Cisco Data Intelligence Platform with Cloudera Data Platform

Deployment Guide for Cisco Data Intelligence Platform with Cloudera Data Platform Data Center 7.0.3

Updated: March 4, 2020

Published: January 21, 2020

Partnered with:

About the Cisco Validated Design Program

The Cisco Validated Design (CVD) program consists of systems and solutions designed, tested, and documented to facilitate faster, more reliable, and more predictable customer deployments. For more information, go to:

http://www.cisco.com/go/designzone.

ALL DESIGNS, SPECIFICATIONS, STATEMENTS, INFORMATION, AND RECOMMENDATIONS (COLLECTIVELY, "DESIGNS") IN THIS MANUAL ARE PRESENTED "AS IS," WITH ALL FAULTS.  CISCO AND ITS SUPPLIERS DISCLAIM ALL WARRANTIES, INCLUDING, WITHOUT LIMITATION, THE WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OR ARISING FROM A COURSE OF DEALING, USAGE, OR TRADE PRACTICE.  IN NO EVENT SHALL CISCO OR ITS SUPPLIERS BE LIABLE FOR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, OR INCIDENTAL DAMAGES, INCLUDING, WITHOUT LIMITATION, LOST PROFITS OR LOSS OR DAMAGE TO DATA ARISING OUT OF THE USE OR INABILITY TO USE THE DESIGNS, EVEN IF CISCO OR ITS SUPPLIERS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

THE DESIGNS ARE SUBJECT TO CHANGE WITHOUT NOTICE.  USERS ARE SOLELY RESPONSIBLE FOR THEIR APPLICATION OF THE DESIGNS.  THE DESIGNS DO NOT CONSTITUTE THE TECHNICAL OR OTHER PROFESSIONAL ADVICE OF CISCO, ITS SUPPLIERS OR PARTNERS.  USERS SHOULD CONSULT THEIR OWN TECHNICAL ADVISORS BEFORE IMPLEMENTING THE DESIGNS.  RESULTS MAY VARY DEPENDING ON FACTORS NOT TESTED BY CISCO.

CCDE, CCENT, Cisco Eos, Cisco Lumin, Cisco Nexus, Cisco StadiumVision, Cisco TelePresence, Cisco WebEx, the Cisco logo, DCE, and Welcome to the Human Network are trademarks; Changing the Way We Work, Live, Play, and Learn and Cisco Store are service marks; and Access Registrar, Aironet, AsyncOS, Bringing the Meeting To You, Catalyst, CCDA, CCDP, CCIE, CCIP, CCNA, CCNP, CCSP, CCVP, Cisco, the Cisco Certified Internetwork Expert logo, Cisco IOS, Cisco Press, Cisco Systems, Cisco Systems Capital, the Cisco Systems logo, Cisco Unified Computing System (Cisco UCS), Cisco UCS B-Series Blade Servers, Cisco UCS C-Series Rack Servers, Cisco UCS S-Series Storage Servers, Cisco UCS Manager, Cisco UCS Management Software, Cisco Unified Fabric, Cisco Application Centric Infrastructure, Cisco Nexus 9000 Series, Cisco Nexus 7000 Series. Cisco Prime Data Center Network Manager, Cisco NX-OS Software, Cisco MDS Series, Cisco Unity, Collaboration Without Limitation, EtherFast, EtherSwitch, Event Center, Fast Step, Follow Me Browsing, FormShare, GigaDrive, HomeLink, Internet Quotient, IOS, iPhone, iQuick Study,  LightStream, Linksys, MediaTone, MeetingPlace, MeetingPlace Chime Sound, MGX, Networkers, Networking Academy, Network Registrar, PCNow, PIX, PowerPanels, ProConnect, ScriptShare, SenderBase, SMARTnet, Spectrum Expert, StackWise, The Fastest Way to Increase Your Internet Quotient, TransPath, WebEx, and the WebEx logo are registered trademarks of Cisco Systems, Inc. and/or its affiliates in the United States and certain other countries.

All other trademarks mentioned in this document or website are the property of their respective owners. The use of the word partner does not imply a partnership relationship between Cisco and any other company. (0809R)

© 2020 Cisco Systems, Inc. All rights reserved.

Table of Contents

Executive Summary

Solution Overview

Introduction

Audience

Purpose of this Document

What’s New in this Release?

What’s Next?

Solution Summary

Cisco Data Intelligence Platform

CDP on CDIP

Reference Architecture

Data Lake Reference Architecture

Scaling the Solution

Technology Overview

Cisco UCS Integrated Infrastructure for Big Data and Analytics

Cisco UCS

Cisco Intersight

Cisco UCS Manager

Cisco UCS 6300 Series Fabric Interconnects

Cisco UCS 6400 Series Fabric Interconnect

Cisco UCS C-Series Rack-Mount Servers

Cisco UCS C240 M5 Rack-Mount Server

Cisco UCS S3260 Storage Servers

Cisco UCS Virtual Interface Cards (VICs)

Cloudera Data Platform (CDP) Data Center

Apache Ozone (Tech preview)

Red Hat Ansible Automation

Solution Design

Requirements

Physical Topology

Port Configuration on Fabric Interconnect

Server Configuration and Cabling for Cisco UCS C240 M5

Software Distributions and Firmware Versions

Cisco Intersight

Connected TAC

Cisco Intersight Integration for HCL

Advisories (PSIRTs)

Deployment Hardware and Software

Cisco Unified Computing System Configuration

Configure Cisco UCS Fabric Interconnect

Configure Fabric Interconnects for a Cluster Setup

Register UCSM with Intersight

Configure Cisco UCS Manager through Intersight

Create Service Profile Template

Install Red Hat Enterprise Linux 7.6

Post OS Install Configuration

Configure /etc/hosts

Set Up Passwordless Login

Create a Red Hat Enterprise Linux (RHEL) 7.6 Local Repository

Create the Red Hat Repository Database

Set Up Ansible

Install httpd

Disable the Linux Firewall

Set Up All Nodes to use the RHEL Repository

Disable SELinux

Upgrade the Cisco Network Driver for VIC1387

Set Up JAVA

Enable Syslog

Set the ulimit

Set TCP Retries

Disable IPv6 Defaults

Disable Swapping

Disable Memory Overcommit

Disable Transparent Huge Pages

NTP Configuration

Install Megaraid StorCLI

Configure the Filesystem for NameNodes and DataNodes

Delete Partitions

Cluster Verification

Install Cloudera Data Platform

Prerequisites for CDP DC Installation

Set Up the Local Parcels for CDP DC 7.0.3

Download Parcels

Install and Configure Database for Cloudera Manager

Databases for CDP

Cloudera Manager Installation

Install Cloudera Manager

Set Up the Cloudera Manager Server Database

Install Cloudera Data Platform Data Center (CDP DC 7)

Scale the Cluster

Enable High Availability

HDFS High Availability

Configure Hive Metastore to Use HDFS High Availability

Configure Hue to Work with HDFS High Availability

YARN High Availability

Configure Yarn (MR2 Included) and HDFS Services

Configure Spark

Tune Resource Allocation for Spark

Submit a Job

Shuffle Performance Improvement

Improve Serialization Performance

Spark SQL Tuning

Compression for Hive

Change the Log Directory for All Applications

Summary

For More Information

Bill of Materials

Appendix

Configure Cisco Boot Optimized M.2 RAID Controller

Configure Disk Group Policy

Configure Storage Profile

Apply Storage Profile in Service Profile Template

Install RHEL 7.6 on Cisco Optimized M.2 RAID Controller

Configure Data Drives on Name Node and Other Management Nodes

Configure Data Drives on Data Nodes

About the Author

Acknowledgements

Executive Summary

Data scientists are constantly searching for newer techniques and methodologies that can unlock the value of big data and distill this data further to identify additional insights which could transform productivity and provide business differentiation.

One such area is Artificial Intelligence/Machine Learning (AI/ML), which has seen tremendous development with bringing in new frameworks and new forms of compute (CPU, GPU and FPGA) to work on data to provide key insights. While data lakes have historically been data intensive workloads, these advancements in technologies have led to a new growing demand of compute intensive workloads to operate on the same data.

While data scientists want to be able to use the latest and greatest advancements in AI/ML software and hardware technologies on their datasets, the IT team is also constantly looking at enabling these data scientists to be able to provide such a platform to a data lake. This has led to architecturally siloed implementations. When data, which is ingested, worked, and processed in a data lake, needs to be further operated by AI/ML frameworks, it often leaves the platform and must be on-boarded to a different platform to be processed. This would be fine if this demand is seen only on a small percentage of workloads. However, AI/ML workloads working closely on the data in a data lake are seeing an increase in adoption. For instance, data lakes in customer environment are seeing deluge of data from new use cases such as IoT, autonomous driving, smart cities, genomics and financials, who are all seeing more and more demand of AI/ML processing of this data.

IT is demanding newer solutions to enable data scientists to operate on both a data lake and an AI/ML platform (or a compute farm) without worrying about the underlying infrastructure. IT also needs this to seamlessly grow to cloud scale while reducing the TCO of this infrastructure and without affecting utilization. Thus, driving a need to plan a data lake along with an AI/ML platform in a systemic fashion.

Seeing this increasing demand by IT, and also envisioning this as a natural extension of a data lake, we announced the Cisco Data Intelligence Platform.  Cisco Data Intelligence Platform is discussed in detail here.

This CVD implements Cisco Data Intelligence Platform on Cisco UCS with Cloudera Data Platform Data Center (CDP DC). CDP DC is an on-premises version of CDP. This new product combines the best of both worlds, such as Cloudera Enterprise Data Hub and Hortonworks Data Platform Enterprise along with new features and enhancements across the stack. This unified distribution is a scalable and customizable platform where you can securely run many types of workloads.

Furthermore, this CVD with CDP DC sets the foundation for CDP private cloud which offers cloud-like user experience with self-service portal where users can efficiently find, curate, and share data, enabling access to trusted data and analytics.

This solution offers cohesive platform for both IT and data scientists by providing a scalable infrastructure for IT while also providing application platform for data scientists.

Solution Overview

Introduction

Both Big Data and machine learning technology have progressed to the point where they are being implemented in production systems running 24x7. There exists a very clear need for a proven, dependable, high-performance platform for the ingestion, processing, storage and analysis of the data, as well as the seamless dissemination of the output, results and insights of the analysis.

This solution implements Cloudera Data Platform Data Center (CDP DC) on Cisco UCS Integrated Infrastructure for Big Data and Analytics based on Cisco Data Intelligence Platform (CDIP) architecture, a world-class platform specifically designed for demanding workloads that is both easy to scale and easy to manage, even as the requirements grow to thousands of servers and petabytes of storage.

Many companies, recognizing the immense potential of big data and machine learning technology, are gearing up to leverage these new capabilities, building out departments and increasing hiring. However, these efforts face a new set of challenges:

·       Making the data available to the diverse set of people who need it

·       Enabling access to high-performance computing resources, GPUs, that also scale with the data growth

·       Allowing people to work with the data using the environments in which they are familiar

·       Publishing their results so the organization can make use of it

·       Enabling the automated production of those results

·       Managing the data for compliance and governance

·       Scaling the system as the data grows

·       Managing and administering the system in an efficient, cost-effective way

This solution is based on the Cisco UCS Integrated Infrastructure for Big Data and Analytics and includes computing, storage, connectivity, and unified management capabilities to help companies manage the immense amount of data being collected. It is built on Cisco Unified Computing System (Cisco UCS) infrastructure, using Cisco UCS 6332 Series Fabric Interconnects, and Cisco UCS C-Series Rack Servers. This architecture is specifically designed for performance and linear scalability for big data and machine learning workload.

Audience

The intended audience of this document includes sales engineers, field consultants, professional services, IT managers, partner engineering and customers who want to deploy the Cloudera Data Platform Data Center on the Cisco UCS Integrated Infrastructure for Big Data and Analytics (Cisco UCS M5 Rack Mount servers).

Purpose of this Document

This document describes the architecture, design choices, and deployment procedures for Cisco Data Intelligence Platform using Cloudera Data Platform DC on Cisco UCS C240 M5.

This document also serves as a step-by-step guide on how to deploy CDP DC on 28 node cluster of Cisco UCS C240 M5 Rack Server.

What’s New in this Release?

This solution extends the portfolio of Cisco Data Intelligence Platform (CDIP) architecture with Cloudera Data Platform Data Center, a state-of-the-art platform, providing a data cloud for demanding workloads that is easy to deploy, scale and manage. Furthermore, as the enterprise’s requirements and needs changes overtime, the platform can grow to thousands of servers, hence providing peta bytes of storage.

The following design consideration will be implemented in this validated design:

·       Data Lake with Cloudera Data Platform Datacenter on Cisco UCS Integrated Infrastructure for Big Data and Analytics

·       Cisco Intersight

What’s Next?

This CVD showcases Cisco UCS Manager (UCSM). This solution can also be deployed using Cisco Intersight. Additional Cisco UCS features will be added to the Appendix in the following months. Some of these include the following:

·       Cloudera Data Platform Private Cloud

·       Apache Ozone – Object Storage

·       A fully integrated CDP on CDIP with

-      Data lake enabled through CDP DC

-      AI/ML enabled through CDP Private Cloud

-      Exabyte storage enabled through Apache Ozone

Solution Summary

This CVD details the process of installing Cloudera Data Platform Data Center and the configuration details of the cluster. The current version of Cisco UCS Integrated Infrastructure for Big Data and Analytics offers the following configurations depending on the compute and storage requirements.

Cisco Data Intelligence Platform

Cisco Data Intelligence Platform (CDIP) is a cloud scale architecture which brings together big data, AI/compute farm, and storage tiers to work together as a single entity while also being able to scale independently to address the IT issues in the modern data center. This architecture allows for:

·       Extremely fast data ingest, and data engineering done at the data lake

·       AI compute farm allowing for different types of AI frameworks and compute types (GPU, CPU, FPGA) to work on this data for further analytics

·       A storage tier, allowing to gradually retire data which has been worked on to a storage dense system with a lower $/TB providing a better TCO

·       Seamlessly scale the architecture to thousands of nodes with a single pane of glass management using Cisco Application Centric Infrastructure (ACI)

Cisco Data Intelligence Platform caters to the evolving architecture bringing together a fully scalable infrastructure with centralized management and fully supported software stack (in partnership with industry leaders in the space) to each of these three independently scalable components of the architecture including data lake, AI/ML and Object stores.

Figure 1        Cisco Data Intelligent Platform

Cisco has developed numerous industry leading Cisco Validated Designs (reference architectures) in the area of Big Data (CVDs with Cloudera, Hortonworks and MapR), compute farm with Kubernetes (CVD with RedHat OpenShift) and Object store (Scality, SwiftStack, Cloudian, and others).

This Cisco Data Intelligence Platform can be deployed in these variants:

·       CDIP with Cloudera with Data Science Workbench (powered by Kubernetes) and Tiered Storage with Hadoop

·       CDIP with Hortonworks with Apache Hadoop 3.1 and Data Science Workbench (powered by Kubernetes) and Tiered Storage with Hadoop

Figure 2        Cisco Data Intelligence Platform with Hadoop, Kubernetes and Object Store

This architecture can start from a single rack and scale to thousands of nodes with a single pane of glass management with Cisco Application Centric Infrastructure (ACI).

Figure 3        Cisco Data Intelligent Platform at Scale

CDP on CDIP

Figure 4        Cloudera Data Platform on Cisco Data Intelligent Platform

A CDIP architecture can fully be enabled by Cloudera Data Platform with the following components:

·       Data lake enabled through CDP DC

·       AI/ML enabled through CDP Private Cloud and

·       Exabyte storage enabled through Apache Ozone

Reference Architecture

Data Lake Reference Architecture

Table 1  lists the data lake reference architecture configuration details for Cisco UCS Integrated Infrastructure for Big Data and Analytics.

Table 1    Cisco UCS Integrated Infrastructure for Big Data and Analytics Configuration Options

Performance

Capacity

High Capacity

Servers

16 x Cisco UCS C240 M5 Rack Servers with small-form-factor (SFF) drives

16 x Cisco UCS C240 M5 Rack Servers with large-form-factor (LFF) drives

8 x Cisco UCS S3260 Storage Servers

CPU

2 x 2nd Gen Intel® Xeon® Scalable 6230 processors (2 x 20 cores, at 2.1 GHz)

2 x 2nd Gen Intel Xeon Scalable 6230 processors (2 x 20 cores, at 2.1 GHz)

2 x 2nd Gen Intel Xeon Processor Scalable Family 5220 (2 x 18 cores, 2.2 GHz)

Memory

12 x 32GB DDR4 (384 GB)

12 x 32GB DDR4 (384 GB)

12 x 32GB DDR4 (384 GB)

Boot

M.2 with 2 x 240-GB SSDs

M.2 with 2 x 240-GB SSDs

2 x 240-GB SATA SSDs

Storage

26 x 2.4TB 10K rpm SFF SAS HDDs or 12 x 1.6-TB Enterprise Value SATA SSDs

12 x 8-TB 7.2K rpm LFF SAS HDDs

28 x 6 TB 7.2K rpm LFF SAS HDDs per server node

Virtual interface card (VIC)

40 Gigabit Ethernet (Cisco UCS VIC 1387) or

25 Gigabit Ethernet (Cisco UCS VIC 1455)

40 Gigabit Ethernet (Cisco UCS VIC 1387) or

25 Gigabit Ethernet (Cisco UCS VIC 1455)

40 Gigabit Ethernet (Cisco UCS VIC 1387)

Storage controller

Cisco 12-Gbps SAS modular RAID controller with 4-GB flash-based write cache (FBWC) or Cisco 12-Gbps modular SAS host bus adapter (HBA)

Cisco 12-Gbps SAS modular RAID controller with 2-GB FBWC or Cisco 12-Gbps modular SAS host bus adapter (HBA)

Cisco 12-Gbps SAS Modular RAID Controller with 4-GB flash-based write cache (FBWC)

Network connectivity

Cisco UCS 6332 Fabric Interconnect or Cisco UCS 6454 Fabric Interconnect

Cisco UCS 6332 Fabric Interconnect or Cisco UCS 6454 Fabric Interconnect

Cisco UCS 6332 Fabric Interconnect

GPU (optional)

Up to 2 x NVIDIA Tesla V100 with 32 GB memory each Or Up to 6 x NVIDIA Tesla T4 with 16 GB memory each

2 x NVIDIA Tesla V100 with 32 GB memory each Or Up to 6 x NVIDIA Tesla T4 with 16 GB memory each

This configuration can also be deployed with the 4th Generation Cisco UCS 6454 Fabric Interconnect with 25G VIC. However, this could lead to a performance slow down compared to a 40G VIC and Fabric Interconnect 6332.

As illustrated in Figure 5, a 28-node cluster with Rack#1 hosting 16 Cisco UCS C240 M5 server. Each link in the figure represents a 40 Gigabit Ethernet link from each of the sixteen servers directly connected to a Fabric Interconnect. Rack#2 hosting 12 Cisco UCS C240 M5 server. Every server is connected to both Fabric Interconnects.

Figure 5        Cisco Data Intelligence Platform with Cloudera Data Platform Data Center – Data Lake

Scaling the Solution

Figure 6 illustrates how to scale the solution. Each pair of Cisco UCS 6332 Fabric Interconnects has 24 Cisco UCS C240 M5 servers connected to it. This allows for eight uplinks from each Fabric Interconnect to the Cisco Nexus 9332 switch. Six pairs of 6332 FI’s can connect to a single switch with four uplink ports each. With 24 servers per FI, a total of 144 servers can be supported. Additionally, this solution can scale to thousands of nodes with the Nexus 9500 series family of switches.

Figure 6        Scaling the Solution

In the reference architectures discussed here, each of the components is scaled separately, and for the purposes of this example, scaling is uniform. Two scale scenarios are as follows:

·       Scaled architecture with 3:1 oversubscription with Cisco fabric interconnects and Cisco ACI

·       Scaled architecture with 2:1 oversubscription with Cisco ACI

In the following scenarios, the goal is to populate up to a maximum of 200 leaf nodes in a Cisco ACI domain. Not all cases reach that number because they use the Cisco Nexus® 9508 Switch for this sizing and not the Cisco Nexus 9516 Switch.

