Hadoop and Cassandra at Rackspace

Making Massive Manageable: Hadoop and Cassandra (at Rackspace) Big Data Workshop Stu Hood (@stuhood) – Technical Lead, Rackspace April 23rd 2010

My, what a large dataset you have...
Processing 3 TB/day of logs
Using Hadoop/Pig
And the sticking points?
“ How fast can we provision machines?”
“ How do we get data on/off the cluster?”
“ How do we add structure?”

MapReduce
Distributed processing methodology
Adapt a problem to MapReduce
Scale forever
Crunch almost anything
Typically adding structure to unstructured data
Logs
Also great for structured
Graph processing
Machine learning

“You want to use how many clients?”
Need to store structured inputs/outputs
Solution needs to
Support arbitrary number of clients
Preferably provide locality
Possibly provide 'web' latency

Solutions of varying quality
Sharding the RDBMS
shard n. - A horizontal partition in a database
Example: Sharding by userid
Provided by ORM?
Fixed partitions: manual rebalancing
Developing from scratch?
Adding/removing nodes
Handling failover
As a library? As a middle tier?

Leaving data in Hadoop
Storage in Map/SequenceFile
Serialized with Thrift/Avro/ProtoBuffs
No random access
High latency

Storing in HBase/Hypertable
Column stores implemented on Hadoop
Modeled after Google's Bigtable
Multiple points of failure
Namenode
Master
High (almost non-web) latency

And the newest contender...

Standing on the shoulders of: Amazon Dynamo
No node in the cluster is special
No special roles
No scaling bottlenecks
No single point of failure
Techniques
Gossip
Eventual consistency

Standing on the shoulders of: Google Bigtable
“Column family” data model
Range queries for rows:
Scan rows in order
Memtable/SSTable structure
Always writes sequentially to disk
Bloom filters to minimize random reads
Trounces B-Trees for big data
Linear insert performance
Log growth for reads

Enter Cassandra
Hybrid of ancestors
Adopts listed features
And adds:
A sweet logo!
Pluggable partitioning
Multi datacenter support
Pluggable locality awareness
Datamodel improvements

Enter Cassandra
Project status
Open sourced by Facebook in 2008 (no longer active)
Apache License
Graduated to Apache TLP February 2010
Major releases: 0.3 through 0.6 (0.7 in two months)
cassandra.apache.org

Enter Cassandra
The code base
Java, Apache Ant, Git/SVN
5+ committers from 3+ companies
Known deployments at:
Cloudkick, Digg, Mahalo, SimpleGeo, Twitter, Rackspace, Reddit

Performance

Like peanut butter with jelly
Apache Cassandra 0.6:
MapReduce input support out of the box
Locality information partially exposed
Hadoop InputFormat
Pig LoadFunc

Hadoop + Cassandra at RAX
Multiple Hadoop clusters deployed
Smaller Cassandra deployments
Preparing for large scale Cassandra deployment

In the pipeline
MapReduce output support
Adding an OutputFormat with locality information
Improving locality for Hadoop inputs

Getting started
http://cassandra.apache.org/
Read "Getting Started"... Roughly:
Start one node
Test/develop app, editing node config as necessary
Launch cluster by starting more nodes with chosen config

Thanks! Big Data Workshop Participants!

Questions?

References
Brandon William's perf tests
http://racklabs.com/~bwilliam/cassandra/04vs05vs06.png
Hadoop/Cassandra Integration
http://issues.apache.org/jira/browse/CASSANDRA-342

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Hadoop and Cassandra at Rackspace

by stuhood on Apr 24, 2010

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Hadoop and Cassandra at Rackspace Presentation Transcript