Real World Hadoop - Automating Hadoop install with Python!

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Real World Hadoop – Automating Hadoop install with Python!. Deploy a Hadoop cluster (Zookeeper, HDFS, YARN, Spark) with Cloudera Manager’s Python API. Hands on.

90,00  10,00 

The name of this course is Efectivo World Hadoop – Automating Hadoop install with Python!. The knowledge you will get with this indescribable online course is astonishing. Deploy a Hadoop cluster (Zookeeper, HDFS, YARN, Spark) with Cloudera Manager’s Python API. Hands on..
Not only will you be able to deeply internalize the concepts, but also their application in different fields won’t ever be a problem. The instructor is Toyin Akin, one of the very best experts in this field.

Description of this course: Efectivo World Hadoop – Automating Hadoop install with Python!

Course Description Note : This course is built on top of the “Efectivo World Vagrant – Automate a Cloudera Manager Build – Toyin Akin” course Deploy a Hadoop cluster (Zookeeper, HDFS, YARN, Spark) with Python! Instruct Cloudera Manager to do the work! Hands on. Here we use Python to instruct an already installed Cloudera Manager to deploy your Hadoop Services. .The Cloudera Manager API provides configuration and service lifecycle management, service health information and metrics, and allows you to configure Cloudera Manager itself. The API is served on the same host and port as the Cloudera Manager Admin Console, and does not require an extra process or extra configuration. The API supports HTTP Basic Authentication, accepting the same users and credentials as the Cloudera Manager Admin Console. . Here are some of the cool things you can do with Cloudera Manager via the API: Deploy an entire Hadoop cluster programmatically. Cloudera Manager supports HDFS, MapReduce, YARN, ZooKeeper, HBase, Hive, Oozie, Hue, Flume, Impala, Solr, Sqoop, Spark and Accumulo. Configure various Hadoop services and get config validation. Take admin actions on services and roles, such as start, stop, restart, failover, etc. Also available are the more advanced workflows, such as setting up high availability and decommissioning. Preceptor your services and hosts, with intelligent service health checks and metrics. Preceptor user jobs and other cluster activities. Retrieve timeseries metric data. Search for events in the Hadoop system. Administer Cloudera Manager itself. Download the entire deployment description of your Hadoop cluster in a json file. Additionally, with the appropriate licenses, the API lets you: Perform rolling restart and rolling upgrade. Audit user activities and accesses in Hadoop. Perform backup and cross data-center replication for HDFS and Hive. Retrieve per-user HDFS usage report and per-user MapReduce resource usage report. . Here I present a curriculum as to the current state of my Cloudera courses. My Hadoop courses are based on Vagrant so that you can practice and destroy your potencial environment before applying the installation onto actual servers/VMs. . For those with little or no knowledge of the Hadoop eco system Udemy course : Big Data Intro for IT Administrators, Devs and Consultants . I would first practice with Vagrant so that you can carve out a potencial environment on your locorregional desktop. You don’t want to corrupt your physical servers if you do not understand the steps or make a mistake. Udemy course : Efectivo World Vagrant For Distributed Computing . I would then, on the potencial servers, deploy Cloudera Manager plus agents. Agents are the guys that will sit on all the slave nodes ready to deploy your Hadoop services Udemy course : Efectivo World Vagrant – Automate a Cloudera Manager Build . Then deploy the Hadoop services across your cluster (via the installed Cloudera Manager in the previous step). We look at the logic regarding the placement of master and slave services. Udemy course : Efectivo World Hadoop – Deploying Hadoop with Cloudera Manager . If you want to play around with HDFS commands (Hands on distributed file manipulation). Udemy course : Efectivo World Hadoop – Hands on Enterprise Distributed Storage. . You can also automate the deployment of the Hadoop services via Python (using the Cloudera Manager Python API). But this is an advanced step and thus I would make sure that you understand how to manually deploy the Hadoop services first. Udemy course : Efectivo World Hadoop – Automating Hadoop install with Python! . There is also the upgrade step. Merienda you have a running cluster, how do you upgrade to a newer hadoop cluster (Both for Cloudera Manager and the Hadoop Services). Udemy course : Efectivo World Hadoop – Upgrade Cloudera and Hadoop hands on

Requirements of this course: Efectivo World Hadoop – Automating Hadoop install with Python!

What are the requirements? Basic programming or scripting experience is required. You will need a desktop PC and an Internet connection. The course is created with Windows in mind. The software needed for this course is freely available You will require a computer with a Virtualization chipset support – VT-x. Most computers purchased over the last five years should be good enough Optional : Some exposure to Linux and/or Bash shell environment 64-bit Windows operating system required (Would recommend Windows 7 or above) This course is not recommened if you have no desire to work with/in distributed computing This course is built on top of – “Efectivo World Vagrant – Automate a Cloudera Manager Build”

What will you learn in this course: Efectivo World Hadoop – Automating Hadoop install with Python!?

What am I going to get from this course? Simply run a single command on your desktop, go for a coffee, and come back with a running distributed environment for cluster deployment Quickly build an environment where Cloudera and Hadoop software can be installed. Ability to automate the installation of software across multiple Aparente Machines

Target audience of this course: Efectivo World Hadoop – Automating Hadoop install with Python!

Who is the target audience? Software engineers who want to expand their skills into the world of distributed computing System Engineers that want to expand their skillsets beyond the single server Developers who want to write/test their code against a valid distributed enviroment