Legal Consultant Interview Questions and Answers

Handling out of memory issue in Spark involves optimizing memory usage, partitioning data, and increasing resources.

• Optimize memory usage by tuning Spark configurations like executor memory, driver memory, and shuffle partitions.

• Partition data to distribute workload evenly across nodes and avoid data skew.

• Increase resources by adding more nodes, increasing memory allocation, or using a larger cluster.

• Use persistence mechanisms like caching or checkpointing to reduce recomputa...read more

Data structures are fundamental in programming. Python and Java have built-in data structures like lists, tuples, and dictionaries.

• Python has built-in data structures like lists, tuples, and dictionaries

• Java has built-in data structures like arrays, lists, sets, and maps

• Data structures are used to store and organize data efficiently

• Choosing the right data structure is important for optimizing performance

• Examples of data structure implementation in Python: creating a list, app...read more

S3 bucket types are Standard, Intelligent-Tiering, Standard-Infrequent Access, One Zone-Infrequent Access, and Glacier. Life cycle policy automates data movement.

• S3 bucket types are designed to optimize storage costs and access patterns.

• Standard is for frequently accessed data, Intelligent-Tiering for variable access patterns, Standard-Infrequent Access for infrequent access, One Zone-Infrequent Access for infrequent access in a single availability zone, and Glacier for long-...read more

Broadcast Join is a type of join operation in distributed computing where one smaller dataset is broadcasted to all nodes for joining with a larger dataset.

• In Broadcast Join, one smaller dataset is broadcasted to all nodes in a distributed system.

• This smaller dataset is then joined with a larger dataset that is partitioned across the nodes.

• Broadcast Join is efficient when the smaller dataset can fit in memory across all nodes.

• It reduces the amount of data shuffling and networ...read more

The highest salary in SQL depends on the data and industry.

• The highest salary in SQL varies depending on the industry and location.

• Factors such as experience, education, and job role also impact salary.

• For example, a senior data engineer in Silicon Valley may earn a higher salary than a junior data engineer in a smaller city.

Water trapping problem involves calculating the amount of water that can be trapped between bars in an array.

• The problem can be solved using two pointers approach.

• Iterate through the array and keep track of the maximum height on the left and right side of each bar.

• Calculate the amount of water trapped at each bar by subtracting the bar's height from the minimum of the maximum heights on both sides.

• Sum up the trapped water at each bar to get the total amount of water trapped.