Sap Hana Graph Processing

1. Public
DMM212 – SAP HANA Graph Processing:
Information and Demonstration

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Speakers
Bangalore, October 5 - 7
B Raghavendra Rao
Las Vegas, Sept 19 - 23
May P. Chen
Barcelona, Nov 8 - 10
Markus Fath

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Disclaimer
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This presentation is provided without a warranty of any kind, either express or implied, including but not limited to, the implied
warranties of merchantability, fitness for a particular purpose, or non-infringement. This presentation is for informational
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All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially
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as of their dates, and they should not be relied upon in making purchasing decisions.

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Agenda
SAP HANA graph architecture overview
 Property graph data model
 Graph processing in SAP HANA
Native HANA graph algorithms
 Neighborhood search (graph traversing)
 Shortest path
 Strongly connected components
 Pattern matching
Graph tools and visualization
 Graph modeler
 Graph viewer
Roadmap & use cases
Demo

5. Public
Architecture overview
Property graph data model
Graph processing in SAP HANA

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To represent and query large sets of highly connected data
No rigid schema requirements and flexible to build graph data on-the-fly
Allows efficient execution of typical graph operations
Simplifies application design and lower development costs
Graph representation & processing
?

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The Property graph model
The Property graph model
The Property graph model provides directed, attributed (vertices and edges) multi-relational graphs
as the central data structure. (BOM, social-, chemical-, biological-, and other networks.)

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Example: family tree
Vertex: MEMBERS
Edge : RELATIONSHIPS

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SAP HANA graph is a core functionality
SAP HANA PlatformOn-premise | Cloud | HybridOn-premise | Cloud | Hybrid
Web server JavaScript
SAP Fiori
UX
Graphic
modeler
Data virtualization ELT and
replication
Application services Integration services
Columnar
OLTP+OLAP
Multicore/
parallelization
Advanced
compression
Multi-
tenancy
Multitier
storage
Spatial Graph Predictive Search
Text
analytics
Data
Quality
Series
data
Function
libraries
ALM
Processing services
Database services
Hadoop/Spark
integration
Streaming
(CEP)
Application lifecycle
management
High availability/
disaster recovery
OpennessData
modeling
Remote data
sync
Admin/
security
SAP HANA
DB Server
DB-oriented Logic
Text Mining
Predictive
SQL Scripts
R Integration
Business Rules
Extended
App Services
(Web Server) Procedural App Logic
ODataJava Script
Unstructured Application Library
HTML
 HANA core functionality
 In-Memory technology leveraging column store and hardware technologies
 Online querying with transactional support and query optimization (OLTP & OLAP)
 Out-of-box security

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Transparent combination of graph
processing with all HANA engines
on business, unstructured and
spatial data
Property graph model embedded in
relational world (easy consumable
with SQL)
Flexible graph workspace concept
with metadata
Graph import / export support
Graphical analysis, visualization and
interaction
Graph processing in SAP HANA

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Interfaces & Capabilities
SQL and SQLScript as main graph interface
Modeler for native graph algorithms
Graph Viewer for graph algorithms and
interaction
Graph Backend
Primary graph store (support for row / column tables,
partitioning and more)
Secondary graph store (adjacency list for accelerated
graph processing)
Graph Engine Runtime
Built-in graph algorithms
Pattern matching

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Consuming graph
CREATE GRAPH WORKSPACE GREEK.FAMILY
EDGE TABLE GREEK.RELATIONSHIP
SOURCE COLUMN source
TARGET COLUMN target
KEY COLUMN key
VERTEX TABLE GREEK.MEMBERS
KEY COLUMN name;
Create Vertex and Edge Tables
With as many attributes as you want
CREATE COLUMN TABLE GREEK.MEMBERS (
name VARCHAR(100) PRIMARY KEY
type VARCHAR(100), residence VARCHAR(100),…);
CREATE COLUMN TABLE GREEK.RELATIONSHIP (
key INTEGER PRIMARY KEY,
source VARCHAR(100) NOT NULL
REFERENCES GREEK.MEMBERS (name)
ON UPDATE CASCADE ON DELETE CASCADE,
target VARCHAR(100) NOT NULL
REFERENCES GREEK.MEMBERS (name)
ON UPDATE CASCADE ON DELETE CASCADE
relationship VARCHAR(50), confidence REAL,…);
GREEK.FAMILY
RelationshipsMembers
Create Graph Workspace

