Cloudera Educational Services

About This Course The Cloudera Operational Database Fundamentals course provides an overview of what an operational database (OpDb) is, the motivation and use cases behind using an OpDb in the enterprise, and how an OpDb fits within the data lifecycle. The course describes the operational database capabilities available in the various form factors, including CDP Private Cloud and CDP Public Cloud, and how to work with an OpDb from the shell, a SQL client, and programmatically in code. Course Length This module includes 1.5 hours of video content. There are no hands-on exercises. Audience and Prerequisites This course is designed for managers, administrators, and developers. We highly recommend that participants be familiar with CDH, HDP, CDP Private Cloud, or CDP Public Cloud to be able to set up an operational database. The CDP Public Cloud Administration and CDP Private Cloud Fundamentals trainings are good starting points to prepare for this training.  Additionally, knowledge of Python is required for using Thrift and knowledge of Java for working with the HBase API. Basic Linux knowledge is required which includes the ability to SSH into a node and starting up a CLI. Knowledge of Apache HBase and Apache Phoenix is not required. Read more

About This Module During this series, Mark Payne, a Principal Software Engineer at Cloudera and co-creator of Apache NiFi, will explain several common ways that people use NiFi incorrectly or inefficiently. After explaining the weaknesses of each approach, Mark then shows how to improve those flows to make better use of NiFi's design and architecture.   Part 1: Flows Overview examines a flow that splits and rejoins data, treats structured/semi-structured data as unstructured text, and blurs the line between FlowFile content and attributes. Part 2: Flow Layout illustrates how a disorganized dataflow can make it difficult to understand and maintain. Mark shares tips for laying out the dataflow to make it clean, simple, and easy for others to follow. Part 3: Load Balancing explains how to make your dataflows more scalable by balancing the load across a cluster of nodes. Mark also references his Cloudera technical blog post that shows how NiFi can process more than one billion events per second. Part 4: Scheduling covers scheduling and concurrency anti-patterns. Mark discusses common problems related to thread pools, scheduling processors, and how to configure settings for best performance. Part 5: Primary Node Only looks at the primary node and how it is sometimes misused. Please note: This course does not award a course completion certificate. Module Length This course includes 1 hour of video content.   Read more

About This Module This module introduces the Cloudera Machine Learning (CML) experience on CDP. Module Length This module includes one hour of video content. Audience and Prerequisites This course is ideal for anyone who wants to understand the capabilities of the Cloudera Machine Learning experience and how to navigate in the CML workbench interface. A Note about This Free Course This course is a free introduction to CML.  The regular (paid) version of this course is Cloudera Machine Learning Training. The course begins with these same five chapters, but it continues to provide much more in-depth training, using either Python or R. If you're interested in learning more, please take a look at that course in our store! (Note that the regular course is available only through the Full OnDemand Library subscription.) Read more

By purchasing and enrolling in this course, you will have access for one year to all our OnDemand training content. That includes the following courses, along with any new courses we add during your subscription. Before you purchase, you can find descriptions of these courses in our store. Please note: You might not be able to access your courses immediately; the system can take up to  30 minutes after purchase is complete to process the new subscription. Please be patient for this process. Administrator Training: CDP Private Cloud Base Apache NiFi Anti-Patterns AWS Fundamentals for CDP Public Cloud CDP Data Governance with SDX: Implementing Regulatory Compliance on the Cloudera Data Platform CDP Data Visualization Training CDP Public Cloud Administration Cloudera Data Analyst Training Cloudera Data Platform: CDP for CDH Administrators Cloudera Data Platform: CDP for HDP Administrators Cloudera Data Science Workbench Training Cloudera DataFlow: Flow Management with Apache NiFi Cloudera Essentials for CDP Cloudera Machine Learning Training Cloudera Operational Database Fundamentals Cloudera Search Training Cloudera Training for Apache HBase Data Warehousing in Cloudera Data Platform Developer Training for Apache Spark and Hadoop Introduction to Apache Kudu Introduction to Cloudera Data Warehouse: Self-Service Analytics in the Cloud with CDP Introduction to Cloudera Machine Learning Just Enough Git Just Enough Python Just Enough Scala Streaming Processing, Management, and Analytics with CDF, including: Cloudera DataFlow: Data-in-Motion Overview Apache Kafka Basics Developing Apache Kafka Client Applications with Java   Cloudera Streams Messaging Manager Cloudera Schema Registry Managing Apache Kafka Clusters with Cloudera Manager Cloudera Kafka Security Apache Kafka Connect Read more

Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription.  About This Course Cloudera University’s Search training course is for developers and data engineers who want to index data in Hadoop for more powerful real-time queries. Participants will learn to get more value from their data by integrating Cloudera Search with external applications. Course Length This course includes 6 hours of video instruction. Hands-on exercises may take 5 to 10 hours; there is an additional (optional) 5 hours of exercise review videos. Audience and Prerequisites This course is intended for developers and data engineers with at least basic familiarity with Hadoop and experience programming in a general-purpose language such as Java, C, C++, Perl, or Python. Participants should be comfortable with the Linux command line and should be able to perform basic tasks such as creating and removing directories, viewing and changing file permissions, executing scripts, and examining file output. No prior experience with Apache Solr or Cloudera Search is required, nor is any experience with HBase or SQL. Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription.  Read more

Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription.  About This Course Cloudera University’s training course for Apache HBase enables participants to store and access massive quantities of multi-structured data and perform hundreds of thousands of operations per second. Apache HBase is a distributed, scalable, NoSQL database built on Apache Hadoop. HBase can store data in massive tables consisting of billions of rows and millions of columns, serve data to many users and applications in real time, and provide fast, random read/write access to users and applications. Course Length This course includes 6.5 hours of video content. Hands-on exercises may take approximately 9 hours. Audience and Prerequisites This course is appropriate for developers and administrators who intend to use HBase. Prior experience with databases and data modeling is helpful, but not required. Knowledge of Java is assumed. Prior knowledge of Hadoop is not required, but Cloudera Developer for Apache Spark and Hadoop provides an excellent foundation for this course. Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription.  Read more