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sebc's Introduction

Services Enablement Boot Camp

This repository contains materials for Cloudera's Services Enablement Boot Camp and Cloudera FCE's internal boot camp.

If you've received this repo as a ZIP file attachment, use the instructions in the email to create your class repo. You can make your GitHub repo Private if you wish, but it is not a free option. For that reason, most students choose to make their GitHub repository public.

NOTE: DO NOT add files to your repository through the GitHub browser interface.

Use GitHub only to receive your lab work by pushing from your local copy. Treat your GitHub repo like a backup to what is on your laptop. Doing so will save a lot of headaches around maintaining the repo, as we will explain in class. The only changes you should make directly to your GitHub copy are Issues and Milestones, which are described in README.md.

Add your instructor(s) as Collaborators to your GitHub repo. The lead instructor's GitHub name is manojsundaram.

Adding your instructors as Collaborators will let them create pull requests on your work. This is a way of editing your submissions without changing them directly. When you review instructor edits, you can choose to reject them. Perhaps you would like to correct problems a different way or ignore them for a while. The pull request stands as a record of that interaction.

We use GitHub's Issues feature to establish a workflow around your lab submissions.

For each lab section, such as Installation or Storage, you will use an Issue to track your progress. You will also use GitHub labels to mark the current state of each lab (e.g., submitted, stuck, review). Your instructors will use labels to evaluate your work once you have marked it for review (such as complete or 'incomplete`).

Finally, we will use GitHub milestones to separate your lab work from your challenge work.

In a large class, it may take some time for an instructor to help you with a difficult problem. Use the Issue to describe the problem and show what diagnostic work you've tried to isolate your problem.

You can include error messages or stack traces as Issue comments, or take a screenshot to show your cluster's current condition. It is quite possible these initial steps will help you solve the problem yourself. Otherwise, they will show an instructor what you have tried so far.

Before you start any labs, make the following changes to your GitHub repo:

  • Add collaborators under Settings -> Collaborators.
  • Enable Issues under Settings -> Options. Click the Features box and enable Issues.
  • Click the Issues tab and the Milestones button
    • Create two milestones: Labs and Challenges
    • Set the deadlines for Thursday and Friday of the current week.
  • Click the Labels button and change your labels as follows:
    • Change bug to stuck
    • Change duplicate to started
    • Change enhancement to didNotSubmit
    • Change help wanted to complete
    • Change invalid to review
    • Change wontfix to incomplete; set the label color to #fbca04.
    • Leave the question Issue as it is

One of the instructors will open an issue on your repo to acknowledge your invitation to collaborate. They will also review your repo for all the settings described here, and point out anything that isn't setup correctly. This issue will be the only one you're asked to close. All other issues are to be closed by an instructor to show no further review is needed.

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sebc's Issues

Storage Labs

These labs will have you:

  • Replicate data to another cluster
  • Use teragen and terasort to test throughput
  • Test HDFS Snapshots
  • Enable NameNode HA configuration

Cloudera Manager Warning

I see a few warning like below. Can we ignore this for lab purpoess?

Memory on host hadoop7.expecc.com is overcommitted. The total memory allocation is 13.2 GiB bytes but there are only 15.6 GiB bytes of RAM (3.1 GiB bytes of which are reserved for the system). Visit the Resources tab on the Host page for allocation details. Reconfigure the roles on the host to lower the overall memory allocation. Note: Java maximum heap sizes are multiplied by 1.3 to approximate JVM overhead.

checkpoint warnign

Dear Manoj,

how to fix this issue? is this normal?

Checkpoint Status Suppress...
The filesystem checkpoint is 3 hour(s), 4 minute(s) old. This is 308.31% of the configured checkpoint period of 1 hour(s). Warning threshold: 200.00%. 6,318 transactions have occurred since the last filesystem checkpoint. This is 0.63% of the configured checkpoint transaction target of 1,000,000.

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