Hadoop Administration: Online Hadoop Admin Training

Learn how to download CentOS, select the correct 32-bit or 64-bit iso image, and download a dvd iso from centos.org for installation.

Learn to set up a VirtualBox VM by selecting Linux, enabling virtualization if needed, allocating 1 GB RAM, and creating a dynamically allocated 16 GB hard drive.

Start and configure two machines, assign IP addresses, and update the hosts file to enable communication between them for Hadoop administration.

Download Hadoop 1.6 for your two virtual machines by visiting the recommended download site, selecting the Hadoop 1.6 package, saving the file, and repeating for both machines.

Create a group and a user, assign a password, and update the user profile across multiple machines to enable Hadoop administration tasks.

Distribute ssh keys across local and remote machines to enable passwordless logins. Create rsa public keys, add them to authorized_keys, and verify known_hosts entries for seamless access.

Learn how to set java for your Hadoop environment by updating the bashrc. Refresh the session, save the changes, and verify that the updates take effect for Hadoop jobs.

Explore setting the Hadoop path and managing version links, switching between Hadoop 2.0 and 2.6 by updating links without altering other configurations.

Learn how to format the NameNode in Hadoop, set ownership and permissions, and verify the namespace with heartbeat signals and namespace IDs.

Create a directory, add data, and read files to verify content in a Hadoop environment.

Examine why storing data in the tmp directory is problematic, as storage becomes unavailable or inaccessible, causing daemons to fail and requiring a cluster rebuild.

Learn to start Hadoop admin commands and navigate the file system, then use the admin report to view present capacity, used blocks, and available data.

Set up and troubleshoot pseudo distributed mode in a Hadoop-like environment, ensuring inter-machine connectivity, configuring master and slave nodes, and preparing and running jobs across the cluster.

Explore how to view the fully distributed mode and manage distributed content, including creating and clearing blogs and books, with practical walkthroughs of a distributed setup.

Use a script file to monitor the cluster, run commands to gather status and availability, and extract essential operational details from the cluster configuration.

Learn to view under replicated blocks in hdfs, identify missing or under replicated blocks, and understand how configured capacity and replication affect block availability when blocks come back online.

Setting the third machine in a fully distributed Hadoop cluster, the session covers provisioning a new host, installing Hadoop, configuring hosts and ports, and ensuring firewall allowances for inter-node communication.

Bring up the third machine to restore replication of under-replicated blocks and reestablish data availability across multiple machines after a machine failure.

Understand commissioning and decommissioning in a Hadoop cluster and how these processes track added and removed machines. Learn how this practice helps maintain a clear, online Hadoop administration record.

Explore the dfsadmin metasave command in Hadoop to inspect block status, replication, and deletions, by saving metadata and reviewing log details for block-level insights.

Learn how to dynamically write data for different applications by setting replication factors, such as replication equal to 1, and verify results in the browser interface.

Learn how rack awareness guides Hadoop block replication across racks to improve fault tolerance by avoiding placing all copies on a single rack and reducing cross-rack traffic.

Enable rack awareness to optimize Hadoop block placement, understand topology driven replication, and manage under replicated blocks by aligning IP addresses and rack mappings.

When a new machine comes online in a Hadoop cluster, it joins the cluster even without topology information, and topology determines which rack the node belongs to, guiding data placement.

Learn how the secondary namenode performs checkpointing by merging edits with the fsimage, updating the image, and reducing log growth on a separate machine.

Explore how the secondary namenode operates within a cluster setup, managing configuration updates every 10 minutes and pushing changes to the image while preserving copies.

Explore how changes in the cluster affect the fsimage, showing how file updates, deletions, and size changes are reflected in the fsimage and its contents.

Shut down the namenode and trace how the image updates reflect changes to blocks, logs, and data state, including reconnection after crashes.

Learn how to manually interact with the NameNode in a Hadoop production environment, including daemon status checks and lock handling. Validate changes with file edits, snapshots, and command verification.

Learn how to manage a Hadoop namespace by applying edits in read-only mode, saving namespace changes, and controlling when writes are allowed during image updates.

Learn to commission and decommission Hadoop cluster nodes by creating include and exclude files, refreshing nodes, stopping daemons, and removing data.

The lecture demonstrates commissioning in Hadoop by bringing machines up, starting daemons, and managing decommissioning, updating configurations, and tracking which nodes are up versus down.

Analyze how changes to running tasks can yield corrupt and missing blocks, and learn to stop and restart the daemons to reflect updates and reduce missing blocks.

Start the second datanode and manage start and stop operations to see that it runs fine in a Hadoop administration context.

Restart the namenode on an old machine by stopping all daemons, validating storage locations, and recovering metadata from the image and checkpoint to restore replication.

Learn to start the Namenode on an old machine by leveraging an existing DFS image, transferring the image, and bringing the Namenode up on the target host while preserving data.

This lecture demonstrates working with updated metadata through checkpoints, logging in, importing a changed file, and verifying its size before proceeding.

Explore multiple paths to run a Hadoop cluster, and learn upgrade and recovery approaches to keep the cluster operating during disk failures and downtime.

Start the cluster and verify all services are running to ensure the Hadoop environment is healthy. Practice starting and stopping components, and check that every machine is working as expected.

Delete the primary path of the Namenode and review logs for inconsistencies. Then restart the Namenode when storage is inaccessible to restore operation.

Explore how to copy metadata from a secondary location to the primary location within Hadoop administration and verify the primary copy with checkpoint validation.