Bridging Structured and Unstructred Data with Apache Hadoop and Vertica

Bridging Unstructured & Structured Data with Hadoop and Vertica
Glenn Gebhart ggebhart@vertica.com
Steve Watt swatt@hp.com

Contents
Our background with Big Data
Accelerating and monitoring Apache Hadoop deployments with HP CMU
I have my Apache Hadoop Cluster deployed….. Now what ?
Sample application scenario with Apache Hadoop and Vertica

3
HP Confidential
Cluster Management Utility

Managing Scale Out with HP CMU
Proven cluster deployment and management tool
11 Years Experience
Proven with clusters of 3500+ nodes
Deployment and Management
Clone a Node (Hadoop Slave) and Deploy to an entire Logical Group.
Provision applications and dependencies with parallel distributed copy (pdcp) and parallel distributed shell (pdsh)
Command Line or GUI based cluster wide configuration
Manage a node individually or manage a cluster as a whole
Monitoring
Scalable Non-intrusive Monitoring across a wide set of infrastructure metrics
Extensible through Collectl integration

5
HP Confidential

6
HP Confidential
Tech Bubble?
What does the Data Say?
Attribution: CC PascalTerjan via Flickr

7
HP Confidential

But what if I could turn that into this?
8
HP Confidential

And see how the amount invested this year differs from previous years?

10
HP Confidential
Where is the money going?

What type of startups get the most investment funding?

Amount invested in Software Startups by Zip Code

How did you do that?
13
HP Confidential
How
did you
Do that?
Attribution: CC Colin_K on Flickr

14
HP Confidential
Apache
Identify Optimal Seed URLs
& Crawl to a depth of 2
http://www.crunchbase.com/companies?c=a&q=privately_held
Crawl data is stored in segment dirs on the HDFS

15
HP Confidential

16
HP Confidential
Making the data STRUCTURED
Retrieving HTML
Prelim Filtering on URL
Company POJO then /t Out

17
HP Confidential
Aargh!
My viz tool requires zipcodes to plot geospatially!

Apache Pig Script to Join on City to get Zip Code and Write the results to VerticaZipCodes = LOAD 'demo/zipcodes.txt' USING PigStorage('t') AS (State:chararray, City:chararray, ZipCode:int);CrunchBase = LOAD 'demo/crunchbase.txt' USING PigStorage('t') AS (Company:chararray,City:chararray,State:chararray,Sector:chararray,Round:chararray,Month:int,Year:int,Investor:chararray,Amount:int);CrunchBaseZip = JOIN CrunchBase BY (City,State), ZipCodes BY (City,State);STORECrunchBaseZip INTO '{CrunchBaseZip(Company varchar(40), City varchar(40), State varchar(40), Sector varchar(40), Round varchar(40), Month int, Year int, Investor int, Amount varchar(40))}’USINGcom.vertica.pig.VerticaStorer(‘VerticaServer','OSCON','5433','dbadmin','');

The Story So Far
Used Nutch to retrieve investment data from web site.
Used Hadoop to extract and structure the data
Used Pig to add zipcode data.
End result is a collection of relations describing investment activity.
We’ve got raw data, now we need to understand it.

Why Vertica?
Vertica and Hadoop are complementary technologies.
Hadoop’s strengths:
Analysis of unstructured data (screen scraping, natural language recognition)
Non-numeric operations (graphics preparation)
Vertica’s strengths
Counting, adding, grouping, sorting, …
Rich suite of advanced analytic functions
All at TB+ scales.

Built from the Ground Up: The Four C’s of Vertica
Columnar storage and execution
Continuous performance
Clustering
Compression
Achieve best data query performance with unique Vertica column store
Linear scaling by adding more resources on the fly
Store more data, provide more views, use less hardware
Query and load 24x7 with zero administration

Getting Data From Here To There

Connecting Vertica And Hadoop
Vertica provides connectors for Hadoop 20.2 and Pig 0.7.
Acts as a passive component; Hadoop/Pig connect to Vertica to read/write data.
Input retrieved from Vertica using standard SQL query.
Output written to Vertica table.

Vertica As a M/R Data Source
// Set up the configuration and job objects
Configuration conf = getConf();
Job job = new Job(conf);
// Set the input format to retrieve data from Vertica
job.setInputFormatClass(VerticaInputFormat.class);
// Set the query to retrieve data from the Vertica DB
VerticaInputFormat.setInput(
job,
“SELECT * FROM foo WHERE bar = ‘baz’
);

Vertica As a M/R Data Sink
// Set up the configuration and job objects
Configuration conf = getConf();
Job job = new Job(conf);
// Set the output format to to write data to Vertica
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(VerticaRecord.class);
job.setOutputFormatClass(VerticaOutputFormat.class);
// Define the table which will hold the output
VerticaOutputFormat.setOutput(
job, <table name>, <truncate table?>,
<col 1 def>, <col 2 def>, …, <col N def>
);

Reading Data Via Pig
# Read some tuples
A = LOAD 'sql://< Your query here >'
USING com.vertica.pig.VerticaLoader(
‘server1,server2,server3',
‘< DB Name>','5433',‘< user >',‘< password >’
);
26

Writing Data Via Pig
# Write some tuples
STORE < some var >
INTO '{
< table name > (< col 1 def >, < col 2 def >, … )
}'
USING com.vertica.pig.VerticaStorer(
‘< server >',‘< DB >','5433',‘< user >',‘< password >’
);
27

Reporting And Data Visualization

Does My Favorite Application Work With Vertica?
Vertica is an ANSI SQL99 compliant DB.
Comes with drivers for ODBC, JDBC, and ADO.Net.
If your tool uses a SQL DB, and speaks one of these protocols, it’ll work just fine.

We Support…

Traditional Reports
Integrates smoothly with reporting frontends such as Jasper and Pentaho.
Scriptable via the vsqlcommand line tool.
C/C++ SDK for parallelized, in-DB computation.
But… you have to know what questions you want to ask.

Graphical, Real-Time Data Exploration

Wrap-Up

Solutions leveraging Vertica in conjunction with Hadoop are capable of solving a tremendous range of analytical challenges.
Hadoop is great for dealing with unstructured data, while Vertica is a superior platform for working with structured/relational data.
Getting them to work together is easy.
In Closing…

Questions?

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Bridging Structured and Unstructred Data with Apache Hadoop and Vertica

by Steve Watt on Jul 31, 2011

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Bridging Structured and Unstructred Data with Apache Hadoop and Vertica Presentation Transcript