9780134846019 - Data Analytics with Spark Using Python (Addison-Wesley Data & Analytics Series) von Aven, Jeffrey (8 Ergebnisse)

Paperback. Zustand: Fair. No Jacket. Former library book; Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.

Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Zustand: Brand New. 400 pages. 9.00x7.00x0.75 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware -Solve Data Analytics Problems with Spark, PySpark, and Related Open Source ToolsSpark 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 developerseven 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 MLlibLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 320 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware - Solve Data Analytics Problems with Spark, PySpark, and Related Open Source ToolsSpark 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.

Taschenbuch. Zustand: Neu. Neuware -Solve Data Analytics Problems with Spark, PySpark, and Related Open Source ToolsSpark 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 developerseven 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 320 pp. Englisch.