Accenture Gcp Data Engineer Interview Questions and Answers

The GCP services used in our project include BigQuery, Dataflow, Pub/Sub, and Cloud Storage.

• BigQuery for data warehousing and analytics

• Dataflow for real-time data processing

• Pub/Sub for messaging and event ingestion

• Cloud Storage for storing data and files

Cloud Functions are event-driven functions that run in response to cloud events.

• Serverless functions that automatically scale based on demand

• Can be triggered by events from various cloud services

• Supports multiple programming languages like Node.js, Python, etc.

To schedule a job to trigger every hour in Airflow, you can use the Cron schedule interval

• Define a DAG (Directed Acyclic Graph) in Airflow

• Set the schedule_interval parameter to '0 * * * *' to trigger the job every hour

• Example: schedule_interval='0 * * * *'

Use Python's slicing feature to display a string in reverse order.

• Use string slicing with a step of -1 to reverse the string.

• Example: 'hello'[::-1] will output 'olleh'.

Pub/Sub is a messaging service that allows communication between independent applications.

• Pub/Sub is used for real-time messaging and event-driven systems.

• It is commonly used for data ingestion, streaming analytics, and event-driven architectures.

• Examples of Pub/Sub services include Google Cloud Pub/Sub, Apache Kafka, and Amazon SNS/SQS.

I have experience working on projects involving data processing, transformation, and analysis using GCP services like BigQuery, Dataflow, and Dataproc.

• Utilized BigQuery for storing and querying large datasets

• Implemented data pipelines using Dataflow for real-time data processing

• Utilized Dataproc for running Apache Spark and Hadoop clusters for data processing

• Worked on data ingestion and transformation using Cloud Stora

Check if a string is a palindrome or not

• Compare the string with its reverse to check for palindrome

• Ignore spaces and punctuation marks when comparing

• Examples: 'racecar' is a palindrome, 'hello' is not

Use Python to create a GCS bucket

• Import the necessary libraries like google.cloud.storage

• Authenticate using service account credentials

• Use the library functions to create a new bucket

Python code to trigger a dataflow job in cloud function

• Use the googleapiclient library to interact with the Dataflow API

• Authenticate using service account credentials

• Submit a job to Dataflow using the projects.locations.templates.launch endpoint

BigQuery is used for analyzing large datasets and running complex queries, while SQL is used for querying databases.

• BigQuery is used for analyzing large datasets quickly and efficiently

• SQL is used for querying databases to retrieve specific data

• BigQuery can handle petabytes of data, making it ideal for big data analysis

• SQL can be used to perform operations like filtering, sorting, and aggregating data

SQL joins are used to combine rows from two or more tables based on a related column between them.

• SQL joins are used to retrieve data from multiple tables based on a related column between them

• Types of SQL joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN

• In BigQuery, joins can be performed using standard SQL syntax

• Example: SELECT * FROM table1 INNER JOIN table2 ON table1.column = table2.column