Order this unique Training E-Learning course Apache Spark Advanced Topics online, 1 year 24/7 access to rich interactive videos and tests.
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Product description
Apache Spark Advanced Topics E-Learning
Order this unique E-Learning course today! ✔️ 1 year 24/7 access to rich interactive videos with voice support. ✔️ Includes progress monitoring via reporting tests to immediately test your knowledge.
Why choose this course?
Apache Spark is a powerful open-source framework that provides advanced big data analytics capabilities combined with speed and ease of use. This course focuses on the advanced features of Spark, allowing you to:
Learn to understand and apply Spark Core better.
Spark Streaming mastered for real-time data analysis.
Used Spark SQL to manage and query data at scale.
Gain knowledge of MLlib for machine learning, GraphX for graph computation, and SparkR for data science.
This training combines theory and practice to take your skills to the next level, ideal for professionals who want to tackle complex big data challenges.
Who should participate?
This course is perfect for:
Big data analysts who want to expand their knowledge with advanced Spark capabilities.
Data scientists who want to integrate machine learning and graph applications.
Software developers who want to build optimized big data solutions.
IT professionals who need a deeper understanding of Spark functionality.
Demo Apache Spark Advanced Topics Training
Course content
Spark RDDs
Course: 1 Hour, 13 Minutes
Course Introduction
Review of Spark Stack
Defining Lazy Evaluation
Examining RDD Lineage
Pre-partitioning RDDs
Storing RDDs in Serialized Form
Performing Numeric Operations
Creating Custom Accumulators
Optimizing Broadcasts
Piping to External Applications
Tuning Garbage Collection
Performing Batch Importing
Determining Memory Consumption
Tuning Data Structures
Minimizing Memory Usage of Reduce Tasks
Setting the Levels of Parallelism
Data Frames and Spark SQL
Course: 43 Minutes
Creating DataFrames
Interoperating with RDDs
Examining the Load and Save Functions
Reading and Writing Parquet Files
Using JSON Dataset as a DataFrame
Reading and Writing Data in Hive Tables
Reading and Writing Data Using JDBC
Running Thrift JDBC/ODBC Server
Practice: Tuning Spark
Course: 9 Minutes
Exercise: Tuning Spark
Privacy and Cookie PolicyTerms of Use
Streaming Analytics
Course: 54 Minutes
Course Introduction
Examining Discretized Streams
Ingesting TCP Socket Input Streams
Reading File Input Streams
Receiving Akka Actor Input Streams
Consuming Kafka Input Streams
Ingesting Flume Input Streams
Setting Up Kinesis Input Streams
Configuring Twitter Input Streams
Implementing Custom Input Streams
Describing Receiver Reliability
Transformations on DStreams
Course: 1 Hour, 19 Minutes
Using UpdateStateByKey Operations
Performing Transform Operations
Performing Window Operations
Performing Join Operations
Using Output Operations on DStreams
Using Data Frames and SQL Operations
Using Learning Algorithms with MLlib
Persisting Stream Data in Memory
Enabling and Configuring Checkpointing
Deploying Applications
Monitoring Applications
Reducing Batch Processing Times
Performance Tuning
Course: 19 Minutes
Setting Batch Intervals
Tuning Memory Usage
Examining the Semantics of Fault Tolerance
Practice: Transformations on Dstreams
Course: 6 Minutes
Exercise: Perform Transformations on DStreams
Machine Learning with MLlib
Course: 1 Hour, 12 Minutes
Course Introduction
Describing Data Types
Examining Basic Statistics
Exploring Linear SVMs
Performing Logistic Regression
Using Naive Bayes
Creating Decision Trees
Using Collaborative Filtering with ALS
Clustering with K-means
Clustering with Latent Dirichlet Allocation (LDA)
Analyzing with Frequent Pattern Mining
GraphX
Course: 57 Minutes
Examining the Property Graph
Exploring the Graph Operators
Performing Analytics with Neighborhood Aggregation
Messaging with Pregel API
Building Graphs
Examining Vertex and Edge RDDs
Optimizing Representation Through Partitioning
Measuring Vertices with PageRank
R and Spark
Course: 37 Minutes
Installing SparkR
Running SparkR
Using Existing R Packages
Exposing RDDs as Distributed Lists
Interoperating with DataFrames
Using Parquet Files
Running on a Cluster
Practice: Use MLlib
Course: 10 Minutes
Exercise: Use MLlib
Get started today!
✔️ Learn advanced techniques to effectively tackle big data challenges. ✔️ Gain access to a comprehensive interactive learning experience. ✔️ Test and track your progress with reports and exercises.
Order your course now and become an expert in Apache Spark Advanced Topics!
Specifications
Article number
107752732
SKU
107752732
Language
English
Qualifications of the Instructor
Certified
Course Format and Length
Teaching videos with subtitles, interactive elements and assignments and tests
Lesson duration
7:42 Hours
Progress monitoring
Access to Material
365 days
Technical Requirements
Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge.
Support or Assistance
Helpdesk and online knowledge base 24/7
Certification
Certificate of participation in PDF format
Price and costs
Course price at no extra cost
Cancellation policy and money-back guarantee
We assess this on a case-by-case basis
Award Winning E-learning
Tip!
Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform.
Order this unique Training E-Learning course Apache Spark Advanced Topics online...
€180,29€149,00
Specifications
Article number
107752732
SKU
107752732
Language
English
Qualifications of the Instructor
Certified
Course Format and Length
Teaching videos with subtitles, interactive elements and assignments and tests
Lesson duration
7:42 Hours
Progress monitoring
Access to Material
365 days
Technical Requirements
Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge.
Support or Assistance
Helpdesk and online knowledge base 24/7
Certification
Certificate of participation in PDF format
Price and costs
Course price at no extra cost
Cancellation policy and money-back guarantee
We assess this on a case-by-case basis
Award Winning E-learning
Tip!
Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform.
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