RSP4J is an API for RDF stream processing that addresses gaps in existing solutions. It provides an extensible architecture, declarative access to streams and queries, and programming abstractions to enable fast prototyping, benchmarking, and dissemination of RSP techniques. The API generalizes common operators, implements execution semantics of engines like YASPER and CSPARQL 2.0, and allows controlling query execution. RSP4J aims to foster practical RSP research by simplifying the implementation of new solutions, engines, and optimizations.

1. 09/06/2021
RSP4J: An API for RDF Stream
Processing
18th Extended Semantic Web Conference,
Riccardo Tommasini (UT🇪🇪)
1

2. Joint Work
2
Pieter Bonte
IMEC/UGENT🇧🇪
Femke Ongenae
IMEC/UGENT🇧🇪
Emanuele Della Valle
POLIMI🇮🇹

3. Community Work
Acknowledgement to users/contributors
3

4. Agenda
• What is Stream Reasoning
• RDF Stream Processing
• Problem Statement
• RSP4J (Finally)
• Final Remarks
There will be memes!
4

5. 5

6. Is it possible to make sense in real time of multiple,
heterogeneous, gigantic and inevitably noisy and
incomplete data streams in order to support the decision
processes of extremely large numbers of concurrent users?
E. Della Valle, S. Ceri, F. van Harmelen & H. Stuckenschmidt, 2010
Research question
STREAM REASONING
Emanuele Della Valle - http://emanueledellavalle.org - @manudellavalle 6

7. Semantic
Web
Stream
Processing
Linked
Data
Stream Reasoning
Logical
Reasoning
State-of-the-art
ETALIS
LARS/LASER
TESLA
RDFox
Calcite
BEAM
OWLAPI
Commons RDF
7
Prominent Solution
Related Work
RSP
IR

8. Semantic
Technologies
Vice-Versa
is also valid
Oh Yes!
Almost Done!! Almost!!
Oh Man!
Stream Processing
8
Semantic
Technologies
Semantic
Technologies
Semantic
Technologies

9. time
What is a Stream?
9
• Streams: unbounded partially ordered sequence of data in
form of object-timestamp pairs <o,t>, e.g.,
• o is a coloured box
• t is a natural number

10. Sort out all the colours in the streams
What is Stream Processing?
stateless
order
…..
…..
…..
…..
…..
…..
10

11. ( , 15)
time
1 minute wide window
How many boxes, grouped by color,
there are in the last minute?
What is Stream Processing?
stateful
11

12. Semantic
Technologies
Vice-Versa
is also valid
Oh Yes!
Almost Done!! Almost!!
Stream Processing
12
Semantic
Technologies
Semantic
Technologies
We are
Here
Semantic
Technologies

13. The CQL continuous query language
Basics
Arasu, Arvind, Shivnath Babu, and
Jennifer Widom. "The CQL continuous
query language: semantic foundations
and query execution." The VLDB Journal
15.2 (2006): 121-142.
Streams Relations
…
<s,τ>
…
<s1>
<s2>
<s3>
infinite
unbounded
sequence
finite
bag
Mapping: T ! R
stream-to-relation
relation-to-stream
relation-to-relation
Stream
Relation R(t)
Relational Algebra (Almost)
*Stream operators
time-based windows

14. W4
W2
CQL Viz
Window Tumbling
R2R operator
S
ω
t
width
…
t0
W0 W1 W3 Wn+1
Wn
…
…
COUNT
2
1
S2R operator (ω)
𝕎
W3
14
NOW()
R2S operator RSTREAM
W2 W4

15. Continuous●Semantic
s
/kənˈtɪnjuːəs●sɪˈmæntɪks
/
1.The result of a query is the set of results that
would be returned if the query were executed
at every instant in time.
15

16. Adding Data Semantics
16

17. time
1 minute wide window
How many colours in the last minute?
From Stream Processing…
17
( , 13),( , 8) , ( , 8)

18. time
How many colours in the last
minute?
…to Stream Processing
18
( , 13),( , 8) , ( , 8)
1 minute wide window

19. Stream Reasoning
Better Questions
How many cool colours in the last minute?
time
( , 13),( , 8) , ( , 8)
1 minute wide window

20. Which are the top-2 most frequent sentiments
in the last minute?
love and wisdom
Stream Reasoning
Even Better Questions
1 minute wide window
time

21. Semantic
Web
Stream
Processing
Linked
Data
Stream Reasoning
Logical
Reasoning
State-of-the-art
LARS/LASER
OWLAPI
Prominent Solution
Related Work
Commons RDF
RSP
IR
TESLA
Calcite
BEAM
ETALIS
RDFox
21

22. Stream Reasoning
State-of-the-art

23. ff
erences
• Syntaxes are not interoperable
• Have di
ff
erent operational
semantics
• Not all of them integrate static
knowledge
• RDF Streams ok, but graphs or
triples?
RSP Dialects & Engines
23

24. Similarities
• Extend SPARQL with windows
• Evaluates queries under
continuous semantics
• Optimise the execution for low-
latency high-throughput (stream
processing requirements)
RSP Dialects & Engines
24

25. Dell’Aglio et al.
• Reference model that uniforms
existing solutions
• has formal semantics
(denotational)
• can explain operational
semantics
• Solutions published after
(e.g., YASPER 1.0, TPF-QS,
Strider) align to it
RSP-QL
Continuous
Querying:
SPARQL
Identifiers: URI
Cryptography
Trust
Ontologies: OWL
Proof
Unifying Logic
Rules: RIF/SWIRL
Taxonomies: RDFS
Data Interchange: RDF
Character Set: UNICODE
Syntax: XML, TTL, NT, JSON-LD
User Interfaces and Applications
25

