TigerGraph 2.4 Overview and Demo

Graph Gurus
Episode 15
Introducing TigerGraph 2.4:
Overview and Demo

© 2019 TigerGraph. All Rights Reserved
Welcome
● Attendees are muted
● If you have any Zoom issues please contact the panelists via chat
● We will have 10 min for Q&A at the end so please send your questions
at any time using the Q&A tab in the Zoom menu
● The webinar will be recorded and sent via email
2

Developer Edition Available
We now offer Docker versions and VirtualBox versions of the TigerGraph
Developer Edition, so you can now run on
● MacOS
● Windows 10
● Linux
Developer Edition Download https://www.tigergraph.com/developer/
3
Version 2.4
Available Now

© 2019 TigerGraph. All Rights
Reserved
Today's Gurus
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Victor Lee
Director of Product Management
● BS in Electrical Engineering and Computer Science
from UC Berkeley, MS in Electrical Engineering from
Stanford University
● PhD in Computer Science from Kent State University
focused on graph data mining
● 15+ years in tech industry
Benyue (Emma) Liu
Senior Product Manager
● BS in Engineering from Harvey Mudd College, MS in
Engineering Systems from MIT
● Prior work experience at Oracle and MarkLogic
● Focus - Cloud, Containers, Enterprise Infra, Monitoring,
Management, Connectors

What's New in TigerGraph 2.4?
5
● GSQL Enhancements
⭐ Pattern Matching
⭐ GSQL Interpreted Mode
● Graph Algorithm Library Improvements
⭐ k-Nearest Neighbor classifier
● Connector Expansion
⭐ Integration with AWS S3 (Graph Studio and GSQL)
⭐ JDBC Driver (Open Source Ecosystem)
● GraphStudio Enhancements
⭐ Loading from S3
⭐ Start / Pause / Resume / Stop Loading Jobs

Reserved
⭐ Different Uses for Graph
Pre-planned
Spur-of-the-
Moment Simple Complex
Complex Applications
(e.g. Fraud Detection)
Interactive
Exploration & Analytics
Graph
Search
Graph Algorithms
Search Analytics / Algorithms Multi-phase Applications

Reserved
⭐ Different Uses for Graph
Pre-planned
Spur-of-the-
Moment Simple Complex
Complex Applications
(e.g. Fraud Detection)
Interactive
Exploration & Analytics
Graph
Search
Graph Algorithms
Search Analytics / Algorithms Multi-phase Applications
Pattern
Match-
ing

Graph Patterns
Any arrangement of connected nodes, used as a search input:
"Find all the occurrences like this"
Pattern Types
● Transactional Patterns
● Social Patterns
● Event Patterns
● Hybrid Patterns
Uses
● Recommendation
● Fraud/Crime
● Security/Risk/Rules
● Trends/Insight

Reserved
⭐ Pattern Matching in GSQL
Express multiple-hop and variable-hop patterns in a single GSQL line
● Benefit: More compact queries, faster and easier to write
Example 1: "What are the common features of products which my friends
have purchased?"
FROM Me:M - (friend_of) - Person:F - (buy>) - Product:P - (<feature_of) - Feature:F
Example 2: "What are the suspicious accounts which Account X has
transacted with, directly or within 3 levels of transactions?"
FROM AccountX:X -(transact_with*1..3)- Account:T WHERE T.alert == true

Reserved
⭐ Pattern Matching in GSQL
Express multiple-hop and variable-hop patterns in a single GSQL line
● Benefit: Lets users write queries closer to the way they think
"What are the common features of products which my friends
have purchased?"
"Me" "My Friends"
"Products they
bought"
"Features of
the products"

Query Pattern P
Data Graph G

Query Pattern P
Data Graph G
First Match

Query Pattern P
Data Graph G
First Match
Second Match

Query Pattern P
Data Graph G
First Match
Second Match
Third Match

For More on Pattern Matching
15
● Webinar - Graph Gurus 14
○ https://info.tigergraph.com/graph-gurus-14
● Tutorial - "GSQL 102"
○ docs.tigergraph.com/intro/gsql-102

● Run queries immediately, without waiting for installing/compiling
● Ideal user experience for ad hoc exploration or when developers are
experimenting / debugging
- BI tool
- Graph exploration tool
- App development
Tool builds and
runs query
immediately
No lag,
Happy user!

Two Modes available:
● Use Interpreted Mode when responsiveness is key
● Use Compiled mode when query optimization is important
- BI tool
- Graph exploration tool
- App development
Tool builds and
runs query
immediately
No lag,
Happy user!
Developer
writes
production
queries
Compile/Install
queries
Optimized queries;
Happy
stakeholders!

Multiple Ways to Create & Run GSQL Queries
18
Compiled Query Mode:
1. CREATE QUERY: define the functionality of the query
2. INSTALL QUERY: compile the query
3. RUN QUERY: execute the query with input values
Define a named query and then interpret (run) it.
1. CREATE QUERY: define the functionality of the query
2. INTERPRET QUERY: execute the query with input values
Define and run an unnamed query immediately:
1. INTERPRET QUERY: execute the query's statements
There is also a built-in REST++ endpoint to interpret a query string:
POST /gsqlserver/interpreted_query See the RESTPP API User Guide for details.

