UDEMI Taming Big Data with MapReduce and Hadoop | 361D863290E1EA2B5673BF4DD77EF053DF8D6027

UDEMI Taming Big Data with MapReduce and Hadoop

Name	UDEMI_Taming Big Data with MapReduce and Hadoop	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	3.4 GB
Total Files	90
Hash	361D863290E1EA2B5673BF4DD77EF053DF8D6027

/1_-_Introduction/
1_-_Introduction.mp4	34.2 MB
2_-_How_to_Use_This_Course.mp4	32.6 MB
/2_-_Getting_Started/
3.1_-_Enthought_Canopy_website.txt	0.0 KB
3_-_Installing_Enthought_Canopy.mp4	50.8 MB
4_-_Installing_MRJob.mp4	21.7 MB
5_-_Downloading_the_MovieLens_Data_Set.mp4	27.9 MB
6_-_Run_Your_First_MapReduce_Job.mp4	40.3 MB
/3_-_Understanding_MapReduce/
10_-_Average_Friends_by_Age_Example_-_Part_1.mp4	12.7 MB
11.1_-_Friends_By_Age_.py	0.5 KB
11.2_-_Data_for_FriendsByAge.py.txt	0.0 KB
11_-_Average_Friends_by_Age_Example_-_Part_2.mp4	35.9 MB
12.1_-_Min_Temperatures_.py	0.6 KB
12_-_Minimum_Temperature_By_Location_Example.mp4	41.8 MB
13.1_-_Max_Temperatures_.py	0.6 KB
13.2_-_Temperature_data_file.txt	0.0 KB
13_-_Maximum_Temperature_By_Location_Example.mp4	19.4 MB
14.1_-_Word_Frequency_.py	0.3 KB
14_-_Word_Frequency_in_a_Book_Example.mp4	20.6 MB
15.1_-_Word_Frequency_Better_.py	0.4 KB
15_-_Making_the_Word_Frequency_Mapper_Better_with_Regular_Expressions.mp4	18.5 MB
16.1_-_Word_Frequency_Sorted_.py	1.0 KB
16.2_-_Book.txt	264.9 KB
16_-_Sorting_the_Word_Frequency_Results_Using_Multi-Stage_MapReduce_Jobs.mp4	43.1 MB
17_-_Activity_-_Design_a_Mapper_and_Reducer_for_Total_Spent_by_Customer.mp4	19.1 MB
18_-_Activity_-_Write_Code_for_Total_Spent_by_Customer.mp4	15.6 MB
19.1_-_Spend_By_Customer_.py	0.4 KB
19_-_Compare_Your_Code_to_Mine._Activity_-_Sort_Results_by_Amount_Spent.mp4	34.1 MB
20.1_-_Spend_By_Customer_Sorted_.py	1.0 KB
20.2_-_Customer_Orders_Data_File.txt	0.1 KB
20_-_Compare_your_Code_to_Mine_for_Sorted_Results..mp4	19.8 MB
21.1_-_Word_Frequency_With_Combiner_.py	0.4 KB
21_-_Combiners.mp4	54.7 MB
7_-_MapReduce_Basic_Concepts.mp4	22.6 MB
8.1_-_Rating_Counter_.py	0.3 KB
8_-_Walkthrough_of_Rating_Histogram_Code.mp4	32.7 MB
9_-_Understanding_How_MapReduce_Scales_Distributed_Computing.mp4	18.9 MB
/4_-_Advanced_MapReduce_Examples/
22.1_-_Most_Popular_Movie_.py	0.7 KB
22_-_Example_-_Most_Popular_Movie.mp4	29.6 MB
23.1_-_Most_Popular_Movie_Nicer_.py	1.2 KB
23_-_Including_Ancillary_Lookup_Data_in_the_Example.mp4	47.6 MB
24_-_Example_-_Most_Popular_Superhero_Part_1.mp4	18.0 MB
25.1_-_Marvel_Graph.txt	1.7 MB
25.2_-_Marvel_Names.txt	351.8 KB