26. Dell’Aglio et al.
• Reference model that uniforms
existing solutions
• has formal semantics
(denotational)
• can explain operational
semantics
• Solutions published after
(e.g., YASPER 1.0, TPF-QS,
Strider) align to it
RSP-QL
Continuous
Querying:
RSP-QL
Identifiers: URI
Cryptography
Trust
Ontologies: OWL
Proof
Unifying Logic
Rules: RIF/SWIRL
Taxonomies: RDFS
Continuous Interchange:
RDF Stream
Character Set: UNICODE
Syntax: XML, TTL, NT, JSON-LD
User Interfaces and Applications
?
?
?
?
26
Continuous
Querying:
SPARQL
Data Interchange: RDF

27. Theoretical
Framework
Applications
The Technological Gap
27

28. The Stream Reasoning community needs systems and tools
that can encourage re-use and foster the adoption of existing
solutions for RDF Stream Processing.
Tommasini, and Della Valle. "Challenges & Opportunities of RSP-QL Implementations."
WSP/WOMoCoE@ ISWC. 2017.
Problem Statement
RSP4J
28

29. Currently, the following tasks are hard to do..
Uncomfortable Truths
You need to
implement your RSP
engine from scratch
29
• Introducing new window operators
• Experiment optimisation techniques
• Comparing di
ff
erent engines
Does he bite? No, but he can hurt
you in other ways!

30. Challenges
Fast Prototyping
30
Benchmarking
Dissemination

31. Requirements
1. Extensible Architecture.
2. Declarative Access
3. Programming Abstractions
4. Experimentation
5. Observability
C1 C2 C3 C4 C5 C6 C7 C8 C9 C10
R1 ✓ ✓ ✓ ✓ ✓
R2 ✓ ✓ ✓
R3 ✓ ✓ ✓
R4 ✓ ✓ ✓
R5 ✓ ✓ ✓ ✓ ✓
R
R
R
R
R
And their relation to the challenges
31

32. RSP4J
30.000ft View: Architecture
Extensible parser based on
the RSP-QL Syntax Proposal
(R1, R2)
Abstract representing the
evaluation under continuous
semantics (R3,R5)
Abstract Representation of A
Streaming Dataset for
backwards compatibility with
SPARQL (R3)
Con
fi
gurable engine capable
of reproducing existing
behaviours (R4,R5)
Versatile Object for
representing streams (non
strictly RDF based) (R1)
Operator Interface based on
RSP-QL/CQL (R1, R3)
(e)
32

33. RSP4J
10.000ft View: Querying
Extensible parser based on
the RSP-QL Syntax Proposal
Rei
fi
ed Object representing
the running query
33

34. 10.000ft View: Streams
• Two main interfaces:
• Web Stream (vid. Vocals)
• Data Stream (generic)
• Simple Approach for production
and consumption
• We recently added the IO
package with lots of sources
RSP4J
34

35. 10.000ft View: Streams
• Two main interfaces:
• Web Stream (vid. Vocals)
• Data Stream (generic)
• Simple Approach for production
and consumption
• We recently added the IO
package with lots of sources
RSP4J
35

36. 10.000ft View: Operators
• Generalise CQL Style of operators
families
• Includes already canonical
examples of S2R
• CQELS’s Window Operator
• CSPARQL’s Window Operator
• Includes generic implementation of
R2S
• RStream, IStream, DStream
RSP4J
36

37. 10.000ft View: Engine
• Allows controlling the engine,
e.g., query registration and
cancellation.
• RSP4J can reproduce the
execution semantics of common
RSP engines
• Already include some bindings,
YASPER, CSPARQL 2.0,
ONSPER*
RSP4J
RSP4J: Engine
YASPER CSPARQL 2.0
Esper + Jena
RDF Commons
+ JGraphT
ONSPER
Esper + Calcite
+ Ontop
binds
Runtime
Interface
37

38. Enables the following research directions
Does the window operator X
outperform window operator Y for
both C-SPARQL and CQELS
execution semantics?
RSP4J
IMPLEMENT
MY RSP
SOLUTION
FROM
SCRATCH
RSP4J
38

39. Enables the following research directions
Does this alternative memory
representation optimise CityBench’
RSP-QL queries using the Strider
Engine?
RSP4J
IMPLEMENT
MY RSP
SOLUTION
FROM
SCRATCH
RSP4J
39

40. Enables the following research directions
Can I apply a bunch of RSP
engines to my use-case and
observe which performs better?
RSP4J
IMPLEMENT
MY RSP
SOLUTION
FROM
SCRATCH
RSP4J
40

41. • June 28-July 2, 2021, Virtual
Event, Italy
• http://streamreasoning.org/
events/web-stream-processing-
with-rsp4j
• We will prototype an engine!
• Big Updates: Publishing &
New Abstract API!
DEBS 21 Tutorial (Free)
Learning N di
ff
erent
RSP Dialects
N > 4
Learning
RSP4J
41

42. Conclusion
Roadmap
RSP4J is a community effort that we hope will
foster further practical research on RSP/SR
We plan to organise events and
hackathons to foster its adoption
We plan to integrate it with RSPLab and
existing benchmarks like CityBench
We plan to integrate more engines, provide
more operators, and (hopefully) optimisations
To foster data science, we plan to make it available via
Jupyter Notebook with python Bindings (RSPLib)
…
Benchmarks
Integration
RSP4J
RELEASE
CQELS
bindings
42
Python
Bindings
DEBS 2021
TUTORIAL
RSP4J Repo
Stream Reasoning
Workshop 2021
Publication and
Abstraction API
Questions?