Scaled Architecture with 3:1 Oversubscription with Cisco Fabric Interconnects and Cisco ACI

The architecture discussed here and shown in Figure 7 supports 3:1 network oversubscription from every node to every other node across a multidomain cluster (nodes in a single domain within a pair of Cisco fabric interconnects are locally switched and not oversubscribed).

From the viewpoint of the data lake, 24 Cisco UCS C240 M5 Rack Servers are connected to a pair of Cisco UCS 6332 Fabric Interconnects (with 24 x 40-Gbps throughput). From each fabric interconnect, 8 x 40-Gbps links connect to a pair of Cisco Nexus 9336 Switches. Three pairs of fabric interconnects can connect to a single pair of Cisco Nexus 9336 Switches (8 x 40-Gbps links per Fabric Interconnect to a pair of Nexus switch). Each of these Cisco Nexus 9336 Switches connects to a pair of Cisco Nexus 9508 Cisco ACI switches with 6 x 100-Gbps uplinks (connecting to a Cisco N9K-X9736C-FX line card). the Cisco Nexus 9508 Switch with the Cisco N9K-X9736C-FX line card can support up to 36 x 100-Gbps ports, each and 8 such line cards.

Figure 7        Scaled Architecture with 3:1 Oversubscription with Cisco Fabric Interconnects and Cisco ACI

Scaled Architecture with 2:1 Oversubscription with Cisco ACI

In the scenario discussed here and shown in Figure 8, the Cisco Nexus 9508 Switch with the Cisco N9K-X9736C-FX line card can support up to 36 x 100-Gbps ports, each and 8 such line cards.

Here, for the 2:1 oversubscription, 30 Cisco UCS C240 M5 Rack Servers are connected to a pair of Cisco Nexus 9336 Switches, and each Cisco Nexus 9336 connects to a pair of Cisco Nexus 9508 Switches with three uplinks each. A pair of Cisco Nexus 9336 Switches can support 30 servers and connect to a spine with 6 x 100-Gbps links on each spine. This single pod (pair of Cisco Nexus 9336 Switches connecting to 30 Cisco UCS C240 M5 servers and 6 uplinks to each spine) can be repeated 48 times (288/6) for a given Cisco Nexus 9508 Switch and can support up to1440 servers.

To reduce the oversubscription ratio (to get 1:1 network subscription from any node to any node), you can use just 15 servers under a pair of Cisco Nexus 9336 Switches and then move to Cisco Nexus 9516 Switches (the number of leaf nodes would double).

To scale beyond this number, multiple spines can be aggregated.

Figure 8        Scaled Architecture with 2:1 Oversubscription with Cisco ACI

Technology Overview

Cisco UCS Integrated Infrastructure for Big Data and Analytics

The Cisco UCS Integrated Infrastructure for Big Data and Analytics solution for Cloudera is based on Cisco UCS Integrated Infrastructure for Big Data and Analytics, a highly scalable architecture designed to meet a variety of scale-out application demands with seamless data integration and management integration capabilities built using the components described in this section.

Cisco UCS

Cisco Unified Computing System™ (Cisco UCS®) is a next-generation data center platform that unites computing, networking, storage access, and virtualization resources into a cohesive system designed to reduce Total Cost of Ownership (TCO) and increase business agility. The system integrates a low-latency, lossless 10/25/40/100 Gigabit Ethernet unified network fabric with enterprise-class, x86-architecture servers. The system is an integrated, scalable, multi-chassis platform in which all resources participate in a unified management domain (Figure 9).

Figure 9        Cisco UCS Component Hierarchy

Cisco Intersight

Cisco Intersight is Cisco’s systems management platform that delivers intuitive computing through cloud-powered intelligence. This platform offers a more intelligent level of management that enables IT organizations to analyze, simplify, and automate their environments in ways that were not possible with prior generations of tools. This capability empowers organizations to achieve significant savings in Total Cost of Ownership (TCO) and to deliver applications faster, so they can support new business initiatives.

Cisco Intersight is a Software as a Service (SaaS) infrastructure management which provides a single pane of glass management of CDIP infrastructure in the data center. Cisco Intersight scales easily, and frequent updates are implemented without impact to operations. Cisco Intersight Essentials enables customers to centralize configuration management through a unified policy engine, determine compliance with the Cisco UCS Hardware Compatibility List (HCL), and initiate firmware updates. Enhanced capabilities and tight integration with Cisco TAC enables more efficient support. Cisco Intersight automates uploading files to speed troubleshooting. The Intersight recommendation engine provides actionable intelligence for IT operations management. The insights are driven by expert systems and best practices from Cisco.

Cisco Intersight offers flexible deployment either as Software as a Service (SaaS) on Intersight.com or running on your premises with the Cisco Intersight virtual appliance. The virtual appliance provides users with the benefits of Cisco Intersight while allowing more flexibility for those with additional data locality and security requirements.

Figure 10     Cisco Intersight

Cisco Intersight has the following:

·       Connected TAC

·       Security Advisories

·       Hardware Compatibility List (HCL) and much more

To learn more about all the features of Intersight go to: https://www.cisco.com/c/en/us/products/servers-unified-computing/intersight/index.html

Cisco UCS Manager

Cisco UCS Manager (UCSM) resides within the Cisco UCS Fabric Interconnect. It makes the system self-aware and self-integrating, managing all the system components as a single logical entity. Cisco UCS Manager can be accessed through an intuitive graphical user interface (GUI), a command-line interface (CLI), or an XML application-programming interface (API). Cisco UCS Manager uses service profiles to define the personality, configuration, and connectivity of all resources within Cisco UCS, radically simplifying provisioning of resources so that the process takes minutes instead of days. This simplification allows IT departments to shift their focus from constant maintenance to strategic business initiatives.

Key Features

·       Supports Cisco UCS B-Series Blade and Cisco UCS C-Series Rack Servers, the Cisco UCS C3260 storage server, Cisco UCS Mini, and the Cisco HyperFlex hyperconverged infrastructure.

·       Programmatically controls server, network, and storage resources, with a unified, policy-driven management, so they can be efficiently managed at scale through software.

·       Works with HTML 5, Java, or CLI graphical user interfaces.

·       Can automatically detect, inventory, manage, and provision system components that are added or changed.

·       Facilitates integration with third-party systems management tools.

·       Builds on existing skills and supports collaboration across disciplines through role-based administration

Cisco UCS 6300 Series Fabric Interconnects

Cisco UCS 6300 Series Fabric Interconnects provide high-bandwidth, low-latency connectivity for servers, with integrated, unified management provided for all connected devices by Cisco UCS Manager. Deployed in redundant pairs, Cisco fabric interconnects offer the full active-active redundancy, performance, and exceptional scalability needed to support the large number of nodes that are typical in clusters serving big data applications. Cisco UCS Manager enables rapid and consistent server configuration using service profiles, automating ongoing system maintenance activities such as firmware updates across the entire cluster as a single operation. Cisco UCS Manager also offers advanced monitoring with options to raise alarms and send notifications about the health of the entire cluster.

The Cisco UCS 6300 Series Fabric Interconnects are a core part of Cisco UCS, providing low-latency, lossless 10 and 40 Gigabit Ethernet, Fiber Channel over Ethernet (FCoE), and Fiber Channel functions with management capabilities for the entire system. All servers attached to Fabric interconnects become part of a single, highly available management domain.

Figure 11     Cisco UCS 6332UP 32 -Port Fabric Interconnect

For more information, go to: https://www.cisco.com/c/en/us/products/collateral/servers-unified-computing/ucs-6300-series-fabric-interconnects/datasheet-c78-736682.html?cachemode=refresh

Cisco UCS 6400 Series Fabric Interconnect

The Cisco UCS 6454 provides the management and communication backbone for the Cisco UCS B-Series Blade Servers, Cisco UCS 5108 B-Series Server Chassis, Cisco UCS Managed C-Series Rack Servers, and Cisco UCS S-Series Storage Servers, providing both network connectivity and management capabilities for the system (Figure 12).

From a networking perspective, the Cisco UCS 6454 uses a cut-through architecture, supporting deterministic, low-latency, line-rate 10/25/40/100 Gigabit Ethernet ports, switching capacity of 3.82 Tbps, and 160 Gbps bandwidth between FI 6454 and IOM 2208 per 5108 blade chassis, independent of packet size and enabled services. The product family supports Cisco® low-latency, lossless 10/25/40/100 Gigabit Ethernet unified network fabric capabilities, which increase the reliability, efficiency, and scalability of Ethernet networks. The Fabric Interconnect supports multiple traffic classes over a lossless Ethernet fabric from the server through the Fabric Interconnect. Significant TCO savings come from an FCoE optimized server design in which Network Interface Cards (NICs), Host Bus Adapters (HBAs), cables, and switches can be consolidated.

Figure 12     Cisco UCS 6454 Fabric Interconnect

Cisco UCS C-Series Rack-Mount Servers

Cisco UCS C-Series Rack-Mount Servers keep pace with Intel Xeon processor innovation by offering the latest processors with increased processor frequency and improved security and availability features. With the increased performance provided by the Intel Xeon Scalable Family Processors, Cisco UCS C-Series servers offer an improved price-to-performance ratio. They also extend Cisco UCS innovations to an industry-standard rack-mount form factor, including a standards-based unified network fabric, Cisco VN-Link virtualization support, and Cisco Extended Memory Technology.

It is designed to operate both in standalone environments and as part of Cisco UCS managed configuration, these servers enable organizations to deploy systems incrementally—using as many or as few servers as needed—on a schedule that best meets the organization’s timing and budget. Cisco UCS C-Series servers offer investment protection through the capability to deploy them either as standalone servers or as part of Cisco UCS. One compelling reason that many organizations prefer rack-mount servers is the wide range of I/O options available in the form of PCIe adapters. Cisco UCS C-Series servers support a broad range of I/O options, including interfaces supported by Cisco and adapters from third parties.

Cisco UCS C240 M5 Rack-Mount Server

The Cisco UCS C240 M5 Rack-Mount Server (Figure 13) is a 2-socket, 2-Rack-Unit (2RU) rack server offering industry-leading performance and expandability. It supports a wide range of storage and I/O-intensive infrastructure workloads, from big data and analytics to collaboration. Cisco UCS C-Series Rack Servers can be deployed as standalone servers or as part of a Cisco Unified Computing System (Cisco UCS) managed environment to take advantage of Cisco’s standards-based unified computing innovations that help reduce customers’ Total Cost of Ownership (TCO) and increase their business agility.

In response to the ever-increasing computing and data-intensive real-time workloads, the enterprise-class Cisco UCS C240 M5 server extends the capabilities of the Cisco UCS portfolio in a 2RU form factor. It incorporates the 2nd generation Intel® Xeon® Scalable and Intel® Xeon® Scalable processors, supporting up to 20 percent more cores per socket, twice the memory capacity, and five times more Non-Volatile Memory Express (NVMe) PCI Express (PCIe) Solid-State Disks (SSDs) compared to the previous generation of servers. These improvements deliver significant performance and efficiency gains that will improve your application performance. The Cisco UCS C240 M5 delivers outstanding levels of storage expandability with exceptional performance, along with the following:

·       Latest Intel Xeon Scalable CPUs with up to 28 cores per socket

·       Up to 24 DDR4 DIMMs for improved performance

·       Up to 26 hot-swappable Small-Form-Factor (SFF) 2.5-inch drives, including 2 rear hot-swappable SFF drives (up to 10 support NVMe PCIe SSDs on the NVMe-optimized chassis version), or 12 Large-Form- Factor (LFF) 3.5-inch drives plus 2 rear hot-swappable SFF drives

·       Support for 12-Gbps SAS modular RAID controller in a dedicated slot, leaving the remaining PCIe Generation 3.0 slots available for other expansion cards

·       Modular LAN-On-Motherboard (mLOM) slot that can be used to install a Cisco UCS Virtual Interface Card (VIC) without consuming a PCIe slot, supporting dual 10- or 40-Gbps network connectivity

·       Dual embedded Intel x550 10GBASE-T LAN-On-Motherboard (LOM) ports

·       Modular M.2 or Secure Digital (SD) cards that can be used for boot

Figure 13     Cisco UCS C240 M5 Rack-Mount Server

Cisco UCS S3260 Storage Servers

The Cisco UCS S3260 Storage Server is a modular storage server with dual M5 server nodes and is optimized to deliver efficient, industry-leading storage for data-intensive workloads. The Cisco UCS S3260 server with dual-node capability that is based on the 2nd Gen Intel® Xeon® Scalable and Intel® Xeon® Scalable processors, the server features up to 840 TB of local storage in a compact 4-Rack-Unit (4RU) form factor. The drives can be configured with enterprise-class Redundant Array of Independent Disks (RAID) redundancy or with a pass-through Host Bus Adapter (HBA) controller. Network connectivity is provided with dual-port 40-Gbps nodes in each server, with expanded unified I/O capabilities for data migration between Network-Attached Storage (NAS) and SAN environments. This storage-optimized server comfortably fits in a standard 32-inch-depth rack, such as the Cisco® R 42610 Rack.

Figure 14     Cisco UCS S3260 Storage Server

The Cisco UCS S3260 Storage Server chassis has 56 top-load LFF HDDs option as shown above with a maximum capacity of 4 TB per HDD and can be mixed with up to 28 SSDs.

The modular Cisco UCS S3260 Storage Server chassis offers flexibility with more computing, storage, and PCIe expansion on the second slot in the chassis. This second slot can be used for:

·       An additional server node

·       Four additional LFF HDDs with up to 10 TB capacity per HDD

·       New PCIe expansion tray with up to two x8 half-height, half-width PCIe slots that can use any industry-standard PCIe card including Fibre Channel and Ethernet cards.

The Cisco UCS S3260 Storage Server Chassis includes a Cisco UCS Virtual Interface Card (VIC) 1300 platform chip onboard the system I/O controller, offering high-performance bandwidth with dual-port 40 Gigabit Ethernet and FCoE interfaces per system I/O controller.

Figure 15     Cisco UCS S3260 Storage Server: Rear View

Cisco UCS Virtual Interface Cards (VICs)

Cisco UCS VIC 1387

Cisco UCS Virtual Interface Cards (VIC) are unique to Cisco. Cisco UCS Virtual Interface Cards incorporate next-generation converged network adapter (CNA) technology from Cisco and offer dual 10- and 40-Gbps ports designed for use with Cisco UCS servers. Optimized for virtualized networking, these cards deliver high performance and bandwidth utilization, and support up to 256 virtual devices.

The Cisco UCS Virtual Interface Card 1387 (Figure 16) offers dual-port Enhanced Quad Small Form-Factor Pluggable (QSFP+) 40 Gigabit Ethernet and Fiber Channel over Ethernet (FCoE) in a modular-LAN-on-motherboard (mLOM) form factor. The mLOM slot can be used to install a Cisco VIC without consuming a PCIe slot providing greater I/O expandability.

Figure 16     Cisco UCS VIC 1387

Cisco UCS VIC 1457

The Cisco UCS VIC 1457 (Figure 17) is a quad-port Small Form-Factor Pluggable (SFP28) mLOM card designed for the M5 generation of Cisco UCS C-Series Rack Servers. The card supports 10/25-Gbps Ethernet or FCoE. The card can present PCIe standards-compliant interfaces to the host, and these can be dynamically configured as either NICs or HBAs.

Figure 17     Cisco UCS VIC 1457

Cloudera Data Platform (CDP) Data Center

CDP is an integrated data platform that is easy to deploy, manage, and use. By simplifying operations, CDP reduces the time to onboard new use cases across the organization. It uses machine learning to intelligently auto scale workloads up and down for more cost-effective use of cloud infrastructure.

Cloudera Data Platform (CDP) Data Center is the on-premises version of Cloudera Data Platform. This new product combines the best of both worlds i.e. Cloudera Enterprise Data Hub and Hortonworks Data Platform Enterprise along with new features and enhancements across the stack. This unified distribution is a scalable and customizable platform where you can securely run many types of workloads.

Figure 18     Cloudera Data Platform – Unity Release

Cloudera Data Platform provides:

·       Unified Distribution: Whether you are coming from CDH or HDP, CDP caters both. It offers richer feature sets and bug fixes with concentrated development and higher velocity.

·       Hybrid & On-prem: Hybrid and multi-cloud experience, on-prem it offers best performance, cost, and security. It is designed for data centers with optimal infrastructure.

·       Management: It provides consistent management and control points for deployments.

·       Consistency: Security and governance policies can be configured once and applied across all data and workloads.

·       Portability: Policies stickiness with data, even if it moves across all supported infrastructure.

Apache Ozone (Tech preview)

Ozone is a scalable, redundant, and distributed object store optimized for big data workloads. Apart from scaling to billions of objects of varying sizes, Ozone can function effectively in containerized environments such as Kubernetes and YARN.

Ozone consists of three important storage elements: volumes, buckets, and keys. Each key is part of a bucket, which, in turn, belongs to a volume. Only an administrator can create volumes. Depending on their requirements, users can create buckets in volumes. Ozone stores data as keys inside these buckets.

When a key is written to Ozone, the associated data is stored on the DataNodes in chunks called blocks. Therefore, each key is associated with one or more blocks. Within the DataNodes, a series of unrelated blocks is stored in a container, allowing many blocks to be managed as a single entity.

Ozone separates management of namespaces and storage, helping it to scale effectively. Ozone Manager manages the namespaces while Storage Container Manager handles the containers.

Figure 19     Basic Architecture for Ozone

Ozone is available for technical preview and considered to be under development. Do not use this component in your production systems.

Red Hat Ansible Automation

This solution uses Red Hat Ansible Automation for all pre and post deployment steps for automating repeatable tasks to maintain consistency.

Red Hat Ansible Automation is a powerful IT automation tool. It is capable of provisioning numerous types of resources and deploying applications. It can configure and manage devices and operating system components. Due to its simplicity, extensibility, and portability, this solution extensively utilizes Ansible for performing repetitive deployment steps across the nodes.

For more information about Ansible, go to: https://www.redhat.com/en/technologies/management/ansible

Solution Design

Requirements

This CVD describes architecture and deployment procedures for Cloudera Data Platform Data Center on a 28-node cluster based on Cisco UCS Integrated Infrastructure for Big Data and Analytics. The solution provides the details to configure CDP DC on the infrastructure.

The cluster configuration consists of the following:

·       2 Cisco UCS 6332UP Fabric Interconnects

·       28 Cisco UCS C240 M5 Rack-Mount servers

·       2 Cisco R42610 standard racks

·       4 Vertical Power distribution units (PDUs) (Country Specific)

Physical Topology

Each rack consists of two vertical PDUs. The first rack consists of two Cisco UCS 6332UP Fabric Interconnects, sixteen Cisco UCS C240 M5 Rack Servers connected to each of the vertical PDUs for redundancy; thereby, ensuring availability during power source failure. The second rack consists of twelve Cisco UCS C240 M5 Servers connected to each of the vertical PDUs for redundancy; thereby, ensuring availability during power source failure, like the first rack. Figure 20 represents a 40 Gigabit Ethernet link from each server is connected to both Fabric Interconnects

Please contact your Cisco representative for country-specific information.

Figure 20     Cisco Data Intelligence Platform - 28 Node Configuration with CDP DC

Port Configuration on Fabric Interconnect

Table 2  lists the port configuration on Cisco UCS FI 6332 Fabric Interconnect.

Table 2    Port Configuration on Fabric Interconnect

Port Type

Port Number

Server

1-28

Network

29-32

Server Configuration and Cabling for Cisco UCS C240 M5

The Cisco UCS C240 M5 Rack Server is equipped with 2 x Intel Xeon Scalable Family Processor 6230 (2 x 20 cores, 2.1 GHz), 384 GB of memory (12 x 32GB @ 2933MHz), Cisco UCS Virtual Interface Card 1387, Cisco 12-Gbps SAS Modular Raid Controller with 4-GB FBWC, 26 x 2.4 TB 10K rpm SFF SAS HDDs or 12 x 1.6 TB Enterprise Value SATA SSDs, M.2 with 2 x 240-GB SSDs for Boot.

