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[DesireCourse.Net] Udemy - The Ultimate Hands-On Hadoop - Tame your Big Data!

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种子名称: [DesireCourse.Net] Udemy - The Ultimate Hands-On Hadoop - Tame your Big Data!
文件类型: 视频
文件数目: 95个文件
文件大小: 2.58 GB
收录时间: 2020-3-8 05:32
已经下载: 3
资源热度: 144
最近下载: 2024-12-28 22:43

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[DesireCourse.Net] Udemy - The Ultimate Hands-On Hadoop - Tame your Big Data!.torrent
  • 1. Learn all the buzzwords! And install the Hortonworks Data Platform Sandbox/1. Udemy 101 Getting the Most From This Course.mp419.73MB
  • 1. Learn all the buzzwords! And install the Hortonworks Data Platform Sandbox/2. Tips for Using This Course.mp411.46MB
  • 1. Learn all the buzzwords! And install the Hortonworks Data Platform Sandbox/4. Installing Hadoop [Step by Step].mp4176.95MB
  • 1. Learn all the buzzwords! And install the Hortonworks Data Platform Sandbox/5. Hadoop Overview and History.mp420.89MB
  • 1. Learn all the buzzwords! And install the Hortonworks Data Platform Sandbox/6. Overview of the Hadoop Ecosystem.mp460MB
  • 10. Analyzing Streams of Data/1. Spark Streaming Introduction.mp431.9MB
  • 10. Analyzing Streams of Data/2. [Activity] Analyze web logs published with Flume using Spark Streaming.mp440.27MB
  • 10. Analyzing Streams of Data/3. [Exercise] Monitor Flume-published logs for errors in real time.mp425MB
  • 10. Analyzing Streams of Data/4. Exercise solution Aggregating HTTP access codes with Spark Streaming.mp415.03MB
  • 10. Analyzing Streams of Data/5. Apache Storm Introduction.mp416.51MB
  • 10. Analyzing Streams of Data/6. [Activity] Count words with Storm.mp444.56MB
  • 10. Analyzing Streams of Data/7. Flink An Overview.mp412.34MB
  • 10. Analyzing Streams of Data/8. [Activity] Counting words with Flink.mp440.64MB
  • 11. Designing Real-World Systems/1. The Best of the Rest.mp416.21MB
  • 11. Designing Real-World Systems/2. Review How the pieces fit together.mp421.87MB
  • 11. Designing Real-World Systems/3. Understanding your requirements.mp414.28MB
  • 11. Designing Real-World Systems/4. Sample application consume webserver logs and keep track of top-sellers.mp418.23MB
  • 11. Designing Real-World Systems/5. Sample application serving movie recommendations to a website.mp419.72MB
  • 11. Designing Real-World Systems/6. [Exercise] Design a system to report web sessions per day.mp44.84MB
  • 11. Designing Real-World Systems/7. Exercise solution Design a system to count daily sessions.mp414.17MB
  • 12. Learning More/1. Books and online resources.mp460.06MB
  • 2. Using Hadoop's Core HDFS and MapReduce/1. HDFS What it is, and how it works.mp431.43MB
  • 2. Using Hadoop's Core HDFS and MapReduce/10. [Exercise] Rank movies by their popularity.mp412.32MB
  • 2. Using Hadoop's Core HDFS and MapReduce/11. [Activity] Check your results against mine!.mp422.15MB
  • 2. Using Hadoop's Core HDFS and MapReduce/2. Installing the MovieLens Dataset.mp422.42MB
  • 2. Using Hadoop's Core HDFS and MapReduce/3. [Activity] Install the MovieLens dataset into HDFS using the command line.mp424.62MB
  • 2. Using Hadoop's Core HDFS and MapReduce/4. MapReduce What it is, and how it works.mp418.86MB
  • 2. Using Hadoop's Core HDFS and MapReduce/5. How MapReduce distributes processing.mp423.99MB
  • 2. Using Hadoop's Core HDFS and MapReduce/6. MapReduce example Break down movie ratings by rating score.mp421.39MB
  • 2. Using Hadoop's Core HDFS and MapReduce/8. [Activity] Installing Python, MRJob, and nano.mp466.12MB
  • 2. Using Hadoop's Core HDFS and MapReduce/9. [Activity] Code up the ratings histogram MapReduce job and run it.mp414.13MB
  • 3. Programming Hadoop with Pig/1. Introducing Ambari.mp416.03MB
  • 3. Programming Hadoop with Pig/2. Introducing Pig.mp416.88MB
  • 3. Programming Hadoop with Pig/3. Example Find the oldest movie with a 5-star rating using Pig.mp429.55MB
  • 3. Programming Hadoop with Pig/4. [Activity] Find old 5-star movies with Pig.mp472.77MB
  • 3. Programming Hadoop with Pig/5. More Pig Latin.mp412.97MB
  • 3. Programming Hadoop with Pig/6. [Exercise] Find the most-rated one-star movie.mp43.39MB
  • 3. Programming Hadoop with Pig/7. Pig Challenge Compare Your Results to Mine!.mp418MB
  • 4. Programming Hadoop with Spark/1. Why Spark.mp420.69MB
  • 4. Programming Hadoop with Spark/2. The Resilient Distributed Dataset (RDD).mp416.72MB
  • 4. Programming Hadoop with Spark/3. [Activity] Find the movie with the lowest average rating - with RDD's.mp439.67MB
  • 4. Programming Hadoop with Spark/4. Datasets and Spark 2.0.mp411.02MB
  • 4. Programming Hadoop with Spark/5. [Activity] Find the movie with the lowest average rating - with DataFrames.mp425.26MB
