Test Bank Solution Manual for Databricks- Already Passed

Test Bank Solution Manual for Databricks- Already Passed What is a clusters in Databricks? - Answers is a collection of Databricks computation resources What are the three key spark interfaces that you should know? - Answers Resilient Distributed Dataset (RDD), DataFrame, and Dataset What is Resilient Distributed Dataset (RDD)? - Answers It is an interface to a sequence of data objects that consist of one or more types that are located across a collection of machines (a cluster). RDDs can be created in a variety of ways and are the "lowest level" API available. While this is the original data structure for Apache Spark, you should focus on the DataFrame API, which is a superset of the RDD functionality. The RDD API is available in - Answers the Java, Python, and Scala languages.? DataFrame - Answers These are similar in concept to the DataFrame you may be familiar with in the pandas Python library and the R language. The DataFrame API is available in the Java, Python, R, and Scala languages. Dataset - Answers A combination of DataFrame and RDD. It provides the typed interface that is available in RDDs while providing the convenience of the DataFrame. The Dataset API is available in the Java and Scala languages. The RDD is - Answers the underlying infrastructure that allows Spark to run so fast and provide data lineage. If you are diving into more advanced components of Spark, - Answers it may be necessary to use RDDs. The visualizations within the Spark UI reference - Answers RDDs. When you develop Spark applications, you typically use ________and ________. - Answers DataFrames and Datasets To write your first Apache Spark job, you add code to the cells of a __________. This example uses ________. - Answers Databricks notebook, Python. This first command lists the contents of a folder in the Databricks File System: - Answers display(("/databricks-datasets/samples/docs/")) The next command uses spark, the ___________available in every notebook, to read the ____________text file and create a __________named ____________: - Answers SparkSession, README.md, DataFrame, textFile The next command uses spark, the SparkSession available in every notebook, to read the README.md text file and create a DataFrame named textFile: - Answers textFile = ("/databricks-datasets/samples/docs/README.md") To count the lines of the text file, apply the count action to the DataFrame: - Answers textF() One thing you may notice is that the second command, reading the text file, does not generate any output while the third command, performing the count, does. The reason for this is that the first command is a __________while the second one is an _________. - Answers transformation, action ________are lazy and run only when an __________is run. This allows __________to optimize for performance (for example, run a filter prior to a join), instead of running commands serially. - Answers Transformations, action, Spark before Spark 2.0, the main programming interface of Spark - Answers was the Resilient Distributed Dataset (RDD) After Spark 2.0, RDDs are replaced by ____________, which is strongly-typed like an RDD, but with richer optimizations under the hood. - Answers Dataset we highly recommend you to switch to use ____________, which has better performance than RDD. - Answers Dataset Spark's shell provides a simple way to learn - Answers the API Start sparks by running - Answers ./bin/spark-shell Spark's primary abstraction is - Answers a distributed collection of items called a Dataset. Datasets can be created from - Answers Hadoop InputFormats (such as HDFS files) or by transforming other Datasets. make a new Dataset from the text of the README file in the Spark source directory:scala - Answers val textFile = File("README.md") textFile: .Dataset[String] = [value: string] What is Application Deployment? - Answers The application deployment is where a set of code (web, services, database etc...) is being installed onto a configured system(s) by some type of process. The process can be manual or automated. Automated deployment is preferred for a continues delivery model. Where does the Application Deployment fit into a continues delivery and improvement flow? - Answers It falls within the release management practices. When code is ready to be deployed to a configured environment, then the testing of that deployment process begins. The release notes for the application deployment begin at this point and matures as the release code is tested, adjusted, and prepared for a production release. What is an Environment Deployment? - Answers An environment deployment (build-out) is where a server or a set of servers (environment sets) has the features, roles, applications and configuration installed manually or automated. Most of the time the operation teams are responsible for this build-out activity. Where does the Environment Deployment fit into a continues delivery and improvement flow? - Answers Environment and configuration changes start at deployment and move through the release cycle in the same way as the application deployment. In the reverse direction, operation, configuration management teams, or individuals can create a build-out script and workflow that creates a production like environment with the correct setting, features, and version of applications. How do you create a Notebook? - Answers Sign into Databricks, select the Home icon from the sidebar, right-click your home-folder, select Create, and then Notebook. In the Create Notebook dialog, specify the name of your notebook and the default programming language. How do you create a cluster? - Answers Select the Clusters icon on the sidebar, click the Create Cluster button, specify the specific settings for your cluster and then click Create Cluster. How do you attach a notebook to a cluster? - Answers If you run a command while detached, you may be prompted to connect to a cluster. To connect to a specific cluster, open the cluster menu by clicking the Attached/Detached menu item and then selecting your desired cluster. Spark offers - Answers a compute engine and connectors to virtually any data source. By