Alluxio (formerly Tachyon): Open Source Memory Speed Virtual Distributed Storage Presented by Gene Pag, Alluxio Introduction to Alluxio Meetup at Princeton http://www.meetup.com/futureofdata-princeton/events/232927731/

1. Alluxio (formerly Tachyon): Open Source
Memory Speed Virtual Distributed Storage
October 2016
Gene Pang

2. About Me and Alluxio, Inc.
2
• Team members from Google, Palantir, Uber, Yahoo with
years of distributed systems development experience
• Graduated from Stanford University, UC Berkeley, CMU,
Peking University, and Tsinghua, with CS masters or PhDs
• Top 9 committers of the Alluxio open source project
Alluxio
Team
Gene Pang, Software Engineer, Alluxio Maintainer
Ph.D. from UC Berkeley AMPLab
Previously on Google F1 team
Twitter: @unityxx
• Andreessen HorowitzInvestors

3. AGENDA
3
• Alluxio Open Source Status and History
• Alluxio Overview
• Alluxio Use Cases
• What’s Next?

4. HISTORY
4
• Started at UC Berkeley AMPLab In Summer 2012
• Original named as Tachyon
• Open Sourced in 2013
• Apache License 2.0
• Latest Stable Release: Alluxio 1.2.0
• Next Release (Alluxio 1.3.0) soon!
• Rebranded as Alluxio in 2016

5. 0
50
100
150
200
250
300
350
Year 1 Year 3Year 2
5
OPEN SOURCE ALLUXIO
• One of the fastest
growing open-
source projects
in the big data
ecosystem
• Currently over
300 contributors
from over 100
organizations
• Welcome to join
our community!
Popular Open Source Projects’ Growth
Spark Kafka Cassandra HDFS
Alluxio

6. BIG DATA ECOSYSTEM TODAYBIG DATA ECOSYSTEM WITH ALLUXIO
6
BIG DATA ECOSYSTEM YESTERDAY
…
…
FUSE Compatible File SystemHadoop Compatible File System Native Key-Value InterfaceNative File System
Enabling any application to access data from
any storage system at memory-speed
BIG DATA ECOSYSTEM ISSUES
GlusterFS InterfaceAmazon S3 Interface Swift InterfaceHDFS Interface

7. • Memory is getting
Faster, Larger,
and Cheaper
• Memory price as
halving every 18
months
• Disk throughput
increasing slowly
7
TECHNOLOGY TRENDS
Top left chart:
https://lazure2.wordpress.com/2013/07/02/
20-years-of-samsung-new-management-as-
manifested-by-the-latest-june-20th-galaxy-
ativ-innovations/
Top right chart:
people.eecs.berkeley.edu/~istoica/classes/c
s294/
15/notes/02-TechnologyTrends.ppt
Bottom chart: jcmit.com/
6.25
12.5
25
18.75
31.25
43.75
37.5
50
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
DDR performance over time
GBs/second
DDR2
DDR4
DDR3

8. File System API
Software Only
8
ALLUXIO ATTRIBUTES
Memory-Speed Virtual Distributed Storage
Scale out
architecture
Virtualizes across
different storage
systems, providing a
unified namespace
Memory-speed
access to data

9. Server A
Applications
Server B
Applications
Server Z
Applications
Server C
ApplicationsAlluxio Alluxio AlluxioAlluxio
9
ALLUXIO SOLUTION DEPLOYMENT
Storage B Storage C Storage ZStorage A

10. 10
ALLUXIO BENEFITS
Unification
New workflows
across any data
in any storage
system
Performance
High
performance
data access
Flexibility
Work with the
compute and
storage frameworks
of your choice
Cost
Grow compute
and storage
systems
independently

11. USE CASE 1 – Accelerate I/O to/from Remote
Storage
11
• Compute and Storage Separation
• Advantages
• Meet different compute and storage hardware
requirements efficiently
• Scale compute and storage independently
• Store data in Traditional filers/SANs and object
stores cost effectively
• Compute on data in existing storage via Big Data
Computational frameworks
• Disadvantage
• Accessing data requires remote I/O

12. Use Case without Alluxio
12
Spark
Storage
Low latency, memory
throughput
High latency, network
throughput

13. Use Case with Alluxio
13
Spark
Storage
Alluxio
Keeping data in Alluxio
accelerates data access

14. 14
CASE STUDY
Baidu File System
The performance was amazing. With
Spark SQL alone, it took 100-150 seconds
to finish a query; using Alluxio, where data
may hit local or remote Alluxio nodes, it
took 10-15 seconds.
- Shaoshan Liu, Baidu
RESULTS
• Data queries are now 30x faster with Alluxio
• Alluxio cluster run stably, providing over 50TB
of RAM space
• By using Alluxio, batch queries usually lasting
over 15 minutes were transformed into an
interactive query taking less than 30 seconds
Accelerate Access to
Remote Storage
• 200+ nodes deployment
• 2+ petabytes of storage
• Mix of memory + HDD

15. USE CASE 2 – Share Data Across Jobs at
Memory Speed
15
• Architectures Requiring Shared Data
• Pipelines: output of one job is input of the next job
• Different applications, jobs, or contexts read the
same data
• Disadvantage
• Sharing data requires I/O

16. Use Case without Alluxio
16
Spark
Storage
MapReduce Spark
Network I/O
Disk I/O
I/O slows down
sharing

17. Use Case with Alluxio
17
Spark
Storage
MapReduce Spark
Sharing data with
Alluxio via memory
Alluxio

18. 18
CASE STUDY
Thanks to Alluxio, we now have the raw
data immediately available at every
iteration and we can skip the costs of
loading in terms of time waiting, network
traffic, and RDBMS activity.
- Henry Powell, Barclays
RESULTS
• Barclays workflow iteration time decreased
from hours to seconds
• Alluxio enabled workflows that were
impossible before
• By keeping data only in memory, the I/O cost
of loading and storing in Alluxio is now on the
order of seconds
Relational Database
Share Data Across Jobs
at Memory-Speed
• 6 node deployment
• 1TB of storage
• Memory only

19. USE CASE 3 - Transparently Manage Data
Across Storage Systems
19
• Reasons
• Most enterprises have multiple storage systems
• New (better, faster, cheaper) storage systems arise
• Disadvantage
• Managing data across systems can be difficult

20. Use Case Explained
20
Storage
Alluxio
Spark MapReduce Spark
Storage Storage
Flexible,
simple
no application
changes,
new mount
point

21. 21
CASE STUDY
We’ve been running Alluxio in production
for over 9 months, resulting in 15x
speedup on average, and 300x speedup at
peak service times.
- Xueyan Li, Qunar
RESULTS
• Alluxio’s unified namespace enables different
applications and frameworks to easily interact
with their data from different storage systems
• Improved the performance of their system
with 15x – 300x speedups
• Tiered storage feature manages various
storage resources including memory, SSD and
disk
Transparently Manage Data
Across Different Storage
Systems
• 200+ nodes deployment
• 6 billion logs (4.5 TB) daily
• Mix of Memory + HDD

22. What’s Next?
22

23. • Contact: gene@alluxio.com or info@alluxio.com
• Twitter: @Alluxio
• Websites: www.alluxio.com and www.alluxio.org
• Alluxio Github: www.github.com/Alluxio/alluxio
Thank you!