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Apache Phoenix with 
Actor Model (Akka.io) 
for Real-time Big Data 
Programming Stack 
Why we still need SQL for Big Data ? 
How to make Big Data more responsive and faster ? 
By http://nguyentantrieu.info 
Tech Lead at eClick team - FPT Online
Contents 
1. What is Big data and Why ? 
2. When standard relational database (Oracle,MySQL, ...) is 
not good enough 
3. Common problems in big data system 
4. Introducing open-source tools in Big Data System 
a. Apache Phoenix for ad-hoc query 
b. Actor Model and Akka.io for reactive data processing
What Does Big Data Actually Mean? 
“Big data means data 
that cannot fit easily into 
a standard relational database.” 
Hal Varian- Chief Economist, Google 
http://www.brookings.edu/blogs/techtank/posts/2014/09/11-big-data-definition
When standard relational database 
(Oracle,MySQL, ...) is not good enough 
the “analytic system” MySQL database from a 
startup, tracking all actions in mobile games: 
iOS, Android, ...
Complex analytic system and the “scale” pain
Definition from the crowd 
“Big data is a term describing the storage 
and analysis of large and or complex 
data sets using a series of techniques 
including, but not limited to: NoSQL, 
MapReduce and machine learning.” 
Jonathan Stuart Ward and Adam Barker 
Source: 
http://arxiv.org/abs/1309.5821 
http://www.technologyreview.com/view/519851/the-big-data-conundrum-how-to-define- 
it/
“Chaotic” fact and the demand 
80% of that data is unstructured or “chaotic” 
Photos, videos and social media posts - data that says so much 
about us - but cannot be analyzed via traditional methods 
Demand: 
“Finding order among chaos”
3 common problems in Big Data System 
1. Size: the volume of the datasets is a critical 
factor. 
2. Complexity: the structure, behaviour and 
permutations of the datasets is a critical 
factor. 
3. Technologies: the tools and techniques 
which are used to process a sizable or 
complex dataset is a critical factor.
Introducing open-source tools in Big Data System 
Apache Phoenix 
as SQL ad-hoc query 
engine 
Actor Model as nano-service 
for reactive data 
computation 
in the dawn of “Fast data”
Some innovative tools were born 
in the dawn of Big Data Age
But could an elephant fly without wings ?
But a phoenix can fly !
What is Apache Phoenix ? 
Apache Phoenix is a SQL skin over HBase. 
It means scaling Phoenix just like scale-up and 
scale-out the Hbase
Phoenix 
SQL Engine
Interesting features of Apache Phoenix 
● Embedded JDBC driver implements the majority of java.sql interfaces, 
including the metadata APIs. 
● Allows columns to be modeled as a multi-part row key or key/value cells. 
● Full query support with predicate push down and optimal scan key 
formation. 
● DDL support: CREATE TABLE, DROP TABLE, and ALTER TABLE for 
adding/removing columns. 
● Versioned schema repository. Snapshot queries use the schema that was 
in place when data was written. 
● DML support: UPSERT VALUES for row-by-row insertion, UPSERT 
SELECT for mass data transfer between the same or different tables, and 
DELETE for deleting rows. 
● Limited transaction support through client-side batching. 
● Single table only - no joins yet and secondary indexes are a work in 
progress. 
● Follows ANSI SQL standards whenever possible 
● Requires HBase v 0.94.2 or above 
● 100% Java
the Phoenix table schema
Setting JDBC Phoenix Driver
Phoenix and SQL tool in Eclipse 4
Phoenix vs Hive 
(running over HDFS and HBase) 
http://phoenix.apache.org/performance.html
Actor Model in the dawn of “Fast data”
http://youtu.be/TnLiEWglqHk - Google I/O 2014 - The dawn of "Fast Data"
The paper: MillWheel: Fault-Tolerant Stream 
Processing at Internet Scale
What is actor model ? 
● Carl Hewitt defined the Actor 
Model in 1973 as a mathematical 
theory that treats “Actors” as the 
universal primitives of concurrent 
digital computation. 
● A fitting model for heavily-parallel 
processing in a cloud environment
What actor model ?
is the framework for 
implementing Actor computation
Inspired by MillWheel of Google and Storm of 
Twitter, I have developed my own framework, the 
“Rfx” (Reactive Functor Extension) with Akka as 
core
The pipeline of finding social trends 
in real-time analytics
Facebook Social Trending from a website
Quick demo 
Using Akka (Rfx) and Apache Phoenix 
for Social Media Real-time Analytics
Links for self-study and research 
Actor Model and Programming: 
● http://nguyentantrieu.info/blog/the-architecture-for-real-time-event-processing-with- 
reactive-actor-model 
● http://www.slideshare.net/drorbr/the-actor-model-towards-better-concurrency 
● http://www.infoq.com/articles/reactive-cloud-actors 
● http://www.mc2ads.com/p/rfx-for-big-data-developer.html 
Apache Phoenix 
● http://java.dzone.com/articles/apache-phoenix-sql-driver 
● http://phoenix.apache.org/Phoenix-in-15-minutes-or-less.html 
Big Data and Data Science 
● http://www.mc2ads.com and http://www.mc2ads.org 
● http://datascience101.wordpress.com 
● http://lambda-architecture.net 
● http://www.bigdata-startups.com 
● https://www.coursera.org/course/datasci

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Apache Phoenix with Actor Model (Akka.io) for real-time Big Data Programming Stack

  • 1. Apache Phoenix with Actor Model (Akka.io) for Real-time Big Data Programming Stack Why we still need SQL for Big Data ? How to make Big Data more responsive and faster ? By http://nguyentantrieu.info Tech Lead at eClick team - FPT Online
  • 2. Contents 1. What is Big data and Why ? 2. When standard relational database (Oracle,MySQL, ...) is not good enough 3. Common problems in big data system 4. Introducing open-source tools in Big Data System a. Apache Phoenix for ad-hoc query b. Actor Model and Akka.io for reactive data processing
  • 3. What Does Big Data Actually Mean? “Big data means data that cannot fit easily into a standard relational database.” Hal Varian- Chief Economist, Google http://www.brookings.edu/blogs/techtank/posts/2014/09/11-big-data-definition
  • 4. When standard relational database (Oracle,MySQL, ...) is not good enough the “analytic system” MySQL database from a startup, tracking all actions in mobile games: iOS, Android, ...