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SAP HANA graph security
Out-of-box security (role concept &
privileges)
Graph workspace based on tables and / or
views on native database tables
Required user group / role privileges on
graph workspace objects
Master data can be updated online
Graph workspaces metadata – is the graph
workspace valid or not / constraints and
keys

14. Public
Native HANA graph algorithms
Neighborhood search
Shortest path
Strongly connected components
Pattern matching

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Neigborhood search
Search for neighborhood
Input Parameters
•Start vertices
•Min / max depth
•Start- / end-level (*)
•Vertex- / edge-filter (*)
Output
•Primary vertex key of vertex table
•Search depth
* := optional parameter
Example:
SELECT * FROM GREEK.NEIGHBORHOOD
WITH PARAMETERS (
'placeholder' = ('$startVertices$', [‘zeus‘]),
'placeholder' = ('$startLevel$',‘0')
'placeholder' = ('$endLevel$',‘2')
'placeholder' = ('$edgeFilter$',‘rel=parentOf'));
Reha Cronus
Hera
ZeusAtlas
Maia Danae ApolloHermes
Artemis
Pleione
Leto
Name Depth
Atlas 1
Hemes 1
Danae 1
Apollo 1
Maia 2
Artemis 2

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Shortest path
Single-Source Shortest Path
• Provides shortest path from start
vertex to all reachable vertices in
the graph
Input Parameters
•Start vertex
•Edge weight column (*)
Output
•Vertex key
•Calculated weight
•Shortest path start to end point
* := optional parameter
1
0.8
1
0.5 0.9
Example:
SELECT * FROM GREEK.SSSP
WITH PARAMETERS (
'placeholder' = ('$startVertex$', ‘zeus‘),
'placeholder' = ('$edgeWeightColumn$',‘confidence'));
Name Confidence Path
Athena 1 Zeus ->
Athena
Hemes 1 Zeus ->
Hermes
Atlas 0.8 Zeus -> Atlas
Maia 1.5 Zeus -> Maia
Athena
Hermes Atlas
Maia
Zeus

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Strongly connected components
Search for strongly connected components
Input Parameters
•Nothing required
Output
•Primary key of vertex
•Component ID
* := optional parameter
Vertex Component
a 1
b 1
c 1
d 1
e 1
h 1
f 2
g 2
aa bb cc dd
ee f g hh
Example - Combine with SQL:
SELECT * FROM MY.SCC
WHERE component <= 2;

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Pattern matching
Pattern Object
• Simple relational predicates on
vertex and edge attributes
• ==,!=,<,>,<=,>=
• Logical connectives
• AND
• Simple matching expressions
• (a)-[b]->(c) with a and c of
type vertex and b edge
Projection on matched patterns
Returns projected attributes of
matched subgraphs
Can be combined with SQL
(filters, aggregation, union, …)
rel=parentof
name=Zeus
V1 V2
V1 V2
V3
rel=punish
Who has punished whom
Who has punished whom

19. Public
Graph tools & visualization
Graph modeler
Graph viewer

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Graph modeler
Create Graph Algorithm
Execute Graph Algorithm
SELECT * FROM NYC.GET_SHORTEST_PATHS
ORDER BY “weight“
WITH PARAMETERS (
'placeholder' = ('$startVertices$', [‘zeus‘]),
'placeholder' = ('$endLevel$',‘2'));

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Graph viewer
• Native HANA Web application
• Visible graph workspace selection
• Graph explorer
• Shows attributes of graph and value
distribution (pie chart)
• Vertex and edge filter
• Graph visualization with SAPUI5 and D3.js
• Color mapping: colorizes all nodes that have
specific attributes
• Grouping: group nodes together on an edge
• Graph interaction & algorithms
• Neighborhood search with filter conditions
• Shortest path: finds all shortest from a single
source or between two nodes
• Strongly connected components
• Pattern matching: search for graph patterns

