Advanced OpenSplice Programming - Part I

Advanced OpenSplice DDS
Programming
- Part I -
OpenSplice DDS

Angelo CORSARO, Ph.D.
Chief Technology Oﬃcer
OMG DDS Sig Co-Chair
PrismTech
angelo.corsaro@prismtech.com

Before we get into technical details let’s try to answer two questions:

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1. What does OpenSplice DDS do?

2. What kind of applications are using it?
OpenSplice DDS

OpenSplice DDS enables seamless, loosely-

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coupled, timely, scalable and dependable
data sharing between distributed applications
OpenSplice DDS

and network connected devices.

Some Use Cases

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OpenSplice DDS

Integrated Modular Vetronics Training & Simulation Systems Naval Combat Systems

Air Trafﬁc Control & Management Unmanned Air Vehicles Aerospace Applications

Some Use Cases

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OpenSplice DDS

Agricultural Vehicle Systems Large Scale SCADA Systems Smart Cities

Train Control Systems Complex Medical Devices Big Data (In-Memory) Analytics

A Fresh Look at OpenSplice
OpenSplice DDS

From Local
OpenSplice DDS

to Distributed Data

Data in Programming Languages

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☐ Statically Typed Programming Languages provide mechanisms to
declare a variable for given type as well as defining new types
OpenSplice DDS

int
x;

class
Rational
{
...
}

☐ Scoping rules are then used to define what values and types are
accessible at any given point in a program text

“Local” Data
☐ Consider the Following code fragment below in an imperative
programming language:

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State
1 { 1
{
}
2

int
x; 2
{
int
x
}
3

x
=
7; 3
{
x
=
7
}
OpenSplice DDS

4

{ 4
{
x
=
7,
{
}
}
5

int
y; 5
{
x
=
7,
{
int
y
}
}
6

y
=
18; 6
{
x
=
7,
{
y
=
18
}
}
7

double
z; 7
{
x
=
7,
{
y
=
18,
double
z
}
}
8

z
=
3.141593 8
{
x
=
7,
{
y
=
18,
z
=
3.1416
}
}
9

x
=
x
-‐
4; 9
{
x
=
3,
{
y
=
2
}
}
10

y
=
x
+
y; 10
{
x
=
3,
{
y
=
21
}
}
11

z
=
2
*
z
*
y; 11
{
x
=
3,
{
y
=
21,
z
=
131.9472
}
}
12

} 12
{
x
=
3,
{

}}
13 } 13
{
}

“Local” Data
☐ One final consideration to do is that variables in a programming
language are in essence alias to a memory location

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int
x;
int
y;
OpenSplice DDS

...

Distributed Data
Extending the elegant model provided by programming

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☐
languages to distributed systems has been and still is a quite
popular research topic
OpenSplice DDS

☐ Historically the solutions to the distributed data problem where
divided into those based on Distributed Shared Memory and those
based on Message Passing

☐ OpenSplice DDS provide a new interesting way of addressing this
problem. Let’s see...

OpenSplice Foundations
OpenSplice DDS

Distributed Data in OpenSplice
☐ OpenSplice DDS provides the abstraction

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of an “Active” Global Data Space

☐ The Global Data Space is fully distributed TopicA
and does not suffer Single Point of Failure TopicE
OpenSplice DDS

issues TopicB
...
TopicD
☐ Applications can autonomously join and TopicC
leave this data space as well as declare
new “Data Types”
OpenSplice DDS Global Data Space
☐ In OpenSplice, “data types” are called
Topics

Global Data Space
☐ The Global Data Space is actually called “Domain” in
OpenSplice DDS

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☐ Domains are identified by integer. An application
can join a domain by creating a domain participant
as follows: TopicA
TopicE
OpenSplice DDS

//
Create
a
Topic ...
int
domain_id
=
18; TopicB
TopicD
auto
dp
=
DomainParticipant(domain_id);
TopicC
☐ A Domain defines a top-level scope thus the
content of a domain is not accessible from
OpenSplice DDS Global Data Space
another domain
☐ Finally an application can join multiple domains
by creating one domain participant per-domain

Topics
☐ A Topic is defined by means of a “Circle”, Square”, “Triangle”
(name, type, qos) tuple, where

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☐ name: identifies the topic within
Name
OpenSplice’s Global Data Space
Topic
☐ type: is the programming language

