Pig with Cassandra: Adventures in Analytics

Pig with Cassandra
Adventures in Analytics

Motivation
What’s our need?
How do we get at data in Cassandra with ad-hoc queries
Don’t reinvent the wheel

Enter Pig
Pig was created at Yahoo! as an abstraction for MapReduce
Designed to eat anything
loadstorefunc created for Cassandra

How it works
Perform queries over all rows in a column family or set of column families
Intermediate results stored in HDFS or CFS
Can mixand match inputs and outputs

Uses
Analytics
Data exploration
How many items did I get from New Jersey?
Data validation
How many items were missing a field and when were they created?
Data correction
Company name correction over all data
Expand Cassandra data model
Make a new column family for querying by US State and back-populate with Pig
Bootstrap local dev environment

Pygmalion
Figure in Greek mythology, sounds like Pig
UDFs, examples scripts for using Pig with Cassandra
Used in production at The Dachis Group
https://github.com/jeromatron/pygmalion/

Digging in the Dirt
Pygmalion basic examples

Tips
Develop incrementally
Output intermediate data frequently to verify
Validate data on input if possible
Use Cassandra data type validation for inputs and outputs
Pygmalion for tabular data
Penny in Pig 0.9!

Cluster Configuration
Split cluster – virtual datacenters
Brisk (built-in pig support in 1.0 beta 2+)
Task trackers on all analytic nodes
With HDFS:
Separate namenode/jobtracker
Data nodes on all analytic nodes
A few settings to bridge the two
Start the server processes
Distributed cache and intermediate data
With Brisk:
Startup includes CFS, job tracker, and task trackers

Topology configuration
# from conf/cassandra-topology.properties
###
# Cassandra Node IP=Data Center:Rack

10.20.114.10=DC-Analytics:Rack-1b

10.0.0.10=DC-Realtime-East:Rack-1a

10.21.119.13=DC-Realtime-West:Rack-1c

# default for unknown nodes
default=DC-Realtime-West:Rack-1c

Configuration Priorities
Data locality
Data locality – no really, biggest performance factor
Memory needs
Cassandra requires lots of memory
Hadoop requires lots of memory
Plan with your data model and analytics in mind
CPU needs
Cassandra doesn’t need a lot of CPU horsepower
Hadoop loves CPU cores
Interconnected
Analytic nodes need to be close to one another

Cassandra/Hadoop properties
Reference: org.apache.cassandra.hadoop.ConfigHelper.java
Basics
cassandra.thrift.address
cassandra.thrift.port
cassandra.partitioner.class
Consistency
cassandra.consistencylevel.read
cassandra.consistencylevel.write
Splits and batches
cassandra.input.split.size
cassandra.range.batch.size

Future Work
Better data type handling (Cassandra-2777)
MapReduce over subsets of rows (Cassandra-1600)
MapReduce over secondary indexes (Cassandra-1600)
Pig pushdown projection
Pig pushdown filter
HCatalog support for Cassandra
Better Cassandra wide-row support (Cassandra-2688)
Support for immutable/snapshot inputs (Cassandra-2527)

Questions
Contact info
Jeremy Hanna
@jeromatron on twitter
jeremy.hanna1234 <at> gmail
jeromatron on irc (in #cassandra, #hadoop-pig, and #hadoop)

http://nosql.io	53
http://paper.li	6
https://twitter.com	3
http://twitter.com	2

Pig with Cassandra: Adventures in Analytics

by Jeremy Hanna on Jul 13, 2011

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