Scalability & Distribution

Question 1

What is Databricks?

Answer 1

A cloud-based data platform that provides collaborative workspaces for data engineering, data science, and machine learning.

Question 2

True or False: Databricks is designed to handle distributed data processing.

Answer 2

True

Question 3

What is the primary underlying engine for Databricks?

Answer 3

Apache Spark

Question 4

Fill in the blank: Databricks allows for __________ scaling of compute resources.

Answer 4

elastic

Question 5

What feature in Databricks enables automatic scaling of clusters?

Answer 5

Autoscaling

Question 6

Which type of cluster in Databricks is designed for interactive workloads?

Answer 6

All-Purpose Cluster

Question 7

What is the purpose of a Job Cluster in Databricks?

Answer 7

To run scheduled jobs or automated tasks.

Question 8

True or False: Databricks supports both batch and streaming data processing.

Answer 8

True

Question 9

What is the maximum number of concurrent clusters that can be created in Databricks?

Answer 9

It varies based on the workspace configuration and subscription plan.

Question 10

How does Databricks optimize data processing tasks?

Answer 10

By using Catalyst optimizer and Tungsten execution engine.

Question 11

What is the role of Apache Spark’s Resilient Distributed Dataset (RDD) in Databricks?

Answer 11

To provide a fault-tolerant collection of elements that can be processed in parallel.

Question 12

Fill in the blank: Databricks uses __________ to manage and optimize data storage.

Answer 12

Delta Lake

Question 13

What is Delta Lake?

Answer 13

An open-source storage layer that brings ACID transactions to Apache Spark and big data workloads.

Question 14

True or False: Databricks allows users to run SQL queries directly on streaming data.

Answer 14

True

Question 15

What is the purpose of the Databricks File System (DBFS)?

Answer 15

To provide a distributed file system for storing data in Databricks.

Question 16

What does the term ‘shuffling’ refer to in the context of Apache Spark?

Answer 16

The process of redistributing data across different partitions.

Question 17

Fill in the blank: __________ is a key feature of Databricks that allows users to visualize data insights.

Answer 17

Dashboards

Question 18

What is the benefit of using a cluster policy in Databricks?

Answer 18

To enforce specific configurations and limits on clusters.

Question 19

What is the maximum number of nodes supported in a Databricks cluster?

Answer 19

It depends on the cloud provider and specific configurations.

Question 20

True or False: Databricks supports integration with machine learning libraries like TensorFlow and Scikit-learn.

Answer 20

True

Question 21

What is the significance of the ‘spark.sql.shuffle.partitions’ configuration?

Answer 21

It determines the number of partitions to use when shuffling data for joins or aggregations.

Question 22

How can Databricks users optimize their Spark jobs?

Answer 22

By using caching, optimizing shuffle partitions, and adjusting resource configurations.

Question 23

What is a ‘spark-submit’ command used for?

Answer 23

To submit a Spark job to a cluster.

Question 24

Fill in the blank: Databricks provides __________ for managing data pipelines and workflows.

Answer 24

Workflows

Question 25

What is the purpose of the Databricks CLI?

Answer 25

To provide a command-line interface for managing Databricks resources.

Question 26

What type of data can be stored in Delta Lake?

Answer 26

Structured, semi-structured, and unstructured data.

Question 27

True or False: Databricks can automatically optimize data layouts for better query performance.

Answer 27

True

Question 28

What is the role of 'data lineage' in Databricks?

Answer 28

To track the origin and transformations of data throughout its lifecycle.

Question 29

Fill in the blank: The __________ feature in Databricks helps to visualize and monitor the execution of Spark jobs.

Answer 29

Spark UI

Question 30

What is the benefit of using 'notebooks' in Databricks?

Answer 30

To create interactive documents that combine code, visualizations, and text.

Question 31

What is 'data partitioning' in Databricks?

Answer 31

The process of dividing a dataset into smaller, manageable pieces for parallel processing.

Question 32

True or False: Databricks supports the use of containerized applications via Docker.

Answer 32

True

Question 33

What is the significance of 'auto-termination' in Databricks clusters?

Answer 33

To automatically shut down idle clusters to save costs.

Question 34

How does Databricks handle data versioning?

