コース概要

Introduction

SMACK Stack Overview

  • What is Apache Spark? Apache Spark features
  • What is Apache Mesos? Apache Mesos features
  • What is Apache Akka? Apache Akka features
  • What is Apache Cassandra? Apache Cassandra features
  • What is Apache Kafka? Apache Kafka features

Scala Language

  • Scala syntax and structure
  • Scala control flow

Preparing the Development Environment

  • Installing and configuring the SMACK stack
  • Installing and configuring Docker

Apache Akka

  • Using actors

Apache Cassandra

  • Creating a database for read operations
  • Working with backups and recovery

Connectors

  • Creating a stream
  • Building an Akka application
  • Storing data with Cassandra
  • Reviewing connectors

Apache Kafka

  • Working with clusters
  • Creating, publishing, and consuming messages

Apache Mesos

  • Allocating resources
  • Running clusters
  • Working with Apache Aurora and Docker
  • Running services and jobs
  • Deploying Spark, Cassandra, and Kafka on Mesos

Apache Spark

  • Managing data flows
  • Working with RDDs and dataframes
  • Performing data analysis

Troubleshooting

  • Handling failure of services and errors

Summary and Conclusion

要求

  • An understanding of data processing systems

Audience

  • Data Scientists
 14 時間

参加者の人数



Price per participant

お客様の声 (1)

関連コース

Kaggle

14 時間

Accelerating Python Pandas Workflows with Modin

14 時間

GPU Data Science with NVIDIA RAPIDS

14 時間

Anaconda Ecosystem for Data Scientists

14 時間

Python and Spark for Big Data (PySpark)

21 時間

Introduction to Graph Computing

28 時間

Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

21 時間

Apache Spark MLlib

35 時間

Introduction to Data Science and AI using Python

35 時間

Big Data Business Intelligence for Telecom and Communication Service Providers

35 時間

A Practical Introduction to Data Science

35 時間

Data Science Programme

245 時間

Data Science for Big Data Analytics

35 時間

Data Science essential for Marketing/Sales professionals

21 時間

F# for Data Science

21 時間

関連カテゴリー