[FreeCoursesOnline.Me] [MANNING] The Ultimate Introduction to Big Data [FCO]
File List
- 01 - Introduction, and install Hadoop on your desktop!.mp4 236.4 MB
- 02 - Hadoop overview and history.mp4 107.7 MB
- 39 - Why NoSQL.mp4 96.3 MB
- 44 - Installing Cassandra.mp4 95.9 MB
- 24 - Find the movie with the lowest average rating with RDDs.mp4 94.7 MB
- 49 - Choosing a database technology.mp4 91.3 MB
- 03 - Overview of the Hadoop ecosystem.mp4 90.6 MB
- 27 - Movie recommendations with MLLib.mp4 90.1 MB
- 80 - Analyze web logs published with Flume using Spark Streaming.mp4 89.2 MB
- 84 - Count words with Storm.mp4 87.4 MB
- 58 - Install Presto and query Hive with it.mp4 85.4 MB
- 47 - Install MongoDB and integrate it with Spark.mp4 84.6 MB
- 67 - Set up a simple Oozie workflow.mp4 82.5 MB
- 56 - Integrate Phoenix with Pig.mp4 79.8 MB
- 75 - Publishing web logs with Kafka.mp4 77.7 MB
- 45 - Write Spark output into Cassandra.mp4 75.4 MB
- 86 - Counting words with Flink.mp4 73.9 MB
- 59 - Query both Cassandra and Hive using Presto.mp4 69.7 MB
- 78 - Set up Flume to monitor a directory and store its data in HDFS.mp4 68.3 MB
- 46 - MongoDB overview.mp4 65.6 MB
- 26 - Find the movie with the lowest average rating wth DataFrames.mp4 65.1 MB
- 42 - Use HBase with Pig to import data at scale.mp4 63.8 MB
- 52 - Setting up Drill.mp4 63.5 MB
- 41 - Import movie ratings into HBase.mp4 61.4 MB
- 17 - Find the oldest movie with a 5-star rating using Pig.mp4 61.2 MB
- 43 - Cassandra overview.mp4 61.0 MB
- 94 - Books and online resources.mp4 60.8 MB
- 29 - Check your results against mine!.mp4 58.9 MB
- 79 - Spark Streaming - introduction.mp4 56.1 MB
- 65 - Simulating a failing master with ZooKeeper.mp4 52.7 MB
- 07 - Install the MovieLens dataset into HDFS using the command line.mp4 52.4 MB
- 48 - Using the MongoDB shell.mp4 52.4 MB
- 18 - Find old 5-star movies with Pig.mp4 52.2 MB
- 81 - Exercise - Monitor Flume-published logs for errors in real time.mp4 52.1 MB
- 14 - Check your results against mine!.mp4 49.1 MB
- 05 - HDFS - what it is and how it works.mp4 49.1 MB
- 62 - Use Hive on Tez and measure the performance benefit.mp4 48.5 MB
- 36 - Install MySQL and import our movie data.mp4 48.4 MB
- 06 - Install the MovieLens dataset into HDFS using the Ambari UI.mp4 47.8 MB
- 09 - How MapReduce distributes processing.mp4 47.6 MB
- 38 - Use Sqoop to export data from Hadoop to MySQL.mp4 47.4 MB
- 73 - Kafka explained.mp4 46.3 MB
- 55 - Install Phoenix and query HBase with it.mp4 45.9 MB
- 60 - YARN explained.mp4 45.6 MB
- 51 - Overview of Drill.mp4 44.8 MB
- 74 - Setting up Kafka and publishing some data.mp4 43.3 MB
- 37 - Use Sqoop to import data from MySQL to HDFS_Hive.mp4 42.7 MB
- 66 - Oozie explained.mp4 42.0 MB
- 63 - Mesos explained.mp4 41.2 MB
- 11 - Installing Python, MRJob, and nano.mp4 41.0 MB
- 77 - Set up Flume and publish logs with it.mp4 40.1 MB
- 10 - MapReduce example - break down movie ratings by rating score.mp4 40.1 MB
- 69 - Use Zeppelin to analyze movie ratings, part 1.mp4 40.0 MB
- 68 - Zeppelin overview.mp4 40.0 MB
- 15 - Introducing Ambari.mp4 39.3 MB
- 21 - Compare your results to mine!.mp4 39.2 MB
- 64 - ZooKeeper explained.mp4 38.4 MB
- 28 - Exercise - Filter the lowest-rated movies by number of ratings.mp4 37.3 MB
- 57 - Overview of Presto.mp4 37.3 MB
- 90 - Sample application - consume webserver logs and keep track of top sellers.mp4 37.0 MB
- 40 - What is HBase.mp4 36.4 MB
- 91 - Sample application - serving movie recommendations to a website.mp4 35.6 MB
- 70 - Use Zeppelin to analyze movie ratings, part 2.mp4 35.3 MB
- 31 - Use Hive to find the most popular movie.mp4 35.3 MB
- 16 - Introducing Pig.mp4 34.4 MB
- 30 - What is Hive.mp4 34.0 MB
- 54 - Overview of Phoenix.mp4 33.8 MB
- 71 - Hue overview.mp4 32.4 MB
- 22 - Why Spark.mp4 31.6 MB
- 93 - Solution - Design a system to report daily sessions.mp4 31.5 MB
- 08 - MapReduce - what it is and how it works.mp4 31.4 MB
- 88 - Review - how the pieces fit together.mp4 31.0 MB
- 82 - Solution - Aggregating HTTP access codes with Spark Streaming.mp4 30.6 MB
- 83 - Apache Storm - Introduction.mp4 28.8 MB
- 87 - The best of the rest.mp4 28.7 MB
- 12 - Code up the ratings histogram MapReduce job and run it.mp4 28.5 MB
- 89 - Understanding your requirements.mp4 28.3 MB
- 04 - Tips for using this course.mp4 28.0 MB
- 72 - Other technologies worth mentioning.mp4 27.6 MB
- 50 - Choose a database for a given problem.mp4 27.6 MB
- 32 - How Hive works.mp4 26.5 MB
- 76 - Flume explained.mp4 25.8 MB
- 33 - Exercise - Use Hive to find the movie with the highest average rating.mp4 24.2 MB
- 35 - Integrating MySQL with Hadoop.mp4 23.0 MB
- 85 - Flink - an overview.mp4 22.4 MB
- 13 - Exercise - Rank movies by their popularity.mp4 21.0 MB
- 23 - The Resilient Distributed Dataset (RDD).mp4 20.6 MB
- 19 - More Pig Latin.mp4 20.3 MB
- 20 - Exercise - Find the most-rated, one-star movie.mp4 19.5 MB
- 53 - Querying across multiple databases.mp4 18.3 MB
- 25 - Datasets and Spark 2.0.mp4 17.4 MB
- 61 - Tez explained.mp4 14.0 MB
- 34 - Compare your solution to mine.mp4 13.9 MB
- 92 - Exercise - Design a system to report web sessions per day.mp4 7.4 MB
- FreeCoursesOnline.Me.html 108.3 KB
- FTUForum.com.html 100.4 KB
- Discuss.FTUForum.com.html 31.9 KB
- How you can help Team-FTU.txt 235 bytes
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