Udemy - Apache Spark for Java Developers

1. 43. Recommender Systems/2. Building the Model.mp4 263.91 MB
2. 41. Decision Trees/2. Building the Model.mp4 259.33 MB
3. 40. Logistic Regression/3. Coding a Logistic Regression.mp4 235.43 MB
4. 38. Pipelines/1. Pipelines.mp4 228.49 MB
5. 42. K Means Clustering/1. K Means Clustering.mp4 216.60 MB
6. 16. SparkSQL Getting Started/1. SparkSQL Getting Started.mp4 203.74 MB
7. 26. More Aggregations/1. How to use the agg method in Spark.mp4 200.68 MB
8. 45. Streaming Chapter 2 - Streaming with Apache Kafka/5. Using KafkaUtils to access a DStream.mp4 192.72 MB
9. 14. RDD Performance/7. Caching and Persistence.mp4 191.58 MB
10. 2. Getting Started/2. Installing Spark.mp4 172.51 MB
11. 29. SparkSQL Performance/1. Understand the SparkUI for SparkSQL.mp4 172.30 MB
12. 25. Pivot Tables/2. Coding a Pivot Table in Spark.mp4 169.53 MB
13. 9. Keyword Ranking Practical/3. Worked Solution (continued) with Sorting.mp4 160.00 MB
14. 46. Streaming Chapter 3- Structured Streaming/1. Structured Streaming Overview.mp4 156.62 MB
15. 45. Streaming Chapter 2 - Streaming with Apache Kafka/3. Using a Kafka Event Simulator.mp4 156.40 MB
16. 39. Case Study/2. Case Study - Walkthrough Part 1.mp4 155.22 MB
17. 24. DataFrames API/1. SQL vs DataFrames.mp4 150.72 MB
18. 23. Ordering/1. Ordering.mp4 149.88 MB
19. 39. Case Study/3. Case Study - Walkthrough Part 2.mp4 143.42 MB
20. 19. In Memory Data/1. In Memory Data.mp4 143.03 MB
21. 17. Datasets/4. Filters using Columns.mp4 142.29 MB
22. 22. Multiple Groupings/1. Multiple Groupings.mp4 142.17 MB
23. 8. Reading from Disk/1. Reading from Disk.mp4 141.32 MB
24. 24. DataFrames API/2. DataFrame Grouping.mp4 140.27 MB
25. 9. Keyword Ranking Practical/2. Worked Solution.mp4 139.27 MB
26. 14. RDD Performance/4. Shuffles.mp4 136.92 MB
27. 46. Streaming Chapter 3- Structured Streaming/2. Data Sinks.mp4 135.49 MB
28. 44. Module 4 -Spark Streaming and Structured Streaming with Kafka/4. Starting a Streaming Job.mp4 130.99 MB
29. 46. Streaming Chapter 3- Structured Streaming/5. What is the Batch Size in Structured Streaming.mp4 129.10 MB
30. 37. Non-Numeric Data/2. Understanding Vectors.mp4 128.32 MB
31. 46. Streaming Chapter 3- Structured Streaming/4. Windows and Watermarks.mp4 126.14 MB
32. 35. Model Fitting Parameters/2. Training, Test and Holdout Data.mp4 126.02 MB
33. 18. The Full SQL Syntax/1. Using a Spark Temporary View for SQL.mp4 123.53 MB
34. 45. Streaming Chapter 2 - Streaming with Apache Kafka/8. Adding a Slide Interval.mp4 123.48 MB
35. 36. Feature Selection/3. Identifying and Eliminating Duplicated Features.mp4 122.01 MB
36. 37. Non-Numeric Data/1. Using OneHotEncoding.mp4 119.11 MB
37. 35. Model Fitting Parameters/1. Setting Linear Regression Parameters.mp4 115.58 MB
38. 30. HashAggregation/3. How can I force Spark to use HashAggregation.mp4 113.25 MB
39. 10. Sorts and Coalesce/2. Why Coalesce is the Wrong Solution.mp4 112.14 MB
40. 30. HashAggregation/2. How does HashAggregation work.mp4 111.63 MB
41. 46. Streaming Chapter 3- Structured Streaming/3. Structured Streaming Output Modes.mp4 111.56 MB
42. 9. Keyword Ranking Practical/1. Practical Requirements.mp4 108.97 MB
43. 14. RDD Performance/1. Transformations and Actions.mp4 108.23 MB
44. 44. Module 4 -Spark Streaming and Structured Streaming with Kafka/5. Streaming Transformations.mp4 100.39 MB
45. 20. Groupings and Aggregations/1. Groupings and Aggregations.mp4 99.42 MB
46. 11. Deploying to AWS EMR (Optional)/2. Packing a Spark Jar for EMR.mp4 96.98 MB
47. 28. User Defined Functions/3. Using a UDF in Spark SQL.mp4 96.35 MB
48. 30. HashAggregation/1. Explaining Execution Plans.mp4 96.20 MB
49. 45. Streaming Chapter 2 - Streaming with Apache Kafka/6. Writing a Kafka Aggegration.mp4 95.96 MB
50. 36. Feature Selection/1. Describing the Features.mp4 95.90 MB