The document discusses HP Vertica, a big data platform that integrates with Hadoop to enhance data processing and query performance. It highlights key features of Vertica, such as columnar storage and real-time analytics, and showcases its application in Facebook, where it significantly improved their data handling capabilities. The text also mentions various connectors and integration options that facilitate the use of Vertica with existing big data infrastructures.

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HPVertica-SolvingFacebooksBig
DataChallenges
Moustafa Soliman/ April 1, 2015

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Hello!
Infrastructure and
Outsourcing
Applications and
Business Services
Analytics & Data
Management
HP Financial
Services
HP Enterprise
Group
HP Enterprise
Services
HP Software
HP Printing &
Personal
Systems
Hewlett-Packard Enterprise HP Inc.

3. HPBigDataPlatform-HAVEn

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HP Big Data platform
Transforming Big Data into business solutions
AudioSocial Media ImagesEmailVideo Search engineDocumentsTexts Transactional
Data
Mobile IT/OT
Catalog massive
volumes of
distributed data
Hadoop/HDFS
Process and index
all information
Autonomy IDOL
Analyze at
extreme scale
in real-time
Vertica
Collect & unify
machine data
Enterprise Security
Powering HP Software
+ your apps
nApps
HAVEn
Standard platform with connectors, applications, and engines

5. TheVerticaTechnology

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HP Vertica: An integrated Big Data ecosystem

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HP Vertica – Core Features
Columnar
Storage
Compression MPP Scale-Out Distributed
Query
Projections
Speeds Query Time
by Reading Only
Necessary Data
Lowers costly I/O to
boost overall
performance
Provides high
scalability on
clusters with no
name node or other
single point of
failure
Any node can
initiate the queries
and use other nodes
for work.
No single point of
failure
Combine high
availability with
special
optimizations for
query performance
CPU
Memory
Disk
CPU
Memory
Disk
CPU
Memory
Disk
A B D C E A

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Verticaco-existingtoconvergence
Vertica - adooH P

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1.Vertica and Hadoop Integration
1. MapReduce & Pig Connector
2. HDFS Flat files
3. HCatalog
Hadoop
HDFS
ANSI SQL
HCatalog Pig
MapReduce
HBase
Billing
Clickstream
Telemetry

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Vertica Map Reduce Connector
Allows flexibility & interoperability
Integrate with Hadoop / MapReduce and Pig
• Vertica-aware extension to Hadoop
• Specialized adapter for distributed streaming
between Hadoop and Vertica
Developers need access to fast DBMS that
co-exists with Hadoop rather than being
embedded
• Operate on different clusters, generally by different
groups of people
• Allows customers to scale computation independent
of DBMS
Hadoop
HDFS
ANSI SQL
HCatalog Pig
MapReduce
HBase
Billing
Clickstream
Telemetry

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Vertica Connector for HDFS
• External Tables: Query/Access
HDFS data directly off HDFS
• Connector for HDFS - Load files
from HDFS into Vertica via Copy
command
• HDFS Storage Location - Store ROS
containers on HDFS
Hadoop
HDFS
ANSI SQL
HCatalog Pig
MapReduce
HBase
Billing
Clickstream
Telemetry

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Vertica HCatalog Connector
The Vertica HCatalog Connector lets you access
data stored in Apache's Hive data warehouse
software the same way you access it within a
native Vertica table.
• Always reflects the current state of data stored
in Hive.
• The HCatalog Connector uses the parallel
nature of both HP Vertica and Hadoop to
process Hive data.
• Since Vertica performs the extraction and
parsing of data, the HCatalog Connector does
not significantly increase the load on your
Hadoop cluster.
Hadoop
HDFS
ANSI SQL
HCatalog Pig
MapReduce
HBase
Billing
Clickstream
Telemetry

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2.Vertica SQL-on-Hadoop
• Vertica and Hadoop co-exist on
shared hardware
• Vertica uses HDFS for its data
storage
Hadoop
HDFS
HCatalog Pig
MapReduce
HBase
Billing
Clickstream
Telemetry

16. HPVertica-SolvingFacebooksBigData
Challenges

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Use-case: Facebook
What do they do Challenge Business Benefit /
Outcomes
Technical Pain
Use-Case
Business Challenge
• Lack of query performance
• Restricted data set due to lack of scalability
• Targeted marketing
• Generating new revenue streams from mobile
Leading social media
website focused on
connecting the world.
largest Database in the
world (> 400PB), driving
revenue through targeted
online marketing/revenue
from data via web and
mobile
• Jobs take 1 day in Hadoop
• X could not scale-up
• Y too expensive
To increase revenue from
information, through massive
volume and variety of queries
and profiling people with the
right advertising campaigns
The queries take < 1 minute
using HP Vertica.
The company said growth had
been fuelled by advertising
income, which leapt 66 per
cent year-on-year.
Facebook were struggling to
generate mobile advertising
revenue prior to implementing
HP Vertica.

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Facebook Production Data Flow
Mobile
PC/Laptop
Web Servers
Logs
Hadoop/ HDFS
2 huge Hadoop Clusters
• 1.7 ExaBytes
• 15000 nodes
• 40000 nodes
Job
Scheduler
Vertica
Logs
15 mins
Hourly
Daily
Legacy
• Schedulers: Data Wormhole and Data Bee (Developed at FB)
• 1500B rows/day, 20TB/hour…..500TB/Day
• Keep 30-90 days. Currently 30 days
• 2 x 270-node Vertica cluster
 Distance apart 60km
 ETL Dual Load
 One (Primary), One (Secondary)
 Grow to 500-1000 nodes per cluster in one year
• 600K MR Jobs/day
• 50K Informatica Jobs/day

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Thankyou!
Contact us:
moustafa.soliman@hp.com
marcus.hansfeldt@hp.com
sten.nikolaev@hp.com
carola.holmstrom@hp.com

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Backup

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“…for Facebook’s CIO, Tim Campos, to get on stage
in Europe and declare that, "A partner like
HP Vertica thinks like we do” and is a “key part” of
Facebook’s big data capabilities, is one the best
endorsements, err … “likes,” that any modern IT
infrastructure vendor could hope for.”
- Dana Gardner, Briefings Direct
Watch the video to see how Vertica empowers Facebook

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The Vertica Technology
The 4 Cs

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HP Vertica Flex Zone
Challenge: Analyzing semi-structured data is
difficult and time consuming
SOLUTION: HP Vertica Flex Zone
Benefits:
• Store and explore semi-structured data cost effectively
• Avoid creating and maintaining time-consuming schemas
• Gain 10X+ performance with one simple step
• http://www.vertica.com/hp-vertica-products/flexzone/
Extensible Analytics
SQL
Flex Zone
Explore
Enterprise Edition
Optimize
HP Vertica Analytics Platform