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Data Analytics with Spark Using Python (Paperback)
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Data Analytics with Spark Using Python (Paperback)
Series: Addison-Wesley Data & Analytics Series
Expected to ship within 18 - 22 working days
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Solve Data Analytics Problems with Spark, PySpark, and Related Open
Source Tools Spark is at the heart of today's Big Data revolution,
helping data professionals supercharge efficiency and performance
in a wide range of data processing and analytics tasks. In this
guide, Big Data expert Jeffrey Aven covers all you need to know to
leverage Spark, together with its extensions, subprojects, and
wider ecosystem. Aven combines a language-agnostic introduction to
foundational Spark concepts with extensive programming examples
utilizing the popular and intuitive PySpark development
environment. This guide's focus on Python makes it widely
accessible to large audiences of data professionals, analysts, and
developers-even those with little Hadoop or Spark experience.
Aven's broad coverage ranges from basic to advanced Spark
programming, and Spark SQL to machine learning. You'll learn how to
efficiently manage all forms of data with Spark: streaming,
structured, semi-structured, and unstructured. Throughout, concise
topic overviews quickly get you up to speed, and extensive hands-on
exercises prepare you to solve real problems. Coverage includes: *
Understand Spark's evolving role in the Big Data and Hadoop
ecosystems * Create Spark clusters using various deployment modes *
Control and optimize the operation of Spark clusters and
applications * Master Spark Core RDD API programming techniques *
Extend, accelerate, and optimize Spark routines with advanced API
platform constructs, including shared variables, RDD storage, and
partitioning * Efficiently integrate Spark with both SQL and
nonrelational data stores * Perform stream processing and messaging
with Spark Streaming and Apache Kafka * Implement predictive
modeling with SparkR and Spark MLlib
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