Filename Size 1_-_Introduction/1_-_Introduction.mp4 32.6 MB 1_-_Introduction/2_-_How_to_Use_This_Course.mp4 31.1 MB 2_-_Getting_Started/3.1_-_Enthought_Canopy_website.txt 42 B 2_-_Getting_Started/3_-_Installing_Enthought_Canopy.mp4 48.4 MB 2_-_Getting_Started/4_-_Installing_MRJob.mp4 20.7 MB 2_-_Getting_Started/5_-_Downloading_the_MovieLens_Data_Set.mp4 26.6 MB 2_-_Getting_Started/6_-_Run_Your_First_MapReduce_Job.mp4 38.4 MB 3_-_Understanding_MapReduce/10_-_Average_Friends_by_Age_Example_-_Part_1.mp4 12.1 MB 3_-_Understanding_MapReduce/11.1_-_Friends_By_Age_.py 469 B 3_-_Understanding_MapReduce/11.2_-_Data_for_FriendsByAge.py.txt 48 B 3_-_Understanding_MapReduce/11_-_Average_Friends_by_Age_Example_-_Part_2.mp4 34.2 MB 3_-_Understanding_MapReduce/12.1_-_Min_Temperatures_.py 597 B 3_-_Understanding_MapReduce/12_-_Minimum_Temperature_By_Location_Example.mp4 39.9 MB 3_-_Understanding_MapReduce/13.1_-_Max_Temperatures_.py 605 B 3_-_Understanding_MapReduce/13.2_-_Temperature_data_file.txt 41 B 3_-_Understanding_MapReduce/13_-_Maximum_Temperature_By_Location_Example.mp4 18.5 MB 3_-_Understanding_MapReduce/14.1_-_Word_Frequency_.py 331 B 3_-_Understanding_MapReduce/14_-_Word_Frequency_in_a_Book_Example.mp4 19.7 MB 3_-_Understanding_MapReduce/15.1_-_Word_Frequency_Better_.py 396 B 3_-_Understanding_MapReduce/15_-_Making_the_Word_Frequency_Mapper_Better_with_Regular_Expressions.mp4 17.6 MB 3_-_Understanding_MapReduce/16.1_-_Word_Frequency_Sorted_.py 951 B 3_-_Understanding_MapReduce/16.2_-_Book.txt 258.7 KB 3_-_Understanding_MapReduce/16_-_Sorting_the_Word_Frequency_Results_Using_Multi-Stage_MapReduce_Jobs.mp4 41.1 MB 3_-_Understanding_MapReduce/17_-_Activity_-_Design_a_Mapper_and_Reducer_for_Total_Spent_by_Customer.mp4 18.2 MB 3_-_Understanding_MapReduce/18_-_Activity_-_Write_Code_for_Total_Spent_by_Customer.mp4 14.8 MB 3_-_Understanding_MapReduce/19.1_-_Spend_By_Customer_.py 351 B 3_-_Understanding_MapReduce/19_-_Compare_Your_Code_to_Mine._Activity_-_Sort_Results_by_Amount_Spent.mp4 32.5 MB 3_-_Understanding_MapReduce/20.1_-_Spend_By_Customer_Sorted_.py 975 B 3_-_Understanding_MapReduce/20.2_-_Customer_Orders_Data_File.txt 52 B 3_-_Understanding_MapReduce/20_-_Compare_your_Code_to_Mine_for_Sorted_Results..mp4 18.9 MB 3_-_Understanding_MapReduce/21.1_-_Word_Frequency_With_Combiner_.py 432 B 3_-_Understanding_MapReduce/21_-_Combiners.mp4 52.2 MB 3_-_Understanding_MapReduce/7_-_MapReduce_Basic_Concepts.mp4 21.5 MB 3_-_Understanding_MapReduce/8.1_-_Rating_Counter_.py 348 B 3_-_Understanding_MapReduce/8_-_Walkthrough_of_Rating_Histogram_Code.mp4 31.2 MB 3_-_Understanding_MapReduce/9_-_Understanding_How_MapReduce_Scales_Distributed_Computing.mp4 18 MB 4_-_Advanced_MapReduce_Examples/22.1_-_Most_Popular_Movie_.py 683 B 4_-_Advanced_MapReduce_Examples/22_-_Example_-_Most_Popular_Movie.mp4 28.2 MB 4_-_Advanced_MapReduce_Examples/23.1_-_Most_Popular_Movie_Nicer_.py 1.2 KB 4_-_Advanced_MapReduce_Examples/23_-_Including_Ancillary_Lookup_Data_in_the_Example.mp4 45.4 MB 4_-_Advanced_MapReduce_Examples/24_-_Example_-_Most_Popular_Superhero_Part_1.mp4 17.1 MB 4_-_Advanced_MapReduce_Examples/25.1_-_Marvel_Graph.txt 1.6 MB 4_-_Advanced_MapReduce_Examples/25.2_-_Marvel_Names.txt 343.6 KB 4_-_Advanced_MapReduce_Examples/25.3_-_Most_Popular_Superhero_.py 1.5 KB 4_-_Advanced_MapReduce_Examples/25_-_Example_-_Most_Popular_Superhero_Part_2.mp4 32.3 MB 4_-_Advanced_MapReduce_Examples/26_-_Example_-_Degrees_of_Separation_-_Concepts.mp4 32.5 MB 4_-_Advanced_MapReduce_Examples/27.1_-_Process_Marvel_.py 