Presented By O'Reilly and Cloudera
Make Data Work
Dec 4–5, 2017: Training
Dec 5–7, 2017: Tutorials & Conference
Singapore

Architecting a next-generation data platform

Jonathan Seidman (Cloudera), Ted Malaska (Blizzard Entertainment)
1:30pm5:00pm Tuesday, December 5, 2017
Data engineering and architecture
Location: 308/309 Level: Intermediate

Who is this presentation for?

  • Software engineers, software architects, technical leads, project managers, and data engineers

Prerequisite knowledge

  • An understanding of Hadoop concepts and the Hadoop ecosystem, traditional data management systems (e.g., relational databases), and programming languages and concepts

What you'll learn

  • Discover how new and existing tools in the Hadoop ecosystem can be integrated to implement new types of data processing and analysis
  • Learn considerations and best practices for implementing these applications

Description

Rapid advancements are causing a dramatic evolution in both the storage and processing capabilities in the open source big data software ecosystem. These advancements include projects like:

  • Apache Kudu, a modern columnar data store that complements HDFS and Apache HBase by offering efficient analytical capabilities and fast inserts and updates with Hadoop;
  • Apache Kafka, which provides a high-throughput and highly reliable distributed message transport;
  • Apache Impala (incubating), a highly concurrent, massively parallel processing query engine for Hadoop;
  • Apache Spark, which is rapidly replacing frameworks such as MapReduce for processing data on Hadoop due to its efficient design and optimized use of memory. Spark components such as Spark Streaming and Spark SQL provide powerful near real-time processing.

Along with the Apache Hadoop platform, these storage and processing systems provide a powerful platform to implement data processing applications on batch and streaming data. While these advancements are exciting, they also add a new array of tools that architects and developers need to understand when architecting solutions with Hadoop.

Using Customer 360 and the IoT as examples, Jonathan Seidman and Ted Malaska explain how to architect a modern, real-time big data platform leveraging recent advancements in the open source software world, using components like Kafka, Impala, Kudu, Spark Streaming, and Spark SQL with Hadoop to enable new forms of data processing and analytics. Along the way, they discuss considerations and best practices for utilizing these components to implement solutions, cover common challenges and how to address them, and provide practical advice for building your own modern, real-time big data architectures.

Topics include:

  • Accelerating data processing tasks such as ETL and data analytics by building near real-time data pipelines using tools like Kafka, Spark Streaming, and Kudu
  • Building a reliable, efficient data pipeline using Kafka and tools in the Kafka ecosystem such as Kafka Connect and Kafka Streams along with Spark Streaming
  • Providing users with fast analytics on data with Impala and Kudu
  • Illustrating how these components complement the batch processing capabilities of Hadoop
  • Leveraging these capabilities along with other tools such as Spark MLlib and Spark SQL to provide sophisticated machine learning and analytical capabilities for users
Photo of Jonathan Seidman

Jonathan Seidman

Cloudera

Jonathan Seidman is a software engineer on the partner engineering team at Cloudera. Previously, he was a lead engineer on the big data team at Orbitz Worldwide, helping to build out the Hadoop clusters supporting the data storage and analysis needs of one of the most heavily trafficked sites on the internet. Jonathan is a cofounder of the Chicago Hadoop User Group and the Chicago Big Data Meetup and a frequent speaker on Hadoop and big data at industry conferences such as Hadoop World, Strata, and OSCON. Jonathan is the coauthor of Hadoop Application Architectures from O’Reilly.

Photo of Ted Malaska

Ted Malaska

Blizzard Entertainment

Ted Malaska is a group technical architect on the Battle.net team at Blizzard, helping support great titles like World of Warcraft, Overwatch, and HearthStone. Previously, Ted was a principal solutions architect at Cloudera, helping clients find success with the Hadoop ecosystem, and a lead architect at the Financial Industry Regulatory Authority (FINRA). He has also contributed code to Apache Flume, Apache Avro, Apache Yarn, Apache HDFS, Apache Spark, Apache Sqoop, and many more. Ted is a coauthor of Hadoop Application Architectures, a frequent speaker at many conferences, and a frequent blogger on data architectures.

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