Cloudera Educational Services

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This course introduces Apache Iceberg, a high-performance open table format for organizing petabyte-scale analytic datasets on a file system or object store, available on Cloudera Data Warehouse and Cloudera Data Engineering on both Private and Public Cloud. Combined with Cloudera Data Platform, Iceberg can enable users to build an open data lakehouse architecture for multi-function analytics and to deploy large-scale end-to-end pipelines. This course covers various aspects of Apache Iceberg, such as benefits, architecture, internal operation, read and write operations, and advanced functions, all while drawing comparisons to Hive and building on the students’ existing knowledge and experience. DATE: 16th-19th July 2024 Virtual Classroom, AMER 9:00 - 17:00 CST Read more

About This Course In this video you will learn how Cloudera enables key hybrid capabilities like application portability, and data replication in order to quickly move workloads and data to the cloud. Let's explore how Cloudera Data Platform (CDP) excels at following hybrid use cases, through data pipeline replication and data pipeline migration exercises to the public cloud. Develop Once and Run Anywhere De-risk Cloud Migration This Course contains demonstrations showing how to add Private Base clusters as Classic Clusters and use CDP replication Manager to migrate HDFS data,Hive tables to the cloud Provider of your choice. This course includes 30 minutes of video content including demonstrations. Audience and Prerequisites This OnDemand course is suitable for CDP Administrators, data administrators, and data operators. Read more

Cloudera Data Platform (CDP) is a fully integrated edge to AI product set. Cloudera Manager is purposely built as the DevOps tooling for building and managing Cloudera Data Platform. This four-day hands-on course presents detailed explanation, comprehensive theory, key skills, and recommended practices for successful platform administration. Upon completion of this course a CDP Administrator will learn the full range of functionality and capability of Cloudera Manager in supporting Cloudera Data Platform. This course provides an in-depth explanation and skills to become highly productive with Cloudera Manager and Cloudera Data Platform. Cloudera Manager is a full featured and mature DevOps tool. It is used to install, configure, operate, troubleshoot, report, and upgrade CDP. Many CDP Administrators only use a fraction of the capabilities built into Cloudera Manager. This course teaches the architecture, deployment, configuration, logging, reporting, REST API, and much more. The course provides references for architecture and recommended practices used by enterprises around the globe Download full course description  What you'll learn This course teaches installation, configuration, operation, management, incident resolution, and troubleshooting of Cloudera Manager. What to expect This course is an entry point for aspiring CDP Administrators and any CDP Administrators not well familiar with the full range of Cloudera Manager capabilities. Students must have a background in Linux and knowledge of SQL. Students must have access to the Internet to reach the classroom environments, which are located on Amazon Web Services.   Read more

This four-day Analyzing with Data Warehouse course will teach you to apply traditional data analytics and business intelligence skills to big data. This course presents the tools data professionals need to access, manipulate, transform, and analyze complex data sets using SQL and familiar scripting languages. What you'll learn Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the ecosystem, learning how to: Use Apache Hive and Apache Impala to access data through queries Identify distinctions between Hive and Impala, such as differences in syntax, data formats, and supported features Write and execute queries that use functions, aggregate functions, and subqueries Use joins and unions to combine datasets Create, modify, and delete tables, views, and databases Load data into tables and store query results Select file formats and develop partitioning schemes for better performance Use analytic and windowing functions to gain insight into their data Store and query complex or nested data structures Process and analyze semi-structured and unstructured data Optimize and extend the capabilities of Hive and Impala Determine whether Hive, Impala, an RDBMS, or a mix of these is the best choice for a given task Utilize the benefits of CDP Public Cloud Data Warehouse What to expect This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Some knowledge of SQL is assumed, as is basic Linux command-line familiarity.   [DATE: Month START - END, YEAR] Virtual Classroom, [APAC, EMEA, AMER] 9:00 - 17:00 (TIMEZONE) Read more

This three-day hands-on training course delivers the key concepts and expertise developers need to improve the performance of their Apache Spark applications. During the course, participants will learn how to identify common sources of poor performance in Spark applications, techniques for avoiding or solving them, and best practices for Spark application monitoring. Apache Spark Application Performance Tuning presents the architecture and concepts behind Apache Spark and underlying data platform, then builds on this foundational understanding by teaching students how to tune Spark application code. The course format emphasizes instructor-led demonstrations illustrate both performance issues and the techniques that address them, followed by hands-on exercises that give students an opportunity to practice what they've learned through an interactive notebook environment. The course applies to Spark 2.4, but also introduces the Spark 3.0 Adaptive Query Execution framework.   Read more

This four-day hands-on training course delivers the key concepts and knowledge developers need to use Apache Spark to develop high-performance, parallel applications on the Cloudera Data Platform (CDP).  Hands-on exercises allow students to practice writing Spark applications that integrate with CDP core components. Participants will learn how to use Spark SQL to query structured data, how to use Hive features to ingest and denormalize data, and how to work with “big data” stored in a distributed file system. After taking this course, participants will be prepared to face real-world challenges and build applications to execute faster decisions, better decisions, and interactive analysis, applied to a wide variety of use cases, architectures, and industries. Download full course description  What you'll learn During this course, you will learn how to: Distribute, store, and process data in a CDP cluster Write, configure, and deploy Apache Spark applications Use the Spark interpreters and Spark applications to explore, process, and analyze distributed data Query data using Spark SQL, DataFrames, and Hive tables Deploy a Spark application on the Data Engineering Service What to expect This course is designed for developers and data engineers. All students are expected to have basic Linux experience, and basic proficiency with either Python or Scala programming languages. Basic knowledge of SQL is helpful.  Prior knowledge of Spark and Hadoop is not required. [DATE: Month START - END, YEAR] Virtual Classroom, [APAC, EMEA, AMER] 9:00 - 17:00 (TIMEZONE) Read more

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