  • 4. Programming Hadoop with Spark/6. [Activity] Movie recommendations with MLLib.mp433.96MB
  • 4. Programming Hadoop with Spark/7. [Exercise] Filter the lowest-rated movies by number of ratings.mp45.2MB
  • 4. Programming Hadoop with Spark/8. [Activity] Check your results against mine!.mp424.43MB
  • 5. Using relational data stores with Hadoop/1. What is Hive.mp416.42MB
  • 5. Using relational data stores with Hadoop/2. [Activity] Use Hive to find the most popular movie.mp423.85MB
  • 5. Using relational data stores with Hadoop/3. How Hive works.mp415.94MB
  • 5. Using relational data stores with Hadoop/4. [Exercise] Use Hive to find the movie with the highest average rating.mp43.42MB
  • 5. Using relational data stores with Hadoop/5. Compare your solution to mine..mp48.47MB
  • 5. Using relational data stores with Hadoop/6. Integrating MySQL with Hadoop.mp413.93MB
  • 5. Using relational data stores with Hadoop/7. [Activity] Install MySQL and import our movie data.mp474.09MB
  • 5. Using relational data stores with Hadoop/8. [Activity] Use Sqoop to import data from MySQL to HFDSHive.mp421.58MB
  • 5. Using relational data stores with Hadoop/9. [Activity] Use Sqoop to export data from Hadoop to MySQL.mp422.65MB
  • 6. Using non-relational data stores with Hadoop/1. Why NoSQL.mp451.47MB
  • 6. Using non-relational data stores with Hadoop/10. [Activity] Using the MongoDB shell.mp423.23MB
  • 6. Using non-relational data stores with Hadoop/11. Choosing a database technology.mp456.9MB
  • 6. Using non-relational data stores with Hadoop/12. [Exercise] Choose a database for a given problem.mp416.88MB
  • 6. Using non-relational data stores with Hadoop/2. What is HBase.mp422.33MB
  • 6. Using non-relational data stores with Hadoop/3. [Activity] Import movie ratings into HBase.mp430.88MB
  • 6. Using non-relational data stores with Hadoop/4. [Activity] Use HBase with Pig to import data at scale..mp433.58MB
  • 6. Using non-relational data stores with Hadoop/5. Cassandra overview.mp432.08MB
  • 6. Using non-relational data stores with Hadoop/6. [Activity] Installing Cassandra.mp436.85MB
  • 6. Using non-relational data stores with Hadoop/7. [Activity] Write Spark output into Cassandra.mp433.71MB
  • 6. Using non-relational data stores with Hadoop/8. MongoDB overview.mp434.17MB
  • 6. Using non-relational data stores with Hadoop/9. [Activity] Install MongoDB, and integrate Spark with MongoDB.mp440MB
  • 7. Querying your Data Interactively/1. Overview of Drill.mp430.51MB
  • 7. Querying your Data Interactively/2. [Activity] Setting up Drill.mp485.84MB
  • 7. Querying your Data Interactively/3. [Activity] Querying across multiple databases with Drill.mp414.34MB
  • 7. Querying your Data Interactively/4. Overview of Phoenix.mp416.6MB
  • 7. Querying your Data Interactively/5. [Activity] Install Phoenix and query HBase with it.mp419.79MB
  • 7. Querying your Data Interactively/6. [Activity] Integrate Phoenix with Pig.mp434.36MB
  • 7. Querying your Data Interactively/7. Overview of Presto.mp422.47MB
  • 7. Querying your Data Interactively/8. [Activity] Install Presto, and query Hive with it..mp442.24MB
  • 7. Querying your Data Interactively/9. [Activity] Query both Cassandra and Hive using Presto..mp434.59MB
  • 8. Managing your Cluster/1. YARN explained.mp424.45MB
  • 8. Managing your Cluster/10. [Activity] Use Zeppelin to analyze movie ratings, part 1.mp424.29MB
  • 8. Managing your Cluster/11. [Activity] Use Zeppelin to analyze movie ratings, part 2.mp424.54MB
  • 8. Managing your Cluster/12. Hue overview.mp416.1MB
  • 8. Managing your Cluster/13. Other technologies worth mentioning.mp416.34MB
  • 8. Managing your Cluster/2. Tez explained.mp48.61MB
  • 8. Managing your Cluster/3. [Activity] Use Hive on Tez and measure the performance benefit.mp428.27MB
  • 8. Managing your Cluster/4. Mesos explained.mp425.9MB
  • 8. Managing your Cluster/5. ZooKeeper explained.mp422.92MB
  • 8. Managing your Cluster/6. [Activity] Simulating a failing master with ZooKeeper.mp418.8MB
  • 8. Managing your Cluster/7. Oozie explained.mp421.48MB
  • 8. Managing your Cluster/8. [Activity] Set up a simple Oozie workflow.mp441.24MB
  • 8. Managing your Cluster/9. Zeppelin overview.mp421.22MB
  • 9. Feeding Data to your Cluster/1. Kafka explained.mp425.29MB
  • 9. Feeding Data to your Cluster/2. [Activity] Setting up Kafka, and publishing some data..mp419.17MB
  • 9. Feeding Data to your Cluster/3. [Activity] Publishing web logs with Kafka.mp431.57MB
  • 9. Feeding Data to your Cluster/4. Flume explained.mp417.62MB
  • 9. Feeding Data to your Cluster/5. [Activity] Set up Flume and publish logs with it..mp418.97MB
  • 9. Feeding Data to your Cluster/6. [Activity] Set up Flume to monitor a directory and store its data in HDFS.mp430.64MB