Apache Spark Training Courses

Apache Spark Training

Apache Spark - an engine for big data processing training

Apache Spark Course Outlines

ID Name Duration Overview
566826 Spark for Developers 21 hours OBJECTIVE: This course will introduce Apache Spark. The students will learn how  Spark fits  into the Big Data ecosystem, and how to use Spark for data analysis.  The course covers Spark shell for interactive data analysis, Spark internals, Spark APIs, Spark SQL, Spark streaming, and machine learning and graphX. AUDIENCE : Developers / Data Analysts Scala primer A quick introduction to Scala Labs : Getting know Scala Spark Basics Background and history Spark and Hadoop Spark concepts and architecture Spark eco system (core, spark sql, mlib, streaming) Labs : Installing and running Spark First Look at Spark Running Spark in local mode Spark web UI Spark shell Analyzing dataset – part 1 Inspecting RDDs Labs: Spark shell exploration RDDs RDDs concepts Partitions RDD Operations / transformations RDD types Key-Value pair RDDs MapReduce on RDD Caching and persistence Labs : creating & inspecting RDDs;   Caching RDDs Spark API programming Introduction to Spark API / RDD API Submitting the first program to Spark Debugging / logging Configuration properties Labs : Programming in Spark API, Submitting jobs Spark SQL SQL support in Spark Dataframes Defining tables and importing datasets Querying data frames using SQL Storage formats : JSON / Parquet Labs : Creating and querying data frames; evaluating data formats Mlib mlib intro mlib algorithms Labs : Writing mlib applications GraphX GraphX library overview GraphX APIs Labs : Processing graph data using Spark Spark Streaming Streaming overview Evaluating Streaming platforms Streaming operations Sliding window operations Labs : Writing spark streaming applications Spark and Hadoop Hadoop Intro (HDFS / YARN) Hadoop + Spark architecture Running Spark on Hadoop YARN Processing HDFS files using Spark Spark Performance and Tuning Broadcast variables Accumulators Memory management & caching Spark Operations Deploying Spark in production Sample deployment templates Configurations Monitoring Troubleshooting
359602 Apache Spark 14 hours Why Spark? Problems with Traditional Large-Scale Systems Introducing Spark Spark Basics What is Apache Spark? Using the Spark Shell Resilient Distributed Datasets (RDDs) Functional Programming with Spark Working with RDDs RDD Operations Key-Value Pair RDDs MapReduce and Pair RDD Operations The Hadoop Distributed File System Why HDFS? HDFS Architecture Using HDFS Running Spark on a Cluster Overview A Spark Standalone Cluster The Spark Standalone Web UI Parallel Programming with Spark RDD Partitions and HDFS Data Locality Working With Partitions Executing Parallel Operations Caching and Persistence RDD Lineage Caching Overview Distributed Persistence Writing Spark Applications Spark Applications vs. Spark Shell Creating the SparkContext Configuring Spark Properties Building and Running a Spark Application Logging Spark, Hadoop, and the Enterprise Data Center Overview Spark and the Hadoop Ecosystem Spark and MapReduce Spark Streaming Spark Streaming Overview Example: Streaming Word Count Other Streaming Operations Sliding Window Operations Developing Spark Streaming Applications Common Spark Algorithms Iterative Algorithms Graph Analysis Machine Learning Improving Spark Performance Shared Variables: Broadcast Variables Shared Variables: Accumulators Common Performance Issues

Course Discounts

Course Venue Course Date Course Price [Remote/Classroom]
Perl Programming Bern Wed, 2016-08-10 09:30 2653EUR / 3303EUR
Excel Advanced with VBA Basel Mon, 2016-10-24 09:30 1500EUR / 2150EUR
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