This document discusses how Clojure can be used for big data applications. It introduces Clojure and several Clojure libraries for distributed stream processing (Apache Storm) and batch processing (Apache Trident, Incanter, Cascalog). Storm is described as a distributed real-time computation system. Trident provides high-level abstractions for exactly-once processing on Storm. Incanter and Cascalog allow interactive analysis and querying of big data using a Clojure API. The document argues Clojure is well-suited for big data due to its focus on immutability, functions, and map-reduce approaches.

1. Clojure 4 Big Data
Michael Pershyn
2018-11-03

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About me and why Clojure 4 Big Data
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Make Software since 2005, work with Big Data since 2012
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Work for ADITION Technologies AG
– Leading european adserving provider
– Part of european tech stack VirtualMinds
– >2.5 bln events per day processed in real-time
– Extra ~12 bln data points in (batch) ETL daily
– 250 TB of data in hadoop data lake
– Several own data centers
– Low latency requirements
– Written mostly in Clojure

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Agenda
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Why Clojure in 3 Minutes
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Apache Storm
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Apache Trident
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Incanter
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Cascalog

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Why Clojure?

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Makes you think diferent and approach problems
diferently and solve them faster
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Immutability, functions and map-reduce
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Powerful, interactive, small, concise
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Makes it hard to fall back to imperative style

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Distributed realtime computation system
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Apache Top-Level Project since September 2014
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Free and open source

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Core Concepts of Storm
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Spouts
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Bolts
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Topology
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Stream
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Cluster (Nimbus & Workers)

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Storm and Clojure

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Storm Pros and Cons
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No “exactly once” guarantee
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Fast, simple
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Multitenance and debugging
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Integrations

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Trident
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The “Cascading” of Storm
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High level abstraction processing library on top of Storm
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Rich API with joins, aggregations, grouping, etc.
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Provides stateful, exactly-once processing primitives

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Marceline
Marceline provides a DSL that allows you to defne all of
the primitives that Trident has to ofer from Clojure

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Trident compiles to Storm

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Incanter

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Incanter and openhub.net

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Cascalog

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Cascading - a Java API
– defning complex data fows
– integrating those fows with back-end systems
– query planner for mapping and executing logical fows onto
a computing platform
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Cascalog – Clojure DSL for Cascading

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Cascading Concepts
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Decouple application logic from integration
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Flow, source, sink, taps, schemes

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Cascading Pros and Cons
Hive Pig Cascading
Pros
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SQL (non-standard)
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Low learning curve
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UDF
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Pig Latin
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Low learning curve
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UDF
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Java API
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Unit testable
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Flow control (if, try-catch)
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Good reusability
Cons
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Testability
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Reusability
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Flow control
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Spread logic
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UDF Programming
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Testability
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Reusability
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Spread logic
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UDF Programming
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Programming

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https://hortonworks.com/blog/cascading-hadoop-big-data-whatever/

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Trident and Cascalog
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Trident for Storm is like Cascading for Hadoop

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Simplicity is about living life with more enjoyment and less pain
- John Maeda
https://www.ted.com/speakers/john_maeda

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There are also other Clojure tools
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Flambo – Clojure DSL for Apache Spark
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http://riemann.io/ - Monitors Distributed System
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...

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Thanks!
Questions?