Answer 34

Through Delta Lake's built-in version control capabilities.

Question 35

Fill in the blank: __________ is a method used to increase the performance of data reads in Databricks.

Answer 35

Data caching

Question 36

What is the purpose of using 'broadcast joins' in Databricks?

Answer 36

To optimize join operations by sending a small dataset to all worker nodes.

Question 37

What is the advantage of using 'Delta tables'?

Answer 37

They provide ACID transactions, scalable metadata handling, and unifies streaming and batch data processing.

Question 38

True or False: Databricks can scale both horizontally and vertically.

Answer 38

True

Question 39

What is the function of 'checkpointing' in Spark Streaming?

Answer 39

To save the state of a streaming application to recover from failures.

Question 40

What does 'data skew' refer to in distributed processing?

Answer 40

Uneven distribution of data across partitions, leading to performance bottlenecks.

Question 41

Fill in the blank: In Databricks, __________ can be used to configure resource allocation for jobs.

Answer 41

Cluster settings

Question 42

What is the purpose of 'data caching' in Databricks?

Answer 42

To store intermediate results in memory for faster access during subsequent queries.

Question 43

True or False: Databricks allows users to run Python, R, SQL, and Scala code.

Answer 43

True

Question 44

What is a 'DataFrame' in Apache Spark?

Answer 44

A distributed collection of data organized into named columns.

Question 45

How does Databricks support collaborative work?

Answer 45

Through shared notebooks and version control features.

Question 46

Fill in the blank: __________ is a key advantage of using Databricks over traditional data processing systems.

Answer 46

Collaboration

Question 47

What is the role of 'spark.sql.autoBroadcastJoinThreshold'?

Answer 47

To specify the maximum size for a table to be broadcasted during a join.

Question 48

What does 'dynamic allocation' in Spark clusters allow?

Answer 48

It allows Spark to add or remove executors dynamically based on workload.

Question 49

True or False: Databricks can be integrated with popular data storage solutions like AWS S3 and Azure Blob Storage.

Answer 49

True

Question 50

What is 'streaming ingestion' in Databricks?

Answer 50

The process of continuously importing data from streaming sources for real-time processing.

Question 51

Fill in the blank: The __________ function in Databricks enables users to create temporary views of DataFrames for SQL queries.

Answer 51

createOrReplaceTempView

Question 52

What is the function of the 'Databricks Runtime'?

Answer 52

To provide a set of optimized configurations and libraries for running Spark applications.

Question 53

What is the purpose of the 'query execution plan' in Spark?

Answer 53

To provide insights into how a query will be executed, including optimization strategies.

Question 54

True or False: Databricks supports real-time analytics through structured streaming.

Answer 54

True

Question 55

Fill in the blank: In Databricks, __________ is used to run SQL commands on data stored in Delta Lake.

Answer 55

Spark SQL

Question 56

What is the purpose of 'data profiling' in Databricks?

Answer 56

To analyze and summarize the characteristics of datasets.

Question 57

What does 'fault tolerance' mean in the context of Databricks?

Answer 57

The ability to recover from failures without losing data or computation.

Question 58

Fill in the blank: __________ allows for parallel processing of large datasets in Databricks.

Answer 58

Distributed computing

Question 59

What is 'windowing' in Spark SQL?

Answer 59

A technique for performing calculations across a set of rows related to the current row.

Question 60

True or False: Databricks notebooks support markdown for documentation.

Answer 60

True

Question 61

What is the significance of 'data governance' in Databricks?

Answer 61

To ensure data integrity, security, and compliance across data workflows.

Question 62

Fill in the blank: __________ is used to automate and schedule jobs in Databricks.

Answer 62

Job Scheduler

Question 63

What is the advantage of using 'managed tables' in Databricks?

Answer 63

Databricks manages the metadata and storage automatically.

Question 64

What does 'resource pooling' refer to in Databricks?

Answer 64

The sharing of resources across multiple clusters to optimize usage.

Question 65

True or False: Databricks allows for the integration of third-party tools for enhanced analytics.

Answer 65

True

Question 66

What is the purpose of using 'notebook workflows' in Databricks?

Answer 66

To orchestrate and manage complex data processing tasks across multiple notebooks.