaderQos
drqos
=
sub.getDefaultDataReaderQos()
!
.withPolicy
(
!
pf.ContentFilter()
.withFilter(
new
JavaScriptFilter<ShapeType>("data.x
>
data.y"))
);
!
final
DataReader<ShapeType>
dr
=
sub.createDataReader(shape,
drqos);
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//
==
Java
5DDS
API
==

58. Query
struct ShapeType {
string color;
long x;
long y;
long shapesize;
};
#pragma keylist ShapeType color
//
==
ISO
C++
DDS
API
==
!
//
Define
filter
expression
and
parameters
!
auto
dr
=
DataReader<ShapeType>(sub,
topic)
val
query
=
Query(dr,
“x
<
100
AND
y
<
200”);
!
!
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dr.select()
.content(query)
.read();

59. Query
struct ShapeType {
string color;
long x;
long y;
long shapesize;
};
#pragma keylist ShapeType color
//
==
Java
5
DDS
API
==
!
Filter<ShapeType>
filter
=
!
new
JavaScriptFilter<ShapeType>("data.x
>
data.y"))
!
!
!
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dr.select()
.content(filter)
.read();

60. Instances
•
DDS provides a very efficient way of reading data belonging to a specific Topic
Instance
•
Obviously, one could use queries to match the key’s value, but this is not as
efficient as the special purpose instance selector
//
==
ISO
C++
DDS
API
==
auto
handle
=
!
dr.lookup_instance(ShapeType(“RED”,
0,
0,
0));
!
auto
data
=
dr.select()
.instance(handle)
.read();
!
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61. State Based Selection

62. Sample, Instance, and View State
The samples included in the DataReader cache have associated some metainformation which, among other things, describes the status of the sample and its
associated stream/instance
•
The Sample State (READ, NOT_READ) allows to distinguish between new samples
and samples that have already been read
•
The View State (NEW, NOT_NEW) allows to distinguish a new instance from an
existing one
•
The Instance State (ALIVE, NOT_ALIVE_DISPOSED, NOT_ALIVE_NO_WRITERS)
allows to track the life-cycle transitions of the instance to which a sample belongs
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•

63. State Selector in Action
//
==
ISO
C++
DDS
API
==
!
//
Read
only
new
samples
auto
data
=
dr.read()
!
!
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!
//
Read
any
samples
from
live
instances
auto
data
=
dr.select()
.state(DataState::any_data())
.read();

64. State Selector in Action
//
==
Java
5
DDS
API
==
!
//
Read
only
new
samples
auto
data
=
dr.read()
!
!
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//
Read
any
samples
from
live
instances
auto
data
=
dr.select()
.dataState(sub.createDataState().withAnySampleState())
.read();

65. Putting all Together
//
==
ISO
C++
DDS
API
==
!
auto
data
=
!
dr.select()
!
.content(query)
.state(data_state)
.instance(handle)
.read();
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•
Selectors can be composed in a flexible and expressive manner

66. Application / DDS
Interaction Models

67. Interaction Models
Polling
•
The application proactively polls for data availability as well as special events, such as a
deadline being missed, etc. Notice that all DDS API calls, exclusion made for wait
operations, are non-blocking
Synchronous Notification
The application synchronously waits for some conditions to be verified, e.g., data
availability, instance lifecycle change, etc.
Asynchronous Notification
•
The application registers the interest to be asynchronously notified when specific
condition are satisfied, e.g. data available, a publication matched, etc.
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•

68. Synchronous Notifications
•
DDS provides a mechanism known as WaitSet to synchronously
wait for a condition
•
Condition can predicate on:
communication statuses
data availability
data availability with specific content
user-triggered conditions
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•
•
•
•

