What is Spark ?
Spark is a fast, scalable,general purpose engine for large scale data processing.
- Written in Scala: Functional programming language that runs on top of JVM.
Spark comes in multiple flavours :
- Spark Shell(Python or Scala) : Interactive data processing / exploration
- Spark Applications: For large scale data processing needs.
Why Spark ?
Spark Context
- Main entry point to the Spark API.
- Spark shell provides a preconfigured Spark context called ‘sc’
Spark RDD (Resilient Distributed Dataset)
RDD are fundamental unit of data in Spark. Most of the processing in Spark is done on RDDs. RDD are immutable which allows : Consistency,Concurrency,Easy & deterministic recreation.
- Resilient : If data in memory is lost, it can be recreated.
- Distributed : Processed accross the cluster
- Dataset : holds data which may come from hetrogenous sources (like file,database etc.) or created programmatically.
Spark MLlib
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What is Spark MLlib ?
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Why you should be using Spark MLlib ?
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How ?
Spark Streaming
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What is Spark Streaming ?
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An extension of core Spark.
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Provides capability for real-time processing of streaming data.
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Use cases : Continous ETL , Website Monitoring , Fraud detection , Ad monetization , Social media analysis , Financial market trends
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Why you should be using Spark Streaming ?
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Integrates batch and real-time processing
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Easy to develop : uses Spark’s high level API
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“Once and only once” processing
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Second-scale latencies
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Scalability and efficient fault tolerance
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How ?
- Divide data stream into batches of n seconds
- Called a Dstream (Discretized Stream)
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Process each batch in Spark as an RDD
- Return results of RDD operations in batches
Spark GraphX
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What is Spark GraphX ?
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Why you should be using Spark GraphX ?
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How ?