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Hadoop and Spark for the Enterprise: Ensuring Quality of Service in Multi-Tenant Environments

Learn how Pepperdata helps ensure Quality of Service in multi-tenant environments by guaranteeing service levels for high priority jobs and ensuring cluster hardware resources are used to maximum potential, to maximize throughput and hardware usage.

The Hadoop Performance Myth (PDF)

Deploying Hadoop involves many choices that can make or break your Hadoop initiative. Find out what successful Hadoop deployments have in common.

Data Analytics with Hadoop: A Practical Guide to Understanding Data Science and Analytics (PDF)

Learn how Pepperdata helps ensure Quality of Service in multi-tenant environments by guaranteeing service levels for high priority jobs and ensuring cluster hardware resources are used to maximum potential, to maximize throughput and hardware usage.

Best Practices for Setting up and Maintaining Reliable Hadoop Clusters (PDF)

Unlock the power of your data by learning how to ensure a successful start to your big data project. We’ll dive into tried and true process for how to build, maintain, and manage successful Hadoop deployments. This guide will show you how.

Analyst Paper: Pepperdata Enables Performance QoS for Hadoop (PDF)

Taneja Group analyst firm comments on the challenges for Enterprises looking to deploy Hadoop, and how Pepperdata helps organizations enforce SLAs and bridge the Hadoop skills gap with its automated cluster performance management.

Yarn: The Definitive Guide (PDF)

This is an excerpt from the O’Reilly book titled “Hadoop: The Definitive Guide.” This chapter, focused exclusively on YARN, will provide a deep dive into the workings of Hadoop schedulers, a comparison of the tools on the market, and best practices for building your own YARN applications.

High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark (PDF)

This exclusive chapter from O’Reilly book “High Performance Spark” introduces Spark’s place in the big data ecosystem, and helps you understand how Spark programs are executed, its model for parallel computing, and improve your general understanding of this open source technology.

A Practical Guide to Understanding Data Science and Analytics (PDF)

These 2 chapters from O’Reilly book “Data Analytics with Hadoop” focuses on the operational piece of how Hadoop works and how to execute workloads related to data analytics. Great for anyone involved in Hadoop operations and/or analytics with Hadoop.