10+ Aark Cargo Care Interview Questions and Answers

Convert a string of multiple lines with 'n' words to multiple arrays of fixed size without overlap.

• Split the string into individual words

• Create arrays of fixed size 'k' and distribute words evenly

• Handle cases where the number of words is not divisible by 'k'

Use SQL query to find columns with timestamp data type in a table.

• Use a SQL query like 'SHOW COLUMNS FROM table_name WHERE Type = 'timestamp''

• Alternatively, query the information_schema.columns table for column data types

• Check for variations of timestamp data types like datetime, timestamp, etc.

Unacknowledged messages in pubsub can be handled by implementing retries, dead letter queues, and monitoring mechanisms.

• Implement retries for unacknowledged messages to be redelivered.

• Use dead letter queues to store messages that repeatedly fail to be processed.

• Set up monitoring mechanisms to track unacknowledged messages and identify potential issues.

Find the second index of 'l' in the string 'Hello'.

• Use the find() method to find the first index of 'l'.

• Use the find() method again starting from the index after the first 'l' to find the second index.

• Handle cases where the first 'l' is not found or there is no second 'l'.

Use the split() method to convert a string with multiple lines into a list of strings.

• Use the split() method with the newline character '\n' as the delimiter to split the string into a list of strings.

• Example: 'Hello\nWorld\n' -> ['Hello', 'World']

count(*) counts all rows in a table, while count(1) counts the number of non-null values in a specific column.

• count(*) counts all rows in a table

• count(1) counts the number of non-null values in a specific column

• count(*) is generally used when you want to count all rows in a table, while count(1) is used when you want to count non-null values in a specific column

Implementing incremental load in a table involves updating only new or changed data without reloading the entire dataset.

• Identify a column in the table that can be used to track changes, such as a timestamp or a version number

• Use this column to filter out only the new or updated records during each load

• Merge the new data with the existing data in the table using SQL queries or ETL tools

• Ensure data integrity by handling any conflicts or duplicates that may arise during the inc...read more

Use the DISTINCT keyword in a SELECT statement to remove duplicate rows from a table.

• Use the DISTINCT keyword in a SELECT statement to retrieve unique rows

• Use the GROUP BY clause with appropriate columns to remove duplicates

• Use the ROW_NUMBER() function to assign a unique row number to each row and then filter out rows with row number greater than 1

Drop removes a table from the database, truncate removes all rows from a table, and delete removes specific rows from a table.

• DROP: Removes the entire table structure and data from the database.

• TRUNCATE: Removes all rows from a table but keeps the table structure.

• DELETE: Removes specific rows from a table based on a condition.

• Example: DROP TABLE table_name;

• Example: TRUNCATE TABLE table_name;

• Example: DELETE FROM table_name WHERE condition;

Hadoop is an open-source framework used for distributed storage and processing of large data sets across clusters of computers.

• Hadoop consists of HDFS (Hadoop Distributed File System) for storage and MapReduce for processing.

• It allows for parallel processing of large datasets across multiple nodes in a cluster.

• Hadoop is scalable, fault-tolerant, and cost-effective for handling big data.

• Popular tools like Apache Hive, Apache Pig, and Apache Spark can be integrated with Hadoop ...read more

Optimizing dags involves reducing unnecessary tasks, parallelizing tasks, and optimizing resource allocation.

• Identify and remove unnecessary tasks to streamline the workflow.

• Parallelize tasks to reduce overall execution time.

• Optimize resource allocation by scaling up or down based on task requirements.

• Use caching and memoization techniques to avoid redundant computations.

• Implement data partitioning and indexing for efficient data retrieval.

Top is used to select the first few rows from a dataset, while limit is used to restrict the number of rows returned in a query.

• Top is commonly used in SQL Server, while limit is commonly used in MySQL.

• Top is used with the SELECT statement in SQL Server to limit the number of rows returned, while limit is used in MySQL to restrict the number of rows returned.

• Example: SELECT TOP 5 * FROM table_name; (SQL Server) vs. SELECT * FROM table_name LIMIT 5; (MySQL)