[FreeCourseSite.com] Udemy - Spark SQL and Spark 3 using Scala HandsOn with Labs

1. 19 - Sample scenarios with solutions/225 - Getting crime count per type per month Implementing the logic Data Frames.mp4263.52 MB
2. 19 - Sample scenarios with solutions/224 - Getting crime count per type per month Implementing the logic Core API.mp4238.78 MB
3. 19 - Sample scenarios with solutions/227 - Get inactive customers using Core Spark API leftOuterJoin.mp4228.77 MB
4. 19 - Sample scenarios with solutions/229 - Get top 3 crimes in RESIDENCE using Core Spark API.mp4212.56 MB
5. 19 - Sample scenarios with solutions/232 - Get word count with custom control arguments num keys and file format.mp4209.56 MB
6. 19 - Sample scenarios with solutions/228 - Get inactive customers using Data Frames and SQL.mp4200.4 MB
7. 19 - Sample scenarios with solutions/230 - Get top 3 crimes in RESIDENCE using Data Frame and SQL.mp4198.24 MB
8. 19 - Sample scenarios with solutions/231 - Convert NYSE data from text file format to parquet file format.mp4179.02 MB
9. 8 - Apache Spark 2 using Scala Data Processing Overview/99 - Overview of Spark read APIs.mp4175.76 MB
10. 19 - Sample scenarios with solutions/223 - Getting crime count per type per month Understanding Data.mp4156.57 MB
11. 6 - Scala Fundamentals/76 - Basic IO Operations and using Scala Collections APIs.mp4141.46 MB
12. 8 - Apache Spark 2 using Scala Data Processing Overview/102 - Overview of Functions to Manipulate Data in Spark Data Frames.mp4135.58 MB
13. 8 - Apache Spark 2 using Scala Data Processing Overview/103 - Overview of Spark Write APIs.mp4130.44 MB
14. 6 - Scala Fundamentals/68 - Basic Programming Constructs.mp4127.14 MB
15. 10 - Apache Spark 2 using Scala Basic Transformations using Data Frames/136 - Solution Getting Delayed Counts By Date using Spark Data Frame APIs.mp4117.37 MB
16. 6 - Scala Fundamentals/74 - Basic Map Reduce Operations.mp4108.39 MB
17. 9 - Apache Spark 2 using Scala Processing Column Data using Predefined Functions/119 - Date and Time Functions in Spark Using dateformat and other functions.mp4106.42 MB
18. 6 - Scala Fundamentals/72 - Object Oriented Concepts Case Classes.mp4105.4 MB
19. 6 - Scala Fundamentals/83 - Development Cycle Develop Scala application using SBT in IntelliJ.mp497.72 MB
20. 19 - Sample scenarios with solutions/222 - Initializing the job General Guidelines.mp495.03 MB
21. 7 - Overview of Hadoop HDFS Commands/87 - Copying files from local to HDFS.mp489 MB
22. 7 - Overview of Hadoop HDFS Commands/86 - Managing HDFS Directories.mp487.88 MB
23. 16 - Apache Spark using SQL Predefined Functions/197 - Date Manipulation Functions using Spark SQL.mp486 MB
24. 13 - Apache Spark using SQL Basic Transformations/166 - Aggregating Data using Spark SQL.mp485.35 MB
25. 9 - Apache Spark 2 using Scala Processing Column Data using Predefined Functions/111 - Manipulating String Columns using Spark Functions substring.mp484.32 MB
26. 9 - Apache Spark 2 using Scala Processing Column Data using Predefined Functions/108 - Using Spark Special Functions col.mp479.79 MB
27. 6 - Scala Fundamentals/82 - Development Cycle Setup IntelliJ with Scala.mp477.74 MB
28. 18 - Apache Spark using SQL Windowing Functions/214 - LEAD or LAG Functions using Spark SQL.mp477.08 MB
29. 3 - Setting up Environment Overview of GCP and Provision Ubuntu VM/18 - Setup Jupyter Lab.mp474.51 MB
30. 18 - Apache Spark using SQL Windowing Functions/216 - Ranking using Windowing Functions in Spark SQL.mp472.95 MB
31. 3 - Setting up Environment Overview of GCP and Provision Ubuntu VM/15 - Setup Docker.mp471.74 MB
32. 12 - Apache Spark using SQL Getting Started/153 - Managing Spark Metastore Databases.mp471.68 MB
33. 12 - Apache Spark using SQL Getting Started/150 - Overview of Spark SQL Properties.mp470.56 MB
34. 16 - Apache Spark using SQL Predefined Functions/196 - String Manipulation Functions using Spark SQL.mp467.69 MB
35. 10 - Apache Spark 2 using Scala Basic Transformations using Data Frames/131 - Filtering Data from Spark Data Frames Task 6 Using functions in Filter.mp467.56 MB
36. 14 - Apache Spark using SQL Basic DDL and DML/170 - Create Spark Metastore Tables using Spark SQL.mp467.4 MB
37. 15 - Apache Spark using SQL DML and Partitioning/189 - Loading Data into Partitioned Spark Metastore Tables using Spark SQL.mp466.27 MB
38. 14 - Apache Spark using SQL Basic DDL and DML/171 - Overview of Data Types for Spark Metastore Table Columns.mp465.91 MB
39. 7 - Overview of Hadoop HDFS Commands/89 - Getting File Metadata.mp465.05 MB
40. 5 - Setup Hive and Spark on Single Node Cluster/54 - Validate Jupyter Lab Setup.mp463.98 MB
41. 9 - Apache Spark 2 using Scala Processing Column Data using Predefined Functions/114 - Manipulating String Columns using Spark Functions Padding Strings.mp463.64 MB
42. 5 - Setup Hive and Spark on Single Node Cluster/52 - Validate Spark 2 using CLIs.mp463.21 MB
43. 9 - Apache Spark 2 using Scala Processing Column Data using Predefined Functions/117 - Date and Time Functions in Spark Date Arithmetic.mp461.55 MB
44. 18 - Apache Spark using SQL Windowing Functions/215 - Getting first and last values using Spark SQL.mp461.31 MB
45. 5 - Setup Hive and Spark on Single Node Cluster/62 - Validate Spark 3 using CLIs.mp459.68 MB
46. 9 - Apache Spark 2 using Scala Processing Column Data using Predefined Functions/118 - Date and Time Functions in Spark Using trunc and datetrunc.mp458.49 MB
47. 14 - Apache Spark using SQL Basic DDL and DML/178 - Overview of Spark Metastore Table File Formats.mp457.26 MB
48. 18 - Apache Spark using SQL Windowing Functions/213 - Aggregations using Windowing Functions using Spark SQL.mp457.2 MB
49. 5 - Setup Hive and Spark on Single Node Cluster/60 - Configure Spark 3.mp456.46 MB
50. 9 - Apache Spark 2 using Scala Processing Column Data using Predefined Functions/112 - Manipulating String Columns using Spark Functions split.mp455.88 MB