Planning and installation Selecting software, Hadoop distributions Sizing the cluster, planning for growth Selecting hardware and network Rack topology Installation Multi-tenancy The directory structure, logs Benchmarking Labs: cluster install, run performance benchmarks

HDFS operations Concepts (horizontal scaling, replication, data locality, rack awareness) Nodes and daemons (NameNode, Secondary NameNode, HA Standby NameNode, DataNode) Health monitoring Command-line and browser-based administration Adding storage, replacing defective drives Labs: getting familiar with HDFS command lines

Data ingestion Flume for logs and other data ingestion into HDFS Sqoop for importing from SQL databases to HDFS, as well as exporting back to SQL Hadoop data warehousing with Hive Copying data between clusters (distcp) Using S3 as complementary to HDFS Data ingestion best practices and architectures Labs: setting up and using Flume, the same for Sqoop

MapReduce operations and administration Parallel computing before MapReduce: compare HPC vs Hadoop administration MapReduce cluster loads Nodes and Daemons (JobTracker, TaskTracker) MapReduce UI walkthrough Mapreduce configuration Job config Optimizing MapReduce Fool-proofing MR: what to tell your programmers Labs: running MapReduce examples

YARN: new architecture and new capabilities YARN design goals and implementation architecture New actors: ResourceManager, NodeManager, Application Master Installing YARN Job scheduling under YARN Labs: investigate job scheduling

Advanced topics Hardware monitoring Cluster monitoring Adding and removing servers, upgrading Hadoop Backup, recovery and business continuity planning Oozie job workflows Hadoop high availability (HA) Hadoop Federation Securing your cluster with Kerberos Labs: set up monitoring

Optional tracks Cloudera Manager for cluster administration, monitoring, and routine tasks; installation, use. In this track, all exercises and labs are performed within the Cloudera distribution environment (CDH5) Ambari for cluster administration, monitoring, and routine tasks; installation, use. In this track, all exercises and labs are performed within the Ambari cluster manager and Hortonworks Data Platform (HDP 2.0)