Before thinking about what is the outcome of data science, maybe I should take the two seconds I think it takes to define it. As how to define data science, […]
Spark in Action’s Chapter Eleven on Working with SQL is in MEAP
A new chapter of Spark in Action, 2e, (formerly known as Spark with Java) is available. Chapter 11 is titled “Working with SQL”. In chapter 11, you will explore how […]
(Almost) All you need to know about file ingestion in Apache Spark
As you may know, I start writing Apache Spark with Java (now renamed Spark in Action, 2nd edition). Usually, as the book develops, authors share a few excerpt of the book […]
Eight very hot data trends for 2019
Read about eight very hot predictions for data management in 2019, in usages, shapes, governance, and people.
What is Apache Spark, the podcast
A couple of weeks ago, I chatted about Apache Spark with Tobias Macey on data engineering on more specifically Apache Spark. Tobias Macey runs the data engineering podcast, which you can directly […]
Checklist for All Things Open (ATO)
The checklist is updated for ATO 2019! All Things Open 2018 (ATO 2018), a premier open source conference, will open its doors on October 21st 2018 in the Raleigh Convention Center, […]
Microsoft SQL Server 2019 gets a Spark
Yesterday, during Ignite 2018, Microsoft announced that they will integrate Apache Spark more tightly with SQL Server 2019. If you missed previous announcements around SQL Server, it now runs on […]
Lazy is good: understand why it’s good for you that Spark is lazy
This new chapter, chapter 4, of Spark with Java (https://www.manning.com/books/spark-with-java) is not only about celebrating laziness, it also teaches, through examples and experiments, the fundamental differences in building a data […]
The majestic dataframe in Apache Spark
Chapter 3 of Spark with Java is focusing on the dataframe. There is something majestic with Apache Spark’s dataframe, like those mountains of Montana. Apache Spark revolves around the concept of […]
Advanced Spark Ingestion
Chapter 9 still covers Spark ingestion (like chapter 7 and chapter 8), but this time, it’s about “anything can become a Spark datasource.” When I was working for Zaloni, we […]