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inovitechnologies-universe · 5 years

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Hadoop Training Institute in noida , Delhi

Hadoop Installation & setupThe architecture of Hadoop 2.0 cluster, what is High Availability and Federation, how to setup a production cluster, the various shell commands in Hadoop, understanding configuration files in Hadoop 2.0, installing single node cluster with Cloudera Manager, understanding Spark, Scala, Sqoop, Pig and Flume.Introduction to Big Data Hadoop. Understanding HDFS & MapreduceIntroducing Big Data & Hadoop, what is Big Data and where does Hadoop fits in, two important Hadoop ecosystem componentsnamely Map Reduce and HDFS, in-depth Hadoop Distributed File System – Replications, Block Size, Secondary Name node, High Availability, in-depth YARN – Resource Manager, Node Manager.Hands-on Exercise – HDFS working mechanism, data replication process, how to determine the size of the block, understanding a DataNode and NameNode.Introduction to HiveAdvance Hive & ImpalaIntroduction to PigFlume, Sqoop & HBaseWriting Spark Applications using ScalaSpark frameworkRDD in SparkData Frames and Spark SQLMachine Learning using Spark (Mlib)Spark StreamingHadoop Administration – Multi Node Cluster Setup using Amazon EC2Create a four node Hadoop cluster setup, running the MapReduce Jobs on the Hadoop cluster, successfully running the MapReduce code, working with the Cloudera Manager setup.Hands-on Exercise – The method to build a multi-node Hadoop cluster using an Amazon EC2 instance, working with the Cloudera Manager.Hadoop Administration – Cluster ConfigurationHadoop Administration – Maintenance, Monitoring and TroubleshootingETL Connectivity with Hadoop EcosystemProject Solution Discussion and Cloudera Certification Tips & TricksWorking towards the solution of the Hadoop project solution, its problem statements and the possible solution outcomes, preparing for the Cloudera Certifications, points to focus for scoring the highest marks, tips for cracking Hadoop interview questions.Hands-on Exercise – The project of a real-world high value Big Data Hadoop application and getting the right solution based on the criteria set by the Intellipaat team.Following topics will be available only in self-paced Mode.Hadoop Application TestingWhy testing is important, Unit testing, Integration testing, Performance testing, Diagnostics, Nightly QA test, Benchmark and end to end tests, Functional testing, Release certification testing, Security testing, Scalability Testing, Commissioning and Decommissioning of Data Nodes Testing, Reliability testing, Release testingRoles and Responsibilities of Hadoop Testing ProfessionalFramework called MR Unit for Testing of Map-Reduce ProgramsUnit TestingTest ExecutionTest Plan Strategy and writing Test Cases for testing Hadoop ApplicationWhat Hadoop Projects You will be working on?

Hadoop Training Institute in noida , Delhi

Inovi Technologies offers the industry recognized Big Data Hadoop Training in Noida that combines corporate training, classroom training effectively to fulfill the educational demands of the students worldwide. Big Data Hadoop training course in Noida provides in-depth knowledge on Hadoop Ecosystem tools and Big Data. Here you learn HDFS, MapReduce, Hbase, Hive, Pig, Oozie, Flume and Sqoop by working on real-world Big Data Hadoop Projects. Big data Hadoop Courses in Noida With this Hadoop training conducted by experienced trainers in our institute, you can easily learn the components of the Hadoop ecosystem, such as Hadoop 2.7, HDFS, Yarn, MapReduce, Pig, Impala, Flume, HBase, Apache Spark, and more. Designed by reputed industry experts, this best Hadoop certification training in Noida provides in-depth knowledge on Hadoop Ecosystem tools and Big Data. We also offer real-time training with case study based projects that provide hands-on experience of the subject.

Course Contents

Deep Dive in Mapreduce

Learning the working mechanism of MapReduce, understanding the mapping and reducing stages in MR, the various terminologies in MR like Input Format, Output Format, Partitioners, Combiners, Shuffle and Sort

Hands-on Exercise – How to write a Word Count program in MapReduce, how to write a custom Partitioner, what is a MapReduce Combiner, how to run a job in a local job runner, deploying unit test, what is a map side join and reduce side join, what is a tool runner, how to use counters, dataset joining with map side and reduce side joins.

