Big Data Management and Analytics

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Die Vorlesungszeit beginnt am 16.10.2017, vorher erscheinen hier keine Inhalte.

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Stream Analytics

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Date: 12.12.2017

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Stream Processing

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  • (00:00:00) > 
    Apache Flink
  • (00:01:54) > 
    Flink Software Stack
  • (00:02:42) > 
    System Legacy
  • (00:02:43) > 
    Architecture
  • (00:03:13) > 
    Dataflow Graphs
  • (00:08:32) > 
    Latency and Throughput
  • (00:14:12) > 
    Stream Windows
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    Batch Processing
  • (00:15:49) > 
    Query Optimization
  • (00:16:26) > 
    Memory Management
  • (00:17:33) > 
    Batch Iterations
  • (00:17:36) > 
    API Examples
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    API Examples
  • (00:19:44) > 
    Outlook
  • (00:25:30) > 
    Maintaining Histograms
  • (00:26:51) > 
    Maintaining Histograms
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    Maintaining Histograms
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    Maintaining Histograms
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    Maintaining Histograms
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    Maintaining Histograms
  • (00:38:48) > 
    Maintaining Histograms
  • (00:42:58) > 
    Maintaining Histograms
  • (00:43:55) > 
    Maintaining Histograms
  • (00:49:24) > 
    Maintaining Histograms
  • (00:52:34) > 
    Change Detection
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    Change Detection
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    Change Detection
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    Change Detection
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    Change Detection
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    Change Detection
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    Change Detection
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    Change Detection
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    Change Detection
  • (01:09:49) > 
    Frequent ItemsetMining
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    Frequent ItemsetMining
  • (01:17:16) > 
    Frequent ItemsetMining
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    Frequent ItemsetMining
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    Frequent ItemsetMining
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    Frequent ItemsetMining
  • (01:33:23) > 
    Frequent ItemsetMining
  • Date: 05.12.2017

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    Apache Flink

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    Date: 28.11.2017

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    Stream Processing

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  • (00:00:00) > 
    Apache Spark
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    Motivation
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    Motivation
  • (00:02:53) > 
    Apache Spark
  • (00:10:24) > 
    Apache Spark
  • (00:12:47) > 
    Architecture
  • (00:16:02) > 
    Lettercountexamples
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    Shuffle reduceByKey
  • (00:16:18) > 
    Lettercountexamples
  • (00:18:39) > 
    Shuffle reduceByKey
  • (00:19:06) > 
    Shuffle groupByKey
  • (00:22:33) > 
    Sources
  • (00:33:55) > 
    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
  • (00:46:19) > 
    Stream Processing
  • (00:48:28) > 
    Stream Processing
  • (00:49:32) > 
    Stream Processing
  • (00:52:32) > 
    Stream Processing
  • (00:55:27) > 
    Stream Processing
  • (00:56:03) > 
    Stream Processing
  • (00:58:11) > 
    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
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    Stream Processing
  • (02:05:37) > 
    Stream Processing
  • (02:08:54) > 
    Stream Processing
  • Date: 21.11.2017

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    Apache Spark

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  • (00:00:00) > 
    Batch Processing Systems
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    Outline
  • (00:02:52) > 
    NoSQL and RBDMS
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    NoSQL and Batch Systems
  • (00:10:42) > 
    Distributed File Systems
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    Distributed File Systems
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    Distributed File Systems
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    Distributed File Systems
  • (00:16:09) > 
    Distributed File Systems
  • (00:17:51) > 
    HDFS-Architecture
  • (00:28:13) > 
    HDFS Robustness
  • (00:28:20) > 
    Overview
  • (00:28:57) > 
    MapReduce
  • (00:29:04) > 
    MapReduce
  • (00:29:56) > 
    MapReduce
  • (00:30:18) > 
    MapReduce
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    MapReduce
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    MapReduce
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    MapReduce
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    MapReduce
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    MapReduce
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    MapReduce
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    MapReduce
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    MapReduce
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    MapReduce
  • (00:42:44) > 
    MapReduce
  • (00:43:03) > 
    Big Data in Hadoop
  • (00:44:32) > 
    Apache Spark
  • (00:44:49) > 
    Motivation
  • (00:46:58) > 
    Motivation
  • (01:07:48) > 
    Architecture
  • (01:13:27) > 
    Shuffle
  • (01:17:34) > 
    Lettercount examples
  • (01:23:27) > 
    Shuffle reduceByKey
  • (01:24:46) > 
    Shuffle groupByKey
  • (01:27:03) > 
    Lettercount examples
  • (01:29:11) > 
    RDD Persistence
  • (01:29:39) > 
    RDD Persistence
  • (01:31:26) > 
    RDD Persistence
  • (01:35:18) > 
    RDD Persistence
  • (01:40:01) > 
    Shared variables
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    Shared variables
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    Shared variables
  • (01:48:57) > 
    Shared variables
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    Shared variables
  • (02:05:29) > 
    Sources
  • Date: 14.11.2017

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    Batch Systems

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  • (00:00:02) > 
    Outline
  • (00:00:52) > 
    NoSQL and RBDMS
  • (00:02:43) > 
    NoSQL and Batch Systems
  • (00:05:52) > 
    Distributed File Systems
  • (00:17:09) > 
    HDFS-Architecture
  • (00:29:51) > 
    HDFS Robustness
  • (00:34:57) > 
    Cluster Rebalancing
  • (00:38:04) > 
    Data Integrity
  • (00:40:38) > 
    Metadata Disk Failure
  • (00:43:57) > 
    Snapshots
  • (00:46:01) > 
    Overview
  • (00:46:32) > 
    MapReduce
  • (01:53:01) > 
    Big Data in Hadoop
  • Date: 07.11.2017
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