Figure 21 illustrates the port connectivity between the Cisco UCS FI 6332 and Cisco UCS C240 M5 Rack Server. 28 Cisco UCS C240 M5 servers are installed in this configuration.

For information on physical connectivity and single-wire management, go to:

https://www.cisco.com/c/en/us/td/docs/unified_computing/ucs/c-series_integration/ucsm4-0/b_C-Series-Integration_UCSM4-0/b_C-Series-Integration_UCSM4-0_chapter_01.html

Figure 21     Fabric Topology for Cisco UCS C240 M5 Rack Server

Software Distributions and Firmware Versions

The software distributions required versions are listed in Table 3

Table 3    Software Distribution and Version

Layer

Component

Version or Release

Compute

Cisco UCS C240 M5

C240M5.4.0.4p

Network

Cisco UCS 6332

UCS 4.0(4g) A

Cisco UCS VIC1387 Firmware

4.3(3b)

Storage

SAS Expander

65.09.16.00

Cisco 12G Modular Raid controller

50.8.0-2649

LSI MegaRAID SAS Driver

07.708.03.00

Software

Red Hat Enterprise Linux Server

7.6

Cisco UCS Manager

4.0(4g)

Cloudera CDP DC

7.0.3

Hadoop

3.1

Spark

2.4

The latest drivers can be downloaded from the link below: https://software.cisco.com/download/home/283862063/type/283853158/release/4.0(4)

Support for Intel second generation scalable family processor added in UCSM version 4.0.4a.

Cisco Intersight

Cisco Intersight provides following features for ease of operations and administrator to the IT staff.

Connected TAC

Connected TAC is an automated transmission of technical support files to the Cisco® Technical Assistance Center (TAC) for accelerated troubleshooting.

Cisco Intersight enables Cisco TAC to automatically generate and upload Tech Support Diagnostic files when a Service Request is opened. If you have devices that are connected to Intersight but not claimed, Cisco TAC can only check the connection status and will not be permitted to generate Tech Support files. When enabled, this feature works in conjunction with the Smart Call Home service and with an appropriate service contract. Devices that are configured with Smart Call Home and claimed in Intersight can use Smart Call Home to open a Service Request and have Intersight collect Tech Support diagnostic files.

Figure 22     Cisco Intersight: Connected TAC

To enable Connected TAC, follow these steps:

1.     Log into Intersight.com

2.     Click the Servers tab. Select Server > Actions tab. From the drop-down list, select Open TAC Case.

3.     Clicking “Open TAC Case” launches Cisco URL for Support case manager where associated service contracts for Server or Fabric Interconnect is displayed.

4.     Click Continue.

5.     Follow the procedure to Open TAC Case.

Cisco Intersight Integration for HCL

Cisco Intersight evaluates the compatibility of your Cisco UCS and Cisco HyperFlex systems to check if the hardware and software have been tested and validated by Cisco or Cisco partners. Cisco Intersight reports validation issues after checking the compatibility of the server model, processor, firmware, adapters, operating system and drivers, and displays the compliance status with the Hardware Compatibility List (HCL).

You can use Cisco UCS Tools, a host utility vSphere Installation Bundle (VIB), or OS Discovery Tool, an open source script to collect OS and driver information to evaluate HCL compliance.

In Intersight, you can view the HCL compliance status in the dashboard (as a widget), the Servers table view, and the Server details page. Below is the server details page.

For more information, go to: https://www.intersight.com/help/features#compliance_with_hardware_compatibility_list_(hcl)

Figure 23     Example of HCL Status and Driver Recommendation for RHEL 7.6

Advisories (PSIRTs)

Cisco Intersight sources critical security advisories from the Cisco Security Advisory service to alert users about the endpoint devices that are impacted by the advisories and deferrals. These alerts are displayed as Advisories in Intersight. The Cisco Security Advisory service identifies and monitors and updates the status of the advisories to provide the latest information on the impacted devices, the severity of the advisory, the impacted products, and any available workarounds. If there are no known workarounds, you can open a support case with Cisco TAC for further assistance. A select list of the security advisories is shown in Intersight under Advisories.

Figure 24     Intersight Dashboard

Figure 25     Example: List of PSIRTs Associated with Sample Intersight Account

Deployment Hardware and Software

Cisco Unified Computing System Configuration

This section details the Cisco Unified Computing System (Cisco UCS) configuration that was done as part of the infrastructure build out. The racking, power, and installation of the Cisco UCS Rack Server is described in the physical topology section earlier in this document. Please refer to the Cisco UCS Manager Getting Started Guide. For more information about each step, see the Cisco UCS Manager - Configuration Guides.

Configure Cisco UCS Fabric Interconnect

This document assumes you are using Cisco UCS Manager Software version 4.0(4c). To upgrade the Cisco UCS Manager software and the Cisco UCS 6332 Fabric Interconnect software to a higher version of the firmware, see the Cisco UCS Manager Install and Upgrade Guides.

Alternatively, if you intend to clear the existing Cisco UCS Manager configuration, follow these steps:

1.     Connect a console cable to the console port on what will become the primary fabric interconnect.

2.     If the fabric interconnects were previously deployed and you want to erase it to redeploy, follow these steps:

a.     Login with the existing username and password.

#connect local-mgmt

#erase config

#yes (to confirm)

3.     After the fabric interconnect restarts, the out-of-box first time installation prompt appears, type “console” and press Enter.

4.     Follow the Initial Configuration steps as outlined in Cisco UCS Manager Getting Started Guide. When configured, log into UCSM IP Address via the web interface to perform the base Cisco UCS configuration.

Configure Fabric Interconnects for a Cluster Setup

To configure the Cisco UCS Fabric Interconnects, follow these steps:

1.     Verify the following physical connections on the fabric interconnect:

-      The management Ethernet port (mgmt0) is connected to an external hub, switch, or router.

-      The L1 ports on both fabric interconnects are directly connected to each other.

-      The L2 ports on both fabric interconnects are directly connected to each other

Configure Fabric Interconnect A

To configure Fabric Interconnect A, follow these steps:

1.     Connect to the console port on the first Cisco UCS 6332 Fabric Interconnect.

At the prompt to enter the configuration method, enter console to continue.

If asked to either perform a new setup or restore from backup, enter setup to continue.

Enter y to continue to set up a new Fabric Interconnect.

Enter y to enforce strong passwords.

2.     Enter the password for the admin user.

3.     Enter the same password again to confirm the password for the admin user.

When asked if this fabric interconnect is part of a cluster, answer y to continue.

Enter A for the switch fabric.

4.     Enter the cluster name for the system name.

5.     Enter the Mgmt0 IPv4 address.

6.     Enter the Mgmt0 IPv4 netmask.

7.     Enter the IPv4 address of the default gateway.

8.     Enter the cluster IPv4 address.

To configure DNS, answer y.

9.     Enter the DNS IPv4 address.

Answer y to set up the default domain name.

10.  Enter the default domain name.

Review the settings that were printed to the console, and if they are correct, answer yes to save the configuration.

11.  Wait for the login prompt to make sure the configuration has been saved.

Configure Fabric Interconnect B

To configure Fabric Interconnect B, follow these steps:

1.     Connect to the console port on the second Cisco UCS 6332 Fabric Interconnect.

When prompted to enter the configuration method, enter console to continue.

The installer detects the presence of the partner Fabric Interconnect and adds this fabric interconnect to the cluster. Enter y to continue the installation.

2.     Enter the admin password that was configured for the first Fabric Interconnect.

3.     Enter the Mgmt0 IPv4 address.

4.     Answer yes to save the configuration.

5.     Wait for the login prompt to confirm that the configuration has been saved.

For more information about configuring Cisco UCS 6332 Series Fabric Interconnect, go to: https://www.cisco.com/c/en/us/td/docs/unified_computing/ucs/ucs-manager/GUI-User-Guides/Getting-Started/4-0/b_UCSM_Getting_Started_Guide_4_0.html

Log into Cisco UCS Manager

To log into Cisco UCS Manager, follow these steps:

1.     Open a Web browser and navigate to the Cisco UCS 6332 Fabric Interconnect cluster address.

2.     Click the Launch link to download the Cisco UCS Manager software.

3.     If prompted to accept security certificates, accept as necessary.

4.     When prompted, enter admin for the username and enter the administrative password.

5.     Click Login to log into the Cisco UCS Manager.

Upgrade Cisco UCS Manager Software to Version 4.0(4g)

This document assumes you’re using Cisco UCS 4.0(4g). Refer to the Cisco UCS 4.0 Release  (upgrade Cisco UCS Manager software and Cisco UCS 6332 Fabric Interconnect software to version 4.0(4g) ). Also, make sure the Cisco UCS C-Series version 4.0(4g) software bundles are installed on the Fabric Interconnects.

Upgrading Cisco UCS firmware is beyond the scope of this document. However for complete Cisco UCS Install and Upgrade Guides, go to: https://www.cisco.com/c/en/us/support/servers-unified-computing/ucs-manager/products-installation-guides-list.html

Register UCSM with Intersight

To register UCSM with Intersight, follow these steps:

1.     Login WebUI for Cisco UCS Manager, go to admin tab. Select Device Connector from the drop-down list. Click Settings.

2.     Enable Device Connector. Select Allow Control in Access Mode.

3.     Complete steps for DNS configuration, NTP Configuration and Proxy Configuration as applicable. Click Save.

4.     Make sure UCSM can communicate to Intersight.

5.     Copy Device Claim ID from right side of Device Connector screen.

6.     Log into Intersight.com

7.     Select Devices tab on the left side menu; Click Claim a New Device.

8.     Enter Device ID and Device Claim Code copied from UCS Manager. Click Claim.

9.     Once Claimed, UCSM can be launched directly from Intersight.

10.  Click Launch UCSM.

For more information, go to: Claiming a Device

For this study, we launched UCSM through Intersight. UCSM WebUI can also be accessed the traditional way which is by entering the IP address of Cisco UCS Manager in a Web Browser. For more information, go to: https://www.cisco.com/c/en/us/td/docs/unified_computing/ucs/UCS_CVDs/Cisco_UCS_Data_Intelligence_Platform_with_Cloudera_and_CDSW.html

Configure Cisco UCS Manager through Intersight

To configure Cisco UCS Manager, follow these high-level steps:

1.     Configure Fabric Interconnects for a Cluster Setup.

2.     Set Fabric Interconnects to Fibre Channel End Host Mode.

3.     Synchronize Cisco UCS to NTP.

4.     Configure Fabric Interconnects for Rack or Chassis and Blade Server Discovery.

5.     Configure Global Policies.

6.     Configure Server Ports.

7.     Configure LAN on Cisco UCS Manager.

8.     Configure Ethernet LAN Uplink Ports.

9.     Set QoS system class and Jumbo Frames in both the Cisco Fabric Interconnect.

10.  Create Uplink Port Channels to Cisco Nexus Switches.

11.  Configure FC SAN Uplink Ports

12.  Configure VLAN

13.  Configure IP, UUID, Server, MAC Pool and policy:

a.     IP Pool Creation

b.     UUID Suffix Pool Creation

c.     Server Pool Creation

d.     Configure Server BIOS Policy.

e.     Create Adapter Policy.

f.      Configure Default Maintenance Policy.

g.     Configure vNIC Template

h.     Create Server Boot Policy

Details for each step are discussed in the following sections.

Synchronize Cisco UCSM to NTP

To synchronize the Cisco UCS environment to the NTP server, follow these steps:

1.     In Cisco UCS Manager, in the navigation pane, click the Admin tab.

2.     Select All > Time zone Management.

3.     In the Properties pane, select the appropriate time zone in the Time zone menu.

4.     Click Save Changes and then click OK.

5.     Click Add NTP Server.

6.     Enter the NTP server IP address and click OK.

7.     Click OK to finish.

8.     Click Save Changes.

Figure 26     Synchronize Cisco UCS Manager to NTP

Configure Global Policies

The rack server and chassis discovery policy determine how the system reacts when you add a new rack server or chassis. We recommend using the platform max value as shown. Using platform max helps ensure that Cisco UCS Manager uses the maximum number of IOM uplinks available.

To configure the global policies, follow this step:

1.     In Cisco UCS Manager; Configure Global Policy. Go to Equipment > Policies (right pane) > Global Policies.

Figure 27     Global Policies in UCSM

Configure Server Ports

Configure Server Ports to initiate Chassis and Blade discovery. To configure server ports, follow these steps:

1.     Go to Equipment > Fabric Interconnects > Fabric Interconnect A > Fixed Module > Ethernet Ports.

2.     Select the ports (for this solution ports are 1-28) which are connected to the Cisco UCS VIC 1387 on Cisco UCS C240 M5 rack server.

3.     Right-click and select Configure as Server Port.

Figure 28     Configure Server Port on Cisco UCS Manager Fabric Interconnect for Server/Chassis Discovery

Configure Uplink Ports

Configure Network Ports to connect to the data center network switch.

In our solution study, we connected to Nexus 9000 series switch.

To configure Network ports, follow these steps:

1.     Go to Equipment > Fabric Interconnects > Fabric Interconnect A > Fixed Module > Ethernet Ports.

2.     Select the ports (for this solution ports are 29-32) which are connected to the Cisco Nexus 9000 series switch for northbound network connectivity.

3.     Right-click and select Configure as Network Port.

Figure 29     Configure Network Port on Cisco UCS Manager Fabric Interconnect

Create New Organization

To configure the necessary Organization for the Cisco UCS environment, follow these steps:

1.     In Cisco UCS Manager, click the Servers tab in the navigation pane.

2.     Select root > Sub-Organization.

3.     Right-click, select Create Sub-Organization.

4.     Enter the name of the Organization.

5.     Click OK.

Figure 30     Create New Organization

Cisco UCS Manager pools and policies required for this solution were created under new “UCS-BDA-CDP” Organization created.

Configure IP, UUID, Server and MAC Pools

IP Pool Creation

An IP address pool on the out-of-band management network must be created to facilitate KVM access to each compute node in the Cisco UCS domain. To create a block of IP addresses for server KVM access in the Cisco UCS environment, follow these steps:

1.     In Cisco UCS Manager, in the navigation pane, click the LAN tab.

2.     Select Pools > root > Sub-Organizations > UCS-BDA-CDP> IP Pools > click Create IP Pool.

3.     Enter name for the IP Pool, select option Sequential to assign IP in sequential order then click Next.

4.     Click Add IPv4 Block.

5.     Enter the starting IP address of the block and the number of IP addresses required, and the subnet and gateway information as shown below.

UUID Suffix Pool Creation

To configure the necessary universally unique identifier (UUID) suffix pool for the Cisco UCS environment, follow these steps:

1.     In Cisco UCS Manager, click the Servers tab in the navigation pane.

2.     Select Pools > root > Sub-Organization > UCS-BDA-CDP.

3.     Right-click UUID Suffix Pools and then select Create UUID Suffix Pool.

4.     Enter the name of the UUID name.

5.     Optional: Enter a description for the UUID pool.

6.     Keep the prefix at the derived option and select Sequential in as Assignment Order then click Next.

Figure 31     UUID Suffix Pool Creation

Figure 32     Create a Block of UUID Suffixes

Server Pool Creation

To configure the necessary server pool for the Cisco UCS environment, follow these steps:

Consider creating unique server pools to achieve the granularity that is required in your environment.

1.     In Cisco UCS Manager, click the Servers tab in the navigation pane.

2.     Select Pools > root > Sub-Organization > UCS-BDA-CDP > right-click Server Pools > Select Create Server Pool.

3.     Enter name of the server pool.

4.     Optional: Enter a description for the server pool then click Next.

Figure 33     Create Server Pool

5.     Select servers to be used for the deployment and click > to add them to the server pool. In our case we added thirty servers in this server pool.

6.     Click Finish and then click OK.

Figure 34     Add Server in the Server Pool

7.     Once the added Servers are in the Pooled servers, click Finish.

MAC Pool Creation

To configure the necessary MAC address pools for the Cisco UCS environment, follow these steps:

1.     In Cisco UCS Manager, click the LAN tab in the navigation pane.

2.     Select Pools > root > Sub-Organization > UCS-BDA-CDP> right-click MAC Pools.

3.     Select Create MAC Pool to create the MAC address pool.

4.     Enter name for MAC pool. Select Assignment Order as “Sequential”.

5.     Enter the seed MAC address and provide the number of MAC addresses to be provisioned.

6.     Click OK and then click Finish.

7.     In the confirmation message, click OK.

Figure 35     Creating a Block of MAC Addresses

Configure VLAN

To configure the necessary virtual local area networks (VLANs) for the Cisco UCS environment, follow these steps:

1.     In Cisco UCS Manager, click the LAN tab in the navigation pane.

2.     Select LAN > LAN Cloud.

3.     Right-click VLANs

4.     Select Create VLANs

5.     Enter the name of the VLAN to be used.

6.     Keep the Common/Global option selected for the scope of the VLAN.

7.     Enter <VLAN Number> as the ID of the VLAN ID.

8.     Keep the Sharing Type as None.

Figure 36     Create VLAN

The NIC will carry the data traffic from VLAN13. A single vNIC is used in this configuration and the Fabric Failover feature in Fabric Interconnects will take care of any physical port down issues. It will be a seamless transition from an application perspective.

Figure 37     Create VLANs

Set System Class QoS and Jumbo Frame in Both Cisco Fabric Interconnects

To configure jumbo frames and enable quality of service in the Cisco UCS fabric, follow these steps:

1.     In Cisco UCS Manager, click the LAN tab in the navigation pane.

2.     Select LAN > LAN Cloud > QoS System Class.

3.     In the right pane, click the General tab.

4.     On the Platinum row, enter 9216 in the box under the MTU column.

5.     Click Save Changes.

6.     Click OK.

Changing the QoS system class MTU requires a reboot of Cisco UCS Fabric Interconnect for changes to be effective.

Figure 38     Configure System Class QoS on Cisco UCS Fabric Interconnects

Create QoS Policies

To create the QoS policy to assign priority based on the class using the Cisco UCS Manager GUI, follow these steps:

1.     Select LAN tab in the left pane in the Cisco UCS Manager GUI.

2.     Select LAN > Policies > root > UCS-BDA-CDP> QoS Policies.

3.     Right-click QoS Policies.

4.     Select Create QoS Policy.

Figure 39     Create QoS Policy

We created a Platinum class QoS policy for this solution.

Figure 40     Platinum QoS Policy

Create vNIC Templates

To create multiple virtual network interface card (vNIC) templates for the Cisco UCS environment, follow these steps:

1.     In Cisco UCS Manager, click the LAN tab in the navigation pane.

2.     Select Policies > root > Sub-Organization > UCS-BDA-CDP> vNIC Template.

3.     Right-click vNIC Templates.

4.     Select Create vNIC Template.

5.     Enter name for vNIC template.

6.     Keep Fabric A selected. Select the Enable Failover checkbox.

7.     Select Updating Template as the Template Type.

8.     Under VLANs, select the checkboxes for desired VLANs to add as part of the vNIC Template.

9.     Set Native-VLAN as the native VLAN.

10.  For MTU, enter 9000.

11.  In the MAC Pool list, select MAC Pool configured.

12.  Select QOS policy created earlier.

13.  Select default Network Control Policy.

14.  Click OK to create the vNIC template.

Figure 41     Create the vNIC Template

Create Host Firmware Package

Firmware management policies allow the administrator to select the corresponding packages for a given server configuration. These policies often include packages for adapter, BIOS, board controller, FC adapters, host bus adapter (HBA) option ROM, and storage controller properties.

