How Quotient uses MariaDB to help customers save money

Copyright © 2019 Quotient Technology Inc. All Rights Reserved. Quotient, the Quotient logo, the Coupons.com logo, the SavingStar logo, Elevaate, QMX, Quotient Retailer iQ, and Ahalogy are trademarks or registered trademarks of Quotient Technology Inc. and its subsidiaries in the United States
and other countries. Other marks are the property of their respective owners. Confidential and Proprietary Information of Quotient Technology Inc. Please Do Not Copy or Circulate. We do not make any guarantees regarding outcomes that this product will meet your company’s unique needs.
How Quotient uses MariaDB to help
customers save money?

Some Stats in 2017 – US grocery retail
• Sales ~641 billion U.S. dollars
• Total Consumer Packaged Goods coupon ~293 billion coupons
distributed of ~573 billion dollars value
• 2.75 billion dollar grocery coupon redemptions
• Survey: 87 percent with annual earnings of $20,000 - $39,000 and 85
percent between $100,000 - $149,000 looking for deals
• Survey: 72% of modern consumers and 90% of millennials searched for
coupons or offers via their mobile device

C o p y r i g h t © 2 0 1 8 Q u o t i e n t T e c h n o l o g y I n c . A l l R i g h t s R e s e r v e d . Q u o t i e n t , t h e C o u p o n s . c o m l o g o a n d t h e Q u o t i e n t l o g o a r e t r a d e m a r k s o f Q u o t i e n t
T e c h n o l o g y I n c . A l l o t h e r t r a d e m a r k s , s e r v i c e m a r k s , l o g o s , a n d c o m p a n y o r p r o d u c t n a m e s a r e t h e p r o p e r t y o f Q u o t i e n t T e c h n o l o g y I n c . ( o r i t s
s u b s i d i a r i e s ) o r t h e i r r e s p e c t i v e o w n e r s . C o n f i d e n t i a l a n d P r o p r i e t a r y I n f o r m a t i o n o f Q u o t i e n t T e c h n o l o g y I n c . – P l e a s e D o N o t C o p y o r D i s t r i b u t e . W e d o
About Quotient
3,500+
Promotional offers
75,000+
Stores use
Quotient
Digital Promotions
~60M+
Quotient
Promotions Network
unique monthly
average users
2000+
Brands
Source: 1 Quotient Internal Reporting; 2 Calculations based on NCH estimates of Quotient Digital Print and Paperless divided by Total Digital Print and Paperless; 3 Chain Store Guide (Q3 2017); 4 ComScore (March 2018)

Desktop
Touch Pad
Mobile
In Store
Machine
Learning
Near RealTime,
Personalized to Each
Audience and
Touchpoint with Speed
& Scale
450M
Digital Personalized
Recommendations
per Day
Quotient Artificial Intelligence: Rich
Data for precision targeting at scale
across multiple touchpoints

Digital
Circular
In-Lane Influencer
Marketing
Targeting
Digital
Media
Reporting
&
Analytics
Digital
Promotions
What We Do
Integrate multiple touchpoints to deliver
personalized and targeted shopper content
Quotient’s Technology Platform

Digital Promotions Architecture

Why MariaDB?
No-SQL databases won’t fit many use cases!
Open source and transparent release
Popular and easy to migrate, cloud support
Performant
Galera active-active master clustering
MariaDB Server

Use case: Coupon modeling
Promotion Types:
Amount off – 2$ off Chips
Percentage Off – 10% of total basket
Points – 100 points on Cereals
BuyXGetY Free – Buy chips and get soda free
Continuity Programs – Spend 20$ and get 2$
EBOX TOPS
Rebates – Submit receipt and get rebate
Cashback – affiliate cash back

50+ tables

Use case: short-lived access tokens
OAuth expiring tokens
Cassandra tombstones
MariaDB cross DC replication for short lived tokens, nightly batch deletes

