[FreeCoursesOnline.Me] [MANNING] The Ultimate Introduction to Big Data [FCO]

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文档列表

01 - Introduction, and install Hadoop on your desktop!.mp4 247.9 MB
02 - Hadoop overview and history.mp4 112.9 MB
39 - Why NoSQL.mp4 101.0 MB
44 - Installing Cassandra.mp4 100.6 MB
24 - Find the movie with the lowest average rating with RDDs.mp4 99.3 MB
49 - Choosing a database technology.mp4 95.8 MB
03 - Overview of the Hadoop ecosystem.mp4 95.0 MB
27 - Movie recommendations with MLLib.mp4 94.5 MB
80 - Analyze web logs published with Flume using Spark Streaming.mp4 93.6 MB
84 - Count words with Storm.mp4 91.7 MB
58 - Install Presto and query Hive with it.mp4 89.5 MB
47 - Install MongoDB and integrate it with Spark.mp4 88.7 MB
67 - Set up a simple Oozie workflow.mp4 86.5 MB
56 - Integrate Phoenix with Pig.mp4 83.7 MB
75 - Publishing web logs with Kafka.mp4 81.5 MB
45 - Write Spark output into Cassandra.mp4 79.0 MB
86 - Counting words with Flink.mp4 77.5 MB
59 - Query both Cassandra and Hive using Presto.mp4 73.1 MB
78 - Set up Flume to monitor a directory and store its data in HDFS.mp4 71.6 MB
46 - MongoDB overview.mp4 68.8 MB
26 - Find the movie with the lowest average rating wth DataFrames.mp4 68.3 MB
42 - Use HBase with Pig to import data at scale.mp4 66.9 MB
52 - Setting up Drill.mp4 66.6 MB
41 - Import movie ratings into HBase.mp4 64.4 MB
17 - Find the oldest movie with a 5-star rating using Pig.mp4 64.2 MB
43 - Cassandra overview.mp4 64.0 MB
94 - Books and online resources.mp4 63.7 MB
29 - Check your results against mine!.mp4 61.7 MB
79 - Spark Streaming - introduction.mp4 58.8 MB
65 - Simulating a failing master with ZooKeeper.mp4 55.3 MB
07 - Install the MovieLens dataset into HDFS using the command line.mp4 55.0 MB
48 - Using the MongoDB shell.mp4 54.9 MB
18 - Find old 5-star movies with Pig.mp4 54.7 MB
81 - Exercise - Monitor Flume-published logs for errors in real time.mp4 54.6 MB
14 - Check your results against mine!.mp4 51.5 MB
05 - HDFS - what it is and how it works.mp4 51.5 MB
62 - Use Hive on Tez and measure the performance benefit.mp4 50.8 MB
36 - Install MySQL and import our movie data.mp4 50.7 MB
06 - Install the MovieLens dataset into HDFS using the Ambari UI.mp4 50.1 MB
09 - How MapReduce distributes processing.mp4 49.9 MB
38 - Use Sqoop to export data from Hadoop to MySQL.mp4 49.7 MB
73 - Kafka explained.mp4 48.5 MB
55 - Install Phoenix and query HBase with it.mp4 48.1 MB
60 - YARN explained.mp4 47.8 MB
51 - Overview of Drill.mp4 47.0 MB
74 - Setting up Kafka and publishing some data.mp4 45.4 MB
37 - Use Sqoop to import data from MySQL to HDFS_Hive.mp4 44.7 MB
66 - Oozie explained.mp4 44.0 MB
63 - Mesos explained.mp4 43.2 MB
11 - Installing Python, MRJob, and nano.mp4 43.0 MB
77 - Set up Flume and publish logs with it.mp4 42.1 MB
10 - MapReduce example - break down movie ratings by rating score.mp4 42.0 MB
69 - Use Zeppelin to analyze movie ratings, part 1.mp4 42.0 MB
68 - Zeppelin overview.mp4 41.9 MB
15 - Introducing Ambari.mp4 41.3 MB
21 - Compare your results to mine!.mp4 41.1 MB
64 - ZooKeeper explained.mp4 40.3 MB
28 - Exercise - Filter the lowest-rated movies by number of ratings.mp4 39.1 MB
57 - Overview of Presto.mp4 39.1 MB
90 - Sample application - consume webserver logs and keep track of top sellers.mp4 38.8 MB
40 - What is HBase.mp4 38.2 MB
91 - Sample application - serving movie recommendations to a website.mp4 37.3 MB
70 - Use Zeppelin to analyze movie ratings, part 2.mp4 37.0 MB
31 - Use Hive to find the most popular movie.mp4 37.0 MB
16 - Introducing Pig.mp4 36.0 MB
30 - What is Hive.mp4 35.6 MB
54 - Overview of Phoenix.mp4 35.5 MB
71 - Hue overview.mp4 33.9 MB
22 - Why Spark.mp4 33.1 MB
93 - Solution - Design a system to report daily sessions.mp4 33.0 MB
08 - MapReduce - what it is and how it works.mp4 32.9 MB
88 - Review - how the pieces fit together.mp4 32.5 MB
82 - Solution - Aggregating HTTP access codes with Spark Streaming.mp4 32.1 MB
83 - Apache Storm - Introduction.mp4 30.2 MB
87 - The best of the rest.mp4 30.1 MB
12 - Code up the ratings histogram MapReduce job and run it.mp4 29.9 MB
89 - Understanding your requirements.mp4 29.7 MB
04 - Tips for using this course.mp4 29.4 MB
72 - Other technologies worth mentioning.mp4 29.0 MB
50 - Choose a database for a given problem.mp4 29.0 MB
32 - How Hive works.mp4 27.8 MB
76 - Flume explained.mp4 27.1 MB
33 - Exercise - Use Hive to find the movie with the highest average rating.mp4 25.4 MB
35 - Integrating MySQL with Hadoop.mp4 24.2 MB
85 - Flink - an overview.mp4 23.5 MB
13 - Exercise - Rank movies by their popularity.mp4 22.1 MB
23 - The Resilient Distributed Dataset (RDD).mp4 21.6 MB
19 - More Pig Latin.mp4 21.3 MB
20 - Exercise - Find the most-rated, one-star movie.mp4 20.4 MB
53 - Querying across multiple databases.mp4 19.2 MB
25 - Datasets and Spark 2.0.mp4 18.2 MB
61 - Tez explained.mp4 14.7 MB
34 - Compare your solution to mine.mp4 14.6 MB
92 - Exercise - Design a system to report web sessions per day.mp4 7.8 MB
FreeCoursesOnline.Me.html 110.9 kB
FTUForum.com.html 102.8 kB
Discuss.FTUForum.com.html 32.7 kB
How you can help Team-FTU.txt 235 Bytes
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