To create a firmware management policy for a given server configuration in the Cisco UCS environment, follow these steps:

1.     In Cisco UCS Manager, click the Servers tab in the navigation pane.

2.     Select Policies > root > Sub-Organization > UCS-BDA-CDP> Host Firmware Packages.

3.     Right-click Host Firmware Packages.

4.     Select Create Host Firmware Package.

5.     Enter name of the host firmware package.

6.     Leave Simple selected.

7.     Select the version.

8.     Click OK to create the host firmware package.

Figure 42     Host Firmware Package

Create Power Control Policy

To create a power control policy for the Cisco UCS environment, follow these steps:

1.     In Cisco UCS Manager, click the Servers tab in the navigation pane.

2.     Select Policies > root > Sub-Organization > UCS-BDA-CDP> Power Control Policies.

3.     Right-click Power Control Policies.

4.     Select Create Power Control Policy.

5.     Select Fan Speed Policy as “Max Power”.

6.     Enter NoPowerCap as the power control policy name.

7.     Change the power capping setting to No Cap.

8.     Click OK to create the power control policy.

Figure 43     Create Power Control Policy

Create Server BIOS Policy

To create a server BIOS policy for the Cisco UCS environment, follow these steps:

1.     In Cisco UCS Manager, click the Servers tab in the navigation pane.

2.     Select Policies > root > Sub-Organization > UCS-BDA-CDP> BIOS Policies.

3.     Right-click BIOS Policies.

4.     Select Create BIOS Policy.

5.     Enter the BIOS policy name.

Figure 44     BIOS Configuration

For more information, go to: Performance Tuning Guide.

BIOS settings can have a significant performance impact, depending on the workload and the applications. The BIOS settings listed in this section is for configurations optimized for best performance which can be adjusted based on the application, performance, and energy efficiency requirements.

Configure Maintenance Policy

To update the default Maintenance Policy, follow these steps:

1.     In Cisco UCS Manager, click the Servers tab in the navigation pane.

2.     Select Policies > root > Sub-Organization > UCS-BDA-CDP> Maintenance Policies.

3.     Right-click Maintenance Policies to create a new policy.

4.     Enter name for Maintenance Policy.

5.     Change the Reboot Policy to User Ack.

6.     Click Save Changes.

7.     Click OK to accept the change.

Figure 45     Create Server Maintenance Policy

Create the Local Disk Configuration Policy

To create local disk configuration in the Cisco UCS Manager GUI, follow these steps:

1.     Select the Servers tab in the Cisco UCS Manager GUI.

2.     Select Policies > root > Sub-Organization > UCS-BDA-CDP> Local Disk Config Policies.

3.     Right-click Local Disk Config Policies and Select Create Local Disk Config Policies.

4.     Enter UCS-Boot as the local disk configuration policy name.

5.     Change the Mode to Any Configuration. Check the Protect Configuration box.

6.     Keep the FlexFlash State field as default (Disable).

7.     Keep the FlexFlash RAID Reporting State field as default (Disable).

8.     Click OK to complete the creation of the Local Disk Configuration Policy.

9.     Click OK.

Figure 46     Create the Local Disk Configuration Policy

Create Boot Policy

To create boot policies within the Cisco UCS Manager GUI, follow these steps:

1.     Select the Servers tab in the Cisco UCS Manager GUI.

2.     Select Policies > root.

3.     Right-click the Boot Policies.

4.     Select Create Boot Policy.

5.     Enter ucs for the boot policy name.

6.     (Optional) enter a description for the boot policy.

7.     Keep the Reboot on Boot Order Change check box unchecked.

8.     Keep Enforce vNIC/vHBA/iSCSI Name check box checked.

9.     Keep Boot Mode Default (Legacy).

10.  Expand Local Devices > Add CD/DVD and select Add Local CD/DVD.

11.  Expand Local Devices and select Add Local Disk.

12.  Expand vNICs and select Add LAN Boot and enter eth0.

13.  Click OK to add the Boot Policy.

14.  Click OK.

Figure 47     Create Boot Policy for Cisco UCS Server(s)

Create Storage Profile for Individual RAID0

To create the storage profile for the individual RAIDP, follow these steps:

1.     On the UCSM navigation page, select the Storage tab.

2.     From the Storage Profiles drop-down list, right-click and select Create Storage Profile.

Figure 48     Create Storage Profile

3.     Enter a name for the Storage Profile and click the LUN Set tab.

4.     Click Add.

The LUN Set policy configures all disks managed through Cisco UCS S3260 Dual Raid Controller on S3260 and Cisco 12G Modular Raid controller to individual disk RAID0.

5.     Select the properties for the LUN set:

a.     Enter a name for LUN set.

b.     Disk Slot Range – 1 – 24/26/56 (Depends on number of drives installed in a server).

c.     Enter Virtual Drive configuration:

i.    Strip Size(kb) – 1024KB

ii.    Access Policy – Read Write

iii.    Read Policy – Read Ahead

iv.    Write Cache Policy – Write Back Good Bbu

v.    IO Policy – Direct

vi.    Drive Cache – Disable

For a LUN set based configuration, set the JBOD disks to unconfigured by selecting all JBOD disk in Server > Inventory > Disks, right-click and select “Set JBOD to Unconfigured Good.”

Figure 49     Set JBOD Disks to Unconfigured Good

Create Storage Policy and Storage Profile

To create a Storage Profile with multiple RAID LUNs, create Storage Policies and attach them to a Storage Profile.

To create a Storage Policy and attach them to a Storage Profile, follow these steps:

1.     Go to the Storage tab on the left side panel selection, select “Storage Policies”.

2.     From the Storage Policies drop-down list, select and right-click “Disk Group Policies”. Select “Create Disk Group Policy”.

3.     Enter name for Disk Group Policy, Select RAID level.

4.     Select “Disk Group Configuration” (Automatic/Manual).

5.     Disk Group Configuration.

6.     Virtual Drive Configuration.

7.     Select Storage Profiles, right-click and select Create Storage Profile.

8.     Enter a name for the Storage profile and click Add.

9.     Enter a Local LUN name and select Auto Deploy.

10.  Check the box for Expand to Available and from the drop-down list select the storage policy you want to attach with the Storage Profile. Click OK.

For Cisco UCS S3260, we created a Storage Profile with a Storage Policy to create a Boot LUN and attached it to a Storage Profile as shown above. The LUN set policy for an individual server node (server node 1 and server node 2) to create an individual RAID0.

Create Service Profile Template

To create a service profile template, follow these steps:

1.     In the Cisco UCS Manager, go to Servers > Service Profile Templates > root Sub Organization > UCS-BDA-CDP> and right-click “Create Service Profile Template” as shown below.

2.     Enter the Service Profile Template name, Updating Template as type of template and select the UUID Pool that was created earlier. Click Next.

3.     Select Local Disk Configuration Policy tab and select Local Storage policy from the drop-down list.

4.     On Storage Profile Policy, select the Storage Profile to attach with the server.

Based on the server model or the role of the server, we created and attached a Storage Profile for NameNode(s), DataNode(s) and Cisco UCS S3260 Storage server in different Service Profile Template for each.

5.     In the networking window, select “Expert” and click “Add” to create vNICs. Add one or more vNICs that the server should use to connect to the LAN.

6.     In the create vNIC menu as vNIC name.

7.     Select vNIC Template as vNIC0 and Adapter Policy as Linux.

Optionally, Network Bonding can be setup on the vNICs for each host for redundancy as well as for increased throughput.

8.     In the SAN Connectivity menu, select no vHBAs.

9.     Click Next in the Zoning tab.

10.  Select Let System Perform Placement for vNIC/vHBA Placement. Click Next.

11.  Click Next in the vMedia Policy tab.

12.  Select Boot Policy in the Server Boot Order tab.

13.  Select UserAck maintenance policy, which requires user acknowledgement prior rebooting server when making changes to policy or pool configuration tied to a service profile.

14.  Select the Server Pool policy to automatically assign a service profile to a server that meets the requirements for server qualification based on the pool configuration. Select Power state when the Service Profile is associated to server

15.  On the same page you can configure “Host firmware Package Policy” which helps to keep the firmware in sync when associated to server.

On the Operational Policy page, we configured the BIOS policy for a Cisco UCS C240 M5 Rack server with the Power Control Policy set to “NoPowerCap” for maximum performance.

16.  Click Finish to create the Service Profile template.

Create Service Profiles from Template

To create a Service Profile from a template, follow these steps:

1.     Right-click the Service Profile Template and select Create Service profile from Template.

Figure 50     Create Service Profile from Template

The Service profile will automatically assign to servers discovered and meets the requirement of Server Pool.

2.     Repeat the steps above to create service profile template(s) and service profile(s) according to different deployment scenario.

Install Red Hat Enterprise Linux 7.6

This section provides detailed procedures for installing Red Hat Enterprise Linux Server using Software RAID (OS based Mirroring) on Cisco UCS C240 M5 servers. There are multiple ways to install the RHEL operating system. The installation procedure described in this deployment guide uses KVM console and virtual media from Cisco UCS Manager.

In this study, RHEL version 7.6 DVD/ISO was utilized for OS the installation on Cisco UCS C240 M5 Rack Servers.

To install the Red Hat Enterprise Linux 7.6 operating system, follow these steps:

1.     Log into the Cisco UCS Manager.

2.     Select the Equipment tab.

3.     In the navigation pane expand Rack-Mounts and then Servers.

4.     Right-click the server and select KVM console.

5.     In the right pane, click the KVM Console >>.

6.     Click the link to launch the KVM console.

7.     Point the cursor over the top right corner and select the Virtual Media tab.

8.     Click the Activate Virtual Devices found in Virtual Media tab.

9.     Click the Virtual Media tab to select CD/DVD.

10.  Select Map Drive in the Virtual Disk Management windows.

11.  Browse to the Red Hat Enterprise Linux 7.6 installer ISO image file.

The Red Hat Enterprise Linux 7.6 Server DVD is assumed to be on the client machine.

12.  Click Open to add the image to the list of virtual media.

13.  Select the Installation option from Red Hat Enterprise Linux 7.6.

14.  Select the language for the installation and click Continue.

15.  Select date and time, which pops up another window as shown below.

16.  Select the location on the map, set the time, and click Done.

17.  Click Installation Destination.

18.  This opens a new window with the boot disks. Make the selection and choose “I will configure partitioning”. Click Done. We selected two M.2 SATA SSDs.

19.  This opens a window to create the partitions. Click the + sign to add a new partition as shown below with a boot partition size 2048 MB.

20.  Click Add Mount Point to add the partition.

21.  Change the device type to RAID and make sure the RAID level is RAID1 (redundancy) and click Update Settings to save the changes.

22.  Click the + sign to create the swap partition of size 2048 MB. Click Add Mount Point.

23.  Change the Device type to RAID and RAID level to RAID1 (Redundancy) and click Update Settings.

24.  Click + to add the / partition. The size can be left empty so it will use the remaining capacity. Click Add Mountpoint.

25.  Change the Device type to RAID and RAID level to RAID1 (Redundancy). Click Update Settings.

26.  Accept Changes.

27.  Click Done to go back to the main screen and continue the Installation.

28.  Click Software Selection.

29.  Select Infrastructure Server and select the Add-Ons as noted below, then click Done:

a.     Network File System Client

b.     Performance Tools

c.     Compatibility Libraries

d.     Development Tools

e.     Security Tools

30.  Click Network and Hostname and configure Hostname and Networking for the Host.

31.  Type in the hostname as shown below.

32.  Click Configure to open the Network Connectivity window. Click IPv4 Settings.

33.  Change the Method to Manual and click Add to enter the IP Address, Netmask and Gateway details.

34.  Click Save, update the hostname, and turn Ethernet ON. Click Done to return to the main menu.

35.  Click Begin Installation in the main menu.

36.  Select Root Password in the User Settings.

37.  Enter the Root Password and click Done.

38.  Once the installation is complete, reboot the system.

39.  Repeat steps 1 to 38 to install Red Hat Enterprise Linux 7.6 on Servers 2 through 30.

The OS installation and configuration of the nodes that is mentioned above can be automated through PXE boot or third-party tools.

Please see the Appendix, section Configure Cisco Boot Optimized M.2 RAID Controller for Installation steps for Cisco Boot Optimized M.2 RAID Controller.

The hostnames and their corresponding IP addresses are shown in Table 4  .

Table 4    Hostname and IP address

Hostname

Eth0

rhel01

10.13.1.31

rhel02

10.13.1.32

rhel03

10.13.1.33

rhel04

10.13.1.34

rhel05

10.13.1.35

…..

…..

Rhel29

10.13.1.59

Rhel30

10.13.1.60

Multi-homing configuration is not recommended in this design, so please assign only one network interface on each host.

For simplicity, outbound NATing is configured for internet access when desired, such as accessing public repos and/or accessing Red Hat Content Delivery Network. However, configuring outbound NAT is beyond the scope of this document.

Post OS Install Configuration

Choose one of the nodes of the cluster or a separate node as the Admin Node for management, such as CDP DC installation, Ansible, creating a local Red Hat repo, and others. In this document, we used rhel01 for this purpose.

Configure /etc/hosts

Setup /etc/hosts on the Admin node; this is a pre-configuration to setup DNS as shown in the next section.

For the purpose of simplicity, /etc/hosts file is configured with hostnames in all the nodes. However, in large scale production grade deployment, DNS server setup is highly recommended. Furthermore, /etc/hosts file is not copied into containers running on the platform.

Below are the sample A records for DNS configuration within Linux environment:

ORIGIN hdp3.cisco.local

rhel01   A 10.13.1.31

rhel02   A 10.13.1.32

rhel03   A 10.13.1.33

…

…

rhel29  A 10.13.1.59

rhel30  A 10.13.1.60

To create the host file on the admin node, follow these steps:

1.     Log into the Admin Node (rhel01).

#ssh 10.13.1.31

2.     Populate the host file with IP addresses and corresponding hostnames on the Admin node (rhel01) and other nodes as follows:

3.     On Admin Node (rhel01):

[root@rhel01 ~]# cat /etc/hosts

127.0.0.1   localhost localhost.localdomain localhost4 localhost4.localdomain4

::1         localhost localhost.localdomain localhost6 localhost6.localdomain6

10.13.1.31 rhel01.cdp.cisco.local

10.13.1.32 rhel02.cdp.cisco.local

10.13.1.33 rhel03.cdp.cisco.local

10.13.1.34 rhel04.cdp.cisco.local

10.13.1.35 rhel05.cdp.cisco.local

10.13.1.36 rhel06.cdp.cisco.local

10.13.1.37 rhel07.cdp.cisco.local

10.13.1.38 rhel08.cdp.cisco.local

10.13.1.39 rhel09.cdp.cisco.local

10.13.1.40 rhel10.cdp.cisco.local

10.13.1.41 rhel11.cdp.cisco.local

10.13.1.42 rhel12.cdp.cisco.local

10.13.1.43 rhel13.cdp.cisco.local

10.13.1.44 rhel14.cdp.cisco.local

10.13.1.45 rhel15.cdp.cisco.local

10.13.1.46 rhel16.cdp.cisco.local

10.13.1.47 rhel17.cdp.cisco.local

10.13.1.48 rhel18.cdp.cisco.local

10.13.1.49 rhel19.cdp.cisco.local

10.13.1.50 rhel20.cdp.cisco.local

10.13.1.51 rhel21.cdp.cisco.local

10.13.1.52 rhel22.cdp.cisco.local

10.13.1.53 rhel23.cdp.cisco.local

10.13.1.54 rhel24.cdp.cisco.local

10.13.1.55 rhel25.cdp.cisco.local

10.13.1.56 rhel26.cdp.cisco.local

10.13.1.57 rhel27.cdp.cisco.local

10.13.1.58 rhel28.cdp.cisco.local

Set Up Passwordless Login

To manage all the nodes in a cluster from the admin node password-less login needs to be setup. It assists in automating common tasks with Ansible, and shell-scripts without having to use passwords.

To enable password-less login across all the nodes when Red Hat Linux is installed across all the nodes in the cluster, follow these steps:

1.     Log into the Admin Node (rhel01).

#ssh 10.13.1.31

2.     Run the ssh-keygen command to create both public and private keys on the admin node.

# ssh-keygen -N '' -f ~/.ssh/id_rsa

Figure 51     Ssh-keygen

3.     Run the following command from the admin node to copy the public key id_rsa.pub to all the nodes of the cluster.  ssh-copy-id appends the keys to the remote-hosts .ssh/authorized_keys.

# for i in {01..28}; do    echo "copying rhel$i.cdp.cisco.local"; ssh-copy-id -i ~/.ssh/id_rsa.pub root@rhel$i.cdp.cisco.local; done;

4.     Enter yes for Are you sure you want to continue connecting (yes/no)?

5.     Enter the password of the remote host.

Create a Red Hat Enterprise Linux (RHEL) 7.6 Local Repository

To create a repository using RHEL DVD or ISO on the admin node (in this deployment rhel01 is used for this purpose), create a directory with all the required RPMs, run the “createrepo” command and then publish the resulting repository.

To create a RHEL 7.6 local repository, follow these steps:

1.     Log into rhel01. Create a directory that would contain the repository.

# mkdir -p /var/www/html/rhelrepo

2.     Copy the contents of the Red Hat DVD to /var/www/html/rhelrepo

3.     Alternatively, if you have access to a Red Hat ISO Image, Copy the ISO file to rhel01.

4.     Log back into rhel01 and create the mount directory.

# scp rhel-server-7.6-x86_64-dvd.iso rhel01:/root/

# mkdir -p /mnt/rheliso

# mount -t iso9660 -o loop /root/rhel-server-7.6-x86_64-dvd.iso /mnt/rheliso/

5.     Copy the contents of the ISO to the /var/www/html/rhelrepo directory.

# cp -r /mnt/rheliso/* /var/www/html/rhelrepo

6.     On rhel01 create a .repo file to enable the use of the yum command.

# vi /var/www/html/rhelrepo/rheliso.repo

[rhel7.6]

name=Red Hat Enterprise Linux 7.6

baseurl=http://10.13.1.31/rhelrepo

gpgcheck=0

enabled=1

7.     Copy rheliso.repo file from /var/www/html/rhelrepo to /etc/yum.repos.d on rhel01.

# cp /var/www/html/rhelrepo/rheliso.repo /etc/yum.repos.d/

Based on this repository file, yum requires httpd to be running on rhel01 for other nodes to access the repository.

8.     To make use of repository files on rhel01 without httpd, edit the baseurl of repo file /etc/yum.repos.d/rheliso.repo to point repository location in the file system.

This step is needed to install software on Admin Node (rhel01) using the repo (such as httpd, create-repo, and so on.)

# vi /etc/yum.repos.d/rheliso.repo

[rhel7.6]

name=Red Hat Enterprise Linux 7.6

baseurl=file:///var/www/html/rhelrepo

gpgcheck=0

enabled=1

Create the Red Hat Repository Database

To create the Red Hat repository database, follow these steps:

1.     Install the “createrepo” package on admin node (rhel01). Use it to regenerate the repository database(s) for the local copy of the RHEL DVD contents.

# yum -y install createrepo

2.     Run “createrepo” on the RHEL repository to create the repo database on admin node

# cd /var/www/html/rhelrepo

# createrepo .

Figure 52     createrepo

Set Up Ansible

To set up Ansible, follow these steps:

1.     Download Ansible rpm from the following link: https://releases.ansible.com/ansible/rpm/release/epel-7-x86_64/ansible-2.7.11-1.el7.ans.noarch.rpm

# wget https://releases.ansible.com/ansible/rpm/release/epel-7-x86_64/ansible-2.7.11-1.el7.ans.noarch.rpm

2.     Run the following command to install ansible:

# yum localinstall -y ansible-2.7.11-1.el7.ans.noarch.rpm

3.     Verify Ansible installation by running the following commands:

# ansible --version

ansible 2.7.11

config file = /etc/ansible/ansible.cfg

configured module search path = [u'/root/.ansible/plugins/modules', u'/usr/share/ansible/plugins/modules']

ansible python module location = /usr/lib/python2.7/site-packages/ansible

executable location = /usr/bin/ansible

python version = 2.7.5 (default, Sep 12 2018, 05:31:16) [GCC 4.8.5 20150623 (Red Hat 4.8.5-36)]

# ansible localhost -m ping

[WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all'

localhost | SUCCESS => {

"changed": false,

"failed": false,

"ping": "pong"

}

4.     Prepare the host inventory file for Ansible as shown below. Various host groups have been created based on any specific installation requirements of certain hosts.

