Programming Hive

Programming Hive

Describes the features and functions of Apache Hive, the data infrastructure for Hadoop.

Author: Edward Capriolo

Publisher: "O'Reilly Media, Inc."

ISBN: 9781449319335

Category: Computers

Page: 328

View: 221

Describes the features and functions of Apache Hive, the data infrastructure for Hadoop.
Categories: Computers

Programming Elastic MapReduce

Programming Elastic MapReduce

This means any table that is created in Hive will cease to exist once the Amazon EMR cluster is terminated. ... To learn more about Hive, see Programming Hive by Edward Capriolo, Dean Wampler, and Jason Rutherglen (O'Reilly).

Author: Kevin Schmidt

Publisher: "O'Reilly Media, Inc."

ISBN: 9781449364052

Category: Computers

Page: 174

View: 256

Although you don’t need a large computing infrastructure to process massive amounts of data with Apache Hadoop, it can still be difficult to get started. This practical guide shows you how to quickly launch data analysis projects in the cloud by using Amazon Elastic MapReduce (EMR), the hosted Hadoop framework in Amazon Web Services (AWS). Authors Kevin Schmidt and Christopher Phillips demonstrate best practices for using EMR and various AWS and Apache technologies by walking you through the construction of a sample MapReduce log analysis application. Using code samples and example configurations, you’ll learn how to assemble the building blocks necessary to solve your biggest data analysis problems. Get an overview of the AWS and Apache software tools used in large-scale data analysis Go through the process of executing a Job Flow with a simple log analyzer Discover useful MapReduce patterns for filtering and analyzing data sets Use Apache Hive and Pig instead of Java to build a MapReduce Job Flow Learn the basics for using Amazon EMR to run machine learning algorithms Develop a project cost model for using Amazon EMR and other AWS tools
Categories: Computers

Databases Illuminated

Databases Illuminated

Jaql is a functional programming and query language that is used with JavaScript Object Notation (JSON). ... Hive was initially developed by Facebook as a way to simplify MapReduce programming. Hive is now a part of the open source ...

Author: Catherine M. Ricardo

Publisher: Jones & Bartlett Publishers

ISBN: 9781284056945

Category: Computers

Page: 760

View: 810

Databases Illuminated, Third Edition Includes Navigate 2 Advantage Access combines database theory with a practical approach to database design and implementation. Strong pedagogical features, including accessible language, real-world examples, downloadable code, and engaging hands-on projects and lab exercises create a text with a unique combination of theory and student-oriented activities. Providing an integrated, modern approach to databases, Databases Illuminated, Third Edition is the essential text for students in this expanding field.
Categories: Computers

Data Analytics with Hadoop

Data Analytics with Hadoop

However, in a big data system like Hive where we are processing large volumes of unstructured data by sequentially scanning ... 3 Edward Capriolo, Dean Wampler, and Jason Rutherglen Programming Hive Structured Data Queries with Hive | 137.

Author: Benjamin Bengfort

Publisher: "O'Reilly Media, Inc."

ISBN: 9781491913765

Category: Computers

Page: 288

View: 766

Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib
Categories: Computers

Learning Spark

Learning Spark

As with the other Spark libraries, in Python no changes to your build are required. When programming against Spark SQL we have two entry points depending on whether we need Hive support. The recommended entry point is the HiveContext to ...

Author: Holden Karau

Publisher: "O'Reilly Media, Inc."

ISBN: 9781449359065

Category: Computers

Page: 276

View: 556

This book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. You'll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning.--
Categories: Computers

Programming Scala

Programming Scala

He has been a vocal advocate for Scala and Functional Programming as the ideal tools for big data applications. Dean is the coauthor of Programming Hive and the author of Functional Programming for Java Developers from O'Reilly.

Author: Dean Wampler

Publisher: "O'Reilly Media, Inc."

