Best hive hadoop to buy in 2019
We spent many hours on research to finding hive hadoop, reading product features, product specifications for this guide. For those of you who wish to the best hive hadoop, you should not miss this article. hive hadoop coming in a variety of types but also different price range. The following is the top 7 hive hadoop by our suggestions:
We spent many hours on research to finding hive hadoop, reading product features, product specifications for this guide. For those of you who wish to the best hive hadoop, you should not miss this article. hive hadoop coming in a variety of types but also different price range. The following is the top 7 hive hadoop by our suggestions:
Best hive hadoop
1. Programming Hive: Data Warehouse and Query Language for Hadoop
Description
Need to move a relational database application to Hadoop? This comprehensive guide introduces you to Apache Hive, Hadoops data warehouse infrastructure. Youll quickly learn how to use Hives SQL dialectHiveQLto summarize, query, and analyze large datasets stored in Hadoops distributed filesystem.
This example-driven guide shows you how to set up and configure Hive in your environment, provides a detailed overview of Hadoop and MapReduce, and demonstrates how Hive works within the Hadoop ecosystem. Youll also find real-world case studies that describe how companies have used Hive to solve unique problems involving petabytes of data.
- Use Hive to create, alter, and drop databases, tables, views, functions, and indexes
- Customize data formats and storage options, from files to external databases
- Load and extract data from tablesand use queries, grouping, filtering, joining, and other conventional query methods
- Gain best practices for creating user defined functions (UDFs)
- Learn Hive patterns you should use and anti-patterns you should avoid
- Integrate Hive with other data processing programs
- Use storage handlers for NoSQL databases and other datastores
- Learn the pros and cons of running Hive on Amazons Elastic MapReduce
2. Practical Hive: A Guide to Hadoop's Data Warehouse System
Description
Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored across your Hadoop environment. From deploying Hive on your hardware or virtual machine and setting up its initial configuration to learning how Hive interacts with Hadoop, MapReduce, Tez and other big data technologies, Practical Hive gives you a detailed treatment of the software.
In addition, this book discusses the value of open source software, Hive performance tuning, and how to leverage semi-structured and unstructured data.
What You Will Learn
- Install and configure Hive for new and existing datasets
- Perform DDL operations
- Execute efficient DML operations
- Use tables, partitions, buckets, and user-defined functions
- Discover performance tuning tips and Hive best practices
Who This Book Is For
Developers, companies, and professionals who deal with large amounts of data and could use software that can efficiently manage large volumes of input. It is assumed that readers have the ability to work with SQL.
3. Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale
Feature
O Reilly MediaDescription
Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, youll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters.
Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, and Spark. Youll learn about recent changes to Hadoop, and explore new case studies on Hadoops role in healthcare systems and genomics data processing.
- Learn fundamental components such as MapReduce, HDFS, and YARN
- Explore MapReduce in depth, including steps for developing applications with it
- Set up and maintain a Hadoop cluster running HDFS and MapReduce on YARN
- Learn two data formats: Avro for data serialization and Parquet for nested data
- Use data ingestion tools such as Flume (for streaming data) and Sqoop (for bulk data transfer)
- Understand how high-level data processing tools like Pig, Hive, Crunch, and Spark work with Hadoop
- Learn the HBase distributed database and the ZooKeeper distributed configuration service
4. Learn Hive in 1 Day: Complete Guide to Master Apache Hive
Description
Apache Hive is the new member in database family that works within the Hadoop ecosystem. It provides all great features like data summarization, ad-hoc query, and analysis of large datasets. If you are not a good programmer, then this edition will teach you how to use hive queries without writing complex codes.
Most users face the problem of not getting a dedicated course on Hive. The goal of this e-book is to cater everything about Hive and only Hive with minimum jargons. The notes, lessons and hands-on examples in this small e-book are simplified and tactfully presented to solve all your Hive queries. Instead of writing long code for MapReduce or Java, the e-book shows tips on writing the same program with a minimum code snippet.
Beginners as well as peers will thoroughly enjoy this book. They will discover and learn more hive patterns for data processing and data integrations. Unlike other e-book, where they skip basic detail thinking users having prior subject knowledge. This edition has given complete attention to each and every small aspect of the hive like how to set up and configure Hive in your environment.
This e-book is also helpful for those who just want to explore Hive and dont want to spend big bucks for short courses. You will quickly learn, apply and share your Hive knowledge with this e-book.
Table of content
Chapter 1: Introduction
What is Hive?
Hive Architecture
Different modes of Hive
What is Hive Server2 (HS2)?
Hive vs Map Reduce
Chapter 2: Installation and Configuration
Installation of Hive
Hive shell commands
Install and configure MYSQL database
Chapter 3: Data operations
Data types in Hive
Creation and dropping of Database in Hive
Create, Drop and altering of tables in Hive
Table types and its Usage
Partitions
Buckets
Chapter 4: Queries and Implementation
Order by query
Group by query
Sort by
Cluster By
Distribute By
Join queries
Different type of joins
Sub queries
Embedding custom scripts
UDFs (User Define Functions)
Chapter 5: Query Language, Built-in Operators and Functions
Hive Query Language (HQL)
Built-in operators
Built-in functions
Chapter 6: Data Extraction
Working with Structured Data using Hive
Working with Semi structured data using Hive (XML, JSON)
Hive in Real time projects When and Where to Use
5. Apache Hive Cookbook
Description
Easy, hands-on recipes to help you understand Hive and its integration with frameworks that are used widely in today's big data world
About This Book
- Grasp a complete reference of different Hive topics.