Introducing Hadoop Hive, detailed architecture of Hive, comparing Hive with Pig and RDBMS, working with Hive Query Language, creation of database, table, Group by and other clauses, the various types of Hive tables, Hcatalog, storing the Hive Results, Hive partitioning and Buckets.Hands-on Exercise – Database creation in Hive, dropping a database, Hive table creation, how to change the database, data loading, Hive table creation, dropping and altering table, pulling data by writing Hive queries with filter conditions, table partitioning in Hive, what is a group by clause

The indexing in Hive, the Map side Join in Hive, working with complex data types, the Hive User-defined Functions, Introduction to Impala, comparing Hive with Impala, the detailed architecture of ImpalaHands-on Exercise – How to work with Hive queries, the process of joining table and writing indexes, external table and sequence table deployment, data storage in a different table.

Apache Pig introduction, its various features, the various data types and schema in Hive, the available functions in Pig, Hive Bags, Tuples and Fields.Hands-on Exercise – Working with Pig in MapReduce and local mode, loading of data, limiting data to 4 rows, storing the data into file, working with Group By,Filter By,Distinct,Cross,Split in Hive.

Apache Sqoop introduction, overview, importing and exporting data, performance improvement with Sqoop, Sqoop limitations, introduction to Flume and understanding the architecture of Flume, what is HBase and the CAP theorem.Hands-on Exercise – Working with Flume to generating of Sequence Number and consuming it, using the Flume Agent to consume the Twitter data, using AVRO to create Hive Table, AVRO with Pig, creating Table in HBase, deploying Disable, Scan and Enable Table.

Using Scala for writing Apache Spark applications, detailed study of Scala, the need for Scala, the concept of object oriented programing, executing the Scala code, the various classes in Scala like Getters,Setters, Constructors, Abstract ,Extending Objects, Overriding Methods, the Java and Scala interoperability, the concept of functional programming and anonymous functions, Bobsrockets package, comparing the mutable and immutable collections.Hands-on Exercise – Writing Spark application using Scala, understanding the robustness of Scala for Spark real-time analytics operation.

Detailed Apache Spark, its various features, comparing with Hadoop, the various Spark components, combining HDFS with Spark, Scalding, introduction to Scala, importance of Scala and RDD.Hands-on Exercise – The Resilient Distributed Dataset in Spark and how it helps to speed up big data processing.

Understanding the Spark RDD operations, comparison of Spark with MapReduce, what is a Spark transformation, loading data in Spark, types of RDD operations viz. transformation and action, what is Key Value pair.Hands-on Exercise – How to deploy RDD with HDFS, using the in-memory dataset, using file for RDD, how to define the base RDD from external file, deploying RDD via transformation, using the Map and Reduce functions, working on word count and count log severity.

The detailed Spark SQL, the significance of SQL in Spark for working with structured data processing, Spark SQL JSON support, working with XML data, and parquet files, creating HiveContext, writing Data Frame to Hive, How to read a JDBC file, significance of a Spark Data Frame, how to create a Data Frame, what is schema manual inferring, how to work with CSV files, JDBC table reading, data conversion from Data Frame to JDBC, Spark SQL user-defined functions. shared variable and accumulators, how to query and transform data in Data Frames, how Data Frame provides the benefits of both Spark RDD and Spark SQL, deploying Hive on Spark as the execution engine.Hands-on Exercise – Data querying and transformation using Data Frames, finding out the benefits of Data Frames over Spark SQL and Spark RDD.

Introduction to Spark MLlib, understanding the various algorithms, what is Spark iterative algorithm, Spark graph processing analysis, introducing machine learning, K-Means clustering, Spark variables like shared and broadcast variables, what are accumulators.Hands-on Exercise – Writing spark code using Mlib.

Introduction to Spark streaming, the architecture of Spark Streaming, working with the Spark streaming program, processing data using Spark streaming, requesting count and Dstream, multi-batch and sliding window operations and working with advanced data sources.Hands-on Exercise – Deploying Spark streaming for data in motion and checking the output is as per the requirement.