[root@rhel01 ~]# cat /etc/ansible/hosts

[admin]

rhel01.cdp.cisco.local

[namenodes]

rhel01.cdp.cisco.local

rhel02.cdp.cisco.local

rhel03.cdp.cisco.local

[datanodes]

rhel04.cdp.cisco.local

rhel05.cdp.cisco.local

rhel06.cdp.cisco.local

rhel07.cdp.cisco.local

rhel08.cdp.cisco.local

rhel09.cdp.cisco.local

rhel10.cdp.cisco.local

rhel11.cdp.cisco.local

rhel12.cdp.cisco.local

rhel13.cdp.cisco.local

rhel14.cdp.cisco.local

rhel15.cdp.cisco.local

rhel16.cdp.cisco.local

rhel17.cdp.cisco.local

rhel18.cdp.cisco.local

rhel19.cdp.cisco.local

rhel20.cdp.cisco.local

rhel21.cdp.cisco.local

rhel22.cdp.cisco.local

rhel23.cdp.cisco.local

rhel24.cdp.cisco.local

rhel25.cdp.cisco.local

rhel26.cdp.cisco.local

rhel27.cdp.cisco.local

rhel28.cdp.cisco.local

[nodes]

rhel01.cdp.cisco.local

rhel02.cdp.cisco.local

rhel03.cdp.cisco.local

rhel04.cdp.cisco.local

rhel05.cdp.cisco.local

rhel06.cdp.cisco.local

rhel07.cdp.cisco.local

rhel08.cdp.cisco.local

rhel09.cdp.cisco.local

rhel10.cdp.cisco.local

rhel11.cdp.cisco.local

rhel12.cdp.cisco.local

rhel13.cdp.cisco.local

rhel14.cdp.cisco.local

rhel15.cdp.cisco.local

rhel16.cdp.cisco.local

rhel17.cdp.cisco.local

rhel18.cdp.cisco.local

rhel19.cdp.cisco.local

rhel20.cdp.cisco.local

rhel21.cdp.cisco.local

rhel22.cdp.cisco.local

rhel23.cdp.cisco.local

rhel24.cdp.cisco.local

rhel25.cdp.cisco.local

rhel26.cdp.cisco.local

rhel27.cdp.cisco.local

rhel28.cdp.cisco.local

5.     Verify host group by running the following commands. Error! Reference source not found. shows the outcome of the ping command.

# ansible datanodes -m ping

Install httpd

Setting up the RHEL repository on the admin node requires httpd. To set up RHEL repository on the admin node, follow these steps:

1.     Install httpd on the admin node to host repositories:

The Red Hat repository is hosted using HTTP on the admin node; this machine is accessible by all the hosts in the cluster.

# yum –y install httpd

2.     Add ServerName and make the necessary changes to the server configuration file:

# vi /etc/httpd/conf/httpd.conf

ServerName 10.13.1.31:80

3.     Start httpd:

# service httpd start

# chkconfig httpd on

Disable the Linux Firewall

The default Linux firewall settings are too restrictive for any Hadoop deployment. Since the Cisco UCS Big Data deployment will be in its own isolated network there is no need for that additional firewall.

# ansible all -m command -a "firewall-cmd --zone=public --add-port=80/tcp --permanent"

# ansible all -m command -a "firewall-cmd --reload"

# ansible all -m command -a "systemctl disable firewalld"

Set Up All Nodes to use the RHEL Repository

To set up all noes to use the RHEL repository, follow these steps:

Based on this repository file, yum requires httpd to be running on rhel1 for other nodes to access the repository.

1.     Copy the rheliso.repo to all the nodes of the cluster:

# ansible nodes -m copy -a "src=/var/www/html/rhelrepo/rheliso.repo dest=/etc/yum.repos.d/."

2.     Copy the /etc/hosts file to all nodes:

# ansible nodes -m copy -a "src=/etc/hosts dest=/etc/hosts"

3.     Purge the yum caches:

# ansible nodes -a “yum clean all”

# ansible nodes -a “yum repolist”

While the suggested configuration is to disable SELinux as shown below, if for any reason SELinux needs to be enabled on the cluster, run the following command to make sure that the httpd can read the Yum repofiles.

#chcon -R -t httpd_sys_content_t /var/www/html/

Disable SELinux

SELinux must be disabled during the install procedure and cluster setup. SELinux can be enabled after installation and while the cluster is running.

SELinux can be disabled by editing /etc/selinux/config and changing the SELINUX line to SELINUX=disabled.

To disable SELinux, follow these steps:

1.     The following command will disable SELINUX on all nodes:

# ansible nodes -m shell -a "sed –i 's/SELINUX=enforcing/SELINUX=disabled/g' /etc/selinux/config"

# ansible nodes -m shell -a "setenforce 0"

The above command may fail if SELinux is already disabled. This requires reboot to take effect.

2.     Reboot the machine, if needed for SELinux to be disabled in case it does not take effect. It can be checked using the following command:

# ansible namenodes -a "sestatus"

rhel01.cdp.cisco.local | CHANGED | rc=0 >>

SELinux status:                 disabled

rhel02.cdp.cisco.local | CHANGED | rc=0 >>

SELinux status:                 disabled

rhel03.cdp.cisco.local | CHANGED | rc=0 >>

SELinux status:                 disabled

Upgrade the Cisco Network Driver for VIC1387

The latest Cisco Network driver is required for performance and updates. The latest drivers can be downloaded from the link below:

https://software.cisco.com/download/home/283862063/type/283853158/release/4.0(4)

In the ISO image, the required driver kmod-enic-3.2.210.27-738.37.rhel7u6.x86_64.rpm can be located at  \Network\Cisco\VIC\RHEL\RHEL7.6\.

To upgrade the Cisco Network Driver for VIC1387, follow these steps:

From a node connected to the Internet, download, extract and transfer kmod-enic-.rpm to rhel01 (admin node).

1.     Copy the rpm on all nodes of the cluster using the following Ansible commands. For this example, the rpm is assumed to be in present working directory of rhel01:

[root@rhel01 ~]# ansible all -m copy -a "src=/root/ kmod-enic-3.2.210.27-738.37.rhel7u6.x86_64.rpm dest=/root/."

2.     Use the yum module to install the enic driver rpm file on all the nodes through Ansible:

[root@rhel01 ~]# ansible all –m yum –a “name=/root/ kmod-enic-3.2.210.27-738.37.rhel7u6.x86_64.rpm state=present”

Make sure that the above installed version of kmod-enic driver is being used on all nodes by running the command "modinfo enic" on all nodes:

[root@rhel01 ~]# ansible all -m shell -a "modinfo enic | head -5"

3.     It is recommended to download the kmod-megaraid driver for higher performance. The RPM can be found in the same package at: \Storage\LSI\Cisco_Storage_12G_SAS_RAID_controller\RHEL\RHEL7.6\kmod-megaraid_sas-07.708.03.00_el7.6-2.x86_64.rpm

4.     Copy the rpm on all nodes of the cluster using the following Ansible commands. For this example, the rpm is assumed to be in present working directory of rhel01:

[root@rhel01 ~]# ansible all -m copy -a "src=/root/ kmod-megaraid_sas-07.708.03.00_el7.6-2.x86_64.rpm dest=/root/."

5.     Use the yum module to install the enic driver rpm file on all the nodes through Ansible:

[root@rhel01 ~]# ansible all –m yum –a “name=/root/ kmod-megaraid_sas-07.708.03.00_el7.6-2.x86_64.rpm state=present”

Make sure that the above installed version of kmod-megaraid_sas driver is being used on all nodes by running the command "modinfo enic" on all nodes:

[root@rhel01 ~]# ansible all -m shell -a "modinfo megaraid_sas | head -5"

Set Up JAVA

To setup JAVA, follow these steps:

CDP DC 7 requires JAVA 8.

1.     Download jdk-8u211-linux-x64.rpm and src the rpm to admin node (rhel01) from the link: https://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html

2.     Copy JDK rpm to all nodes:

# ansible nodes -m copy -a "src=/root/jdk-8u241-linux-x64.rpm dest=/root/."

3.     Extract and Install JDK all nodes:

# ansible all -m command -a "rpm -ivh jdk-8u241-linux-x64.rpm "

4.     Create the following files java-set-alternatives.sh and java-home.sh on admin node (rhel01):

# vi java-set-alternatives.sh

#!/bin/bash

for item in java javac javaws jar jps javah javap jcontrol jconsole jdb; do

rm -f /var/lib/alternatives/$item

alternatives --install /usr/bin/$item $item /usr/java/jdk1.8.0_241-amd64/bin/$item 9

alternatives --set $item /usr/java/jdk1.8.0_241-amd64/bin/$item

done

# vi java-home.sh

export JAVA_HOME=/usr/java/jdk1.8.0_241-amd64

5.     Make the two java scripts created above executable:

chmod 755 ./java-set-alternatives.sh ./java-home.sh

6.     Copying java-set-alternatives.sh to all nodes.

ansible nodes -m copy -a "src=/root/java-set-alternatives.sh dest=/root/."

ansible nodes -m file -a "dest=/root/java-set-alternatives.sh mode=755"

ansible nodes -m copy -a "src=/root/java-home.sh dest=/root/."

ansible nodes -m file -a "dest=/root/java-home.sh mode=755"

7.     Setup Java Alternatives

[root@rhel01 ~]# ansible all -m shell -a "/root/java-set-alternatives.sh"

8.     Make sure correct java is setup on all nodes (should point to newly installed java path).

# ansible all -m shell -a "alternatives --display java | head -2"

rhel01.cdp.cisco.local | CHANGED | rc=0 >>

java - status is manual.

link currently points to /usr/java/jdk1.8.0_241-amd64/bin/java

rhel04.cdp.cisco.local | CHANGED | rc=0 >>

java - status is manual.

link currently points to /usr/java/jdk1.8.0_241-amd64/bin/java

rhel05.cdp.cisco.local | CHANGED | rc=0 >>

java - status is manual.

link currently points to /usr/java/jdk1.8.0_241-amd64/bin/java

9.     Setup JAVA_HOME on all nodes.

# ansible all -m copy -a "src=/root/java-home.sh dest=/etc/profile.d"

10.  Display JAVA_HOME on all nodes.

# ansible all -m command -a "echo $JAVA_HOME"

rhel19.cdp.cisco.local | CHANGED | rc=0 >>

/usr/java/jdk1.8.0_241-amd64

11.  Display current java –version.

# ansible all -m command -a "java -version"

rhel20.cdp.cisco.local | CHANGED | rc=0 >>

java version "1.8.0_241"

Java(TM) SE Runtime Environment (build 1.8.0_241-b11)

Java HotSpot(TM) 64-Bit Server VM (build 25.241-b11, mixed mode)

Enable Syslog

Syslog must be enabled on each node to preserve logs regarding killed processes or failed jobs. Modern versions such as syslog-ng and rsyslog are possible, making it more difficult to be sure that a syslog daemon is present.

Use one of the following commands to confirm that the service is properly configured:

# ansible all -m command -a "rsyslogd –v"

# ansible all -m command -a "service rsyslog status"

Set the ulimit

On each node, ulimit -n specifies the number of inodes that can be opened simultaneously. With the default value of 1024, the system appears to be out of disk space and shows no inodes available. This value should be set to 64000 on every node.

Higher values are unlikely to result in an appreciable performance gain.

To set ulimit, follow these steps:

1.     For setting the ulimit on Redhat, edit “/etc/security/limits.conf” on admin node rhel01 and add the following lines:

# vi /etc/security/limits.conf

root soft nofile 64000

root hard nofile 64000

2.     Copy the /etc/security/limits.conf file from admin node (rhel01) to all the nodes using the following command:

# ansible nodes -m copy -a "src=/etc/security/limits.conf dest=/etc/security/limits.conf"

3.     Make sure that the /etc/pam.d/su file contains the following settings:

# cat /etc/pam.d/su

#%PAM-1.0

auth            sufficient      pam_rootok.so

# Uncomment the following line to implicitly trust users in the "wheel" group.

#auth           sufficient      pam_wheel.so trust use_uid

# Uncomment the following line to require a user to be in the "wheel" group.

#auth           required        pam_wheel.so use_uid

auth            include         system-auth

auth            include         postlogin

account         sufficient      pam_succeed_if.so uid = 0 use_uid quiet

account         include         system-auth

password        include         system-auth

session         include         system-auth

session         include         postlogin

session         optional        pam_xauth.so

The ulimit values are applied on a new shell, running the command on a node on an earlier instance of a shell will show old values.

Set TCP Retries

Adjusting the tcp_retries parameter for the system network enables faster detection of failed nodes. Given the advanced networking features of UCS, this is a safe and recommended change (failures observed at the operating system layer are most likely serious rather than transitory).

To set TCP retries, follow these steps:

On each node, set the number of TCP retries to 5 can help detect unreachable nodes with less latency.

1.     Edit the file /etc/sysctl.conf and on admin node rhel01 and add the following lines:

net.ipv4.tcp_retries2=5

Copy the /etc/sysctl.conf file from admin node (rhel01) to all the nodes using the following command:

# ansible nodes -m copy -a "src=/etc/sysctl.conf dest=/etc/sysctl.conf"

2.     Load the settings from default sysctl file /etc/sysctl.conf by running the following command:

# ansible nodes -m command -a "sysctl -p"

Disable IPv6 Defaults

To disable IPv6 defaults, follow these steps:

1.     Run the following command:

# ansible all -m shell -a "echo 'net.ipv6.conf.all.disable_ipv6 = 1' >> /etc/sysctl.conf"

# ansible all -m shell -a "echo 'net.ipv6.conf.default.disable_ipv6 = 1' >> /etc/sysctl.conf"

# ansible all -m shell -a "echo 'net.ipv6.conf.lo.disable_ipv6 = 1' >> /etc/sysctl.conf"

2.     Load the settings from default sysctl file /etc/sysctl.conf:

# ansible all -m shell -a "sysctl –p"

Disable Swapping

To disable swapping, follow these steps:

1.     Run the following on all nodes. Variable vm.swappiness defines how often swap should be used, 60 is default:

# ansible all -m shell -a "echo 'vm.swappiness=0' >> /etc/sysctl.conf"

2.     Load the settings from default sysctl file /etc/sysctl.conf and verify the content of sysctl.conf:

# ansible all -m shell -a "sysctl –p"

# ansible all -m shell -a "cat /etc/sysctl.conf"

Disable Memory Overcommit

To disable Memory Overcommit, follow these steps:

1.     Run the following on all nodes. Variable vm.overcommit_memory=0

# ansible all -m shell -a "echo 'vm.overcommit_memory=0' >> /etc/sysctl.conf"

2.     Load the settings from default sysctl file /etc/sysctl.conf and verify the content of sysctl.conf:

# ansible all -m shell -a "sysctl –p"

# ansible all -m shell -a "cat /etc/sysctl.conf"

rhel28.cdp.cisco.local | CHANGED | rc=0 >>

# sysctl settings are defined through files in

# /usr/lib/sysctl.d/, /run/sysctl.d/, and /etc/sysctl.d/.

#

# Vendors settings live in /usr/lib/sysctl.d/.

# To override a whole file, create a new file with the same in

# /etc/sysctl.d/ and put new settings there. To override

# only specific settings, add a file with a lexically later

# name in /etc/sysctl.d/ and put new settings there.

#

# For more information, see sysctl.conf(5) and sysctl.d(5).

net.ipv4.tcp_retries2=5

net.ipv6.conf.all.disable_ipv6 = 1

net.ipv6.conf.default.disable_ipv6 = 1

net.ipv6.conf.lo.disable_ipv6 = 1

vm.swappiness = 0

vm.overcommit_memory = 0

Disable Transparent Huge Pages

Disabling Transparent Huge Pages (THP) reduces elevated CPU usage caused by THP.

To disable Transparent Huge Pages, follow these steps:

1.     You must run the following commands for every reboot; copy this command to /etc/rc.local so they are executed automatically for every reboot:

# ansible all -m shell -a "echo never > /sys/kernel/mm/transparent_hugepage/enabled”

# ansible all -m shell -a "echo never > /sys/kernel/mm/transparent_hugepage/defrag"

2.     On the Admin node, run the following commands:

#rm –f /root/thp_disable

#echo "echo never > /sys/kernel/mm/transparent_hugepage/enabled" >>

/root/thp_disable

#echo "echo never > /sys/kernel/mm/transparent_hugepage/defrag " >>

/root/thp_disable

3.     Copy file to each node:

# ansible nodes -m copy -a "src=/root/thp_disable dest=/root/thp_disable"

4.     Append the content of file thp_disable to /etc/rc.d/rc.local:

# ansible nodes -m shell -a "cat /root/thp_disable >> /etc/rc.d/rc.local"

# ansible nodes -m shell -a "chmod +x /etc/rc.d/rc.local"

NTP Configuration

The Network Time Protocol (NTP) is used to synchronize the time of all the nodes within the cluster. The Network Time Protocol daemon (ntpd) sets and maintains the system time of day in synchronism with the timeserver located in the admin node (rhel01). Configuring NTP is critical for any Hadoop Cluster. If server clocks in the cluster drift out of sync, serious problems will occur with HBase and other services.

To configure NTP, follow these steps:

# ansible all -m yum -a "name=ntp state=present"

Installing an internal NTP server keeps your cluster synchronized even when an outside NTP server is inaccessible.

1.     Configure /etc/ntp.conf on the admin node only with the following contents:

# vi /etc/ntp.conf

driftfile /var/lib/ntp/drift

restrict 127.0.0.1

restrict -6 ::1

server 127.127.1.0

fudge 127.127.1.0 stratum 10

includefile /etc/ntp/crypto/pw

keys /etc/ntp/keys

2.     Create /root/ntp.conf on the admin node and copy it to all nodes:

# vi /root/ntp.conf

server 10.13.1.31

driftfile /var/lib/ntp/drift

restrict 127.0.0.1

restrict -6 ::1

includefile /etc/ntp/crypto/pw

keys /etc/ntp/keys

3.     Copy ntp.conf file from the admin node to /etc of all the nodes by executing the following commands in the admin node (rhel01):

# ansible nodes -m copy -a “src=/root/ntp.conf dest=/etc/ntp.conf”

4.     Run the following to syncronize the time and restart NTP daemon on all nodes:

# ansible all -m service -a “name=ntpd state=stopped”

# ansible all -m command -a “ntpdate rhel01.cdp.cisco.local”

# ansible all -m service -a “name=ntpd state=started”

5.     Make sure to restart of NTP daemon across reboots:

# ansible all -a  "systemctl enable ntpd"

6.     Verify NTP is up and running in all nodes by running the following commands:

# ansible all -a "systemctl status ntpd"

Alternatively, the new Chrony service can be installed, which is quicker to synchronize clocks in mobile and virtual systems.

7.     Install the Chrony service:

# ansible all -m yum -a "name=chrony state=present"

8.     Activate the Chrony service at boot:

# ansible all -a "systemctl enable chronyd"

9.     Start the Chrony service:

# ansible all -m service -a "name=chronyd state=started"

# systemctl start chronyd

10.  The Chrony configuration is in the /etc/chrony.conf file, configured similar to /etc/ntp.conf.

Install Megaraid StorCLI

This section explains the steps needed to install StorCLI (Storage Command Line Tool) which is a command line interface designed to be easy to use, consistent, and script. For more details, go to: https://docs.broadcom.com/docs/12352476

To install StorCLI, follow these steps:

1.     Download StorCLI:  https://www.broadcom.com/support/download-search/?pg=&pf=&pn=&po=&pa=&dk=storcli.

2.     Extract the .zip file and copy storcli-1.23.02-1.noarch.rpm from the linux directory.

3.     Download StorCLI and its dependencies and transfer to Admin node:

#scp storcli-1.23.02-1.noarch.rpm rhel01:/root/

4.     Copy storcli rpm to all the nodes using the following commands:

# ansible all -m copy -a "src=/root/storcli-1.23.02-1.noarch.rpm dest=/root/."

5.     Run this command to install storcli on all the nodes:

# ansible all -m shell -a "rpm -ivh storcli-1.23.02-1.noarch.rpm"

6.     Run this command to copy storcli64 to root directory:

# ansible all -m shell -a "cp /opt/MegaRAID/storcli/storcli64 /root/."

7.     Run this command to check the state of the disks:

# ansible all -m shell -a "./storcli64 /c0 show all"

The Cisco UCS Manager configuration explains the steps to deploy the required storage configuration via Storage Policy and Storage Profile attached to Service Profile Template for NameNode(s), Management Node(s), GPU Node(s) and DataNode(s). To configure Storage with StorCLI, go to section Configure Cisco Boot Optimized M.2 RAID Controller.