⭐ Graph Algorithm Library Improvements
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docs.tigergraph.com/graph-algorithm-library
● New Section for Machine Learning Algorithms
● Classifier:
○ k-Nearest Neighbors (kNN)
● New location:
○ Old: https://github.com/tigergraph/ecosys/tree/master/graph_algorithms
○ New: https://github.com/tigergraph/gsql-graph-algorithms

k-Nearest Neighbor Algorithm Classifier
20
Predict the class of an entity by
looking at the class of entities
which are nearest to it.
● "Near" usually means most similar.
● Depends on how you measure
similarity (we use Cosine Similarity)
● Also depends on an integer
parameter K = how many
neighbors use, e.g. the 3 nearest
neighbors
X
Class Y
Class Y
Class Y Class R
Class R
Class B
Class B
If k=3, then the 3 nearest neighbors have classes
(Y,R,R). R is the most frequent, so Classify as R.

kNN as Machine Learning
21
Learn the best value of k:
Suppose you have some training
data (the class is known for all the
entities in this dataset).
1. Pick a value for k.
• Apply kNN to "predict" the class
of each vertex in the dataset.
• Compare the prediction with the
truth, and record the % correct
guesses.
2. Try other values of k and repeat.
3. Pick the value of k that yield the
most accurate class predictions.
X
Class Y
Class Y
Class Y Class R
Class R
Class B
Class B
If k=3, the neighbors are (Y,R,R) → R → Incorrect
If k=5, the neighbors are (Y,R,R,Y,Y) → Y → Correct
Class Y

DEMO
● Pattern Matching
● Interpreted Mode
22

⭐ NEW: AWS S3 Import - Easy to Use in Cloud
● For AWS Users, Painless Data Import from S3 Storage
• Consistent experience: same GSQL file loading syntax as before
and consistent GraphStudio loading experience
• Format friendly: CSV and Parquet
● Embrace Benefits of S3 Storage
• Scalable cloud storage
• Connect to whole family of AWS services
• Built-in fault tolerance
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S3 Loader

⭐ GraphStudio - More Loading Capability
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● Load from either local files or S3
○ Simply pick your source
○ Provide credentials as needed
○ CSV or Parquet
● Start / Pause / Resume / Stop Loading Jobs
○ Pick one or more jobs to control
● New Loading Status Display

⭐ JDBC Driver
● Type 4 driver
● Supports REST endpoints of built-in and compiled GSQL queries
● Open Source:
https://github.com/tigergraph/ecosys/tree/master/etl/tg-java-driver

Speed to Value from Popular Cloud Storage
- Native Integration with AWS S3
27
• Import Directly from Your Popular Data Store
• Native Integration with S3 Storage
• Decrease Learning Curve with Familiar Syntax
• GSQL Support with Consistent Data Loading Syntax
• GraphStudio through Similar Loading UX/UI
• Maintain Separation of Control for Data Loading
• Designed with Built-in MultiGraph Support

S3 and TigerGraph Data Pipeline
Static
Data
Sources
S3
Loader
Streaming
Data
Sources

S3 Import High Level Architecture (GSQL)
• Connect to S3 Bucket
• User Commands Through GSQL
Server
• Configuration Files:
• Config 1: S3 Connection
Configuration
• Config 2: S3 File Configuration
File
29

S3 Import (GSQL) : Three Steps
30
Consistent with GSQL Data Loading Steps
Step 1: Define the Data Source
Step 2: Create a Loading Job
Step 3: Run the Loading Job

Prerequisites: S3 Configuration Files (GSQL)
31
Connect to AWS S3
Through
S3 Connection
Configuration
In Step 1
(S3’s access ID and
secret key)
Define S3 File Structure
Through
S3 File Configuration
In Step 2
(File URIs, file format, and
batch size and etc.)

Manage Loading Job (GSQL)
• SHOW LOADING STATUS
• ABORT LOADING JOB
• RESUME LOADING JOB
32
Consistent with GSQL Data Loading Syntax

Example Scripts
33
USE GRAPH test_graph
DROP JOB load_person
DROP DATA_SOURCE s1
# Create data_source s3 s1 = "s3_config.json" for graph test_graph.
CREATE DATA_SOURCE S3 s1 FOR GRAPH test_graph
SET s1 = "s3_config.json"
# Define the loading jobs.
CREATE LOADING JOB load_person FOR GRAPH test_graph {
DEFINE FILENAME f1 = "$s1:s3_file_config.json";
LOAD f1
TO VERTEX Person VALUES ($2, $0, $1),
TO EDGE Person2Comp VALUES ($2, $2, $1)
USING SEPARATOR=",";
}
# load the data
RUN LOADING JOB load_person

GraphStudio S3 Import
34

DEMO: GraphStudio AWS S3 Import
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DEMO
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1. Prep Work:
a. External S3 Bucket is setup
b. Graph is created in TigerGraph: Friends Network

Summary
• TigerGraph 2.4 is Released
• Enhancements in GSQL
• Interpreted Mode
• Pattern Matching
• Native Integration with AWS S3 (GSQL & GraphStudio)
• Open Source Connector/Driver: JDBC Driver
• Graph Algorithms Library is Expanded
37
Version 2.4
Available Now

Q&A
Please send your questions via the Q&A menu in Zoom
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Additional Resources
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New Developer Portal
https://www.tigergraph.com/developers/
Download the Developer Edition or Enterprise Free Trial
https://www.tigergraph.com/download/
Guru Scripts
https://github.com/tigergraph/ecosys/tree/master/guru_scripts
Join our Developer Forum
https://groups.google.com/a/opengsql.org/forum/#!forum/gsql-users
@TigerGraphDB youtube.com/tigergraph facebook.com/TigerGraphDB linkedin.com/company/TigerGraph

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