davidjhon21 Posted June 20, 2017 Report Share Posted June 20, 2017 21st Century Software Solutions Private Limited is the best Online Training providers worldwide with real time experts: Course Outline: Describe Features of Apache Spark How Spark fits in Big Data ecosystem Why Spark & Hadoop fit together Define Spark Components Driver Program Spark Context Cluster Manager Worker Executor Task Spark RDD Spark Context Spark Libraries Load data into Spark Different data sources and formats HDFS Amazon S3 Local File System Text JSON CSV Sequence File Create & Use RDD, Data Frames Apply dataset operations to Resilient Distributed Datasets Transformation Actions Cache Intermediate RDD Lineage Graph Lazy Evaluation Use Spark DataFrames for simple queries Create Data Frame Spark Interactive shell (Scala & Python) Spark SQL Define different ways to run your application Build and launch a standalone application Spark Program Life Cycle Function of Spark Context Different Way to Launch Spark Application Local Standalone Hadoop YARN Apache Mesos Launch Spark Application Spark-Submit Monitor the Spark Job Describe & Create pair RDD Key-Value pair Apache Spark vs Apache Hadoop MapReduce Create RDD from existing non-pair RDD Create pair RDD by loading certain formats Create pair RDD from in-memory collection of pairs Apply Operations on pair RDD Group ByKey Reduce ByKey Other Transformations Joins Control partitioning across nodes RDD Partition Types of Partition Hash Partitioning Range Partitioning Benefit of Partitioning Best Practices More on Data Frames Explore Data in DataFrames Create UDFs (user define functions) UDF with Scala DSL UDF with SQL Repartition Data Frames. Infer Schema by Reflection DataFrame from database table DataFrame from JSON Monitor Apache Spark Applications Spark Execution Model Debug and Tune Spark Applications Identify Spark Unified Stack Components Spark SQL Spark Streaming Spark MLib Spark GraphX Benefits of Apache Spark over Hadoop Ecosystem Describe Spark Data pipeline Use Cases Spark Streaming Architecture Dstream and a spark streaming application Define Use Case (Time Series Data) Basic Steps Save Data to HBase Operations on DStream Transformations Data Frame and SQL Operations Define Windowed Operation Sliding Window Windowed Computation Window based Transformation Window Operations Fault tolerance of streaming applications Fault Tolerance in Spark Streaming Fault Tolerance in Spark RDD Check pointing Describe Graph X Define Regular, Directed, and property graphs Create a Property Graph Perform Operations on Graphs Describe Apache Spark MLib Describe the Machine Learning Techniques Classifications Clustering Collaborative Filtering Use Collaborative filtering to predict user choice Scala Introduction A first example Expressions and Simple Functions First Class function Classes and Objects Case classes and Pattern matching Generic types and methods Lists For- Comprehension Mutable State Computing with Streams Lazy Values Implicit Parameters and Conversions Handley / Milner type Interface Abstraction for concurrency Quote Link to comment Share on other sites More sharing options...
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