Apache Spark 2

Build efficient data flow and machine learning programs with this flexible multi-functional open-source cluster-computing frameworkKey FeaturesMaster the art of real-time big data processing and machine learning Explore a wide range of use-cases to analyze large data Discover ways to optimize your work by using many features of Spark 2.x and ScalaBook DescriptionApache Spark is an in-memory cluster-based data processing system that provides a wide range of functionalities such as big data processing analytics machine learning and more. With this Learning Path you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform.You will work with the different modules in Apache Spark such as interactive querying with Spark SQL using DataFrames and datasets implementing streaming analytics with Spark Streaming and applying machine learning and deep learning techniques on Spark using MLlib and various external tools.By the end of this elaborately designed Learning Path you will have all the knowledge you need to master Apache Spark and build your own big data processing and analytics pipeline quickly and without any hassle.This Learning Path includes content from the following Packt products:Mastering Apache Spark 2.x by Romeo KienzlerScala and Spark for Big Data Analytics by Md. Rezaul Karim Sridhar AllaApache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi Meenakshi Rajendran Broderick Hall Shuen MeiCookbookWhat you will learnGet to grips with all the features of Apache Spark 2.xPerform highly optimized real-time big data processing Use ML and DL techniques with Spark MLlib and third-party toolsAnalyze structured and unstructured data using SparkSQL and GraphXUnderstand tuning debugging and monitoring of big data applications Build scalable and fault-tolerant streaming applications Develop scalable recommendation enginesWho this book is forIf you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path you must know the fundamentals of Apache Spark and Scala. About the Author Romeo Kienzler works as the chief data scientist in the IBM Watson IoT worldwide team helping clients to apply advanced machine learning at scale on their IoT sensor data. He holds a Master's degree in computer science from the Swiss Federal Institute of Technology Zurich with a specialization in information systems bioinformatics and applied statistics.Md. Rezaul Karim is a researcher author and data science enthusiast with a strong computer science background coupled with 10 years of research and development experience in machine learning deep learning and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning knowledge graphs and explainable artificial intelligence (XAI). Currently he is working as a research scientist at Fraunhofer FIT Germany. He is also a PhD candidate at RWTH Aachen University Germany. Before joining FIT he worked as a researcher at the Insight Centre for Data Analytics Ireland. Previously he worked as a lead software engineer at Samsung Electronics Korea.Sridhar Alla is a big data expert helping companies solve complex problems in distributed computing large scale data science and analytics practice. He holds a bachelor's in computer science from JNTU India. He loves writing code in Python Scala and Java. He also has extensive hands-on knowledge of several Hadoop-based technologies