Clock
Test duration:
20
min
Notes
No. of questions:
10
Tie
Level of experience:
Entry/Mid/Senior

Apache Airflow Skills Test

Our Apache Airflow skills test is the most preferred pre-hire test for recruiters and hiring managers to assess the skills of building data pipelines with Airflow. The Apache Airflow development test is useful for hiring Airflow Developers, Airflow Engineers, Senior Data Engineers, and Python Developers. This test can reduce screening time by 80%.

23846
+
Candidates
Assessed
116
+
Organizations Served
Fujitsu
Paypal
Capgemini
Deloitte
Coupa
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Vanguard
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About

Apache Airflow Skills Test

Apache Airflow is an open-source workflow management platform. Apache Airflow is developed as a solution to manage complex workflows of an organization. Using Apache Airflow, it is possible to programmatically author and schedule the workflow and monitor them using the built-in user interface. It is developed in Python, and developers can build complicated workflows using Python features. Apache Airflow skills test based on Airflow v1.10 helps recruiters & hiring managers to assess candidates' skills in building data pipelines with Airflow.

The Apache Airflow development test is designed by experienced Subject Matter Experts (SME) to evaluate and hire Apache Airflow developers based on industry standards.

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How it works

Test Summary

The Apache Airflow skills test helps to screen the candidates who possess the following traits:    

  

  • Knowledge of configuration and monitoring of Airflow 
  • Excellent knowledge of core functionalities such as DAGs, Operators, Tasks, Workflow, Kerberos Integration, etc. 
  • Ability to implement solutions using Airflow to real data processing problems 

Apache Airflow development test is designed considering EEOC guidelines; it will help you assess and hire diverse talent without any bias. With role-based access control, you can now maintain security within your account by providing access to each user based on their established role. Moreover, with the help of our advanced cheating prevention tools (like image, audio, & video proctoring and window violation detection), you can allow candidates to take the test online from anywhere in the comfort of their time zone. 

 

This test may contain MCQs (Multiple Choice Questions), MAQs (Multiple Answer Questions), Fill in the Blanks, Whiteboard Questions, Audio / Video Questions, AI-LogicBox, Coding Simulators, True or False Questions, etc. 

Test Duration
20
No. of Questions
10
Level of Expertise
Entry/Mid/Senior
Useful for hiring
  • Airflow Developer
  • Airflow Engineer
  • Senior Data Engineer
  • Python Developer
  • ML Ops Engineer
Topics Covered
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LDAP Configuration

The Apache Airflow skills test assesses a candidate's knowledge of front-end authentication.

Tasks

This test also gauges knowledge of Apache tasks to build operations for the project.
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Service Key

iMocha's Apache Airflow development test evaluates the candidate's knowledge of Service keys to provide foreign and primary keys behavior.
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Operators

Skill assessment lets you check the knowledge of the Apache operator, which represents a single, ideally idempotent, task.
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Logging

Our pre-hire test assesses understanding of storing information about events that occurred on your Apache web server.
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Kerberos Integration

Our pre-hire test evaluates understanding of protocol that supports Singal sign-on.
Sample Question
Choose from our 100,000+ questions library or add your own questions to make powerful custom tests.

Question types :

Multiple Option

Topic:

Difficulty:

Hard


Q 1. You have been asked to train « Naive Bayes model for spam detection dataset

Using Python command, what wil you add in the given code at XXXX to deciore, it and train your modal for the given dataset?

import numpy os np

X= nporroyll 3. 2b[1 21 [2.21.[3,21)
Y= nporray(fi.a,a.1))

XXXX

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

Question types :

Multiple Option

Topic:

Machine teaming

Difficulty:

Hard


Q 1. Q2 Lets assume that you have 6 Pandas DataFrome(af) in the below tole.

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074

When the following commend is executed, what hoppens to the DatoFrome?

df= defiinat()
Y= nporray(fi.a,a.1))

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
it gives an error becouse of the third row which has on empty string.
None of these

Question types :

Multiple Option

Topic:

Taks

Difficulty:

Hard

Question:

An Apache Airflow task returns a value from a Python Operators python_callable function. In the given context which of these statements should be considered valid?


Options

  • An XCom containing that value is automatically pushed.
  • The value returned by the task is automatically pulled by all existing XCom
  • The DAG will generate a separate task to pull the value returned via a XCOM
  • None of these
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