Altimetrik Senior Data Engineer Interview Questions, Process, and Tips

Q1. What are accumulators in spark?
Ans. 
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.
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Q2. Explain spark architecture
Ans. 
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 architectu...read more
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Q3. Write a query to find duplicate data using SQL
Ans. 
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
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Q1. What is pub/sub?
Ans. 
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
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Q2. What services have you used in GCP
Ans. 
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
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Hackerearth, advanced sql queries on joins, string literals, sql conceptual MCQ

Q1. Design etl flow in gcp
Ans. 
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...read more
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Q2. Hive, pyspark, python, sql questions
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