25.3_-_Most_Popular_Superhero_.py	1.5 KB
25_-_Example_-_Most_Popular_Superhero_Part_2.mp4	33.9 MB
26_-_Example_-_Degrees_of_Separation_-_Concepts.mp4	34.1 MB
27.1_-_Process_Marvel_.py	1.0 KB
27_-_Degrees_of_Separation_-_Preprocessing_the_Data.mp4	37.0 MB
28_-_Degrees_of_Separation_-_Code_Walkthrough.mp4	33.5 MB
29.1_-_BFS_Iteration.py	2.8 KB
29_-_Degrees_of_Separation_-_Running_and_Analyzing_the_Results.mp4	41.2 MB
30_-_Example_-_Similar_Movies_Based_on_Ratings_-_Concepts.mp4	27.4 MB
31_-_Similar_Movies_-_Code_Walkthrough.mp4	42.8 MB
32.2_-_MovieLens_Data_Website.txt	0.0 KB
32_-_Similar_Movies_-_Running_and_Analyzing_the_Results.mp4	71.1 MB
33_-_Learning_Activity_-_Improving_our_Movie_Similarities_MapReduce_Job.mp4	26.1 MB
/5_-_Using_Hadoop_and_Elastic_MapReduce/
34.1_-_Hadoop_website.txt	0.0 KB
34_-_Fundamental_Concepts_of_Hadoop.mp4	32.2 MB
35_-_The_Hadoop_Distributed_File_System_HDFS_.mp4	11.1 MB
36.1_-_YARN_website.txt	0.1 KB
36_-_Apache_YARN.mp4	21.2 MB
37_-_Hadoop_Streaming_-_How_Hadoop_Runs_your_Python_Code.mp4	21.3 MB
38.1_-_Amazon_Web_Services_Homepage.txt	0.0 KB
38_-_Setting_Up_Your_Amazon_Elastic_MapReduce_Account.mp4	33.1 MB
39_-_Linking_Your_EMR_Account_with_MRJob.mp4	14.7 MB
40_-_Exercise_-_Run_Movie_Recommendations_on_Elastic_MapReduce.mp4	27.2 MB
41_-_Analyze_the_Results_of_Your_EMR_Job.mp4	26.4 MB
/6_-_Advanced_Hadoop_and_EMR/
42_-_Distributed_Computing_Fundamentals.mp4	17.5 MB
43.1_-_Movie_Similarities_.py	4.5 KB
43_-_Activity_-_Running_Movie_Similarities_on_Four_Machines.mp4	27.7 MB
44_-_Analyzing_the_Results_of_the_4-Machine_Job.mp4	69.1 MB
45_-_Troubleshooting_Hadoop_Jobs_with_EMR_and_MRJob_Part_1.mp4	24.4 MB
46.1_-_MRJob_EMR_Documentation.txt	0.1 KB
46_-_Troubleshooting_Hadoop_Jobs_Part_2.mp4	64.8 MB
47_-_Analyzing_One_Million_Movie_Ratings_Across_16_Machines_Part_1.mp4	33.6 MB
48.1_-_Movie_Similarities_Large_.py	4.4 KB
48_-_Analyzing_One_Million_Movie_Ratings_Across_16_Machines_Part_2.mp4	54.8 MB
/7_-_Other_Hadoop_Technologies/
49.1_-_Hive_Website.txt	0.0 KB
49_-_Introducing_Apache_Hive.mp4	16.4 MB
50.1_-_Pig_Website.txt	0.0 KB
50_-_Introducing_Apache_Pig.mp4	23.8 MB
51.1_-_Spark_website.txt	0.0 KB
51_-_Apache_Spark_-_Concepts.mp4	32.7 MB
52.1_-_AWS_Spark_on_EMR_blog_entry.txt	0.1 KB
52.2_-_Scala_source_code_for_the_flights_example.txt	0.1 KB
52_-_Spark_Example_-_Part_1.mp4	67.7 MB
53_-_Spark_Example_-_Part_2.mp4	18.1 MB
54_-_Congratulations_.mp4	13.9 MB
/All Files - tamingBigdata/
	0.0 KB
/
keiso_utbigdwmh.iso	1.7 GB
Total files 90