Use case: User targeting
Target millions of users with custom offers
Cassandra massive/bulk update, clean up challenges
MariaDB strong at large number of batch updates and batch deletes

Use case: Business Rules
Rule Engine controls coupon life cycle
Updates are eventually consistent in Cassandra
MariaDB consistency important for modeling business rules based on tracking counts

Use case: Adhoc Analytics
Track daily, hourly transactions periodically
Cassandra not suited for realtime analytics and aggregations
MariaDB really consistent and fast at aggregate queries

Cloud Datacenter

• Multiple Master-Master, Master-Slave and Galera Clusters
• GTID Replication
• ~15,000 peak requests per seconds on Digital Promotion database cluster
• Log slow queries > 100ms
• MONYog/ SQL Diagnostic Manager monitoring
• Automated Backup Validation
• Data at Rest Encryption
MariaDB at Quotient

GRAPH TRENDS
• In-house Graphite/ Grafana
monitoring
• Helps to diagnose a problem
• Growth Trends
• Helps Identify usage in
multi-tenant database
• Historic Information
Queries
CPU
Disks
Network
Memory
Database

GRAPH ESTIMATED TABLE/ USER USAGE
Enable userstat plugin
Information_schema tables:
• TABLE_STATISTICS -> rows_read
• TABLE_STATISTICS -> rows_changed
• TABLES -> table_rows
• USER_STATISTICS -> total_connections, cpu_time, bytes_received,
bytes_sent
• CLIENT_STATISTICS -> total_connections, select commands,
update_commands, rows_inserted, rows_read,

MONITORING DISKS/ CPU/ MEMORY

MONITORING TABLES
select TABLE_NAME, ROWS_READ from information_schema.table_statistics where TABLE_SCHEMA not in ('mysql','information_schema','performance_schema') order by ROWS_READ desc limit 10;
select TABLE_NAME, ROWS_CHANGED from information_schema.table_statistics where TABLE_SCHEMA not in ('mysql','information_schema','performance_schema') order by ROWS_CHANGED desc limit 10;
select TABLE_NAME, TABLE_ROWS from information_schema.tables where TABLE_SCHEMA not in ('mysql','information_schema','performance_schema') order by TABLE_ROWS desc limit 10;
*Table names changed for presentation
Estimating Table changes

MONITORING USER/ CLIENT CONNECTIONS
select CLIENT, TOTAL_CONNECTIONS from information_schema.client_statistics;
select USER, TOTAL_CONNECTIONS from information_schema.user_statistics;
Estimating User/ Client connections

CHALLENGES
• NUMA architecture Swap issues/ Memory imbalance
10.2.3 onwards have NUMA enabled builds
• Data at Rest Encryption Performance
• Bulk load on Galera Clusters

WHAT HAS HELPED US
• Capturing Processlist every minute
• Turning on userstat and graphing user/ table statistics on multi-
tenant databases
• Working closely with developers on slow query log
• Disable CPU frequency scaling
Use Performance instead of on-demand/ power-save governor
• Battery backed RAID cache

WHAT’S NEXT
• Exploring MariaDB Column Store
• MariaDB MaxScale
• Kafka streaming with MaxScale CDC
• Cloud Migration

and other countries. Other marks are the property of their respective owners. Confidential and Proprietary Information of Quotient Technology Inc. Please Do Not Copy or Circulate. We do not make any guarantees regarding outcomes that this product will meet your company’s unique needs.32
Thank You
Arun Subramanian -
asubramanian@quotient.com
Radha Krishna Proddaturi-
rproddaturi@quotient.com
Ashu Sahijpal –
asahijpal@quotient.com

How Quotient uses MariaDB to help customers save money

Recommended

Recommended

More Related Content

Similar to How Quotient uses MariaDB to help customers save money

Similar to How Quotient uses MariaDB to help customers save money (20)

More from MariaDB plc

More from MariaDB plc (20)

Recently uploaded

Recently uploaded (20)

How Quotient uses MariaDB to help customers save money

Editor's Notes