The overview of Hadoop configuration, the importance of Hadoop configuration file, the various parameters and values of configuration, the HDFS parameters and MapReduce parameters, setting up the Hadoop environment, the Include’ and Exclude configuration files, the administration and maintenance of Name node, Data node directory structures and files, What is a File system image, understanding Edit log.Hands-on Exercise – The process of performance tuning in MapReduce.

Introduction to the Checkpoint Procedure, Name node failure and how to ensure the recovery procedure, Safe Mode, Metadata and Data backup, the various potential problems and solutions, what to look for, how to add and remove nodes.Hands-on Exercise – How to go about ensuring the MapReduce File system Recovery for various different scenarios, JMX monitoring of the Hadoop cluster, how to use the logs and stack traces for monitoring and troubleshooting, using the Job Scheduler for scheduling jobs in the same cluster, getting the MapReduce job submission flow, FIFO schedule, getting to know the Fair Scheduler and its configuration.

How ETL tools work in Big data Industry, Introduction to ETL and Data warehousing. Working with prominent use cases of Big data in ETL industry, End to End ETL PoC showing big data integration with ETL tool.Hands-on Exercise – Connecting to HDFS from ETL tool and moving data from Local system to HDFS, Moving Data from DBMS to HDFS, Working with Hive with ETL Tool, Creating Map Reduce job in ETL tool

Understanding the Requirement, preparation of the Testing Estimation, Test Cases, Test Data, Test bed creation, Test Execution, Defect Reporting, Defect Retest, Daily Status report delivery, Test completion, ETL testing at every stage (HDFS, HIVE, HBASE) while loading the input (logs/files/records etc) using sqoop/flume which includes but not limited to data verification, Reconciliation, User Authorization and Authentication testing (Groups, Users, Privileges etc), Report defects to the development team or manager and driving them to closure, Consolidate all the defects and create defect reports, Validating new feature and issues in Core Hadoop.

Report defects to the development team or manager and driving them to closure, Consolidate all the defects and create defect reports, Responsible for creating a testing Framework called MR Unit for testing of Map-Reduce programs.

Automation testing using the OOZIE, Data validation using the querysurge tool.

Test plan for HDFS upgrade, Test automation and result

How to test install and configure

Project 1 : Working with MapReduce, Hive, Sqoop

Industry : General

Problem Statement : How to successfully import data using Sqoop into HDFS for data analysis.

Topics : As part of this project you will work on the various Hadoop components like MapReduce, Apache Hive and Apache Sqoop. Work with Sqoop to import data from relational database management system like MySQL data into HDFS. Deploy Hive for summarizing data, querying and analysis. Convert SQL queries using HiveQL for deploying MapReduce on the transferred data. You will gain considerable proficiency in Hive, and Sqoop after completion of this project

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Mobile. No:- 9354482334,8810643463

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Address:- F7 Sector-3 Noida UP 201301

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amrselim · 3 years

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#IFTTT #YouTube

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growinstablog · 4 years

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Bullying Instagramer Gets 150,000 Followers: Is Censorship Even Good?

Today, social media has played an enormous part in people’s everyday life. From daily updates like news and politics to personal posts, social media has made a significant impact on how people see the world. You’ll find different social media platforms online today, including Facebook, Instagram, Twitter, YouTube, and many more. With the vast expansion of social media platforms online, personal life has never been seen this much publicity. Social media enables people to connect, communicate, share, and even view other people’s content.

Social Media On The Censor!

Since social media is growing rampant on the web, a lot of people gather information like a sponge. For instance, social media influencers often use this as the catalyst to increase followers and subscribers. Utilizing the capabilities of social media to reach their target audiences instantly, people create enticing and attractive content to increase their popularity or fame.

Furthermore, video creation and online streaming is a big trend right now. Often, you will find videos talking about social affairs, news, and politics. Also, you will find different content with reviews, opinions, and intriguing ideas as their primary objective. Although most people may perceive this as genuine effort and intriguing, most are filled with discrimination and discrepancies. This is the exact situation faced by a 13-year-old boy on his Instagram account.

