This document discusses using Pig with Cassandra to perform analytics and data processing tasks. Pig allows running queries over Cassandra data and storing intermediate results in HDFS or Cassandra. Example uses include analytics, data exploration, validation, and correction. Configuration involves splitting the cluster into virtual datacenters and setting properties. Future work includes improving data type handling and adding support for secondary indexes and wide rows.

1. Pig with CassandraAdventures in Analytics

2. MotivationWhat’s our need?How do we get at data in Cassandra with ad-hoc queriesDon’t reinvent the wheel

3. Enter PigPig was created at Yahoo! as an abstraction for MapReduceDesigned to eat anythingloadstorefunc created for Cassandra

4. How it worksPerform queries over all rows in a column family or set of column familiesIntermediate results stored in HDFS or CFSCan mixand match inputs and outputs

5. UsesAnalyticsData explorationHow many items did I get from New Jersey?Data validationHow many items were missing a field and when were they created?Data correctionCompany name correction over all dataExpand Cassandra data modelMake a new column family for querying by US State and back-populate with PigBootstrap local dev environment

6. PygmalionFigure in Greek mythology, sounds like PigUDFs, examples scripts for using Pig with CassandraUsed in production at The Dachis Grouphttps://github.com/jeromatron/pygmalion/

7. Digging in the DirtPygmalion basic examples

8. TipsDevelop incrementallyOutput intermediate data frequently to verifyValidate data on input if possibleUse Cassandra data type validation for inputs and outputsPygmalion for tabular dataPenny in Pig 0.9!

9. Cluster ConfigurationSplit cluster – virtual datacentersBrisk (built-in pig support in 1.0 beta 2+)Task trackers on all analytic nodesWith HDFS:Separate namenode/jobtrackerData nodes on all analytic nodesA few settings to bridge the twoStart the server processesDistributed cache and intermediate dataWith Brisk:Startup includes CFS, job tracker, and task trackers

10. Topology configuration# from conf/cassandra-topology.properties#### Cassandra Node IP=Data Center:Rack 10.20.114.10=DC-Analytics:Rack-1b10.20.114.11=DC-Analytics:Rack-1b10.20.114.12=DC-Analytics:Rack-2b 10.0.0.10=DC-Realtime-East:Rack-1a10.0.0.11=DC-Realtime-East:Rack-1a10.0.0.12=DC-Realtime-East:Rack-2a 10.21.119.13=DC-Realtime-West:Rack-1c10.21.119.14=DC-Realtime-West:Rack-1c10.21.119.15=DC-Realtime-West:Rack-2c # default for unknown nodesdefault=DC-Realtime-West:Rack-1c

11. Configuration PrioritiesData localityData locality – no really, biggest performance factorMemory needsCassandra requires lots of memoryHadoop requires lots of memoryPlan with your data model and analytics in mindCPU needsCassandra doesn’t need a lot of CPU horsepowerHadoop loves CPU coresInterconnectedAnalytic nodes need to be close to one another

12. Cassandra/Hadoop propertiesReference: org.apache.cassandra.hadoop.ConfigHelper.javaBasicscassandra.thrift.addresscassandra.thrift.portcassandra.partitioner.classConsistencycassandra.consistencylevel.readcassandra.consistencylevel.writeSplits and batchescassandra.input.split.sizecassandra.range.batch.size

13. Future WorkBetter data type handling (Cassandra-2777)MapReduce over subsets of rows (Cassandra-1600)MapReduce over secondary indexes (Cassandra-1600)Pig pushdown projectionPig pushdown filterHCatalog support for CassandraBetter Cassandra wide-row support (Cassandra-2688)Support for immutable/snapshot inputs (Cassandra-2527)

14. QuestionsContact infoJeremy Hanna@jeromatron on twitterjeremy.hanna1234 <at> gmailjeromatron on irc (in #cassandra, #hadoop-pig, and #hadoop)