UDEMI_Taming Big Data with MapReduce and Hadoop

1. 1_-_Introduction/1_-_Introduction.mp432.59MB
2. 1_-_Introduction/2_-_How_to_Use_This_Course.mp431.08MB
3. 2_-_Getting_Started/3.1_-_Enthought_Canopy_website.txt42B
4. 2_-_Getting_Started/3_-_Installing_Enthought_Canopy.mp448.41MB
5. 2_-_Getting_Started/4_-_Installing_MRJob.mp420.67MB
6. 2_-_Getting_Started/5_-_Downloading_the_MovieLens_Data_Set.mp426.58MB
7. 2_-_Getting_Started/6_-_Run_Your_First_MapReduce_Job.mp438.39MB
8. 3_-_Understanding_MapReduce/10_-_Average_Friends_by_Age_Example_-_Part_1.mp412.13MB
9. 3_-_Understanding_MapReduce/11.2_-_Data_for_FriendsByAge.py.txt48B
10. 3_-_Understanding_MapReduce/11_-_Average_Friends_by_Age_Example_-_Part_2.mp434.24MB
11. 3_-_Understanding_MapReduce/12_-_Minimum_Temperature_By_Location_Example.mp439.86MB
12. 3_-_Understanding_MapReduce/13.2_-_Temperature_data_file.txt41B
13. 3_-_Understanding_MapReduce/13_-_Maximum_Temperature_By_Location_Example.mp418.46MB
14. 3_-_Understanding_MapReduce/14_-_Word_Frequency_in_a_Book_Example.mp419.68MB
15. 3_-_Understanding_MapReduce/15_-_Making_the_Word_Frequency_Mapper_Better_with_Regular_Expressions.mp417.6MB
16. 3_-_Understanding_MapReduce/16.2_-_Book.txt258.67KB
17. 3_-_Understanding_MapReduce/16_-_Sorting_the_Word_Frequency_Results_Using_Multi-Stage_MapReduce_Jobs.mp441.15MB
18. 3_-_Understanding_MapReduce/17_-_Activity_-_Design_a_Mapper_and_Reducer_for_Total_Spent_by_Customer.mp418.2MB
19. 3_-_Understanding_MapReduce/18_-_Activity_-_Write_Code_for_Total_Spent_by_Customer.mp414.85MB
20. 3_-_Understanding_MapReduce/19_-_Compare_Your_Code_to_Mine._Activity_-_Sort_Results_by_Amount_Spent.mp432.49MB
21. 3_-_Understanding_MapReduce/20.2_-_Customer_Orders_Data_File.txt52B
22. 3_-_Understanding_MapReduce/20_-_Compare_your_Code_to_Mine_for_Sorted_Results..mp418.86MB
23. 3_-_Understanding_MapReduce/21_-_Combiners.mp452.17MB
24. 3_-_Understanding_MapReduce/7_-_MapReduce_Basic_Concepts.mp421.55MB
25. 3_-_Understanding_MapReduce/8_-_Walkthrough_of_Rating_Histogram_Code.mp431.16MB
26. 3_-_Understanding_MapReduce/9_-_Understanding_How_MapReduce_Scales_Distributed_Computing.mp418.02MB
27. 4_-_Advanced_MapReduce_Examples/22_-_Example_-_Most_Popular_Movie.mp428.22MB
28. 4_-_Advanced_MapReduce_Examples/23_-_Including_Ancillary_Lookup_Data_in_the_Example.mp445.39MB
29. 4_-_Advanced_MapReduce_Examples/24_-_Example_-_Most_Popular_Superhero_Part_1.mp417.13MB
30. 4_-_Advanced_MapReduce_Examples/25.1_-_Marvel_Graph.txt1.6MB
31. 4_-_Advanced_MapReduce_Examples/25.2_-_Marvel_Names.txt343.6KB
32. 4_-_Advanced_MapReduce_Examples/25_-_Example_-_Most_Popular_Superhero_Part_2.mp432.33MB
33. 4_-_Advanced_MapReduce_Examples/26_-_Example_-_Degrees_of_Separation_-_Concepts.mp432.54MB
34. 4_-_Advanced_MapReduce_Examples/27_-_Degrees_of_Separation_-_Preprocessing_the_Data.mp435.29MB
35. 4_-_Advanced_MapReduce_Examples/28_-_Degrees_of_Separation_-_Code_Walkthrough.mp431.94MB
36. 4_-_Advanced_MapReduce_Examples/29_-_Degrees_of_Separation_-_Running_and_Analyzing_the_Results.mp439.33MB
