Students who successfully complete this course will be able to: Understand Apache Spark’s architecture, job execution, and how techniques such as lazy execution and pipelining can improve runtime performance

This PySpark job will ingest daily logs for machine efficiency, ambient weather conditions and employee data. It will create two (2) Impala databases, HR and FACTORY with its corresponding tables. NOTE: Before running the job, we need to modify one (1) variable in ingest_CDE.py.

Install Anaconda on a Cloudera cluster to build and run Python based solutions easily across the cluster and alongside PySpark jobs. Leverage Anaconda For Distributed Data Science On Cloudera Give your data scientists the most popular Python packages they know and love while empowering your data science team to explore, build and deploy ...

Cloudera Certification provides the benchmark in verifying your proficiency with Cloudera Data Platform. Each role-based exam assesses your knowledge and skills in working with the Cloudera platform, from system administration to solution development to data analysis and more.

Optimize your time with detailed tutorials that clearly explain the best way to deploy, use, and manage Cloudera products.

Introduction to PySpark. How DataFrame Operations Become Spark Jobs. How Spark Executes a Job. Running a Spark Application. Running a Spark Application. Reading data into a Spark SQL DataFrame. Examining the Schema of a DataFrame. Computing the Number of Rows and Columns of a DataFrame. Examining a Few Rows of a DataFrame. Stopping a Spark ...

Download CDS 2.4 Release 2 Powered By Apache Spark™ The de facto processing engine for Hadoop. Apache Spark is the open standard for fast and flexible general purpose big-data processing, enabling batch, real-time, and advanced analytics on the Apache Hadoop platform.

CDS 3.3.2 Powered by Apache Spark The de facto processing engine for Data Engineering. Apache Spark is the open standard for fast and flexible general purpose big-data processing, enabling batch, real-time, and advanced analytics on the Apache Hadoop platform.

K-means Clustering Overview. Clustering is an unsupervised machine learning algorithm that performs the task of dividing the data into similar groups and helps to segregate groups with the similar data points into clusters.

Run Jobs using CLI . We can run a job immediately (ad-hoc), which is good for testing your application. Another option is to define a resource, which stores a collection of Python files or applications required for a job; great for running jobs periodically.