- Get to know the latest recipes in development in Hive including CRUD operations
- Understand Hive internals and integration of Hive with different frameworks used in today's world.
Who This Book Is For
The book is intended for those who want to start in Hive or who have basic understanding of Hive framework. Prior knowledge of basic SQL command is also required
What You Will Learn
- Learn different features and offering on the latest Hive
- Understand the working and structure of the Hive internals
- Get an insight on the latest development in Hive framework
- Grasp the concepts of Hive Data Model
- Master the key concepts like Partition, Buckets and Statistics
- Know how to integrate Hive with other frameworks such as Spark, Accumulo, etc
In Detail
Hive was developed by Facebook and later open sourced in Apache community. Hive provides SQL like interface to run queries on Big Data frameworks. Hive provides SQL like syntax also called as HiveQL that includes all SQL capabilities like analytical functions which are the need of the hour in today's Big Data world.
This book provides you easy installation steps with different types of metastores supported by Hive. This book has simple and easy to learn recipes for configuring Hive clients and services. You would also learn different Hive optimizations including Partitions and Bucketing. The book also covers the source code explanation of latest Hive version.
Hive Query Language is being used by other frameworks including spark. Towards the end you will cover integration of Hive with these frameworks.
Style and approach
Starting with the basics and covering the core concepts with the practical usage, this book is a complete guide to learn and explore Hive offerings.
6. Apache Hive Essentials: Essential techniques to help you process, and get unique insights from, big data, 2nd Edition
Description
This book takes you on a fantastic journey to discover the attributes of big data using Apache Hive.
Key Features
- Grasp the skills needed to write efficient Hive queries to analyze the Big Data
- Discover how Hive can coexist and work with other tools within the Hadoop ecosystem
- Uses practical, example-oriented scenarios to cover all the newly released features of Apache Hive 2.3.3
Book Description
In this book, we prepare you for your journey into big data by frstly introducing you to backgrounds in the big data domain, alongwith the process of setting up and getting familiar with your Hive working environment.
Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skills in using the Hive language in an effcient manner. Toward the end, the book focuses on advanced topics, such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey.
By the end of the book, you will be familiar with Hive and able to work effeciently to find solutions to big data problems
What you will learn
- Create and set up the Hive environment
- Discover how to use Hive's definition language to describe data
- Discover interesting data by joining and filtering datasets in Hive
- Transform data by using Hive sorting, ordering, and functions
- Aggregate and sample data in different ways
- Boost Hive query performance and enhance data security in Hive
- Customize Hive to your needs by using user-defined functions and integrate it with other tools
Who This Book Is For
If you are a data analyst, developer, or simply someone who wants to quickly get started with Hive to explore and analyze Big Data in Hadoop, this is the book for you. Since Hive is an SQL-like language, some previous experience with SQL will be useful to get the most out of this book.
Table of Contents
- OVERVIEW OF BIG DATA AND HIVE
- SETTING UP THE HIVE ENVIRONMENT
- DATA DEFINITION AND DESCRIPTION
- Data Correlation and Scope
- DATA MANIPULATION
- DATA AGGREGATION AND SAMPLING
- Extensibility Considerations
- Working with Other Tools
- Performance Considerations
- Security Considerations
7. Apache Hive Essentials
Description
Immerse yourself on a fantastic journey to discover the attributes of big data by using Hive
About This Book
- Discover how Hive can coexist and work with other tools in the Hadoop ecosystem to create big data solutions
- Grasp the skills needed, learn the best practices, and avoid the pitfalls in writing efficient Hive queries to analyze the big data
- Create an environment to analyze big data using practical, example-oriented scenarios
Who This Book Is For
If you are a data analyst, developer, or simply someone who wants to use Hive to explore and analyze data in Hadoop, this is the book for you. Whether you are new to big data or an expert, with this book, you will be able to master both the basic and the advanced features of Hive. Since Hive is an SQL-like language, some previous experience with the SQL language and databases is useful to have a better understanding of this book.
What You Will Learn
- Create and set up the Hive environment
- Discover how to use Hive's definition language to describe data
- Discover interesting data by joining and filtering datasets in Hive
- Transform data by using Hive sorting, ordering, and functions
- Aggregate and sample data in different ways
- Boost Hive query performance and enhance data security in Hive
- Customize Hive to your needs by using user-defined functions and integrate it with other tools
In Detail
In this book, we prepare you for your journey into big data by firstly introducing you to backgrounds in the big data domain along with the process of setting up and getting familiar with your Hive working environment. Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skill in using the Hive language in an efficient manner. Towards the end, the book focuses on advanced topics such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey.
By the end of the book, you will be familiar with Hive and able to work efficiently to find solutions to big data problems.