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Data Science Hadoop Ecosystem E-learning
Hadoop Ecosystem E-learning
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Hadoop Ecosystem E-learning

Brand: Data Science
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€159,00 Excl. tax
€192,39 Incl. tax
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Hadoop Ecosystem E-learning

Order this unique E-learning Hadoop Ecosystem course online, 1 year 24/7 access to rich interactive videos, voice, progress monitoring through reports and tests per chapter to directly test the knowledge.

Ecosystem for Hadoop

  • start the course
  • describe supercomputing
  • recall three major functions of data analytics
  • define Big Data
  • describe the two different types of data
  • describe the components of the Big Data stack
  • identify the data repository components
  • identify the data refinery components
  • identify the data factory components
  • recall the design principles of Hadoop
  • describe the design principles of sharing nothing
  • describe the design principles of embracing failure
  • describe the components of the Hadoop Distributed File System (HDFS)
  • describe the four main HDFS daemons
  • describe Hadoop YARN
  • describe the roles of the Resource Manager daemon
  • describe the YARN NodeManager and ApplicationMaster daemons
  • define MapReduce and describe its relations to YARN
  • describe data analytics
  • describe the reasons for the complexities of the Hadoop Ecosystem
  • describe the components of the Hadoop ecosystem

Installation of Hadoop

  • start the course
  • recall the minimum system requirements for installation
  • configure the start-up shell and yum repositories
  • install the Java Developers Kit
  • setup SSH for Hadoop
  • recall why version 2.0 was significant
  • describe the three different installation modes
  • download and install Apache Hadoop
  • configure Hadoop environmental variables
  • configure Hadoop HDFS
  • start and stop Hadoop HDFS
  • configure Hadoop YARN and MapReduce
  • start and stop Hadoop YARN
  • validate the installation and configuration
  • recall the structure of the HDFS command
  • recall the importance of the output directory
  • run WordCount
  • recall the ports of the NameNode and Resource Manager Web UIs
  • use the NameNode and Resource Manager Web UIs
  • describe the best practices for changing configuration files
  • recall some of the most common errors and how to fix them
  • access Hadoop logs and troubleshoot Hadoop installation errors
  • to install and configure Hadoop and its associated components

Data Repository with HDFS and HBase

  • start the course
  • configure the replication of data blocks
  • configure the default file system scheme and authority
  • describe the functions of the NameNode
  • recall how the NameNode operates
  • recall how the DataNode maintains data integrity
  • describe the purpose of the CheckPoint Node
  • describe the role of the Backup Node
  • recall the syntax of the file system shell commands
  • use shell commands to manage files
  • use shell commands to provide information about the file system
  • perform common administration functions
  • configure parameters for NameNode and DataNode
  • troubleshoot HDFS errors
  • describe key attributes of NoSQL databases
  • describe the roles of HBase and ZooKeeper
  • install and configure ZooKeeper
  • instause the HBase command line to create tables and insert datall and configure HBase
  • instause the HBase command line to create tables and insert datall and configure HBase
  • manage tables and view the web interface
  • create and change HBase data
  • provide a basic understanding of how Hadoop Distributed File System functions

Data Repository with Flume

  • start the course
  • describe the three key attributes of Flume
  • recall some of the protocols cURL supports
  • use cURL to download web server data
  • recall some best practices for the Agent Conf files
  • install and configure Flume
  • create a Flume agent
  • describe a flume agent in detail
  • use a flume agent to load data into HDFS
  • identify popular sources
  • identify popular sinks
  • describe Flume channels
  • describe what is happening during a file roll
  • recall that Avro can be used as both a sink and a source
  • use Avro to capture a remote file
  • create multiple-hop Flume agents
  • describe interceptors
  • create a Flume agent with a TimeStampInterceptor
  • describe multifunction Flume agents
  • configure Flume agents for mutliflow
  • create multi-source Flume agents
  • compare replicating to multiplexing
  • create a Flume agent for multiple data sinks
  • recall some common reasons for Flume failures
  • use the logger to troubleshoot Flume agents
  • configure the various Flume agents