Configure the Filesystem for NameNodes and DataNodes

The following script formats and mounts the available volumes on each node whether it is NameNode or Data node. OS boot partition will be skipped. All drives are mounted based on their UUID as /data/disk1, /data/disk2, etc. To configure the filesystem for NameNodes and DataNodes, follow these steps:

1.     On the Admin node, create a file containing the following script:

#vi /root/driveconf.sh

2.     To create partition tables and file systems on the local disks supplied to each of the nodes, run the following script as the root user on each node:

This script assumes there are no partitions already existing on the data volumes. If there are partitions, delete them before running the script. This process is in section Delete Partitions.

#vi /root/driveconf.sh

#!/bin/bash

[[ "-x" == "${1}" ]] && set -x && set -v && shift 1

count=1

for X in /sys/class/scsi_host/host?/scan

do

echo '- - -' > ${X}

done

for X in /dev/sd?

do

list+=$(echo $X " ")

done

for X in /dev/sd??

do

list+=$(echo $X " ")

done

for X in $list

do

echo "========"

echo $X

echo "========"

if [[ -b ${X} && `/sbin/parted -s ${X} print quit|/bin/grep -c boot` -

ne 0

]]

then

echo "$X bootable - skipping."

continue

else

Y=${X##*/}1

echo "Formatting and Mounting Drive => ${X}"

166

/sbin/mkfs.xfs –f ${X}

(( $? )) && continue

#Identify UUID

UUID=`blkid ${X} | cut -d " " -f2 | cut -d "=" -f2 | sed 's/"//g'`

/bin/mkdir -p /data/disk${count}

(( $? )) && continue

echo "UUID of ${X} = ${UUID}, mounting ${X} using UUID on

/data/disk${count}"

/bin/mount -t xfs -o inode64,noatime,nobarrier -U ${UUID}

/data/disk${count}

(( $? )) && continue

echo "UUID=${UUID} /data/disk${count} xfs inode64,noatime,nobarrier 0

0" >> /etc/fstab

((count++))

fi

done

3.     Run the following command to copy driveconf.sh to all the nodes:

# chmod 755 /root/driveconf.sh

# ansible datanodes -m copy -a “src=/root/driveconf.sh dest=/root/.”

# ansible nodes -m file -a "dest=/root/driveconf.sh mode=755"

4.     Run the following command from the admin node to run the script across all data nodes:

# ansible datanodes -m shell -a “/root/driveconf.sh”

5.     Run the following from the admin node to list the partitions and mount points:

# ansible datanodes -m shell -a “df –h”

# ansible datanodes -m shell -a “mount”

# ansible datanodes -m shell -a “cat /etc/fstab”

Delete Partitions

To delete a partition, follow these steps:

1.     Run the mount command (‘mount’) to identify which drive is mounted to which device /dev/sd<?>

2.     umount the drive for which partition is to be deleted and run fdisk to delete as shown below.

Be sure not to delete the OS partition since this will wipe out the OS.

# mount

# umount /data/disk1 ç (disk1 shown as example)

#(echo d; echo w;) | sudo fdisk /dev/sd<?>

Cluster Verification

This section explains the steps to create the script cluster_verification.sh that helps to verify the CPU, memory, NIC, and storage adapter settings across the cluster on all nodes. This script also checks additional prerequisites such as NTP status, SELinux status, ulimit settings, JAVA_HOME settings and JDK version, IP address and hostname resolution, Linux version and firewall settings.

To verify a cluster, follow these steps:

The following script uses cluster shell (clush) which needs to be installed and configured.

1.     Create the script cluster_verification.sh as shown, on the Admin node (rhel01).

#vi cluster_verification.sh

#!/bin/bash

shopt -s expand_aliases,

# Setting Color codes

green='\e[0;32m'

red='\e[0;31m'

NC='\e[0m' # No Color

echo -e "${green} === Cisco UCS Integrated Infrastructure for Big Data and Analytics \ Cluster Verification === ${NC}"

echo ""

echo ""

echo -e "${green} ==== System Information  ==== ${NC}"

echo ""

echo ""

echo -e "${green}System ${NC}"

clush -a -B " `which dmidecode` |grep -A2 '^System Information'"

echo ""

echo ""

echo -e "${green}BIOS ${NC}"

clush -a -B " `which dmidecode` | grep -A3 '^BIOS I'"

echo ""

echo ""

echo -e "${green}Memory ${NC}"

clush -a -B "cat /proc/meminfo | grep -i ^memt | uniq"

echo ""

echo ""

echo -e "${green}Number of Dimms ${NC}"

clush -a -B "echo -n 'DIMM slots: ';  `which dmidecode` |grep -c \ '^[[:space:]]*Locator:'"

clush -a -B "echo -n 'DIMM count is: ';  `which dmidecode` | grep \ "Size"| grep -c "MB""

clush -a -B " `which dmidecode` | awk '/Memory Device$/,/^$/ {print}' |\ grep -e '^Mem' -e Size: -e Speed: -e Part | sort -u | grep -v -e 'NO \ DIMM' -e 'No Module Installed' -e Unknown"

echo ""

echo ""

# probe for cpu info #

echo -e "${green}CPU ${NC}"

clush -a -B "grep '^model name' /proc/cpuinfo | sort -u"

echo ""

clush -a -B "`which lscpu` | grep -v -e op-mode -e ^Vendor -e family -e\ Model: -e Stepping: -e BogoMIPS -e Virtual -e ^Byte -e '^NUMA node(s)'"

echo ""

echo ""

# probe for nic info #

echo -e "${green}NIC ${NC}"

clush -a -B "`which ifconfig` | egrep '(^e|^p)' | awk '{print \$1}' | \ xargs -l  `which ethtool` | grep -e ^Settings -e Speed"

echo ""

clush -a -B "`which lspci` | grep -i ether"

echo ""

echo ""

# probe for disk info #

echo -e "${green}Storage ${NC}"

clush -a -B "echo 'Storage Controller: '; `which lspci` | grep -i -e \ raid -e storage -e lsi"

echo ""

clush -a -B "dmesg | grep -i raid | grep -i scsi"

echo ""

clush -a -B "lsblk -id | awk '{print \$1,\$4}'|sort | nl"

echo ""

echo ""

echo -e "${green} ================ Software  ======================= ${NC}"

echo ""

echo ""

echo -e "${green}Linux Release ${NC}"

clush -a -B "cat /etc/*release | uniq"

echo ""

echo ""

echo -e "${green}Linux Version ${NC}"

clush -a -B "uname -srvm | fmt"

echo ""

echo ""

echo -e "${green}Date ${NC}"

clush -a -B date

echo ""

echo ""

echo -e "${green}NTP Status ${NC}"

clush -a -B "ntpstat 2>&1 | head -1"

echo ""

echo ""

echo -e "${green}SELINUX ${NC}"

clush -a -B "echo -n 'SElinux status: '; grep ^SELINUX= \ /etc/selinux/config 2>&1"

echo ""

echo ""

clush -a -B "echo -n 'CPUspeed Service: ';  `which service` cpuspeed \ status 2>&1"

clush -a -B "echo -n 'CPUspeed Service: '; `which chkconfig` --list \ cpuspeed 2>&1"

echo ""

echo ""

echo -e "${green}Java Version${NC}"

clush -a -B 'java -version 2>&1; echo JAVA_HOME is ${JAVA_HOME:-Not \ Defined!}'

echo ""

echo ""

echo -e "${green}Hostname LoOKup${NC}"

clush -a -B " ip addr show"

echo ""

echo ""

echo -e "${green}Open File Limit${NC}"

clush -a -B 'echo -n "Open file limit(should be >32K): "; ulimit -n'

2.     Change permissions to executable:

# chmod 755 cluster_verification.sh

3.     Run the Cluster Verification tool from the admin node. This can be run before starting Hadoop to identify any discrepancies in Post OS Configuration between the servers or during troubleshooting of any cluster / Hadoop issues:

#./cluster_verification.sh

Install Cloudera Data Platform

This section provides instructions for installing Cloudera software, including Cloudera Manager, Cloudera Runtime, and other managed services, in a production environment.

Review the Cloudera Production Installation: Before You Install steps prior to the production installation of Cloudera Manager, Cloudera Runtime, and other managed services, review the Cloudera Data Platform 7 Requirements and Supported Versions, in addition to the Cloudera Data Platform Release Notes.

Prerequisites for CDP DC Installation

This section details the prerequisites for the CDP DC installation, such as setting up Cloudera Repo.

Cloudera Manager Repository

To setup the Cloudera Manager Repository, follow these steps:

1.     From a host connected to the Internet, download the Cloudera’s repositories as shown below and transfer it to the admin node:

#mkdir -p /tmp/cloudera-repos/

2.     Download Cloudera Manager Repository:

#cd /tmp/cloudera-repos/

# wget https://archive.cloudera.com/cm7/7.0.3/redhat7/yum/cloudera-manager-trial.repo

# reposync --config=./cloudera-manager-trial.repo --repoid=cloudera-manager

# wget https://archive.cloudera.com/cm7/7.0.3/allkeys.asc

This downloads the Cloudera Manager RPMs needed for the Cloudera repository.

3.     Run the following command to move the RPMs:

4.     Copy the repository directory to the admin node (rhel1):

# scp -r /tmp/cloudera-repos/ rhel01:/var/www/html/

# scp allkeys.asc rhel01:/var/www/html/cloudera-repos/cm7/

5.     On admin node (rhel1) run create repo command:

#cd /var/www/html/cloudera-repos/

#createrepo --baseurl http://10.13.1.31/cloudera-repos/cm7/ /var/www/html/cloudera-repos/cm7/

Go to: http://10.13.1.31/cloudera-repos/cm7/ to verify the files.

6.     Create the Cloudera Manager repo file with following contents:

# vi /var/www/html/cloudera-repos/cm7/cloudera-repo.repo

# cat /var/www/html/cloudera-repos/cm7/cloudera-repo.repo

[cloudera-repo]

name=Cloudera Manager 7.0.3

baseurl=http://10.13.1.31/cloudera-repo/cm7/

gpgcheck=0

enabled=1

7.     Copy the file cloudera-repo.repo into /etc/yum.repos.d/ on the admin node to enable it to find the packages that are locally hosted:

#cp /var/www/html/cloudera-repos/cm7/cloudera-repo.repo /etc/yum.repos.d/

From the admin node copy the repo files to /etc/yum.repos.d/ of all the nodes of the cluster:

# ansible all -m copy -a "src=/etc/yum.repos.d/cloudera-repo.repo dest=/etc/yum.repos.d/."

Set Up the Local Parcels for CDP DC 7.0.3

From a host connected the internet, download CDP DC 7.0.3 parcels that are meant for RHEL7.6 from the URL: https://archive.cloudera.com/cdh7/7.0.3.0/parcels/ and place them in the directory /var/www/html/cloudera-repos/ " of the Admin node.

The following are the required files for RHEL7.6:

·       CDH-7.0.3-1.cdh7.0.3.p0.1635019-el7.parcel

·       CDH-7.0.3-1.cdh7.0.3.p0.1635019-el7.parcel.sh256

·       manifest.json

Download Parcels

To download parcels, follow these steps:

1.     From a host connected to the Internet, download the Cloudera’s parcels as shown below and transfer it to the admin node:

#mkdir -p /tmp/cloudera-repos/CDH7.0.3.1parcels

2.     Download parcels:

#cd /tmp/cloudera-repos/CDH7.0.3.1parcels

# wget https://archive.cloudera.com/cdh7/7.0.3.0/parcels/CDH-7.0.3-1.cdh7.0.3.p0.1635019-el7.parcel

# wget https://archive.cloudera.com/cdh7/7.0.3.0/parcels/CDH-7.0.3-1.cdh7.0.3.p0.1635019-el7.parcel.sha256

# wget https://archive.cloudera.com/cdh7/7.0.3.0/parcels/manifest.json

3.     Copy /tmp/cloudera-repos/CDH7.0.3.1parcels to the admin node (rhel01):

# scp -r /tmp/cloudera-repos/CDH7.0.3.1parcels rhel01:/var/www/html/cloudera-repos/

# chmod -R ugo+rX /var/www/html/cloudera-repos/cdh7

4.     Verify that these files are accessible by visiting the URL http://10.13.1.31/cloudera-repos/cdh7/7.0.3.0/parcels/ in admin node.

5.     Download Sqoop Connectors.

# mkdir -p /tmp/cloudera-repos/sqoop-connectors

# wget --recursive --no-parent --no-host-directories http://archive.cloudera.com/sqoop-connectors/parcels/latest/ -P /tmp/cloudera-repos/

6.     Copy /tmp/cloudera-repos/sqoop-connectors to the admin node (rhel01).

# scp -r /tmp/cloudera-repos/sqoop-connectors rhel01:/var/www/html/cloudera-repos/

# sudo chmod -R ugo+rX /var/www/html/cloudera-repos/sqoop-connectors

Install and Configure Database for Cloudera Manager

You will set up the following for Cloudera Manager:

·       Install the PostgreSQL Server

·       Installing the psycopg2 Python Package

·       Configure and Start the PostgreSQL Server

Install PostgreSQL Server

To install the PostgreSQL packages on the PostgreSQL server, follow these steps:

1.     In the admin node where Cloudera Manager will be installed, use the following command to install PostgreSQL server.

#yum –y install postgresql-server

2.     Install psycopg2 Python package 2.7.5 or higher if lower version is installed.

# yum install -y python-pip

# pip install psycopg2==2.7.5 --ignore-installed

Check installing dependencies for hue: https://docs.cloudera.com/documentation/enterprise/upgrade/topics/ug_cdh_upgrade_hue_psycopg2.html

Configure and Start PostgreSQL Server

To configure and start the PostgreSQL server, follow these steps:

1.     To configure and start the PostgreSQL Server, stop PostgreSQL server if it is running.

# systemctl stop postgresql.service

Backup the existing database.

By default, PostgreSQL only accepts connections on the loopback interface. You must reconfigure PostgreSQL to accept connections from the fully qualified domain names (FQDN) of the hosts hosting the services for which you are configuring databases. If you do not make these changes, the services cannot connect to and use the database on which they depend.

2.     Make sure that LC_ALL is set to en_US.UTF-8 and initialize the database as follows::

# echo 'LC_ALL="en_US.UTF-8"' >> /etc/locale.conf

# sudo su -l postgres -c "postgresql-setup initdb"

3.     To enable MD5 authentication, edit /var/lib/pgsql/data/pg_hba.conf by adding the following line:

# host all all 127.0.0.1/32 md5

The host line specifying md5 authentication shown above must be inserted before this ident line:

# host all all 127.0.0.1/32 ident

Failure to do so may cause an authentication error when running the scm_prepare_database.sh script. You can modify the contents of the md5 line shown above to support different configurations. For example, if you want to access PostgreSQL from a different host, replace 127.0.0.1 with your IP address and update postgresql.conf, which is typically found in the same place as pg_hba.conf, to include:

# listen_addresses = '*'

4.     Configure settings to ensure your system performs as expected. Update these settings in the /var/lib/pgsql/data/postgresql.conf file. Settings vary based on cluster size and resources as follows:

max_connection – 100

shared_buffers - 1024 MB

wal_buffers - 16 MB

checkpoint_segments - 128

checkpoint_completion_target - 0.9

Refer to section Configuration and Starting the PostgreSQL Server, in the Cloudera Data Platform Data Center Installation guide: https://docs.cloudera.com/cdpdc/7.0/installation/topics/cdpdc-configuring-starting-postgresql-server.html

5.     Start the PostgreSQL Server and configure to start at boot.

# systemctl start postgresql

# systemctl enable postgresql

Databases for CDP

Create databases and service accounts for components that require a database.

Create databases for the following components:

·       Cloudera Manager Server

·       Cloudera Management Service Roles: Activity Monitor, Reports Manager, Hive Metastore Server, Data Analytics Studio, Ranger, hue, and oozie.

The databases must be configured to support the PostgreSQL UTF8 character set encoding.

Record the values you enter for database names, usernames, and passwords. The Cloudera Manager installation wizard requires this information to correctly connect to these databases.

To create databases for CDP, follow these steps:

1.     In the admin node, connect to PostgreSQL:

# sudo -u postgres psql

2.     Create databases using the following command:

CREATE ROLE scm LOGIN PASSWORD 'password';

CREATE DATABASE scm OWNER scm ENCODING 'UTF8';

CREATE ROLE amon LOGIN PASSWORD 'password';

CREATE DATABASE amon OWNER amon ENCODING 'UTF8';

CREATE ROLE rman LOGIN PASSWORD 'password';

CREATE DATABASE rman OWNER rman ENCODING 'UTF8';

CREATE ROLE hue LOGIN PASSWORD 'password';

CREATE DATABASE hue OWNER hue ENCODING 'UTF8';

CREATE ROLE hive LOGIN PASSWORD 'password';

CREATE DATABASE metastore OWNER hive ENCODING 'UTF8';

CREATE ROLE nav LOGIN PASSWORD 'password';

CREATE DATABASE nav OWNER nav ENCODING 'UTF8';

CREATE ROLE navms LOGIN PASSWORD 'password';

CREATE DATABASE navms OWNER navms ENCODING 'UTF8';

CREATE ROLE oozie LOGIN PASSWORD 'password';

CREATE DATABASE oozie OWNER oozie ENCODING 'UTF8';

CREATE ROLE rangeradmin LOGIN PASSWORD 'password';

CREATE DATABASE ranger OWNER rangeradmin ENCODING 'UTF8';

CREATE ROLE das LOGIN PASSWORD 'password';

CREATE DATABASE das OWNER das ENCODING 'UTF8';

ALTER DATABASE metastore SET standard_conforming_strings=off;

ALTER DATABASE oozie SET standard_conforming_strings=off;

For Apache Ranger specific configuration for PostgreSQL, see: Configuring a PostgreSQL Database for Ranger

Cloudera Manager Installation

The following sections describe how to install Cloudera Manager and then using Cloudera Manager to install CDP DC 7.0.3.

Install Cloudera Manager

Cloudera Manager, an end-to-end management application, is used to install and configure CDP DC. During CDP Installation, Cloudera Manager's Wizard will help to install Hadoop services and any other role(s)/service(s) on all nodes using the following procedure:

·       Discovery of the cluster nodes

·       Configure the Cloudera parcel or package repositories

·       Install Hadoop, Cloudera Manager Agent (CMA) and Impala on all the cluster nodes.

·       Install the Oracle JDK or Open JDK if it is not already installed across all the cluster nodes.

·       Assign various services to nodes.

·       Start the Hadoop services

Please see the JAVA requirements for CDP DC.

To install Cloudera Manager, follow these steps:

1.     Update the repo files to point to local repository.

#rm -f /var/www/html/clouderarepo/*.repo

#cp /etc/yum.repos.d/c*.repo /var/www/html/clouderarepo/

2.     Install the Oracle Java Development Kit on the Cloudera Manager Server host.

# ansible nodes -m shell -a "yum install -y java-1.8.0-openjdk-devel"

Please see the CDP DC documentation for more information: Manually Installing OpenJDK and Manually Installing Oracle JDK

3.     Install the Cloudera Manager Server packages either on the host where the database is installed, or on a host that has access to the database:

#yum install -y cloudera-manager-agent cloudera-manager-daemons cloudera-manager-server

Set Up the Cloudera Manager Server Database

The Cloudera Manager Server Database includes a script that can create and configure a database for itself.

