ETL in Clojure ETL in Clojure Dmitriy Morozov / JEEConf 2015
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ETL in ClojureETL in Clojure
Dmitriy Morozov / JEEConf 2015
Dmitriy MorozovDmitriy Morozov
Software engineer at Functional programming junkyOccasional cyclist
Zoomdata.com
@argc
Plan of attackPlan of attack
ETL at ZoomdataETL at Zoomdata
CascalogCascalog
SparkSpark
DemoDemo
ConclusionConclusion
Is a modern BI application focused onIs a modern BI application focused onallowing everyday business users toallowing everyday business users tobe able to visually interact andbe able to visually interact andexplore their data and discoverexplore their data and discoverinsight out of that data.insight out of that data.
What we do at ZoomdataWhat we do at Zoomdata
What we do at ZoomdataWhat we do at Zoomdata
We did ETL inWe did ETL inHive/ImpalaHive/Impala
Using SQL for ETLUsing SQL for ETL
Hive is slow, and so is Hive on TezSQL is horrible for doing anything complicatedCode is hard to maintain, reuse and test
Lessons learnedLessons learned
Why Clojure?Why Clojure?
Functional!
Runs on JVM
Interactive development
Zero delta between prototyp code andproduction code
CascalogCascalog
Datalog DSL in CLojure
Built on top of Hadoop and Cascading
Query compiles to Hadoop MapReduce jobs
Supports local execution for prototyping
Great testing story
DatalogDatalog
language
Syntactically is a subset of Prolog
It is often used as a fordeductive databases.
Query statements can be stated in any order
Logic programming
query language
DatalogDatalog
Word Count using Hadoop API
Word count in CascalogWord count in Cascalog
Cascalog Query StructureCascalog Query Structure
Cascalog / GeneratorsCascalog / Generators
Cascalog / OperationsCascalog / Operations
Cascalog / OperationsCascalog / Operations
Cascalog / JoinsCascalog / Joins
Cascalog / OperationsCascalog / Operations
Cascalog / AggregatorsCascalog / Aggregators
Cascalog / AggregatorsCascalog / Aggregators
Cascalog / TroubleshootingCascalog / Troubleshooting
Cascalog / TestingCascalog / Testing
Cascalog / TroubleshootingCascalog / Troubleshooting
Flow Visualisation / Flow Visualisation / DOTDOT
DEMODEMO
Cascalog DownsidesCascalog Downsides
No supportNo supportfor streamingfor streaming
datadata
Cascalog DownsidesCascalog Downsides
What are the alternatives?What are the alternatives?
Java API for Java API for
FlamboFlamboSparklingSparkling
SparkSpark
Customer XCustomer X
Customer X wants to do DataCustomer X wants to do DataScience!Science!
Drug PersistenceDrug Persistence
Determining whether a patient isDetermining whether a patient ispersistent or not based on whether shepersistent or not based on whether she
refilled the prescription in time.refilled the prescription in time.
Drug PersistenceDrug Persistence
Drug PersistenceDrug Persistence
Drug PersistenceDrug Persistence
Drug PersistenceDrug Persistence
Example: Drug PersistenceExample: Drug Persistence
Things to check outThings to check out
How Yieldbot does Data science in ClojureCascalog for the ImpatientStreaming MapReduce in ClojureSparklingFlambo
Thank you!Thank you!
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