22. Public
Roadmap & use cases

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 Property graph model with SQL
and SQLScript interfaces
 Graph node in calculation
scenario
 Graph algorithms:
• Neighborhood search
• Shortest path
• Strongly connected components
• Pattern matching
• Import / export graph workspace
• Security based on roles and
privileges
 Graph tools & visualization
 Custom graph algorithm support
 Standard graph language
 Demos, PoC’s & co-innovation
results
 Integration with predictive, spatial
& text
 Graph partitioning & scalability
 Graph compression, indices
 Parallelization BFS (Breadth First
Search), DFS (Depth First Search)
 HANA Vora integration
 Additional interfaces and
components
 SQL optimizer & statistics
Today (Recent SPS12) Future DirectionPlanned Q4 2016
This is the current state of planning and may be changed by SAP at any time.
SAP HANA graph roadmap

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SAP HANA real-time graph solutions
HANA Medical Insights builds up knowledge
graphs by extracting structured from unstructured
clinical data and combining it with additional
medical data sources. Doctors and researchers
can leverage this knowledge to derive information
specific to the situation they are in.
An SAP cloud-based solution that provides
multi-tier visibility of supplier network. Buyers
and sellers can understand how organizations,
products, documents, sites, and events relate to
each other across the Ariba network, so that
they can mitigate risks of failure in their supplier
networks.
Partition independent graphs, calculate maximum distance from a node to the end of the
graph and loop detection.
End-to-end product traceability supports
tracing of all materials purchased, consumed,
manufactured, and distributed in the supply
and distribution network.
SAP SuccessFactors LearnFit helps
employees stay competitive by connecting
them with other learners and personalized
learning beyond traditional course catalogs
to fit their learning goals and situation.
To consolidate from various systems
and associate them to enable “silo
searching” to “transverse searching”.
Associate person to person, person to
data.
Money laundering detection, stock trade,
national security, and armed conflict location and
event data project.
When use with a graph query that
includes some traversal operations, it is
possible to retrieve the full text search,
instead of only the results nodes.

25. Public
Demo
SAP HANA Rock Festival Demo

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Related SAP TechEd sessions
Other TechEd session:
Other information:
For more information on SAP HANA
Graph in SAP Community Network at:
http://scn.sap.com/docs/DOC-74495
i
SAP HANA Graph Processing:
Information and Demonstration
i
DMM212 – SAP HANA Graph Processing:
Information and Demonstration
Thursday, Sept 22, 8:00AM – 9:00AM
Friday, Sept 23, 9:15AM – 10:15AM
DMM117 – SAP HANA Processing Services: Text,
Spatial, Graph, Series, and Predictive
Wednesday, Sept 21,10:30AM – 12:30PM
Thursday, Sept 22, 10:30AM – 12:30PM
DMM212(L1)
SAP HANA Processing Services: Text,
Spatial, Graph, Series, and Predictive
i
DMM117(L2)

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Further information
SAP Public Web
• scn.sap.com - What’s new in SAP HANA SPS12 – HANA Graph http://scn.sap.com/docs/DOC-74495
• SAP HANA Platform (Core): http://help.sap.com/hana_platform -> Graph
• SAP HANA Graph Reference Guide: http://help.sap.com/hana/SAP_HANA_Graph_Reference_en.pdf
• SAP HANA Graph Data Model:
http://help.sap.com/saphelp_hanaplatform/helpdata/en/b7/bd8a7f157c4201910d40917f410237/frameset.htm
• Graph Modeling for XSA:
• http://help.sap.com/hana/SAP_HANA_Modeling_Guide_for_SAP_HANA_XS_Advanced_Model_en.pdf
• http://help.sap.com/saphelp_hanaplatform/helpdata/en/22/a479fcf53d4e60ad2cdafb6dcbb210/frameset.htm
SAP Education and Certification Opportunities
• SAP HANA Academy video series on SAP HANA Graph processing:
https://www.youtube.com/playlist?list=PLkzo92owKnVwCuJeNPcC7J_v4eT5_s6-d
Watch SAP TechEd Online
• www.sapteched.com/online

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Contact information:
May P. Chen
SAP HANA Product Management
may.chen@sap.com
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