Ready to unlock the power of your data? With this comprehensive guide, you’ll 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.
You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN).
- Store large datasets with the Hadoop Distributed File System (HDFS)
- Run distributed computations with MapReduce
- Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence
- Discover common pitfalls and advanced features for writing real-world MapReduce programs
- Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud
- Load data from relational databases into HDFS, using Sqoop
- Perform large-scale data processing with the Pig query language
- Analyze datasets with Hive, Hadoop’s data warehousing system
- Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems
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Book description
Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, youâ??ll 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. Youâ??ll learn about recent changes to Hadoop, and explore new case studies on Hadoopâ??s 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
Ready to unlock the power of your data? With this comprehensive guide, you’ll 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.
You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN).
- Store large datasets with the Hadoop Distributed File System (HDFS)
- Run distributed computations with MapReduce
- Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence
- Discover common pitfalls and advanced features for writing real-world MapReduce programs
- Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud
- Load data from relational databases into HDFS, using Sqoop
- Perform large-scale data processing with the Pig query language
- Analyze datasets with Hive, Hadoop’s data warehousing system
- Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems
Описание книги.
Apache Hadoop — фреймворк с открытым исходным кодом, в котором реализована вычислительная парадигма, известная как MapReduce, позволившая Google построить свою империю. Эта книга поможет вам изучить и использовать всю мощь Hadoop, чтобы создавать надежные, масштабируемые, распределенные системы и обрабатывать гигантские наборы данных. Программисты найдут здесь методики анализа, администраторы узнают, как установить и запустить кластеры Hadoop.
Если вы работаете с большими массивами данных, гигабайтами или петабайтами информации, то Hadoop — это идеальное решение. «Hadoop: Подробное руководство» — книга, в которой досконально и доступно описаны все возможности Apache Hadoop. Издание включает последние разработки Hadoop, в том числе подробности новой исполнительной среды MapReduce, называемой MapReduce 2, которая использует базовую систему YARN (Yet Another Resource Negotiator) — общей методики управления ресурсами для распределенных приложений.