Tweets by StopBullyingGov

The Boy Who Faced Bullying

Sharing your opinions, recommendations, and suggestions is an all-too-common situation online. You can answer questions posted by other people through commenting or sending a message. Also, voicing out your ideas today has never been more accessible due to the introduction of an extensive array of social media platforms like Instagram. Today, Instagram is an inclusive environment for people to post their content for their audience to see. For instance, you will find several celebrities updating their profiles multiple times a day. You will also discover influencers using Instagram’s broad niche to promote products and services.

Last week, a 13-year-old boy named Callum Manning from South Shield started his own Instagram account. Although, you will find most teens posting memes and rich content like videos and GIFS at the age of 13. However, in Callum’s case, everything is different. He started his Instagram page discreetly named “ Cal’s Book Account” for the sense of reviewing books he has read. Callum decided to curate such content with a mindset of flagging up books he liked to his friends. However, the toxicity of the online environment made a devastating impact on his account.

Misinformation or Freedom?

Apart from misleading information and worthless comments, people often dove into bullying users online for several reasons, including “nerdy” content. When you’re young, and your interests are way different in your age group, you’re heading to a world full of hurt. Bullying is prevalent in younger generations, and this is precisely what happened with Callum. People started sending insulting and degrading messages to a group chat he had joined at his new school.

Callum’s love for reading books knows no bounds. When compared to other teens on his age, Callum’s interest is unique. However, the bullying he experienced left him scathed and utterly dumfounded. With his knack for being impervious to crying, the amount of humiliation he received that day was too much, leaving him in shambles.

The Boy Who Regained His Composure

Although Callum’s account was riddled with a lot of discrimination and purposeful bullying, this headed to a brighter side when his sister entered the fray. Ellis Landreth, 24, wrote on Twitter mentioning the issue his brother is facing. Next, Ellis posted Callums’s Instagram on Twitter and stated the condition of bullying experienced by his brother. Ellis suggested that she could not perceive how awful kids are online. Also, she said that his brother’s new school ridiculed him all the while, creating a group chat saying that Callum’s a creep. In addition to this, the group chat added Callum for him to see the embarrassment he is in.

Callum’s sister said that she was hoping some of her friends would see the issue and, in turn, like a few of Callum’s posts or follow him to show some encouraging results for Callum’s interest in books. However, not only are Ellis’ friends showing their support on Callum’s account, but within a few hours, Callum’s follower count has risen exponentially. Garnering thousands of new followers, Callum’s account was filled with comments showing support for the teen’s love of reading. In addition to this, this sudden rise of followers also helps mitigate the cause of bullying online. Callum said, “ People saw it, and people just thought, “it’s not right” because it isn’t .”

The Boy Who Overcome Despair

Even though bashed with several comments on his fondness of reviewing books, Callum never stopped. And, after attaining a considerable amount of followers, Callum said that he is delighted since there are still people in the world who are kind. Callum’s account surpassed 150,000 followers at the beginning of March and is still growing. With people propelling his account amidst the bullying, it caught the attention of several book enthusiasts, including notable authors and publishers.

Caroline Kepnes, the author of the book You, contacted Callum and offered to send him more books to read and review. What’s more, several of Callum’s new followers were shocked to see books written by Mary Shelley, Jane Austen, and George Orwell. In addition to these, Callum also read and reviewers novels, including the Harry Potter and Twilight literary pieces. With a vast supply of books coming from several directions, Callum’s mother, Carla Landreth, said that her problem now is where will she put all the books Callum is receiving. Besides, Ms. Landreth hopes that Callum’s experience will make a considerable impact on alleviating bullying.

The Bottom Line: Is Censorship Online Permissible?

