Mastering Large Datasets with Python

List of Tables

Chapter 7. Processing truly big datasets with Hadoop and Spark

Table 7.1. A comparison of compression formats available for use out of the box with Hadoop

Chapter 9. PageRank with map and reduce in PySpark

Table 9.1. Differences between the RDD’s .reduce, .fold, and .aggregate methods

Chapter 10. Faster decision-making with machine learning and PySpark

Table 10.1. A subset of mushroom data for a small decision tree classifier

Table 10.2. Five randomly seeded decision trees for an example random forest

Chapter 11. Large datasets in the cloud with Amazon Web Services and S3

Table 11.1. Three major S3 storage classes are available, depending on how often you need to access your data.

Table 11.2. Useful AWS Security Policies ...