Neurons-IT Interview Questions and Answers

I have used services like BigQuery, Dataflow, Pub/Sub, and Cloud Storage in GCP.

• 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

Accumulators are shared variables that are updated by worker nodes and can be used for aggregating information across tasks.

• Accumulators are used for implementing counters and sums in Spark.

• They are only updated by worker nodes and are read-only by the driver program.

• Accumulators are useful for debugging and monitoring purposes.

• Example: counting the number of errors encountered during processing.

Query to find duplicate data using SQL

• Use GROUP BY and HAVING clause to identify duplicate records

• Select columns to check for duplicates

• Use COUNT() function to count occurrences of each record

Pub/sub is a messaging pattern where senders (publishers) of messages do not program the messages to be sent directly to specific receivers (subscribers).

• Pub/sub stands for publish/subscribe.

• Publishers send messages to a topic, and subscribers receive messages from that topic.

• It allows for decoupling of components in a system, enabling scalability and flexibility.

• Examples include Apache Kafka, Google Cloud Pub/Sub, and MQTT.

Spark architecture is a distributed computing framework that consists of a driver program, cluster manager, and worker nodes.

• Spark architecture includes a driver program that manages the execution of the Spark application.

• It also includes a cluster manager that allocates resources and schedules tasks on worker nodes.

• Worker nodes are responsible for executing the tasks and storing data in memory or disk.

• Spark architecture supports fault tolerance through resilient distributed ...read more

Designing ETL flow in Google Cloud Platform (GCP) involves defining data sources, transformation processes, and loading destinations.

• Identify data sources and extract data using GCP services like Cloud Storage, BigQuery, or Cloud SQL.

• Transform data using tools like Dataflow or Dataprep to clean, enrich, and aggregate data.

• Load transformed data into target destinations such as BigQuery, Cloud Storage, or other databases.

• Schedule and automate the ETL process using Cloud Compose...read more