Prepstellar

DP-700 · Practice set 5 of 17

Spark Workspace Settings: 10 practice questions

10 questions · Untimed · Free

10 free DP-700 practice questions on Spark Workspace Settings, with an explanation for every answer. Untimed. The full mock exam and the timed version are in the app.

Set 5 · Spark Workspace Settings · 10 questions Read the lesson
  1. Question 1 of 10

    A workspace admin turns on Set maximum job lifetime with a value of 2 hours. Which of these runs can still be active after 3 hours?

    1. AA Livy interactive session in high concurrency mode
    2. BA scheduled notebook run that a pipeline orchestrates
    3. CA Spark job definition run that was submitted on a schedule
    4. DA lakehouse table maintenance operation that runs optimize
    Show the answer

    The limit separates jobs by who starts them. Jobs that a user starts and that run with the user's identity are cancelled at the limit. Jobs that Fabric starts for you, such as optimize and vacuum on lakehouse tables, are system-managed and always run to the end.

    Next → 1 / 10
  2. Question 2 of 10

    A workspace on an F64 capacity runs small notebooks on the starter pool. A new job needs nodes with 128 GB of memory. It should use 2 nodes on quiet days, grow to 12 on busy days, and release nodes when the work is done. Which configuration fits?

    1. AThe starter pool with its maximum raised to 12 nodes
    2. BA custom pool of Large nodes with autoscale from 2 to 12
    3. CA custom pool of Large nodes with autoscale off and 12 nodes
    4. DAn environment on the starter pool with 128 GB of executor memory
    Show the answer

    Two needs decide it. The node size is chosen only in a custom pool, and Large is the size with 128 GB. The node count should follow the load, which is what autoscale does between a minimum and a maximum.

    Next → 2 / 10
  3. Question 3 of 10

    Users report that the notebook menu no longer offers the option to start a new high concurrency session. Which workspace Spark setting was changed?

    1. AThe default environment option was disabled in the Environment tab
    2. BReserve maximum cores for active Spark jobs was enabled
    3. CThe For notebooks setting under High concurrency was disabled
    4. DCustomize compute configurations for items was turned off
    Show the answer

    Match the symptom to the area of Spark settings that owns it. Session sharing is owned by the High concurrency section. Workspaces start with the mode enabled, and disabling its For notebooks setting hides the option in the notebook menu.

    Next → 3 / 10
  4. Question 4 of 10

    A workspace admin opens Spark settings to create a custom pool and cannot create one. Which setting must a capacity admin enable for the capacity?

    1. ACustomize compute configurations for items
    2. BCustomized workspace pools
    3. CReserve maximum cores for active Spark jobs
    4. DDynamically allocate executors
    Show the answer

    Custom pools have a prerequisite at each level. In the workspace you need the Admin role. On the capacity, the Spark Compute settings must allow workspace pools. That option is on by default, so when it blocks you, somebody turned it off.

    Next → 4 / 10
  5. Question 5 of 10

    A contributor opens an environment to raise the executor memory for one notebook, but the Compute section is disabled. What should the workspace admin change?

    1. ATurn on Reserve maximum cores for active Spark jobs
    2. BTurn on Customize compute configurations for items
    3. CCreate a custom pool and make it the workspace default pool
    4. DSet that environment as the workspace default environment
    Show the answer

    A disabled Compute section is the sign that item-level customization is off. With the toggle on the Pool tab turned on, members and contributors can pick a pool in an environment and set driver and executor cores and memory.

    Next → 5 / 10
  6. Keep the ones you got wrong

    In the app, every question you miss comes back exactly when you’re about to forget it.

    Opens in your browser. Nothing to install.

    Start studying

    On your phone, with the same account

    Get it on Google Play Download on the App Store
  7. Question 6 of 10

    An F32 capacity can use up to 192 Spark VCores with burst. A workspace admin enables Reserve maximum cores for active Spark jobs, and every job uses a pool with a maximum of 64 Spark VCores. How many of these jobs can run at the same time?

    1. A8 jobs
    2. B3 jobs
    3. C24 jobs
    4. D32 jobs
    Show the answer

    With maximum cores reserved, each admitted job holds its full pool maximum. Divide the cores of the capacity by that number: 192 divided by 64 is 3. Optimistic admission would divide by the minimum instead.

    Next → 6 / 10
  8. Question 7 of 10

    All notebooks in a workspace must start with the same Spark runtime and the same custom library packages. Contributors must not be able to change driver or executor sizes for their own items. Which setup meets both needs?

    1. ASelect a default Environment and keep item compute customization off
    2. BCreate a custom pool as the default pool and select a runtime version
    3. CDisable the default Environment and select a runtime version
    4. DSelect a default Environment and turn item compute customization on
    Show the answer

    Take the needs one at a time. Shared libraries and a shared runtime travel together in an environment, so the workspace needs a default one. Fixed driver and executor sizes mean the Pool tab toggle for item customization stays off.

    Next → 7 / 10
  9. Question 8 of 10

    On a busy capacity, the jobs of one workspace start quickly but then stay at their minimum nodes for hours. The team wants each job to be sure of its full compute from the moment it starts, and accepts that fewer jobs will run at once. The autoscale ranges of the pools must stay as they are. What should the admin do?

    1. AEnable Reserve maximum cores for active Spark jobs
    2. BRaise the maximum node count of the workspace default pool
    3. CSet a maximum job lifetime to cancel long-running jobs
    4. DDisable autoscale and set a fixed node count on the default pool
    Show the answer

    The symptom is optimistic job admission at work: jobs enter on their minimum cores and then find no room to grow. The Jobs tab has the opposite mode, where each admitted job holds its maximum. The price is concurrency, which the team accepts.

    Next → 8 / 10
  10. Question 9 of 10

    Customize compute configurations for items is on in a workspace that has only the starter pool. A contributor's notebook needs Large nodes. What is needed before the notebook can run on Large nodes?

    1. AThe contributor must create a custom pool in Spark settings, now that the toggle is on
    2. BA workspace admin must create a custom pool of Large nodes in Spark settings
    3. CThe contributor must create a custom pool in the Compute section of an environment
    4. DThe contributor must set the starter pool to Large nodes in an environment
    Show the answer

    Separate building a pool from using one. Pools are built in Spark settings, and that page needs the Admin role. The toggle only lets members and contributors pick an existing pool in an environment and tune driver and executor sizes.

    Next → 9 / 10
  11. Question 10 of 10

    A new workspace uses its starter pool, and nobody has edited the pool. What is the state of Autoscale and of Dynamically allocate executors?

    1. ABoth options are disabled by default
    2. BOnly Dynamically allocate executors is enabled
    3. CBoth options are enabled by default
    4. DOnly Autoscale is enabled
    Show the answer

    The starter pool is built to work with no setup, so both scaling options start enabled. Autoscale moves the number of nodes with activity. Dynamic allocation adds and releases executors inside those nodes. An admin only adjusts their limits.

    Next → 10 / 10
  12. You’ve finished this set

    That’s 10 questions on Spark Workspace Settings. In the app the ones you miss come back exactly when you’re about to forget them.

    Back to the course Next lesson: Domain Workspace Settings

    Opens in your browser. Nothing to install.

    Start studying

    On your phone, with the same account

    Get it on Google Play Download on the App Store

The whole course, on your computer and your phone

Lessons you can read, audio you can listen to on the way to work, and practice that remembers what you got wrong.

Opens in your browser. Nothing to install.

Start studying

On your phone, with the same account

Get it on Google Play Download on the App Store

“This app is the ‘One Lake’ for preparing the certification exams. Really worth it.”

Abdelhak Y. Google Play review