Typ

S
OpenSplice DDS

DURABILITY,

Qo
type associated with the topic. This

e
DEADLINE,
type can be defined in IDL, XML, and ShapeType
PRIORITY,
Java. Types are extensible and …
evolvable
☐ qos: is a collection of policies that struct ShapeType {
string color;
control non-functional properties of long x;
this topic, such as its durability, long
long
y;
size;
reliability, etc. };

Deﬁning a Topic

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☐ In code, if we wanted to define the Square topic we would do
(with the new DDS-PSM-Cxx v1.0 API):

// Create a Topic
OpenSplice DDS

auto dp = DomainParticipant(18);
auto topic = Topic<ShapeType>(dp, “Square”, dp.default_topic_qos());

// Or equivalently and more concisely:
auto topic = Topic<ShapeType>(dp, “Square”);

☐ The effect of this code is to define a topic called “Square” with
type ShapeType and default QoS within the OpenSplice Global
Data Space

Looking with the Spyglass
domain 18

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Topic
Square
struct&ShapeType&{
&&string&&&color;&&&&&&
&&long&&&x;&&&
&&long&&&y;
OpenSplice DDS

&&long&&&size;
};

Policies

auto topic = Topic<ShapeType>(dp, “Square”);

Topics Scope
☐ Topic definitions are (somewhat) equivalent to type definitions in a programming

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language. In the sense that they define a new, generalized, type to be used
within the global data space

☐ The scope of a Topic definition is the entire Domain, thus one could say that
there is only one level of scoping. To make the parallel with Java, one could say
OpenSplice DDS

that it is as if Topics where defined in a namespace named after the domain-id

domain0
{TopicA,
TopicB,
...}

domain1
{Topic1,
Topic2,
...}

☐ As a consequence topic definitions in one domain are not visible from a
different domain

If Topic are Types what are Variables?

☐ As described earlier a Topic definition can be thought as a Type

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definition in a programming language

☐ In a statically typed programming language (e.g. Java), given a
type Foo I can define a variable of type Foo as:
OpenSplice DDS

Foo
x;

☐ Then I can initialize it as: x
=
new
Foo(...);

☐ Then I can mutate it, by: x.setBar(...);

☐ How are instance of a Topic defined?

DataWriter

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☐ OpenSplice DDS uses DataWriters to declare and write
instances of a Topic

☐ A DataWriter for our Square topic can be defined as follows:
OpenSplice DDS

// Create a Publisher
auto pub = Publisher(dp);

// Create a DataWriter
auto dw = DataWriter<ShapeType>(pub, topic);

// Write data
dw.write(ShapeType(“RED”,11,77,99));


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Topic
Square
struct&ShapeType&{
&&long&&&x;&&&
&&long&&&y;
OpenSplice DDS

dw &&long&&&size;
};

Policies

color x y size



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Topic
Square
struct&ShapeType&{
&&long&&&x;&&&
&&long&&&y;
OpenSplice DDS

dw &&long&&&size;
};

Policies

color x y size
"RED" 11 77 99


An Experiment...
☐ What does the following code do?

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// Create DataWriters
auto dw1 = DataWriter<ShapeType>(pub, topic);
OpenSplice DDS


// Write Data
dw1.write(ShapeType(“RED”,10,20,30));
dw2.write(ShapeType(“BLUE”,30,20, 10));


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Topic
Square
struct&ShapeType&{
&&long&&&x;&&&
&&long&&&y;
OpenSplice DDS

&&long&&&size;
};

dw1 Policies
Data Writers for the same topic
color x y size are aliased to the same variable!

dw2



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Topic
Square
struct&ShapeType&{
&&long&&&x;&&&
&&long&&&y;
OpenSplice DDS

&&long&&&size;
};

dw1 Policies

color x y size
RED 10 20 30

dw2

dw1.write(ShapeType(“RED”,10,20,30));


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Topic
Square
struct&ShapeType&{
&&long&&&x;&&&
&&long&&&y;
OpenSplice DDS

&&long&&&size;
};

dw1 Policies

color x y size
BLUE 30 20 10

dw2

dw2.write(ShapeType(“BLUE”,30,20, 10));

Topic Instances
☐ Topic type can identify an arbitrary number of attributes as defining the

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topic key
☐ In this case, each unique key value defines a topic instance
☐ Example:
OpenSplice DDS

struct ShapeType {
@Key
long color;
long x;
long y;
long size;
};

Let’s Experiment...
☐ What does the following code do?