69. WaitSet
//
==
Java
5
DDS
API
==
!
//
Create
the
waitset
WaitSet
ws
=
runtime.createWaitSet();
!
Subscriber.DataState
ds
=
sub.createDataState();
!
!
//
Attach
the
condition
ws.attachCondition(c);
!
//
Wait
for
the
condition
ws.wait();
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//
Create
the
condition
!
Condition
c
=
dr.createReadCondition(
!
ds.withAnyViewState()
.with(InstanceState.ALIVE)
.with(SampleState.NOT_READ));

70. Asynchronous Notifications
•
DDS provides a mechanism known as Listeners for asynchronous
notification of a given condition
•
Listener interest can predicate on:
communication statuses
data availability
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•
•

71. Listener Declaration
//
==
ISO
C++
DDS
API
==
!
class
ShapeListener
:
public
dds::sub::NoOpDataReaderListener<ShapeType>
{
public:
ShapeListener()
{}
virtual
void
on_data_available(dds::sub::DataReader<ShapeType>&
dr)
{
auto
samples
=
dr.read();
std::for_each(samples.begin(),
samples.end(),
!
[](const
dds::sub::Sample<ShapeType>&
sample)
{
!
if
(sample.info().valid())
//
Check
if
sample
contains
valid
data
std::cout
<<
sample.data()
<<
std::endl;
});
}
!
virtual
void
on_liveliness_changed(dds::sub::DataReader<ShapeType>&
the_reader,
const
dds::core::status::LivelinessChangedStatus&
status)
{
std::cout
<<
">>
Liveliness
Changed!
"
<<
std::endl;
}
};
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72. Listener Registration
//
==
ISO
C++
DDS
API
==
!
auto
l
=
new
ShapeListener();
!
//
Create
a
“nothing”
status
mask
StatusMask
mask
=
StatusMask::none();
!
//
Add
the
statuses
we
are
interested
in.
mask
<<
StatusMask::data_available()
<<
StatusMask::liveliness_changed()
<<
StatusMask::liveliness_lost();
!
//
Register
the
listener
with
the
associated
mask
dr.listener(l,
mask);
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!
!

73. Common Bootstrap Questions

74. Can I use C++11?
If you want to use C++11 in your DDS applications then you need
to enable support for it. Check:
•
http://dev.opensplice.org/releases/downloads/docs/isocpp/html/
isocpp_customlibs.html
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•
•
OpenSplice default configuration does not require C++11

75. Which DDS Implementation
If you are planning to use C/C++ or C# you may consider
OpenSplice DDS
•
If you are developing Java Applications or are interested in targeting
Android then you may consider OpenSplice Mobile
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•

76. Where can I find the Java 5 API?
The Java 5 API is currently implemented only as part of OpenSplice
Mobile
•
OpenSplice Mobile is a pure Java implementation of DDS
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•

77. Can I “Script” DDS Applications?
Assuming you deploy on the JVM then you have two options
•
Use the DDS Java 5 API through Scala, and then run your scala
program as a script
•
The Molière Scala API for DDS and run the resulting program as a
script
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•
Use the DDS API from JavaScript (or any other script language
supported by the JVM) and execute the script through the
javax.script.ScriptEngine

78. How can I Debug my DDS App?
OpenSplice DDS
•
Use the Tuner to inspect entities and QoS
OpenSplice Mobile
•
Use OpenSplice Monitor to inspect entities and QoS
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!

79. Copyright
2013,
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–
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OpenSplice Monitor

80. Part II
Summary & Concluding Remarks

81. Summary & Remarks
•
DDS a rich set of QoS to control the key non-functional properties
of data
•
DDS provides idiomatic API which are highly expressive and simple
to use
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•
DDS provides an elegant Data Space abstraction that allows
application to share data ubiquitously and efficiently -- the Data
Space implementation is fully distributed

82. :: Connect with Us ::
¥opensplice.com
¥opensplice.org
¥forums.opensplice.org
¥opensplicedds@prismtech.com
¥@acorsaro
¥@prismtech
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¥youtube.com/opensplicetube
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¥sales@prismtech.com