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I. Introduction |
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A. Hadoop history, concepts |
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B. Ecosystem |
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C. Distributions |
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D. High level architecture |
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E. Hadoop challenges (hardware / software) |
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Hands on session. Preparing to Install Hadoop |
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II. Planning and Installation |
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A. Selecting software, Hadoop distributions |
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B. Sizing the cluster, planning for growth |
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C. Rack topology |
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D. Installation of Core Hadoop and Ecosystem tools |
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E. Directory structure, logs |
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Hands on Session: Cluster installation |
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III. HDFS |
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A. Concepts (horizontal scaling, block replication, data locality, rack awareness) |
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B. Nodes and daemons (NameNode, Secondary NameNode, HA Standby NameNode, DataNode) |
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C. Health monitoring |
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D. Command-line and browser-based administration |
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E. Adding storage, replacing defective drives - Commissioning / De-Comissioning of Datanodes |
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Hands on Session: getting familiar with HDFS commands |
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IV. Mapreduce2 |
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A. MapReduce1 |
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B. Terminology and Data Flow - (Map – Shuffle – Reduce) |
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C. YARN Architecture |
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D. MapReduce Essential Configuration |
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Hands on Session : MapReduce UI walk through |
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V. Schedulers |
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A. Working with Jobs |
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B. Scheduling Concepts |
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C. FIFO Scheduler |
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D. Fair Scheduler |
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E. Capacity Scheduler - Configuration |
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Hands on Session: Working with Schedulers |
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VI. Data Ingestion & Security |
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A. Flume for logs and other data ingestion into HDFS |
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B. Sqoop for importing from SQL databases to HDFS, as well as exporting back to SQL |
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C. Overview of Hive |
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D. Copying data between clusters (distcp) |
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E. Ranger installation and configuration for HDFS, Hive, Hbase |
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Hands on session: setup and configure Flume, Sqoop, Range Installing Hadoop with Ambari Lab Tasks |
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