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// Create DataWriters
OpenSplice DDS


// Write Data
dw.write(ShapeType(“BLUE”,30,20,10));


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Topic
Square
struct&ShapeType&{
&&long&&&x;&&&
&&long&&&y;
OpenSplice DDS

dw &&long&&&size;
};

Policies

color x y size

RED 10 20 30



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Topic
Square
struct&ShapeType&{
&&long&&&x;&&&
&&long&&&y;
OpenSplice DDS

dw &&long&&&size;
};

Policies

color x y size

RED 10 20 30
BLUE 30 20 10

dw.write(ShapeType(“BLUE”,30,20,10));

LongVariable Example
☐ The “distributed” version of the following code:

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int
x;
int
y;
x
=
10;
y
=
20;
OpenSplice DDS

Topic Type
☐ Becomes:
// Create a Publisher struct LongVariable {
auto lvt = Topic<LongVariable>(dp, “TLongVariable”); @Key
string name;
// Create DataWriters long value;
auto dw = DataWriter<LongVariable>(pub, topic); };

// Write Data
dw.write(LongVariable(“x”,10));
dw.write(LongVariable(“y”,20));


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Topic
TLongValue
struct LongVariable {
@Key
string name;
long value;
OpenSplice DDS

dw };

Policies
name value

x 10

y 20

DataReader

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☐ OpenSplice DDS uses DataReaders to read instances of a Topic

☐ A DataReader for our Square topic can be defined as follows:
OpenSplice DDS

// Create a Subscriber
auto sub = Subscriber(dp);

// Create a DataWriter
auto dr = DataReader<ShapeType>(sub, topic);

// Read data
auto data = dr.read();

☐ The read operation will read by default all instance values. Special selector
operation are available to pick a specific instance. More later

DataReader/DataWriter Matching
☐ DataWriters and DataReaders

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are automatically and
dynamically matched by the Data
Reader
DDS Dynamic Discovery
Data
Writer
OpenSplice DDS

Data
Reader
☐ A rich set of QoS Policies Data
Writer
TopicA
TopicD

allows to control existential, TopicB
Data
Reader
temporal, and spatial
Data
Writer
TopicC
...
properties of data and Data Data
impacts DataReader/ Writer Reader

DataWriter matching DDS Global Data Space

Publishers and Subscribers
OpenSplice DDS

Publishers / Subscribers
Domain (e.g. Domain 123)

Domain
Participant

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Topic
Partition (e.g. “Telemetry”, “Shapes”, )

T1 Publisher
T1 T3 Subscriber
Tx
OpenSplice DDS

Topic Instances/Samples
Ty
Tb
Ta DataWrter DataReader
Tc

Publishers and Subscribers in DDS play two roles:
☐ Coordinate actions across DataReaders/DataWriters
☐ e.g. Atomic writes across data-writers
☐ Control access to DDS partitions, a mechanism provided by DDS to further

DDS Partitions
Domain

Partitions DDS Publishers and

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☐
Subscribers can specify a
M:0:0 M:0:1 M:0:2 list of regular expressions
representing the partitions
OpenSplice DDS

to join
M:1:0 M:1:1 M:1:2
☐ Actual partition can be
any string, but some
M:2:0 M:2:1 M:2:2 structure can be given in
order mimic hierarchy

DDS Partitions Matching
Domain

Partitions

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M:0:0 M:0:1 M:0:2 M:0:*
OpenSplice DDS

M:1:0 M:1:1 M:1:2

M:2:0 M:2:1 M:2:2

Domain

Partitions

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M:0:0 M:0:1 M:0:2
OpenSplice DDS

M:1:0 M:1:1 M:1:2

M:2:0 M:2:1 M:2:2
M:*:2

Domain

Partitions

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M:0:0 M:0:1 M:0:2
OpenSplice DDS

M:1:0 M:1:1 M:1:2

M:2:0 M:2:1 M:2:2 M:0:0, M:1:1, M:2:2

Anatomy of a DDS Application
OpenSplice DDS

[DDS C++ API 2010]

Domain
Domain

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auto dp = DomainParticipant(domainId);
Participant

