January 2019
Beginner to intermediate
154 pages
4h 31m
English
Content preview from Apache Spark Quick Start Guide
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Making the most of Hadoop and Spark
People generally get confused between Hadoop and Spark and how they are related. The intention of this section is to discuss the differences between Hadoop and Spark, and also how they can be used together.
Hadoop is mainly a combination of the following components:
- Hive and Pig
- MapReduce
- YARN
- HDFS
HDFS is the storage layer where underlying data can be stored. HDFS provides features such as the replication of the data, fault tolerance, high availability, and more. Hadoop is schema-on-read; for instance, you don’t have to specify the schema while writing the data to Hadoop, rather, you can use different schemas while reading the data. HDFS also provides different types of files formats, such as TextInputFormat ...
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