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Big Data Placement Training

(0 Ratings) 0 Students Enrolled
Created By admin Last Updated Wed,23-July-2019 English
  • Course Duration
    6 Hours
  • Mode of Training
    Self-Paced
  • Lessons
    71 Lessons
  • Placement Assistance
    Guaranteed
Free
12k+ satisfied learners Read Reviews
What Will I Learn?
  • Good understanding of Big data components
  • Aspirants will be ready to attend Interviews

Requirements
  • Any Degree Completion with no back logs (Mandatory)
  • Candidates who is willing to shine in IT career
  • Big data aspirants
  • Aspirants who want to learn new skills
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Description

This Course specially designed for candidates who are looking to take part in our placement program. Well designed Big data placement program .

Curriculum For This Course
71 Lessons 6 Hours
  • Hive Incremental dataload 00:15:40
  • Introduction 00:01:04 Preview
  • Bigdata Overview 00:10:18 Preview
  • Traditional data processing vs Big data 00:03:32 Preview
  • Traditional method vs Hadoop Map reduce method 00:02:26
  • Basic Flow of a MapReduce Program 00:04:41
  • Mapreduce Program flow with Example 00:04:48
  • Introduction to Hive 00:03:45 Preview
  • Motivation Of Hive 00:01:21
  • Sql vs Hive 00:01:32
  • Working Of Hive 00:02:08
  • Architecture Of Hive 00:04:58
  • Hadoop And Hive Installation 00:05:01
  • Create Databases 00:07:15
  • Table Creation and Data loading - Part 1 00:08:16
  • Table Creation and Data loading - Part 2 00:03:33
  • Managed Table vs External Table 00:10:28
  • Insert Statement 00:06:30
  • Multi Insert statement 00:02:44
  • Alter table schema 00:06:53
  • Sorting- Sort by, Order by , Cluster by , Distribute by, Cluster by 00:07:24
  • Date & Mathematical functions 00:06:08
  • String functions 00:05:39
  • Split, Substr, instr functions 00:03:06
  • Conditional statements 00:04:57
  • Explode And Lateral View 00:07:21
  • Rlike function 00:03:04
  • Rank, Dense_rank(),Row_number() 00:10:12
  • What is partitioning? 00:01:42
  • Static partitioning 00:07:02
  • Dynamic partitioning 00:04:38
  • Alter partitioned table and Msck repair table 00:06:26
  • What is Bucketing? 00:02:27
  • Create Bucketed table 00:08:11
  • Tablesampling 00:05:09
  • No_drop, offline command 00:05:04
  • Inner joins on 2 tables 00:03:39
  • Outer joins on 2 tables 00:04:35
  • Join 3 tables in Hive 00:04:32
  • Memory Management & Optimization of Joins 00:02:23
  • Map joins 00:05:47
  • What are views? 00:02:07
  • Creating views in different ways 00:07:22
  • Advantages of Views 00:02:40
  • Index Creation ( compact & bitmap ) 00:09:52
  • Multiple indexes on same table 00:08:16
  • when to use and when not to use indexing 00:01:33
  • skip header and footer record while loading in table 00:08:03
  • Immutable table property 00:10:29
  • Purge property + Difference between drop and truncate 00:05:13
  • Null property 00:07:26
  • ACID/Transactional features in Hive 00:10:12
  • ORC table properties 00:04:01
  • Part 1 00:10:18
  • Part 2 00:03:33
  • Merge files in Hive 00:02:55
  • Parallelism Property 00:06:38
  • Executing Hive queries from Bash shell 00:04:51
  • Run Unix and Hadoop commands from hive shell 00:03:47
  • Variables in Hive (hiveconf & hivevar) 00:06:47
  • Difference between hiveconf & hivevar 00:02:30
  • Using variables in bash shell 00:04:47
  • Substituting value of a Variable 00:02:23
  • Text, Sequence, Avro Files 00:05:35
  • RC, ORC, Parquet Files 00:02:30
  • Performance Test results of Various Files 00:02:39
  • Which File Format to choose 00:01:56
  • What is Tez engine and its comparison with MR 00:07:15

Big Data Placement Training