Session
// Create a Topic
Publisher
Topic
Subscriber
OpenSplice DDS

auto topic = Topic<ShapeType>(dp, “Circle”);
// Create a Publisher / Subscriber

Reader/Writers for User Deﬁned for Types DataWriter
DataReader
// Create a DataWriter/DataWriter
auto writer = DataWriter<ShapeType>(pub, topic); Reader/Writer for
auto reader = DataReader<ShapeType>(sub, topic);
application deﬁned
Topic Types

[DDS C++ API 2010]

Domain
Domain

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auto dp = DomainParticipant(domainId);
Participant

Session
// Create a Topic
Publisher
Topic
Subscriber
OpenSplice DDS

// Create a Publisher / Subscriber

Reader/Writers for User Deﬁned for Types DataWriter
DataReader
// Write data
writer.write(ShapeType(“RED”, 131, 107, 89)); Reader/Writer for
// But you can also write like this...
writer << ShapeType(“RED”, 131, 107, 89);
application deﬁned
Topic Types
// Read new data (loaned)
auto data = reader.read();

Data Reader/Writer Caches
OpenSplice DDS

Reader/Writer Caches
Application Application Application

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DataWriter DataReader DataReader

...
OpenSplice DDS

DataWriter Cache DataReader Cache DataReader Cache

Network

write( ) Application Application

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...
OpenSplice DDS


Network


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...
OpenSplice DDS


Topic Instance
Network


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...
OpenSplice DDS


Topic Instance Topic Instance

Network


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...
OpenSplice DDS


Writer History

Network


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...
OpenSplice DDS


Reader History Reader History

Network


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...
OpenSplice DDS


QoS Policies
‣ History
‣ Destination Order Network
‣ Presentation
‣ Partition QoS Policies
‣ Time Based Filter ‣ Reliability ‣ Durability
‣ Ownership ‣ History ‣ Transport Priority
‣ Latency Budget ‣ Time Based Filter

Writer Cache Properties
☐ An entry for each topic instance

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☐ Each cache entry might contain one
or more samples, the number of
DataWriter
samples is controlled by the History
QoS Policy
OpenSplice DDS

...
☐ Depending on the setting of the
Durability QoS Policy, the content of
the cache may be made available DataWriter Cache
to late joiners. The depth of the
cache controls how many samples
per instance will be delivered to late
joiners

Reader Cache Properties
☐ An entry for each topic instance

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☐ Each cache entry might contain one or
more samples, the number of samples is
controlled by the History QoS Policy DataReader
☐ History.KeepLast(n) keeps the last n samples
OpenSplice DDS

per instance
☐ History.KeepAll maintains all the samples,
...
modulo resource constraints

☐ For a given instance: DataReader Cache
☐ Samples from the same writer are inserted in
write-order
☐ Samples from multiple-writers are ordered
using time-stamps (source or reception
depending on configurable a QoS Policy)

Eventual Consistency
DDS caches provide eventual consistency semantics

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☐

☐ This means that a read will see the effect of a preceding write
eventually
OpenSplice DDS

☐ Furthermore, given a data-writer that is currently matching N
readers, we can think of DDS as providing eventual consistency
with W=0 and R=1
☐ W: the number of Acks expected in order to return from a write
☐ R: the number of sources from which a read access data

Understanding History
OpenSplice DDS


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...
OpenSplice DDS


Network

Assumptions: DataReader configured with history depth of 2 and
DataWriter with default history depth of 1

write( 1 ) Application Application

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...
OpenSplice DDS


Network



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1
...
OpenSplice DDS


Network



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1
...
OpenSplice DDS


1 Network



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1 1 1
...
OpenSplice DDS


Network



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2 1 1
...
OpenSplice DDS


Network



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2 1 1
...
OpenSplice DDS


2 Network



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2 1 1
...
OpenSplice DDS

2 2


Network


Caches or Streams?
OpenSplice DDS

Eventual View of a Stream
Assumptions (Default Settings):
Reader History = KeepLast (1)
WriterHistory = KeepLast (1)

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Writer History
Reader History ‘Past’ Samples
OpenSplice DDS


Interacting with the
DataReader Cache
OpenSplice DDS

Reading Data Samples
☐ Samples can be read from the Data Reader History Cache

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☐ The action of reading a sample is non-destructive. Samples are
not removed from the cache
OpenSplice DDS

DataReader DataReader

... read ...