Data Repository with Sqoop

  • start the course
  • describe MySQL
  • install MySQL
  • create a database in MySQL
  • create MySQL tables and load data
  • describe Sqoop
  • describe Sqoop's architecture
  • recall the dependencies for Sqoop installation
  • install Sqoop
  • recall why it's important for the primary key to be numeric
  • perform a Sqoop import from MySQL into HDFS
  • recall what concerns the developers should be aware of
  • perform a Sqoop export from HDFS into MySQL
  • recall that you must execute a Sqoop import statement for each data element
  • perform a Sqoop import from MySQL into HBase
  • recall how to use chain troubleshooting to resolve Sqoop issues
  • use the log files to identify common Sqoop errors and their resolutions
  • to use Sqoop to extract data from a RDBMS and load the data into HDFS

Data Refinery with YARN and MapReduce

Data Factory with Hive

  • start the course
  • recall the key attributes of Hive
  • describe the configuration files
  • install and configure Hive
  • create a table in Derby using Hive
  • create a table in MySQL using Hive
  • recall the unique delimiter that Hive uses
  • describe the different operators in Hive
  • use basic SQL commands in Hive
  • use SELECT statements in Hive
  • use more complex HiveQL
  • write and use Hive scripts
  • recall what types of joins Hive can support
  • use Hive to perform joins
  • recall that a Hive partition schema must be created before loading the data
  • write a Hive partition script
  • recall how buckets are used to improve performance
  • create Hive buckets
  • recall some best practices for user defined functions
  • create a user defined function for Hive
  • recall the standard error code ranges and what they mean
  • use a Hive explain plan
  • understand configuration option, data loading and querying

Data Factory with Pig

  • start the course
  • describe Pig and its strengths
  • recall the minimal edits needed to be made to the configuration file
  • install and configure Pig
  • recall the complex data types used by Pig
  • recall some of the relational operators used by Pig
  • use the Grunt shell with Pig Latin
  • set parameters from both a text file and with the command line
  • write a Pig script
  • use a Pig script to filter data
  • use the FOREACH operator with a Pig script
  • set parameters and arguments in a Pig script
  • write a Pig script to count data
  • perform data joins using a Pig script
  • group data using a Pig script
  • cogroup data with a Pig script
  • flatten data using a pig script
  • recall the languages that can be used to write user defined functions
  • create a user defined function for Pig
  • recall the different types of error categories
  • use explain in a Pig script
  • install Pig, use Pig operators and Pig Latin, and retrieve and group records

Data Factory with Oozie and Hue

  • start the course
  • describe metastore and hiveserver2
  • install and configure metastore
  • install and configure HiveServer2
  • describe HCatalog
  • install and configure WebHCat
  • use HCatalog to flow data
  • recall the Oozie terminology
  • recall the two categories of environmental variables for configuring Oozie
  • install Oozie
  • configure Oozie
  • configure Oozie to use MySQL
  • enable the Oozie Web Console
  • describe Oozie workflows
  • submit an Oozie workflow job
  • create an Oozie workflow
  • run an Oozie workflow job
  • describe Hue
  • recall the configuration files that must be edited
  • install Hue
  • configure the hue.ini file
  • install and configure Hue on MySQL
  • use the Hue File Browser and Job Scheduler
  • configure Hive daemons, Oozie, and Hue

Data Flow for the Hadoop Ecosystem

  • start the course
  • describe the data life cycle management
  • recall the parameters that must be set in the Sqoop import statement
  • create a table and load data into MySQL
  • use Sqoop to import data into Hive
  • recall the parameters that must be set in the Sqoop export statement
  • use Sqoop to export data from Hive
  • recall the three most common date datatypes and which systems support each
  • use casting to import datetime stamps into Hive
  • export datetime stamps from Hive into MySQL
  • describe dirty data and how it should be preprocessed
  • use Hive to create tables outside the warehouse
  • use pig to sample data
  • recall some other popular components for the Hadoop Ecosystem
  • recall some best practices for pseudo-mode implementation
  • write custom scripts to assist with administrative tasks
  • troubleshoot classpath errors
  • create complex configuration files
  • to use Sqoop and Hive for data flow and fusion in the Hadoop ecosystem
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Specifications
General properties
Availabilty: 29 hours
Language: English
Certificate of participation: Yes
Online access: 90 days
Progress monitoring: Yes
Award Winning E-learning: Yes
Suitable for mobile: Yes
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