Denny Lee

Data is bigger, arrives faster, and comes in a variety of formats and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark™.

Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through… Show more

Data is bigger, arrives faster, and comes in a variety of formats and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark™.

Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you'll be able to:

- Learn Python, SQL, Scala, or Java high-level Structured APIs
- Understand Spark operations and SQL Engine
- Inspect, tune, and debug Spark operations with Spark configurations and Spark UI
- Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka
- Perform analytics on batch and streaming data using Structured Streaming
- Build reliable data pipelines with open source Delta Lake and Spark
- Develop machine learning pipelines with MLlib and productionize models using MLflow Show less

It is estimated that in 2013 the whole world produced around 4.4 zettabytes of data; that is, 4.4 billion terabytes! By 2020, we (as a human race) are expected to produce ten times that. With data getting larger literally by the second there is a growing appetite for making sense out of it.

In our book, Learning PySpark, we will guide you through the latest incarnation of Apache Spark using Python. We will show you how to read structured and unstructured data, how to use some fundamental… Show more

It is estimated that in 2013 the whole world produced around 4.4 zettabytes of data; that is, 4.4 billion terabytes! By 2020, we (as a human race) are expected to produce ten times that. With data getting larger literally by the second there is a growing appetite for making sense out of it.

In our book, Learning PySpark, we will guide you through the latest incarnation of Apache Spark using Python. We will show you how to read structured and unstructured data, how to use some fundamental data types available in PySpark, how to build machine learning models, operate on graphs, read streaming data and deploy your models in the cloud. Each chapter will tackle different problem and by the end of the book we hope you will be knowledgeable enough to solve other problems we did not have space to cover here. Show less

Discover how to solve real-world BI problems by leveraging a slew of powerful new Analysis Services features and capabilities. These include the new DAX language, which is a more user-friendly version of MDX; PowerPivot & Power View, new tools for performing simplified & visual analysis of data; and much more.

Discover how to solve real-world BI problems by leveraging a slew of powerful new Analysis Services features and capabilities. These include the new DAX language, which is a more user-friendly version of MDX; PowerPivot & Power View, new tools for performing simplified & visual analysis of data; and much more.

This white paper describes how business intelligence developers can apply query and processing performance-tuning techniques to their Microsoft SQL Server 2008 R2 Analysis Services OLAP solutions.

Contributed to this article based on a specific case I worked at Microsoft that showcased issues with floating point percision in Analysis Services and best practices to avoid problems.

Contributed to this article based on a specific case I worked at Microsoft that showcased issues with floating point percision in Analysis Services and best practices to avoid problems.

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