DataReader Cache DataReader Cache

Taking Data Samples
☐ Samples can be taken from the Data Reader History Cache

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☐ The action of taking a sample is destructive. Samples are
removed from the cache
OpenSplice DDS

DataReader DataReader

... take ...

DataReader Cache DataReader Cache

Read vs. Take

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☐ The read operation should always be access the latest know value
for topics that represent distributed state
OpenSplice DDS

☐ The take operation should be used to get the last notification from a
topic that represent an event

Cherry Picking in DDS

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☐ DDS provides some very flexible mechanisms for selecting the data
to be read:
OpenSplice DDS

☐ Data Content
☐ Data Status

☐ These mechanisms are composable

Content-Based Data Selection
OpenSplice DDS

Filters and Queries Application

☐ DDS Filters allow to control what gets
into a DataReader cache

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Query
☐ DDS Queries allow to control what gets
out of a DataReader cache DataReader
OpenSplice DDS

☐ Filters are defined by means of
...
ContentFilteredTopics

...
...

...
☐ Queries operate in conjunction with DataReader Cache
read operations
Filter
☐ Filters and Queries are expressed as SQL
where clauses

struct ShapeType {

Filters
@Key
string color;
long x;
long y;
[C++ API] };
long shapesize;

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/**
* NOTE: The Scala API if not provided with DP/Sub/Pub assumes
* default domains and default partition.
**/
// Create a Topic
OpenSplice DDS

// 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)

struct ShapeType {

Query
@Key
string color;
long x;
long y;
[C++ API] };
long shapesize;

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// Define filter expression and parameters
auto dr = DataReader<ShapeType>(sub, topic)
OpenSplice DDS

val query = Query(dr, “x < 100 AND y < 200”);

dr.select()
.content(query)
.read();

Instances
☐ DDS provides a very efficient way of reading data belonging to a

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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
OpenSplice DDS

auto handle =
dr.lookup_instance(ShapeType(“RED”, 0, 0, 0));

auto data =
dr.select()
.instance(handle)
.read();

State-Based Selection
OpenSplice DDS

Sample, Instance, and View State
☐ The samples included in the DataReader cache have associated

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some meta-information 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
OpenSplice DDS

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 Intance State (ALIVE, NOT_ALIVE_DISPOSED,
NOT_ALIVE_NO_WRITERS) allows to track the life-cycle transitions of
the instance to which a sample belongs

State Selector in Action
[C++ API]

Copyright
2011,
PrismTech
–

All
Rights
Reserved.
// Read only new samples
auto data = dr.read()

// Read any samples from live instances
auto data =
dr.select()
OpenSplice DDS

.state(DataState::any_data())
.read();

Putting all Together
[C++ API]

Copyright
2011,
PrismTech
–

All
Rights
Reserved.
☐ Selectors can be composed in a flexible and expressive manner
OpenSplice DDS

auto data =
dr.select()
.content(query)
.state(data_state)
.instance(handle)
.read();

OpenSplice DDS

Summing Up

Concluding Remarks
OpenSplice DDS provides a very powerful abstraction for building

Copyright
2011,
PrismTech
–

All
Rights
Reserved.
☐
distributed applications grounded on the concept of a fully
distributed global data space
OpenSplice DDS

☐ Topics are used to define the types that populate the global data
space while DataWriters and DataReaders are used to produce
and consume values

☐ DataReaders allow very flexible data access through cache
access operations

References

Copyright
2011,
PrismTech
–

All
Rights
Reserved.
OpenSplice | DDS Escalier
¥ #1 OMG DDS Implementation ¥ Fastest growing JVM Language ¥ Scala API for OpenSplice DDS
¥ Open Source ¥ Open Source ¥ Open Source
¥ www.opensplice.org ¥ www.scala-lang.org ¥ github.com/kydos/escalier
OpenSplice DDS

¥ Simple C++ API for DDS ¥ DDS-PSM-Java for OpenSplice DDS ¥ DDS-based Advanced Distributed
¥ Open Source ¥ Open Source Algorithms Toolkit
¥ github.com/kydos/simd-cxx ¥ github.com/kydos/simd-java ¥ Open Source
¥ github.com/kydos/dada

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OpenSplice DDS

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Advanced OpenSplice Programming - Part I

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