Learn how to use ElasticSearch in combination with the rest of the Elastic Stack to ship, parse, store, and analyze logs! You’ll start by getting an understanding of what ElasticSearch is, what it’s used for, and why it’s important before being introduced to the new features of Elastic Search 5.0.
- Access 35 lectures & 3 hours of content 24/7
- Go through each of the fundamental concepts of ElasticSearch such as queries, indices, & aggregation
- Add more power to your searches using filters, ranges, & more
- See how ElasticSearch can be used w/ other components like LogStash, Kibana, & Beats
- Build, test, & run your first LogStash pipeline to analyze Apache web logs
Apache Spark is one of the most widely-used large-scale data processing engines and runs at extremely high speeds. It’s a framework that has tools that are equally useful for app developers and data scientists. This book starts with the fundamentals of Spark 2 and covers the core data processing framework and API, installation, and application development setup.
- Access 45 lectures & 5.5 hours of content 24/7
- Learn the Spark programming model through real-world examples
- Explore Spark SQL programming w/ DataFrames
- Cover the charting & plotting features of Python in conjunction w/ Spark data processing
- Discuss Spark’s stream processing, machine learning, & graph processing libraries
- Develop a real-world Spark application
Amazon Web Services (AWS) provides trusted, cloud-based solutions to help businesses meet all of their needs. Running solutions in the AWS Cloud can help you (or your company) get applications up and running faster while providing the security needed to meet your compliance requirements. This course leaves no stone unturned in getting you up to speed with administering AWS.
- Access 19 lectures & 2 hours of content 24/7
- Familiarize yourself w/ the key capabilities to architect & host apps, websites, & services on AWS
- Explore the available options for virtual instances & demonstrate launching & connecting to them
- Design & deploy networking & hosting solutions for large deployments
- Focus on security & important elements of scalability & high availability
Businesses today have access to more data than ever before, and a key challenge is ensuring that data can be easily accessed and used efficiently. MongoDB makes it possible to store and process large sets of data in a ways that drive up business value. Learning MongoDB will give you the flexibility of unstructured storage, combined with robust querying and post processing functionality, making you an asset to enterprise Big Data needs.
- Access 64 lectures & 40 hours of content 24/7
- Master data management, queries, post processing, & essential enterprise redundancy requirements
- Explore advanced data analysis using both MapReduce & the MongoDB aggregation framework
- Delve into SSL security & programmatic access using various languages
- Learn about MongoDB’s built-in redundancy & scale features, replica sets, & sharding
Hadoop emerged in response to the proliferation of masses and masses of data collected by organizations, offering a strong solution to store, process, and analyze what has commonly become known as Big Data. It comprises a comprehensive stack of components designed to enable these tasks on a distributed scale, across multiple servers and thousand of machines. In this course, you’ll learn Hadoop 2, introducing yourself to the powerful system synonymous with Big Data.
- Access 19 lectures & 1.5 hours of content 24/7
- Get an overview of the Hadoop component ecosystem, including HDFS, Sqoop, Flume, YARN, MapReduce, Pig, & Hive
- Install & configure a Hadoop environment
- Explore Hue, the graphical user interface of Hadoop
- Discover HDFS to import & export data, both manually & automatically
- Run computations using MapReduce & get to grips working w/ Hadoop’s scripting language, Pig
- Siphon data from HDFS into Hive & demonstrate how it can be used to structure & query data sets
ElasticSearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. Through this ebook, you’ll be guided through comprehensive recipes covering what’s new in ElasticSearch 5.x as you create complex queries and analytics. By the end, you’ll have an in-depth knowledge of how to implement the ElasticSearch architecture and be able to manage data efficiently and effectively.
- Access 696 pages of content 24/7
- Perform index mapping, aggregation, & scripting
- Explore the modules of Cluster & Node monitoring
- Understand how to install Kibana to monitor a cluster & extend Kibana for plugins
- Integrate your Java, Scala, Python, & Big Data apps w/ ElasticSearch
Compared to Hadoop, Spark is a significantly more simple way to process Big Data at speed. It is increasing in popularity with data analysts and engineers everywhere, and in this course you’ll learn how to use Spark with minimum fuss. Starting with the fundamentals, this ebook will help you take your Big Data analytical skills to the next level.
- Access 274 pages of content 24/7
- Get to grips w/ some simple APIs before investigating machine learning & graph processing
- Learn how to use the Spark shell
- Load data & build & run your own Spark applications
- Discover how to manipulate RDD
- Understand useful machine learning algorithms w/ the help of Spark MLlib & R
MongoDB is a high-performance, feature-rich, NoSQL database that forms the backbone of the systems that power many organizations. Packed with easy-to-use features that have become essential for a variety of software professionals, MongoDB is a vital technology to learn for any aspiring data scientist or systems engineer. This cookbook contains many solutions to the everyday challenges of MongoDB, as well as guidance on effective techniques to extend your skills and capabilities.
- Access 274 pages of content 24/7
- Initialize the server in three different modes w/ various configurations
- Get introduced to programming language drivers in Java & Python
- Learn advanced query operations, monitoring, & backup using MMS
- Find recipes on cloud deployment, including how to work w/ Docker containers along MongoDB
Apache Kafka is simple describe at a high level bust has an immense amount of technical detail when you dig deeper. This step-by-step, practical guide will help you take advantage of the power of Kafka to handle hundreds of megabytes of messages per second from multiple clients.
- Access 120 pages of content 24/7
- Set up Kafka clusters
- Understand basic blocks like producer, broker, & consumer blocks
- Explore additional settings & configuration changes to achieve more complex goals
- Learn how Kafka is designed internally & what configurations make it most effective
- Discover how Kafka works w/ other tools like Hadoop, Storm, & more
Apache Flume is a distributed, reliable, and available service used to efficiently collect, aggregate, and move large amounts of log data. It’s used to stream logs from application servers to HDFS for ad hoc analysis. This ebook start with an architectural overview of Flume and its logical components, and pulls everything together into a real-world, end-to-end use case encompassing simple and advanced features.
- Access 178 pages of content 24/7
- Explore channels, sinks, & sink processors
- Learn about sources & channels
- Construct a series of Flume agents to dynamically transport your stream data & logs from your systems into Hadoop
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