37. 4_-_Advanced_MapReduce_Examples/30_-_Example_-_Similar_Movies_Based_on_Ratings_-_Concepts.mp426.11MB
38. 4_-_Advanced_MapReduce_Examples/31_-_Similar_Movies_-_Code_Walkthrough.mp440.84MB
39. 4_-_Advanced_MapReduce_Examples/32.2_-_MovieLens_Data_Website.txt40B
40. 4_-_Advanced_MapReduce_Examples/32_-_Similar_Movies_-_Running_and_Analyzing_the_Results.mp467.8MB
41. 4_-_Advanced_MapReduce_Examples/33_-_Learning_Activity_-_Improving_our_Movie_Similarities_MapReduce_Job.mp424.85MB
42. 5_-_Using_Hadoop_and_Elastic_MapReduce/34.1_-_Hadoop_website.txt26B
43. 5_-_Using_Hadoop_and_Elastic_MapReduce/34_-_Fundamental_Concepts_of_Hadoop.mp430.74MB
44. 5_-_Using_Hadoop_and_Elastic_MapReduce/35_-_The_Hadoop_Distributed_File_System_HDFS_.mp410.6MB
45. 5_-_Using_Hadoop_and_Elastic_MapReduce/36.1_-_YARN_website.txt76B
46. 5_-_Using_Hadoop_and_Elastic_MapReduce/36_-_Apache_YARN.mp420.23MB
47. 5_-_Using_Hadoop_and_Elastic_MapReduce/37_-_Hadoop_Streaming_-_How_Hadoop_Runs_your_Python_Code.mp420.35MB
48. 5_-_Using_Hadoop_and_Elastic_MapReduce/38.1_-_Amazon_Web_Services_Homepage.txt22B
49. 5_-_Using_Hadoop_and_Elastic_MapReduce/38_-_Setting_Up_Your_Amazon_Elastic_MapReduce_Account.mp431.61MB
50. 5_-_Using_Hadoop_and_Elastic_MapReduce/39_-_Linking_Your_EMR_Account_with_MRJob.mp414MB
51. 5_-_Using_Hadoop_and_Elastic_MapReduce/40_-_Exercise_-_Run_Movie_Recommendations_on_Elastic_MapReduce.mp425.95MB
52. 5_-_Using_Hadoop_and_Elastic_MapReduce/41_-_Analyze_the_Results_of_Your_EMR_Job.mp425.15MB
53. 6_-_Advanced_Hadoop_and_EMR/42_-_Distributed_Computing_Fundamentals.mp416.67MB
54. 6_-_Advanced_Hadoop_and_EMR/43_-_Activity_-_Running_Movie_Similarities_on_Four_Machines.mp426.41MB
55. 6_-_Advanced_Hadoop_and_EMR/44_-_Analyzing_the_Results_of_the_4-Machine_Job.mp465.9MB
56. 6_-_Advanced_Hadoop_and_EMR/45_-_Troubleshooting_Hadoop_Jobs_with_EMR_and_MRJob_Part_1.mp423.31MB
57. 6_-_Advanced_Hadoop_and_EMR/46.1_-_MRJob_EMR_Documentation.txt57B
58. 6_-_Advanced_Hadoop_and_EMR/46_-_Troubleshooting_Hadoop_Jobs_Part_2.mp461.76MB
59. 6_-_Advanced_Hadoop_and_EMR/47_-_Analyzing_One_Million_Movie_Ratings_Across_16_Machines_Part_1.mp432.05MB
60. 6_-_Advanced_Hadoop_and_EMR/48_-_Analyzing_One_Million_Movie_Ratings_Across_16_Machines_Part_2.mp452.27MB
61. 7_-_Other_Hadoop_Technologies/49.1_-_Hive_Website.txt24B
62. 7_-_Other_Hadoop_Technologies/49_-_Introducing_Apache_Hive.mp415.62MB
63. 7_-_Other_Hadoop_Technologies/50.1_-_Pig_Website.txt23B
64. 7_-_Other_Hadoop_Technologies/50_-_Introducing_Apache_Pig.mp422.74MB
65. 7_-_Other_Hadoop_Technologies/51.1_-_Spark_website.txt24B
66. 7_-_Other_Hadoop_Technologies/51_-_Apache_Spark_-_Concepts.mp431.19MB
67. 7_-_Other_Hadoop_Technologies/52.1_-_AWS_Spark_on_EMR_blog_entry.txt64B
68. 7_-_Other_Hadoop_Technologies/52.2_-_Scala_source_code_for_the_flights_example.txt52B
69. 7_-_Other_Hadoop_Technologies/52_-_Spark_Example_-_Part_1.mp464.56MB
70. 7_-_Other_Hadoop_Technologies/53_-_Spark_Example_-_Part_2.mp417.22MB
71. 7_-_Other_Hadoop_Technologies/54_-_Congratulations_.mp413.21MB
72. keiso_utbigdwmh.iso1.6GB