Whether you’re bullying someone or the one taking the brunt of it, social media will still be unpredictable. Some people despise others to increase their popularity, while some support others to build up better relationships. In addition to this, Instagram is a place where if you lack followers, immersion, and relevant content, your profile can be forfeited. With Callum’s example, having a more comprehensive range of audience and resources, you’ll reach your goal in no time and can even turn the worst of events into a fruitful future.

https://growinsta.xyz/bullying-instagramer-gets-150000-followers-is-censorship-even-good/

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autobizupdate · 7 years

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Fully Autonomous Vehicles Spur LIDAR Sensors Mass Adoption

Leading vehicle OEMs develop roadmaps for LIDAR, finds Frost & Sullivan's Mobility team

LONDON, Jan. 26, 2017 /PRNewswire/ -- Cost-effective, high-resolution light detection and ranging (LIDAR) sensors capable of long-range object detection will be essential for high-to-fully automated driving applications. Demand for 3D mapping and imaging, better overall performance, automated processing of graphic data gathering and self-sufficient sensor with best-in-class performance in low-visibility conditions are factors driving the development and adoption of LIDAR sensors within the advanced driver assistance systems (ADAS) sensor suite for automated passenger vehicles.

Fully Autonomous Vehicles Spur LIDAR Sensors Mass Adoption - Leading vehicle OEMs develop roadmaps for LIDAR, finds Frost & Sullivan's Mobility team

"Most original equipment manufacturers (OEMs) will use LIDAR as a complement to camera and radar until a robust sensing solution is achieved," said Frost & Sullivan Intelligent Mobility Senior Analyst Anirudh Venkitaraman. "Consolidation in the market has led to the emergence of a few major players such as Ibeo-ZF, LEDDARTECH-Valeo, Quanergy-Delphi, and ASC-Continental that will play a crucial role in technology development. This will enable cost-effective, solid-state LIDAR development for mass adoption post 2025."

Automotive LIDAR Market for ADAS and Automated Driving, Global 2016 is part of Frost & Sullivan's Mobility: Automotive & Transportation Growth Partnership Service program. According to the research, short-range LIDAR for autonomic emergency braking (AEB) is predominant in Japan and Europe. North America prefers to use radar and camera-based AEB, while Korea has high penetration of sensor fusion AEB.

Click here (https://goo.gl/3c755j) for complimentary access to more information on this analysis and to register for a Growth Strategy Dialogue, a free interactive briefing with Frost & Sullivan's thought leaders.

In the next four years, there is a possibility of commoditization of level-2 automation with volume OEMs -- such as Ford, Hyundai, and General Motors -- introducing the technology in some of their premium offerings. Leading players have adopted a variety of roadmaps for LIDAR:

BMW is initially expected to introduce the city and highway pilot features, along with fully automated parking by 2022 on the i-8, 7-Series, and i-5

Mercedes-Benz is expected to introduce a level-3 highway pilot and an improved parking feature with the E-Class in 2017

Commercialization of level-3 features in Ford vehicles is expected in 2025 or later

General Motors wants level-4 automation with Cadillac by 2025

Toyota is advocating intelligent systems to aid drivers, but is hesitant on committing to a fully autonomous driving timeline

After introducing an automated vehicle with LIDAR, Google is expected to compete against top OEMs in the North American market

"Mechanical LIDARs will be the only LIDAR solution enabling automated driving applications until solid-state LIDARs become the standard closer to 2020," noted Venkitaraman. "When deployed, solid-state LIDARs will be used for level-3 and level-4 autonomous driving features like lane keeping and highway auto pilot applications, forcing the phasing out of mechanical systems by 2025."

About Frost & Sullivan

Frost & Sullivan, the Growth Partnership Company, works in collaboration with clients to leverage visionary innovation that addresses the global challenges and related growth opportunities that will make or break today's market participants. For more than 50 years, we have been developing growth strategies for the global 1000, emerging businesses, the public sector and the investment community. Contact us: Start the discussion.

Automotive LIDAR Market for ADAS and Automated Driving, Global 2016 MB5C-18

Contact: Jana Schoneborn Corporate Communications -- Europe P: +49 (0)69 77033 43 E: [email protected]

Twitter: @Frost_Sullivan or @FS_Automotive Facebook: FrostandSullivan Linkedin: Future of Mobility -- A Frost & Sullivan Forum

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Read this news on PR Newswire Asia website: Fully Autonomous Vehicles Spur LIDAR Sensors Mass Adoption

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asialogistics · 7 years