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Spark In Depth


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53:06 Hours
90 Days access to the course
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Curriculum

  • 1. Introduction to Spark-I  57 Mins  
  • 2.Introduction to Spark-II  75 Mins  
  • 3.Installing Spark 3.2.0 in Windows  21 Mins  
  • 4.WordCount Using REPL Windows  35 Mins  
  • 5.WordCount in Spark IntelliJ(Windows)  31 Mins  
  • 6.Installing Scala Spark in Ubuntu  17 Mins  
  • 7. WordCount in IntelliJ Ubuntu  12 Mins  
  • 8. Exploring RDD-Part I  59 Mins  
  • 9.Spark RDD-Part II  60 Mins  
  • 10.Coalesce and Repartition  61 Mins  
  • 11.Spark Transformation-Part I  49 Mins  
  • 12.Spark Transformation-Part II  47 Mins  
  • 13.Spark Action-Part I  45 Mins  
  • 14.Spark Action-Part II  28 Mins  
  • 15.Spark Action-Part III  53 Mins  
  • 16.Spark Action Part IV  39 Mins  
  • 17.Caching RDD  37 Mins  
  • 18.Paired RDD-I  36 Mins  
  • 19.Paired RDD-II  47 Mins  
  • 20.Paired RDD-III  67 Mins  
  • 21.Paired RDD-IV  36 Mins  
  • 22.Paired RDD-V  50 Mins  
  • 23.Types of Partitioner  38 Mins  
  • 24.Practice Exercise 1  3 Mins  
  • 25.Practice Exercise 2  8 Mins  
  • 26.Accumulators  37 Mins  
  • 27.Broadcast Variable  30 Mins  
  • 28.Inner Join  29 Mins  
  • 29.Spark Deployment Mode-Part I  62 Mins  
  • 30.Spark Deployment Mode-Part II  40 Mins  
  • 31.Loading and Saving of Data-Part I  57 Mins  
  • 32.Working with CSV,TSV,Sequence,Object File  48 Mins  
  • 33.Working with Amazon S3 and HBase  40 Mins  
  • 34.Spark Graphx  29 Mins  
  • 35.Real time Assignment on Graphx  25 Mins  
  • 36.Spark SQL Intro  57 Mins  
  • 37. Comparing code of Dataset,Data Frame,RDD  49 Mins  
  • 38.Exploring DataFrame  61 Mins  
  • 39.Programatically creating DataFrame  14 Mins  
  • 40. Spark SQL Builtin Functions-I  49 Mins  
  • 41. Spark SQL Builtin Functions-II  48 Mins  
  • 42. Spark SQL Builtin Functions-III  81 Mins  
  • 43.Joins in DataFrame and Spark UI  64 Mins  
  • 44.DataFrame in IntelliJ  14 Mins  
  • 45.Working with DataSets  41 Mins  
  • 46.Converting RDD,DF,DS  22 Mins  
  • 47.Comparing RDD,DS,DF  16 Mins  
  • 48.row_number,rank,dense_rank  30 Mins  
  • 49.Lag,Lead,Aggregate  33 Mins  
  • 50.Pivot and Unpivot  12 Mins  
  • 51.Partitioning in DataFrame  34 Mins  
  • 52.Spark Connecting to Hive  39 Mins  
  • 50.Realtime Project  68 Mins  
  • 53.BroadCast Hash Join  26 Mins  
  • 54.Shuffle Hash Join  13 Mins  
  • 55.Shuffle Sort Merge Join  14 Mins  
  • 56.Broadcast Nested Loop Join  12 Mins  
  • 57.Cross Join  8 Mins  
  • 58.Semi and Anti Join  8 Mins  
  • 59.Self Join  25 Mins  
  • 60.Cartesian Join  9 Mins  
  • 61.Hinting Join Strategies  24 Mins  
  • 62.How Spark Decides Join Strategies  21 Mins  
  • 63.Avoid Data Skewing with Salting Technique  51 Mins  
  • 64.Replacing Nulls  12 Mins  
  • 65.Writing UDF  24 Mins  
  • 66.Bucketing  22 Mins  
  • 67.Vectorization using ORC and Parquet  18 Mins  
  • 68.Understanding Tungsten  21 Mins  
  • 69.Catalyst Optimizer  26 Mins  
  • 70. Dynamic Resource Allocation  34 Mins  
  • 71.Adaptive Query Execution  23 Mins  
  • 72.Introduction to Spark Streaming  30 Mins  
  • 73. Writing First Streaming Job  22 Mins  
  • 74.Working with Multiple Streams  22 Mins  
  • 75.Aggregation using checkpointing  28 Mins  
  • 76.Realtime Coding Standard  14 Mins  
  • 77.Foreach in Streaming  12 Mins  
  • 78. Streaming and writing to a File  27 Mins  
  • 79.Transformation and Queue Streams  15 Mins  
  • 80.Sliding window Technique  51 Mins  
  • 81.Assignment on Spark Streaming  21 Mins  
  • 82.Spark Streaming with Kafka  34 Mins  
  • 83.Spark Structured Streaming  40 Mins  
  • 84. Streaming files using Structured Streaming  19 Mins  
  • 85.Various Configuration for File Streaming  17 Mins  
  • 86. Windowing in Structured Streaming  11 Mins  
  • 87.Watermarking- Late Data  18 Mins  
  • 88.Unit Testing RDD and DataFrames  40 Mins  
  • 89. 20 Different Spark Optimisation Recap  82 Mins  
  • 90. From Development to Production  47 Mins  
  • 91.Deciding resources for any Spark Job  40 Mins  
  • 92. Daily activity of a Data Engineer  6 Mins  
  • 93. My Last Project- Building Maps  59 Mins  

Certificate

Certificate

Instructor

Suraj Ghimire
Suraj Ghimire

Scala,Spark,Kafka,ElasticSearch,Bigdata


  1. 10 Years of IT experience
  2. Working in  BigData since last 7.5 Years
  3. Training bigdata since 2014
  4. Good Numbers of 5 star review on facebook
  5. 70% average hike from all students who are placed.