The script can:

·       Create the Cloudera Manager Server database configuration file.

·       (PostgreSQL) Create and configure a database for Cloudera Manager Server to use.

·       (PostgreSQL) Create and configure a user account for Cloudera Manager Server.

The following sections describe the syntax for the script and demonstrate how to use it.

Prepare a Cloudera Manager Server External Database

To prepare a Cloudera Manager Server external database, follow these steps:

1.     Run the scm_prepare_database.sh script on the host where the Cloudera Manager Server package is installed (rhel1) admin node:

# cd /opt/cloudera/cm/schema/

# ./scm_prepare_database.sh postgresql scm scm <password>

# ./scm_prepare_database.sh postgresql amon amon <password>

# ./scm_prepare_database.sh postgresql rman rman <password>

# ./scm_prepare_database.sh postgresql hue hue <password>

# ./scm_prepare_database.sh postgresql metastore hive <password>

# ./scm_prepare_database.sh postgresql oozie oozie<password>

# ./scm_prepare_database.sh postgresql das das <password>

# ./scm_prepare_database.sh postgresql ranger rangeradmin <password>

Start the Cloudera Manager Server

To start the Cloudera Manager Server, follow these steps:

1.     Start the Cloudera Manager Server:

#systemctl start cloudera-scm-server

2.     Access the Cloudera Manager using the URL, http://10.13.1.31:7180 to verify that the server is up.

3.     Once the installation of Cloudera Manager is complete, install CDP DC 7 using the Cloudera Manager Web interface.

Install Cloudera Data Platform Data Center (CDP DC 7)

To install the Cloudera Data Platform Data Center, follow these steps:

1.     Log into the Cloudera Manager. Enter "admin" for both the Username and Password fields.

2.     Upload license file. Click Continue after successfully uploading license for CDP DC.

3.     Click Continue on the Welcome screen.

4.     Enter name for the Cluster.

5.     Specify the hosts that are part of the cluster using their IP addresses or hostname. The figure below shows a pattern that specifies the IP addresses range.

10.13.1.[31-58] or rhel[01-28].cdp.cisco.local

6.     After the IP addresses or hostnames are entered, click Search.

7.     Cloudera Manager will "discover" the nodes in the cluster. Verify that all desired nodes have been found and selected for installation.

Edit the Cloudera Data Platform Data Center Parcel Settings to Use the CDP 7.0.3 Parcels

To edit the CDP DC Parcel settings, follow these steps:

1.     Add custom repository path for Cloudera Manager local repository created.

2.     On the Cloudera Manager installation wizard, click Parcels.

3.     Click Parcel Repositories and Network Settings.

4.     Click to remove the entire remote repository URLs and add the URL to the location where we kept the CDP DC 7.0.3 parcels i.e. http://10.13.1.31/cloudera-repos/cdh7/7.0.3.0/parcels/

5.     Click Save Changes to finish the configuration.

6.     Click Continue on the confirmation page.

7.     For the method of installation, select the Use Parcels (Recommended) radio button.

8.     For the CDP DC 7 version, select the Cloudera Runtime 7.0.3.1-cdh7.0.3.p0-1635019 radio button.

9.     For the specific release of Cloudera Manager, select the Custom Repository radio button.

10.  Enter the URL for the repository within the admin node. http://10.13.1.50/clouderarepo/cloudera-manager and click Continue.

11.  Select appropriate option for JDK.

We selected the Manually Manager JDK option as shown in the screenshot above.

12.  Provide SSH login credentials for the cluster and click Continue.

The installation of the local Cloudera repository and using parcels begins.

13.  Run the inspect the hosts and network performance test through Cloudera Manager on which it has just performed the installation.

14.  Review and verify the summary. Click Continue.

15.  Select services that need to be started on the cluster.

We selected Custom Services for this study.

16.  This is a critical step in the installation: Inspect and customize the role assignments of all the nodes based on your requirements and click Continue.

17.  Reconfigure the service assignment to match Table 5

Table 5    Service/Role Assignment

Service Name

Host

NameNode

rhel01, rhel02 (HA)

HistoryServer

rhel01

JournalNodes

rhel01, rhel02, rhel03

ResourceManager

rhel02, rhel03 (HA)

Hue Server

rhel02

HiveMetastore Server

rhel01

HiveServer2

rhel02

HBase Master

rhel02

Oozie Server

rhel01

ZooKeeper

rhel01, rhel02, rhel03

DataNode

rhel04 to rhel28

NodeManager

rhel04 to rhel28

RegionServer

rhel04 to rhel28

Sqoop Server

rhel01

Impala Catalog Server Daemon

rhel01

Impala State Store

rhel02

Impala Daemon

rhel04 to rhel28

Solr Server

rhel04 (can be installed on all hosts if needed, if there is a search use case)

Spark History Server

rhel01

Spark Executors

rhel04 to rhel28

Figure 53     Assign Roles in Cloudera Manager; Cluster Creation Wizard Example

Set Up the Database

The role assignment recommendation above is for clusters of up to 64 servers. For clusters larger than 64 nodes, use the high availability recommendation defined in Table 5

To set up the database, follow these steps:

1.     In the Database Host Name sections use port 3306 for TCP/IP because connection to the remote server always uses TCP/IP.

2.     Enter the Database Name, username and password that were used during the database creation stage earlier in this document.

3.     Click Test Connection to verify the connection and click Continue.

4.     Enter required parameters for Data Analytics Studio.

5.     Review Data Analytics Studio (DAS) configuration.

6.     Review and customize the configuration changes based on your requirements.

7.     Click Continue to start running the cluster services.

8.     Hadoop services are installed, configured, and now running on all the nodes of the cluster. Click Finish to complete the installation.

9.     Cloudera Manager now displays the status of all Hadoop services running on the cluster.

Scale the Cluster

The role assignment recommendation above is for cluster with at least 64 servers and in High Availability. For smaller cluster running without High Availability the recommendation is to dedicate one server for NameNode and a second server for secondary name node and YARN Resource Manager. For larger clusters larger than 28 nodes the recommendation is to dedicate one server each for name node, YARN Resource Manager and one more for running both NameNode (High Availability) and Resource Manager (High Availability) as in the table (no Secondary NameNode when in High Availability).

For production clusters, it is recommended to set up NameNode and Resource manager in High Availability mode.

This implies that there will be at least 3 master nodes, running the NameNode, YARN Resource manager, the failover counter-part being designated to run on another node and a third node that would have similar capacity as the other two nodes.

All the three nodes will also need to run zookeeper and quorum journal node services. It is also recommended to have a minimum of 7 DataNodes in a cluster. Please refer to the next section for details on how to enable HA.

Enable High Availability

Setting up High Availability is done after the Cloudera Installation is completed.

HDFS High Availability

The HDFS High Availability feature provides the option of running two NameNodes in the same cluster, in an Active/Passive configuration. These are referred to as the Active NameNode and the Standby NameNode. Unlike the Secondary NameNode, the Standby NameNode is a hot standby, allowing a fast failover to a new NameNode in case that a machine crashes, or a graceful administrator-initiated failover for the purpose of planned maintenance. There cannot be more than two NameNodes.

For more information go to: https://docs.cloudera.com/content/www/en-us/documentation/enterprise/6/6.3/PDF/cloudera-administration.pdf

Set Up HDFS High Availability

The Enable High Availability workflow leads through adding a second (standby) NameNode and configuring JournalNodes. During the workflow, Cloudera Manager creates a federated namespace. To set up HDFS High Availability, follow these steps:

1.     Log into the admin node (rhel01) and create the Edit directory for the JournalNode:

# ansible namenodes -m shell -a "mkdir -p /data/disk1/namenode-edits"

# ansible namenodes -m shell -a "chmod 77 /data/disk1/namenode-edits"

2.     Log into the Cloudera manager and go to the HDFS service.

3.     Select Actions> Enable High Availability. A screen showing the hosts that are eligible to run a standby NameNode and the JournalNodes displays.

4.     Specify a name for the nameservice or accept the default name nameservice1 and click Continue.

5.     In the NameNode Hosts field, click Select a host. The host selection dialog displays.

6.     Check the checkbox next to the hosts (rhel2) where the standby NameNode is to be set up and click OK.

7.     In the JournalNode Hosts field, click Select hosts. The host selection dialog displays.

8.     Check the checkboxes next to an odd number of hosts (a minimum of three) to act as JournalNodes and click OK. We used the same nodes for the Zookeeper nodes.

9.     Click Continue.

The standby NameNode cannot be on the same host as the active NameNode, and the host that is chosen should have the same hardware configuration (RAM, disk space, number of cores, and so on) as the active NameNode.

10.  In the JournalNode Edits Directory property, enter a directory location created earlier in step 1 for the JournalNode edits directory into the fields for each JournalNode host.

The directories specified should be empty and must have the appropriate permissions.

11.  Extra Options: Decide whether Cloudera Manager should clear existing data in ZooKeeper, Standby NameNode, and JournalNodes. If the directories are not empty (for example, re-enabling a previous HA configuration), Cloudera Manager will not automatically delete the contents—select to delete the contents by keeping the default checkbox selection. The recommended default is to clear the directories.

If you choose not to configure any of the extra options, the data should be in sync across the edits directories of the JournalNodes and should have the same version data as the NameNodes.

12.  Click Continue.

13.  Cloudera Manager executes a set of commands that will stop the dependent services, delete, create, and configure roles and directories as appropriate, create a nameservice and failover controller, and restart the dependent services and deploy the new client configuration.

Formatting the name directory is expected to fail, if the directories are not empty.

14.  In the next screen additional steps are suggested by the Cloudera Manager to update the Hue and Hive metastore. Click Finish.

The following subsections explain configuring Hue and Hive for High Availability as needed.

Configure Hive Metastore to Use HDFS High Availability

To configure the Hive Megastore to use HDFS High Availability, follow these steps:

1.     Go the Hive service.

2.     Select Actions > Stop.

3.     Click Stop to confirm the command.

4.     Back up the Hive Metastore Database (if any existing data is present).

5.     Select Actions> Update Hive Metastore NameNodes and confirm the command.

6.     Select Actions> Start.

7.     Restart the Hue and Impala services if stopped prior to updating the Metastore.

Configure Hue to Work with HDFS High Availability

To configure Hue to work with HDFS High Availability, follow these steps:

1.     Go to the HDFS service.

2.     Click the Instances tab.

3.     Click Add Role Instances.

4.     Select the text box below the HttpFS field. The Select Hosts dialog displays.

5.     Select the host on which to run the role and click OK.

6.     Click Continue.

7.     Check the checkbox next to the HttpFS role and select Actions for Selected> Start.

8.     After the command has completed, go to the Hue service.

9.     Click the Configuration tab.

10.  Locate the HDFS Web Interface Role property or search for it by typing its name in the Search box.

11.  Select the HttpFS role that was just created instead of the NameNode role and save your changes.

12.  Restart the Hue service.

Refer to the High Availability section in the Cloudera Management document: https://www.cloudera.com/documentation/enterprise/6/6.2/topics/admin_ha.html for more information on setting up High Availability for other components like Impala, Oozie, and so on.

YARN High Availability

The YARN Resource Manager (RM) is responsible for tracking the resources in a cluster and scheduling applications (for example, MapReduce jobs). Before CDH 5, the RM was a single point of failure in a YARN cluster. The RM high availability (HA) feature adds redundancy in the form of an Active/Standby RM pair to remove this single point of failure. Furthermore, upon failover from the Standby RM to the Active, the applications can resume from their last check-pointed state; for example, completed map tasks in a MapReduce job are not re-run on a subsequent attempt. This allows events such the following to be handled without any significant performance effect on running applications.

·       Unplanned events such as machine crashes.

·       Planned maintenance events such as software or hardware upgrades on the machine running the ResourceManager.

For more information, go to: https://www.cloudera.com/documentation/enterprise/latest/topics/cdh_hag_rm_ha_config.html#xd_583c10bfdbd326ba--43d5fd93-1410993f8c2--7f77

Set Up YARN High Availability

To set up YARN high availability, follow these steps:

1.     Log into the Cloudera manager and go to the YARN service.

2.     Select Actions> Enable High Availability.

3.     A screen showing the hosts that are eligible to run a standby ResourceManager displays.

4.     The host where the current ResourceManager is running is not available as a choice.

5.     Select the host (rhel3) where the standby ResourceManager is to be installed and click Continue.

6.     Cloudera Manager proceeds to execute a set of commands that stop the YARN service, add a standby ResourceManager, initialize the ResourceManager high availability state in ZooKeeper, restart YARN, and redeploy the relevant client configurations.

7.     Click Finish once the installation is completed successfully.

Configure Yarn (MR2 Included) and HDFS Services

The parameters in Table 6  and Table 7  are used for Cisco UCS Integrated Infrastructure for Big Data and Analytics Performance Optimized cluster configuration described in this document. These parameters are to be changed based on the cluster configuration, number of nodes and specific workload.

Table 6    YARN

Service

Value

mapreduce.output.fileoutputformat.compress.type

BLOCK

mapreduce.output.fileoutputformat.compress.codec

org.apache.hadoop.io.compress.DefaultCodec

mapreduce.map.output.compress.codec

org.apache.hadoop.io.compress.SnappyCodec

mapreduce.map.output.compress

True

zlib.compress.level

BEST_SPEED

mapreduce.task.io.sort.factor

64

mapreduce.map.sort.spill.percent

0.9

mapreduce.reduce.shuffle.parallelcopies

20

yarn.nodemanager.resource.memory-mb

320GB

yarn.nodemanager.resource.cpu-vcores

64

yarn.scheduler.maximum-allocation-vcores

64

yarn.scheduler.maximum-allocation-mb

320GB

mapreduce.task.io.sort.mb

2047

mapreduce.job.reduce.slowstart.completedmap

0.8

yarn.app.mapreduce.am.resource.cpu-vcores

1

mapreduce.map.memory.mb

5G

mapreduce.reduce.memory.mb

5G

mapreduce.job.heap.memory-mb.ratio

0.8

mapreduce.job.shuffle.merge.percent

0.95

mapreduce.job.shuffle.input.buffer.percent

0.7

mapreduce.job.reduce.input.buffer.percent

0.7

mapreduce.input.fileinputformat.split.minsize

4096000000

mapreduce.ifile.readahead.bytes

16777216

mapreduce.inmem.merge.threshold

0

Enable Optimized Map-side Output Collector

Enable – Gateway Default Group

Table 7    HDFS

Service

Value

dfs.datanode.failed.volumes.tolerated

6

dfs.datanode.du.reserved

50 GiB

dfs.datanode.data.dir.perm

755

Java Heap Size of Namenode in Bytes

2628 MiB

dfs.namenode.handler.count

54

dfs.namenode.service.handler.count

54

Java Heap Size of Secondary namenode in Bytes

2628 MiB

Configure Spark

The two main resources that Spark (and YARN) are dependent on are CPU and memory. Disk and network I/O, play a part in Spark performance as well, but neither Spark nor YARN currently can actively manage them. Every Spark executor in any application has the same fixed number of cores and same fixed heap size. The number of cores can be specified with the executor-cores flag when invoking spark-submit, spark-shell, and pyspark from the command line, or by setting the spark.executor.cores property in the spark-defaults.conf file or in the SparkConf object.

The heap size can be controlled with the executor-memory flag or the spark.executor.memory property. The cores property controls the number of concurrent tasks an executor can run, executor-cores = 5 mean that each executor can run a maximum of five tasks at the same time. The memory property impacts the amount of data Spark can cache, as well as the maximum sizes of the shuffle data structures used for grouping, aggregations, and joins.

The num-executors command-line flag or spark.executor.instances configuration property control the number of executors requested. Dynamic Allocation can be enabled from CDH5.4 instead setting the spark.dynamicAllocation.enabled to true. Dynamic allocation enables a Spark application to request executors when there is a backlog of pending tasks and free up executors when idle.

Asking for five executor cores will result in a request to YARN for five virtual cores. The memory requested from YARN is a little more complex for a couple reasons:

·       executor-memory/spark.executor.memory controls the executor heap size, but JVMs can also use some memory off heap, for example for VM overhead, interned Strings and direct byte buffers. The value of the spark.yarn.executor.memoryOverhead property is added to the executor memory to determine the full memory request to YARN for each executor. It defaults to max (384, 0.10 * spark.executor.memory).

·       YARN may round the requested memory up a little. YARN’s yarn.scheduler.minimum-allocation-mb and yarn.scheduler.increment-allocation-mb properties control the minimum and increment request values respectively.

·       The application master is a non-executor container with the special capability of requesting containers from YARN, takes up resources of its own that must be budgeted in. In yarn-client mode, it defaults to a 1024MB and one vcore. In yarn-cluster mode, the application master runs the driver, so it’s often useful to add its resources with the –driver-memory and –driver-cores properties.

·       Running executors with too much memory often results in excessive garbage collection delays. 64GB is a rough guess at a good upper limit for a single executor.

·       A good estimate is that at most five tasks per executor can achieve full write throughput, so it’s good to keep the number of cores per executor around that number.

·       Running tiny executors (with a single core and just enough memory needed to run a single task, for example) throws away the benefits that come from running multiple tasks in a single JVM. For example, broadcast variables need to be replicated once on each executor, so many small executors will result in many more copies of the data.

Tune Resource Allocation for Spark

Below is an example of configuring a Spark application to use as much of the cluster as possible, we are using an example cluster with 16 nodes running NodeManagers, each equipped with 56 cores and 256GB of memory. yarn.nodemanager.resource.memory-mb and yarn.nodemanager. resource.cpu-vcores should be set to 180 * 1024 = 184320 (megabytes) and 48 respectively.

spark.default.parallelism=10000

spark.driver.memoryOverhead=4096

spark.executor.memoryOverhead=4096

spark.executor.extraJavaOptions=-XX:+UseParallelGC -XX:ParallelGCThreads=4

spark.shuffle.file.buffer=1024k

spark.broadcast.compress=true

spark.shuffle.compress=true

spark.io.compression.codec=org.apache.spark.io.SnappyCompressionCodec

spark.io.compression.snappy.blockSize=512k

This configuration results in four executors on all nodes except for the one with the AM, which will have three executors.

executor-memory is derived as (180/4 executors per node) = 45; 45 * 0.10 = 4.5 45 – 4.5 ~ 40.

For taking care of long running processes use 2G for the spark driver

spark.driver.memory = 2G

Submit a Job

--driver -memory 2G –executor -memory 40G --num-executors 63 --executor-cores 5 --properties-file /opt/cloudera/parcels/CDH/etc/spark/conf.dist/spark-defaults.conf

In yarn-cluster mode, the local directories used by the Spark executors and the Spark driver will be the local directories configured for YARN (Hadoop YARN config yarn.nodemanager.local-dirs). If the user specifies spark.local.dir, it will be ignored.

In yarn-client mode, the Spark executors will use the local directories configured for YARN while the Spark driver will use those defined in spark.local.dir. The Spark driver does not run on the YARN cluster in yarn-client mode, only the Spark executors do.

spark.local.dir /tmp (Directory to use for "scratch" space in Spark, including map output files and RDDs that get stored on disk. This should be on a fast, local disk in your system).

Every Spark stage has several tasks, each of which processes data sequentially. In tuning Spark jobs, this parallelism number is the most important parameter in determining performance. The number of tasks in a stage is the same as the number of partitions in the last RDD in the stage. The number of partitions in an RDD is the same as the number of partitions in the RDD on which it depends, with a couple exceptions: the coalesce transformation allows creating an RDD with fewer partitions than its parent RDD, the union transformation creates an RDD with the sum of its parents’ number of partitions, and Cartesian creates an RDD with their product.

RDDs produced by a file have their partitions determined by the underlying MapReduce InputFormat that’s used. Typically there will be a partition for each HDFS block being read. Partitions for RDDs produced by parallelize come from the parameter given by the user, or spark.default.parallelism if none is given.