  • 5. Complex analytic system and the “scale” pain
  • 6. Definition from the crowd “Big data is a term describing the storage and analysis of large and or complex data sets using a series of techniques including, but not limited to: NoSQL, MapReduce and machine learning.” Jonathan Stuart Ward and Adam Barker Source: http://arxiv.org/abs/1309.5821 http://www.technologyreview.com/view/519851/the-big-data-conundrum-how-to-define- it/
  • 7. “Chaotic” fact and the demand 80% of that data is unstructured or “chaotic” Photos, videos and social media posts - data that says so much about us - but cannot be analyzed via traditional methods Demand: “Finding order among chaos”
  • 8. 3 common problems in Big Data System 1. Size: the volume of the datasets is a critical factor. 2. Complexity: the structure, behaviour and permutations of the datasets is a critical factor. 3. Technologies: the tools and techniques which are used to process a sizable or complex dataset is a critical factor.
  • 9. Introducing open-source tools in Big Data System Apache Phoenix as SQL ad-hoc query engine Actor Model as nano-service for reactive data computation in the dawn of “Fast data”
  • 10. Some innovative tools were born in the dawn of Big Data Age
  • 11. But could an elephant fly without wings ?
  • 12.
  • 13. But a phoenix can fly !
  • 14. What is Apache Phoenix ? Apache Phoenix is a SQL skin over HBase. It means scaling Phoenix just like scale-up and scale-out the Hbase
  • 16. Interesting features of Apache Phoenix ● Embedded JDBC driver implements the majority of java.sql interfaces, including the metadata APIs. ● Allows columns to be modeled as a multi-part row key or key/value cells. ● Full query support with predicate push down and optimal scan key formation. ● DDL support: CREATE TABLE, DROP TABLE, and ALTER TABLE for adding/removing columns. ● Versioned schema repository. Snapshot queries use the schema that was in place when data was written. ● DML support: UPSERT VALUES for row-by-row insertion, UPSERT SELECT for mass data transfer between the same or different tables, and DELETE for deleting rows. ● Limited transaction support through client-side batching. ● Single table only - no joins yet and secondary indexes are a work in progress. ● Follows ANSI SQL standards whenever possible ● Requires HBase v 0.94.2 or above ● 100% Java
  • 17.
  • 20. Phoenix and SQL tool in Eclipse 4
  • 21. Phoenix vs Hive (running over HDFS and HBase) http://phoenix.apache.org/performance.html
  • 22. Actor Model in the dawn of “Fast data”
  • 23. http://youtu.be/TnLiEWglqHk - Google I/O 2014 - The dawn of "Fast Data"
  • 24. The paper: MillWheel: Fault-Tolerant Stream Processing at Internet Scale
  • 25. What is actor model ? ● Carl Hewitt defined the Actor Model in 1973 as a mathematical theory that treats “Actors” as the universal primitives of concurrent digital computation. ● A fitting model for heavily-parallel processing in a cloud environment
  • 27. is the framework for implementing Actor computation
  • 28. Inspired by MillWheel of Google and Storm of Twitter, I have developed my own framework, the “Rfx” (Reactive Functor Extension) with Akka as core
  • 29. The pipeline of finding social trends in real-time analytics
  • 30. Facebook Social Trending from a website
  • 31. Quick demo Using Akka (Rfx) and Apache Phoenix for Social Media Real-time Analytics
  • 32. Links for self-study and research Actor Model and Programming: ● http://nguyentantrieu.info/blog/the-architecture-for-real-time-event-processing-with- reactive-actor-model ● http://www.slideshare.net/drorbr/the-actor-model-towards-better-concurrency ● http://www.infoq.com/articles/reactive-cloud-actors ● http://www.mc2ads.com/p/rfx-for-big-data-developer.html Apache Phoenix ● http://java.dzone.com/articles/apache-phoenix-sql-driver ● http://phoenix.apache.org/Phoenix-in-15-minutes-or-less.html Big Data and Data Science ● http://www.mc2ads.com and http://www.mc2ads.org ● http://datascience101.wordpress.com ● http://lambda-architecture.net ● http://www.bigdata-startups.com ● https://www.coursera.org/course/datasci