ISBN: 9781491950159

Category: Computers

Page: 598

View: 693

Get up to speed on Scala, the JVM language that offers all the benefits of a modern object model, functional programming, and an advanced type system. Packed with code examples, this comprehensive book shows you how to be productive with the language and ecosystem right away, and explains why Scala is ideal for today's highly scalable, data-centric applications that support concurrency and distribution. This second edition covers recent language features, with new chapters on pattern matching, comprehensions, and advanced functional programming. You’ll also learn about Scala’s command-line tools, third-party tools, libraries, and language-aware plugins for editors and IDEs. This book is ideal for beginning and advanced Scala developers alike. Program faster with Scala’s succinct and flexible syntax Dive into basic and advanced functional programming (FP) techniques Build killer big-data apps, using Scala’s functional combinators Use traits for mixin composition and pattern matching for data extraction Learn the sophisticated type system that combines FP and object-oriented programming concepts Explore Scala-specific concurrency tools, including Akka Understand how to develop rich domain-specific languages Learn good design techniques for building scalable and robust Scala applications
Categories: Computers

Trino The Definitive Guide

Trino  The Definitive Guide

For example, Programming Hive by Edward Cap‐riolo et al. (O'Reilly) has proven to be a great guide to us. For now, we need to discuss certain Hadoop and Hive concepts to provide enough context for the Trino usage. At its very core, ...

Author: Matt Fuller

Publisher: "O'Reilly Media, Inc."

ISBN: 9781098107680

Category: Computers

Page: 310

View: 932

Perform fast interactive analytics against different data sources using the Trino high-performance distributed SQL query engine. With this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's Hive, Cassandra, a relational database, or a proprietary data store. Analysts, software engineers, and production engineers will learn how to manage, use, and even develop with Trino. Initially developed by Facebook, open source Trino is now used by Netflix, Airbnb, LinkedIn, Twitter, Uber, and many other companies. Matt Fuller, Manfred Moser, and Martin Traverso show you how a single Trino query can combine data from multiple sources to allow for analytics across your entire organization. Get started: Explore Trino's use cases and learn about tools that will help you connect to Trino and query data Go deeper: Learn Trino's internal workings, including how to connect to and query data sources with support for SQL statements, operators, functions, and more Put Trino in production: Secure Trino, monitor workloads, tune queries, and connect more applications; learn how other organizations apply Trino
Categories: Computers

Hadoop Application Architectures

Hadoop Application Architectures

The Hive project also provides a meta‐data store, which in addition to storing metadata (i.e., data about data) on Hive structures is also accessible to other interfaces such as Apache Pig (a high-level parallel programming abstraction) ...

Author: Mark Grover

Publisher: "O'Reilly Media, Inc."

ISBN: 9781491900079

Category: Computers

Page: 400

View: 891

Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book’s second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you’re designing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process. This book covers: Factors to consider when using Hadoop to store and model data Best practices for moving data in and out of the system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics Giraph, GraphX, and other tools for large graph processing on Hadoop Using workflow orchestration and scheduling tools such as Apache Oozie Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume Architecture examples for clickstream analysis, fraud detection, and data warehousing
Categories: Computers

Network Data Analytics

Network Data Analytics

Create a Hive table by name Movies with different columns as shown in the table and write HiveQL for the following. (i) Display the movies that ... Programming Hive: Data warehouse and query language for Hadoop. O'Reilly Media, Inc. 4.

Author: K. G. Srinivasa

Publisher: Springer

ISBN: 9783319778006

Category: Computers

Page: 398

View: 164

In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.
Categories: Computers

Learning Apache Drill

Learning Apache Drill

Hive is a schema-on-read system, meaning that you must define a schema before you query data using Hive. The schema information is ... For more information about Hive, we recommend Programming Hive by Edward Capriolo, Dean Wampler, ...

Author: Charles Givre

Publisher: O'Reilly Media

ISBN: 9781492032779

Category: Computers

Page: 332

View: 298

Get up to speed with Apache Drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as Parquet, JSON, and CSV. Drill reads data in HDFS or in cloud-native storage such as S3 and works with Hive metastores along with distributed databases such as HBase, MongoDB, and relational databases. Drill works everywhere: on your laptop or in your largest cluster. In this practical book, Drill committers Charles Givre and Paul Rogers show analysts and data scientists how to query and analyze raw data using this powerful tool. Data scientists today spend about 80% of their time just gathering and cleaning data. With this book, you’ll learn how Drill helps you analyze data more effectively to drive down time to insight. Use Drill to clean, prepare, and summarize delimited data for further analysis Query file types including logfiles, Parquet, JSON, and other complex formats Query Hadoop, relational databases, MongoDB, and Kafka with standard SQL Connect to Drill programmatically using a variety of languages Use Drill even with challenging or ambiguous file formats Perform sophisticated analysis by extending Drill’s functionality with user-defined functions Facilitate data analysis for network security, image metadata, and machine learning
Categories: Computers