The primary concern is that the number of tasks will be too small. If there are fewer tasks than slots available to run them in, the stage won’t be taking advantage of all the CPU available.

If the stage in question is reading from Hadoop, your options are:

·       Use the repartition transformation, which will trigger a shuffle.

·       Configure your InputFormat to create more splits.

·       Write the input data out to HDFS with a smaller block size.

If the stage is getting its input from another stage, the transformation that triggered the stage boundary will accept a numPartitions argument.

The most straightforward way to tune the number of partitions is experimentation: Look at the number of partitions in the parent RDD and then keep multiplying that by 1.5 until performance stops improving.

In contrast with MapReduce for Spark when in doubt, it is almost always better to be on the side of a larger number of tasks (and thus partitions).

Shuffle Performance Improvement

spark.shuffle.compress true (compress map output files)

spark.broadcast.compress true (compress broadcast variables before sending them)

spark.io.compression.codec org.apache.spark.io.SnappyCompressionCodec (codec used to compress internal data such as RDD partitions, broadcast variables and shuffle outputs)

spark.shuffle.spill.compress true (Whether to compress data spilled during shuffles.)

spark.shuffle.io.numConnectionsPerPeer 4 (Connections between hosts are reused in order to reduce connection buildup for large clusters. For clusters with many hard disks and few hosts, this may result in insufficient concurrency to saturate all disks, and so users may consider increasing this value.)

spark.shuffle.file.buffer 64K (Size of the in-memory buffer for each shuffle file output stream. These buffers reduce the number of disk seeks and system calls made in creating intermediate shuffle file)

Improve Serialization Performance

Serialization plays an important role in the performance of any distributed application. Often, this will be the first thing that should be tuned to optimize a Spark application.

spark.serializer org.apache.spark.serializer.KryoSerializer (when speed is necessary)

spark.kryo.referenceTracking false

spark.kryoserializer.buffer 2000 (If the objects are large, may need to increase the size further to fit the size of the object being deserialized).

SparkSQL is ideally suited for mixed procedure jobs where SQL code is combined with Scala, Java, or Python programs. In general, the SparkSQL command line interface is used for single user operations and ad hoc queries.

For multi-user SparkSQL environments, it is recommended to use a Thrift server connected via JDBC.

Spark SQL Tuning

Below are some guidelines for Spark SQL tuning:

·       To compile each query to Java bytecode on the fly, turn on sql.codegen. This can improve performance for large queries but can slow down very short queries.

spark.sql.codegen true

spark.sql.unsafe.enabled true

·       Configuration of in-memory caching can be done using the setConf method on SQLContext or by running SET key=value commands using SQL.

·       spark.sql.inMemoryColumnarStorage.compressed true (will automatically select a compression codec for each column based on statistics of the data)

·       spark.sql.inMemoryColumnarStorage.batchSize 5000 (Controls the size of batches for columnar caching. Larger batch sizes can improve memory utilization and compression, but risk OOMs when caching data)

·       The columnar nature of the ORC format helps avoid reading unnecessary columns, but it is still possible to read unnecessary rows. ORC avoids this type of overhead by using predicate push-down with three levels of built-in indexes within each file: file level, stripe level, and row level. This combination of indexed data and columnar storage reduces disk I/O significantly, especially for larger datasets where I/O bandwidth becomes the main bottleneck for performance.

·       By default, ORC predicate push-down is disabled in Spark SQL. To obtain performance benefits from predicate push-down, enable it explicitly, as follows:

spark.sql.orc.filterPushdown=true

·       In SparkSQL to automatically determine the number of reducers for joins and groupbys, use the parameter:

spark.sql.shuffle.partitions 200, (default value is 200)

·       This property can be put into hive-site.xml to override the default value.

·       Set log to WARN in log4j.properties to reduce log level.

Running the Thrift server and connecting to spark-sql through beeline is the recommended option for multi-session testing.

Compression for Hive

Set the following Hive parameters to compress the Hive output files using Snappy compression:

hive.exec.compress.output=true

hive.exec.orc.default.compress=SNAPPY

Change the Log Directory for All Applications

To change the default log from the /var prefix to /data/disk1, follow these steps:

1.     Log into the cloudera home page and click My Clusters.

2.     From the configuration drop-down list select “All Log Directories.”

3.     Click Save.

Summary

When building an infrastructure to enable this modernized architecture which could scale to thousands of nodes, operational efficiency can’t be an afterthought.

To achieve a seamless operation of the application at this scale, you need:

·       Infrastructure automation of Cisco UCS servers with service profiles and Cisco Data Center network automation with application profiles with Cisco ACI.

·       Centralized Management and Deep telemetry and Simplified granular trouble-shooting capabilities and • Multi-tenancy allowing application workloads including containers, micro-services, with the right level of security and SLA for each workload.

·       Cisco UCS with Cisco Intersight and Cisco ACI can enable this cloud scale architecture deployed and managed with ease.

·       CDP on CIDP delivers new approach to data where machine learning intelligently auto scale workloads up and down for more cost-effective use of private cloud infrastructure.

For More Information

For additional information, see the following resources:

·       To find out more about Cisco UCS big data solutions, see http://www.cisco.com/go/bigdata.

·       TO find out more about Cisco Data Intelligence Platform, see https://www.cisco.com/c/dam/en/us/products/servers-unified-computing/ucs-c-series-rack-servers/solution-overview-c22-742432.pdf

·       To find out more about Cisco UCS big data validated designs, see http://www.cisco.com/go/bigdata_design

·       To find out more about Cisco UCS AI/ML solutions, see http://www.cisco.com/go/ai-compute

·       To find out more about Cisco ACI solutions, see http://www.cisco.com/go/aci

·       To find out more about Cisco validated solutions based on Software Defined Storage, see https://www.cisco.com/c/en/us/solutions/data-center-virtualization/software-defined-storage-solutions/index.html

·       Cloudera Data Platform Data Center 7.0 release note, see https://docs.cloudera.com/cdpdc/7.0/release-guide/topics/cdpdc-release-notes-links.html

·       CDP Data Center Requirements and Supported Versions, see https://docs.cloudera.com/cdpdc/7.0/release-guide/topics/cdpdc-requirements-supported-versions.html

Bill of Materials

This section provides the BoM for the 28 Nodes Hadoop Base Rack. See Table 8  for BOM for the Hadoop Base rack and Table 9  for Red Hat Enterprise Linux License.

Table 8    Bill of Materials for Cisco UCS C240M5SX Hadoop Nodes Base Rack

Part Number

Description

Qty

UCSC-C240-M5SX

UCS C240 M5 24 SFF + 2 rear drives w/o CPU, mem, HD, PCIe, PS

28

CON-OSP-C240M5SX

SNTC 24X7X4OS UCS C240 M5 24 SFF + 2 rear drives w/o CPU, mem

28

UCSC-PCI-1-C240M5

Riser 1 incl 3 PCIe slots (x8, x16, x8); slot 3 req CPU2

28

UCSC-MLOM-C40Q-03

Cisco VIC 1387 Dual Port 40Gb QSFP CNA MLOM

28

UCS-M2-240GB

240GB SATA M.2

56

UCSC-PSU1-1600W

Cisco UCS 1600W AC Power Supply for Rack Server

56

UCSC-RAILB-M4

Ball Bearing Rail Kit for C220 & C240 M4 & M5 rack servers

28

CIMC-LATEST

IMC SW (Recommended) latest release for C-Series Servers.

28

UCS-SID-INFR-BD

Big Data and Analytics Platform (Hadoop/IoT/ITOA/AI/ML)

28

UCS-SID-WKL-BD

Big Data and Analytics (Hadoop/IoT/ITOA)

28

UCSC-HS-C240M5

Heat sink for UCS C240 M5 rack servers 150W CPUs & below

56

UCSC-PCIF-240M5

C240 M5 PCIe Riser Blanking Panel

28

UCS-M2-HWRAID

Cisco Boot optimized M.2 Raid controller

28

CBL-SC-MR12GM5P

Super Cap cable for UCSC-RAID-M5HD

28

UCSC-SCAP-M5

Super Cap for UCSC-RAID-M5, UCSC-MRAID1GB-KIT

28

UCSC-RAID-M5HD

Cisco 12G Modular RAID controller with 4GB cache

28

UCS-HD24TB10K4KN

2.4 TB 12G SAS 10K RPM SFF HDD (4K)

728

UCS-MR-X32G2RT-H

32GB DDR4-2933-MHz RDIMM/2Rx4/1.2v

336

UCSC-RSAS-240M5X

C240 Rear UCS-RAID-M5HD SAS cbl(1)kitinclfan,bkpln

28

UCS-CPU-I6230

Intel 6230 2.1GHz/125W 20C/27.50MB  DCP DDR4  2933 MHz

56

UCS-HD24TB10K4KN

2.4 TB 12G SAS 10K RPM SFF HDD (4K)

56

RHEL-2S2V-3A

Red Hat Enterprise Linux (1-2 CPU,1-2 VN); 3-Yr Support Req

28

CON-ISV1-EL2S2V3A

ISV 24X7 RHEL Server 2Socket-OR-2Virtual; ANNUAL List Price

28

CAB-N5K6A-NA

Power Cord, 200/240V 6A North America

56

RACK2-UCS2

Cisco R42612 standard rack, w/side panels

2

CON-SNT-RCK2UCS2

SNTC 8X5XNBD, Cisco R42612 standard rack, w side panels

2

UCS-SP-FI6332

(Not sold standalone) UCS 6332 1RU FI/12 QSFP+

4

CON-OSP-SPFI6332

ONSITE 24X7X4 (Not sold standalone) UCS 6332 1RU FI/No PSU/3

4

UCS-PSU-6332-AC

UCS 6332 Power Supply/100-240VAC

8

For NameNode, we configured ten 1.2TB 10K RPM SAS HDD.

Table 9    Red Hat Enterprise Linux License

Part Number

Description

Qty

RHEL-2S2V-3A

Red Hat Enterprise Linux

30

CON-ISV1-EL2S2V3A

3-year Support for Red Hat Enterprise Linux

30

For Cloudera Data Platform Data Center (CDP DC) software licensing requirement, contact Cloudera Data Platform software - Sales

Appendix

Configure Cisco Boot Optimized M.2 RAID Controller

Beginning with 4.0(4a), Cisco UCS Manager supports Cisco boot optimized M.2 RAID controller (UCS-M2-HWRAID), which is based on Marvell® 88SE92xx PCIe to SATA 6Gb/s controller.

The following M.2 drives are managed by the Cisco boot optimized M.2 RAID controller:

·       240GB M.2 6G SATA SSD

·       960GB M.2 6G SATA SSD

The Cisco boot optimized M.2 RAID controller supports only RAID1/JBOD (default - JBOD) mode and only UEFI boot mode.

The following are the limitations of the Cisco boot optimized M.2 RAID controller:

·       Existing LUN migration is not supported.

·       Local Disk Configuration policy is not supported.

·       Entire disk capacity is used while creating single LUN.

·       LUN is created using the Local LUN tab (see Configuring Local LUNs) under storage profile and not using the controller definitions.

·       You cannot mix different capacity M.2 drives.

To create a Disk Group Policy and Storage Profile Policy to be attach with Service Profile for Cisco Optimized M.2 RAID Controller follow the steps in the following sections.

Configure Disk Group Policy

To configure the disk group policy, follow these steps:

1.     In the UCSM WebUI, Go to storage tab. In the Storage Policy section, right-click Disk Group Policies. Click Create Disk Group Policy.

2.     Enter a name and description for the new Disk Group Policy. Select Manual Disk Group Configuration. Click Add.

M.2 disks are allocated Disk slot Number 253 and 254.

3.     Enter Slot Number 253 for the first disk. Click OK.

4.     Click Add to add second disk, enter Slot Number 254.

5.     In Virtual Drive Configuration section leave all option as Platform Default. Click OK.

Configure Storage Profile

To configure the storage profile, follow these steps:

1.     In the Storage Profiles section, select Storage Profiles. Right-click and select Create Storage Profile.

2.     Enter a name for the Storage Profile. Click Add.

3.     Enter a name for the Local LUN to be created, click Auto Deploy, check the box for Expand to Available, and from the drop-down list for Disk Group Configuration, select RAID 1 Disk Group Policy created for M.2 SATA Disks. Click OK.

4.     Attach a Storage Profile created to a Service profile or create a new Service Profile.

5.     Go to the Storage tab on the Service Profile, select Storage Profile. Select Modify Storage Profile. Select Storage Profile created for M.2 SATA Disks.

Figure 54     Example of the Service Profile Associated to a Cisco UCS C240 M5 Server with Cisco UCS-M2-HWRAID and 2 240GB M.2 SATA SSD Installed

Figure 55     Example of Virtual Drive Created from 2 M.2 SATA SSD

Apply Storage Profile in Service Profile Template

To create a new Service Profile template or update an existing template for Service Profile to attach a newly created Storage Profile for Cisco Boot Optimized RAID Controller, follow these steps:

1.     Go to Service Profile Template.

2.     Select Storage tab in Service Profile Template.

3.     Select Storage Profile tab. Click Modify Storage Profile.

4.     From the Storage Profile drop-down list, select Storage Profile for Cisco Boot Optimized RAID Controller.

5.     If updating a Service Profile Template, once saved the changes in the configuration change in the Service Profile Template and are automatically applied to all Service Profile binded with the template.

Install RHEL 7.6 on Cisco Optimized M.2 RAID Controller

To install Red Hat Enterprise Linux 7.6 OS on Cisco UCS server with Virtual Drive created from Cisco Optimized M.2 RAID Controller (UCS-M2-HWRAID) in UEFI Boot Mode, follow these steps:

1.     On the Welcome screen, select a language and click Continue.

2.     Select DATE & TIME.

3.     Select region and City.

4.     Select SOFTWARE SELECTION.

5.     Select Infrastructure Server in Base Environment. For Add-Ons for the selected environment, choose:

-      Network File System Client

-      Performance Tools

-      Compatibility Libraries

-      Development Tools

-      Security Tools

6.     Select Installation Destination.

7.     Select the Virtual Drive created from M.2 SATA SSDs. Select I will Configure Partitioning. Click DONE.

8.     Click the + button to add manual configuration to install Red Hat Enterprise Linux 7.6. Enter /boot/efi as mount point and 2048mb as Desired Capacity.

9.     Click the + button for the following mountpoint and desired capacity as shown below.

Table 10      Mount Point and Desired Capacity for RHEL Installation

Mountpoint

Desired Capacity

/boot/efi

2048mb

/boot

2048mb

Swap

2048mb

/

10.  Verify the mount points and desired capacity. Click DONE.

11.  Click Accept Changes.

12.  Click NETWORK & HOST NAME.

13.  Enter Host name, click Apply. Select Configure.

14.  Select IPv4 Settings, Enter IP Address, Netmask and Gateway. Click Save.

15.  Click OFF to turn ON the network adapter. Click Done.

16.  Click Begin Installation.

17.  Click ROOT PASSWORD.

18.  Enter Root Password. Click Done.

19.  Reboot when the installation process completes.

Configure Data Drives on Name Node and Other Management Nodes

This section describes the steps needed to configure non-OS disk drives as RAID1 using the StorCli command. All drives are part of a single RAID1 volume. This volume can be used for staging any client data to be loaded to HDFS. This volume will not be used for HDFS data.

To configure data drives on the Name node and other nodes, if the drive state displays as JBOD, creating RAID in the subsequent steps will fail with the error “The specified physical disk does not have the appropriate attributes to complete the requested command.”

To configure data drive on the Name node and other management nodes, follow these steps:

1.     If the drive state shows up as JBOD, it can be converted into Unconfigured Good using Cisco UCSM or storcli64 command. The following steps should be performed if the state is JBOD.

2.     Get the enclosure id as follows:

ansible all -m shell -a "./storcli64 pdlist -a0 | grep Enc | grep -v 252 | awk '{print $4}' | sort | uniq -c | awk '{print $2}'"

It has been observed that some earlier versions of storcli64 complains about the above mentioned command as if it is deprecated. In this case, please use “./storcli64 /c0 show all| awk '{print $1}'| sed -n '/[0-9]:[0-9]/p'|awk '{print substr($1,1,2)}'|sort -u” command to determine enclosure id.

With S3260, use -a0 and -a1 or c0 and c1 since there are two controller per node.

3.     Convert to unconfigured good:

ansible datanodes -m command -a "./storcli64 /c0 /e66 /sall set good force"

4.      Verify status by running the following command:

# ansible datanodes -m command -a "./storcli64 /c0 /e66 /sall show"

5.     Run this script as root user on rhel01 to rhel3 to create the virtual drives for the management nodes:

#vi /root/raid1.sh

./storcli64 -cfgldadd r1[$1:1,$1:2,$1:3,$1:4,$1:5,$1:6,$1:7,$1:8,$1:9,$1:10,$1:11,$1:12,$1:13,$1:14,$1:15,$1:16,$1:17,$1:18,$1:19,$1:20,$1:21,$1:22,$1:23,$1:24] wb ra nocachedbadbbu strpsz1024 -a0

The script (above) requires enclosure ID as a parameter.

6.     Run the following command to get enclosure id:

#./storcli64 pdlist -a0 | grep Enc | grep -v 252 | awk '{print $4}' | sort | uniq -c | awk '{print $2}'

#chmod 755 raid1.sh

7.     Run MegaCli script:

#./raid1.sh <EnclosureID> obtained by running the command above

WB: Write back

RA: Read Ahead

NoCachedBadBBU: Do not write cache when the BBU is bad.

Strpsz1024: Strip Size of 1024K

The command (above) will not override any existing configuration. To clear and reconfigure existing configurations refer to Embedded MegaRAID Software Users Guide available: www.broadcom.com.

8.     Run the following command. State should change to Online:

ansible namenodes -m command -a "./storcli64 /c0 /e66 /sall show"

9.     State can also be verified in UCSM as show below in Equipment>Rack-Mounts>Servers>Server # under Inventory/Storage/Disk tab:

Configure Data Drives on Data Nodes

To configure non-OS disk drives as individual RAID0 volumes using StorCli command, follow this step. These volumes will be used for HDFS Data.

1.     Issue the following command from the admin node to create the virtual drives with individual RAID 0 configurations on all the data nodes:

[root@rhel01 ~]# ansible datanodes -m command -a "./storcli64 -cfgeachdskraid0 WB RA direct NoCachedBadBBU strpsz1024 -a0"

rhel7.hdp3.cisco.local | SUCCESS | rc=0 >>

Adapter 0: Created VD 0

Configured physical device at Encl-66:Slot-7.

Adapter 0: Created VD 1

Configured physical device at Encl-66:Slot-6.

Adapter 0: Created VD 2

Configured physical device at Encl-66:Slot-8.

Adapter 0: Created VD 3

Configured physical device at Encl-66:Slot-5.

Adapter 0: Created VD 4

Configured physical device at Encl-66:Slot-3.

Adapter 0: Created VD 5

Configured physical device at Encl-66:Slot-4.

Adapter 0: Created VD 6

Configured physical device at Encl-66:Slot-1.

Adapter 0: Created VD 7

Configured physical device at Encl-66:Slot-2.

…… Omitted Ouput

24 physical devices are Configured on adapter 0.

Exit Code: 0x00

The command (above) will not override existing configurations. To clear and reconfigure existing configurations, refer to the Embedded MegaRAID Software Users Guide available at www.broadcom.com.

About the Author

Hardik Patel, Big Data Solutions Architect, Cisco Systems, Inc.

Hardik Patel is a Big Data Solutions Architect at Computing Systems Product Group. He is part of the solution engineering team focusing on big data infrastructure, solutions, and performance.

Acknowledgements

For their support and contribution to the design, validation, and creation of this Cisco Validated Design, the author would like to thank:

·       Karthik Kulkarni, Architect, Computing Systems Product Group, Cisco Systems, Inc.

·       Muhammad Afzal, Architect, Computing Systems Product Group, Cisco Systems, Inc.

·       Sarath Gonugunta, TME, Computing Systems Product Group, Cisco Systems, Inc.