Big data Processing with Apache Spark & Scala
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This document discusses an introduction to processing big data with Scala and Spark. It provides an overview of objectives which include explaining what big data, Spark, and Scala are and why they are useful tools. It also summarizes Spark's ecosystem of tools and provides a brief introduction to getting started with Spark.
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[Please copy the link and paste it into any web browser to access the content.]
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- 2. Objectives of this Session What is Big Data? What is Spark? Why Spark? Spark Ecosystem A note about Scala Why Scala? Hello Spark! For Queries during the session and class recording: Post on Twitter @edurekaIN: #askEdureka Post on Facebook /edurekaIN Slide 2 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 3. Big Data Lots of Data (Terabytes or Petabytes) Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization cloud tools statistics No SQL Big Data compression support database storage analyze information mobile processing terabytes Slide 3 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 4. What is Spark? Apache Spark is a general-purpose cluster in-memory computing system Provides high-level APIs in Java, Scala and Python, and an optimized engine that supports general execution graphs Provides various high level tools like Spark SQL for structured data processing, Mlib for Machine Learning and more.. High Level APIs High Level Tools More… Slide 4 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 5. Why Spark? via YARN Cluster Manager The Spark framework can be deployed through Apache Mesos, Apache Hadoop via Yarn, or Spark’s own cluster manager. Deployment Slide 5 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 6. Why Spark? Spark framework is polyglot – Can be programmed in several programming languages (Currently Scala, Java and Python supported). Polyglot Scala Slide 6 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 7. Why Spark? A fully Apache Hive compatible data warehousing system that can run 100x faster than Hive. 100x faster than for certain applications. Slide 7 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 8. Why Spark? Provides powerful caching and disk persistence capabilities Interactive Data Analysis Faster Batch Iterative Algorithms Real-Time Stream Processing Faster Decision-Making Slide 8 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 9. Spark Community is Super Active! Slide 9 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 10. Spark Ecosystem MLLib (Machine learning) Spark Core Engine Aplha/Pre-alpha BlindDB (Approximate SQL) Shark (SQL) Spark Streaming (Streaming) GraphX (Graph Computation) SparkR (R on Spark) Slide 10 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 11. Spark Ecosystem (Contd.) An approximate query engine. To run over Core Spark Engine. Used for structured data. Can run unmodified hive queries on existing Hadoop deployment. MLLib (Machine learning) Enables analytical and interactive apps for live streaming data. Spark Core Engine Aplha/Pre-alpha BlindDB (Approximate SQL) Shark (SQL) Spark Streaming (Streaming) Graph Computation engine. (Similar to Giraph) GraphX (Graph Computation) Package for R language to enable R-users to leverage Spark power from R shell. SparkR (R on Spark) Machine learning library being built on top of Spark. Provision for support to many machine learning algorithms with speeds upto 100 times faster than Map-Reduce. Slide 11 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 12. A Note on Scala Scala is a general-purpose programming language designed to express common programming patterns in a concise, elegant, and type-safe way Scala supports both Object Oriented Programming and Functional Programming Scala is very much in fabric of present and Future Big Data frameworks like Scalding, Spark, Akka » All examples of Spark in class will be covered in Scala » Scala would be covered before Spark coverage as part of course! Slide 12 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 13. Why Scala? Scala is a pure object-oriented language. Conceptually, every value is an object and every operation is a method-call. The language supports advanced component architectures through classes and traits Scala is also a functional language. Supports functions, immutable data structures and preference for immutability over mutation Seamlessly integrated with Java Being used heavily for future Big data and we developments frameworks like Spark, Akka, Scalding, Play etc Slide 13 Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions www.edureka.co/apache-spark-scala-training
- 14. Hello Spark! Hello Spark! Slide 14 www.Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions edureka.co/apache-spark-scala-training
- 15. Questions? Buy Spark Course at : www.edureka.co Slide 15 www.edureka.Twitter @edurekaIN, Facebook /edurekaIN, use #askEdureka for Questions co/apache-spark-scala-training