955 B 4_-_Advanced_MapReduce_Examples/27_-_Degrees_of_Separation_-_Preprocessing_the_Data.mp4 35.3 MB 4_-_Advanced_MapReduce_Examples/28_-_Degrees_of_Separation_-_Code_Walkthrough.mp4 31.9 MB 4_-_Advanced_MapReduce_Examples/29.1_-_BFS_Iteration.py 2.7 KB 4_-_Advanced_MapReduce_Examples/29_-_Degrees_of_Separation_-_Running_and_Analyzing_the_Results.mp4 39.3 MB 4_-_Advanced_MapReduce_Examples/30_-_Example_-_Similar_Movies_Based_on_Ratings_-_Concepts.mp4 26.1 MB 4_-_Advanced_MapReduce_Examples/31_-_Similar_Movies_-_Code_Walkthrough.mp4 40.8 MB 4_-_Advanced_MapReduce_Examples/32.2_-_MovieLens_Data_Website.txt 40 B 4_-_Advanced_MapReduce_Examples/32_-_Similar_Movies_-_Running_and_Analyzing_the_Results.mp4 67.8 MB 4_-_Advanced_MapReduce_Examples/33_-_Learning_Activity_-_Improving_our_Movie_Similarities_MapReduce_Job.mp4 24.9 MB 5_-_Using_Hadoop_and_Elastic_MapReduce/34.1_-_Hadoop_website.txt 26 B 5_-_Using_Hadoop_and_Elastic_MapReduce/34_-_Fundamental_Concepts_of_Hadoop.mp4 30.7 MB 5_-_Using_Hadoop_and_Elastic_MapReduce/35_-_The_Hadoop_Distributed_File_System_HDFS_.mp4 10.6 MB 5_-_Using_Hadoop_and_Elastic_MapReduce/36.1_-_YARN_website.txt 76 B 5_-_Using_Hadoop_and_Elastic_MapReduce/36_-_Apache_YARN.mp4 20.2 MB 5_-_Using_Hadoop_and_Elastic_MapReduce/37_-_Hadoop_Streaming_-_How_Hadoop_Runs_your_Python_Code.mp4 20.4 MB 5_-_Using_Hadoop_and_Elastic_MapReduce/38.1_-_Amazon_Web_Services_Homepage.txt 22 B 5_-_Using_Hadoop_and_Elastic_MapReduce/38_-_Setting_Up_Your_Amazon_Elastic_MapReduce_Account.mp4 31.6 MB 5_-_Using_Hadoop_and_Elastic_MapReduce/39_-_Linking_Your_EMR_Account_with_MRJob.mp4 14 MB 5_-_Using_Hadoop_and_Elastic_MapReduce/40_-_Exercise_-_Run_Movie_Recommendations_on_Elastic_MapReduce.mp4 26 MB 5_-_Using_Hadoop_and_Elastic_MapReduce/41_-_Analyze_the_Results_of_Your_EMR_Job.mp4 25.1 MB 6_-_Advanced_Hadoop_and_EMR/42_-_Distributed_Computing_Fundamentals.mp4 16.7 MB 6_-_Advanced_Hadoop_and_EMR/43.1_-_Movie_Similarities_.py 4.4 KB 6_-_Advanced_Hadoop_and_EMR/43_-_Activity_-_Running_Movie_Similarities_on_Four_Machines.mp4 26.4 MB 6_-_Advanced_Hadoop_and_EMR/44_-_Analyzing_the_Results_of_the_4-Machine_Job.mp4 65.9 MB 6_-_Advanced_Hadoop_and_EMR/45_-_Troubleshooting_Hadoop_Jobs_with_EMR_and_MRJob_Part_1.mp4 23.3 MB 6_-_Advanced_Hadoop_and_EMR/46.1_-_MRJob_EMR_Documentation.txt 57 B 6_-_Advanced_Hadoop_and_EMR/46_-_Troubleshooting_Hadoop_Jobs_Part_2.mp4 61.8 MB 6_-_Advanced_Hadoop_and_EMR/47_-_Analyzing_One_Million_Movie_Ratings_Across_16_Machines_Part_1.mp4 32 MB 6_-_Advanced_Hadoop_and_EMR/48.1_-_Movie_Similarities_Large_.py 4.3 KB 6_-_Advanced_Hadoop_and_EMR/48_-_Analyzing_One_Million_Movie_Ratings_Across_16_Machines_Part_2.mp4 52.3 MB 7_-_Other_Hadoop_Technologies/49.1_-_Hive_Website.txt 24 B 7_-_Other_Hadoop_Technologies/49_-_Introducing_Apache_Hive.mp4 15.6 MB 7_-_Other_Hadoop_Technologies/50.1_-_Pig_Website.txt 23 B 7_-_Other_Hadoop_Technologies/50_-_Introducing_Apache_Pig.mp4 22.7 MB 7_-_Other_Hadoop_Technologies/51.1_-_Spark_website.txt 24 B 7_-_Other_Hadoop_Technologies/51_-_Apache_Spark_-_Concepts.mp4 31.2 MB 7_-_Other_Hadoop_Technologies/52.1_-_AWS_Spark_on_EMR_blog_entry.txt 64 B 7_-_Other_Hadoop_Technologies/52.2_-_Scala_source_code_for_the_flights_example.txt 52 B 7_-_Other_Hadoop_Technologies/52_-_Spark_Example_-_Part_1.mp4 64.6 MB 7_-_Other_Hadoop_Technologies/53_-_Spark_Example_-_Part_2.mp4 17.2 MB 7_-_Other_Hadoop_Technologies/54_-_Congratulations_.mp4 13.2 MB All Files - tamingBigdata 0 B keiso_utbigdwmh.iso 1.6 GB