Fill in the blank: A retort also known as a _______ is the unit designed for the cremation process. 

B. Verbos: A rotina da Ana. Unlike you, Ana is not on vacation in Brasília. She is spending her break in Columbus. She wants to share her routine with you, though. She sent you some pictures of her daily activities. What does she mean? First, look at the pictures that Ana sent you. Then, select the appropriate verb from the options. Lastly, conjugate the verb in the present tense according to the subject. (6 pts. each: 1/2 pt. for correct verb, 1/2 pt. for correct conjugation; 6 pts. total)   1. Ana [1] (acordar/dormir/sair) todas as manhãs, às 7:00  2. Ana e suas amigas [2] (conversar/sentar/esperar) o ônibus. 3. Ana [3] (trabalhar/estudar/organizar) no escritório da universidade todas as manhãs. 4. Ana e eu [4] (fotografar/telefonar/conversar) por telefone todos os dias.  5. Ana [5] (ir/vir/visitar) ao supermercado comprar comida. 6. Ana e sua namorada [6] (sair para/fazer/comer) o jantar todas as noites.

B. Verbos: A rotina da Ana. Unlike you, Ana is not on vacation in Brasília. She is spending her break in Columbus. She wants to share her routine with you, though. She sent you some pictures of her daily activities. What does she mean? First, look at the pictures that Ana sent you. Then, select the appropriate verb from the options. Lastly, conjugate the verb in the present tense according to the subject. (6 pts. each: 1/2 pt. for correct verb, 1/2 pt. for correct conjugation; 6 pts. total)   1. Ana [1] (acordar/dormir/sair) todas as manhãs, às 7:00  2. Ana e suas amigas [2] (conversar/sentar/esperar) o ônibus. 3. Ana [3] (trabalhar/estudar/organizar) no escritório da universidade todas as manhãs. 4. Ana e eu [4] (fotografar/telefonar/conversar) por telefone todos os dias.  5. Ana [5] (ir/vir/visitar) ao supermercado comprar comida. 6. Ana e sua namorada [6] (sair para/fazer/comer) o jantar todas as noites.

The following figure in chapter 40 is on-disk layout of of 64 4-KB disk blocks in a very simple file system (vsfs). S in the diagram denotes disk block for superblocki in the diagram denotes the disk block for the inode bitmap d in the diagram denotes the disk block for the user data bitmap Select one statement *INCORRECTLY (falsely)* describe the above on-disk layout in vsfs.  

After you completed your exam, scan your solution pages into a single PDF, name it Midterm1_Student Name (example: Midterm1_JohnSmith).  Before uploading, verify your file has all the pages you need to submit. Upload it by clicking on “Choose a File” button in “Question 1” below. You are only allowed to upload one file to a question. Then click “Submit Quiz”. You may get a warning saying that you have some unanswered questions if you do not use optional file upload sections, click OK to submit anyway. View quiz document here. Use double-sided arrow icon on the tool bar below to preview it in full screen mode. You can also download it by clicking on the downwards arrow to the right of the exam file and open it on your computer. Math4261_Fall_2024_Final exam.pdf

Consider the ERD below with tables C and D, each of which has a primary key column named “ID”. How should the relationship between C and D be expressed?  

After you completed your exam, scan your solution pages into a single PDF, name it Midterm1_Student Name (example: Midterm1_JohnSmith).  Before uploading, verify your file has all the pages you need to submit. Upload it by clicking on “Choose a File” button in “Question 1” below. You are only allowed to upload one file to a question. Then click “Submit Quiz”. You may get a warning saying that you have some unanswered questions if you do not use optional file upload sections, click OK to submit anyway. View quiz document here. Use double-sided arrow icon on the tool bar below to preview it in full screen mode. You can also download it by clicking on the downwards arrow to the right of the exam file and open it on your computer. Math4261_Fall_2024_Final exam.pdf

Internet_Scale_Computing_2c Map Reduce   The context for this question is the same as the previous question. 2. Consider the following implementation of a MapReduce Application. It operates on a cluster of server nodes with the following execution model: Each worker thread executes its assigned map tasks sequentially (one map task at a time) Intermediate data from each map task is stored on the worker’s local disk Data transfer occurs for reducers to collect the intermediate data from the mapper tasks  No network cost for accessing data on the same server node Network transfer cost applies only between different server nodes All inter-server-node data transfers can occur in parallel A reduce task begins processing only after receiving all its required intermediate data. Each worker thread executes its assigned reduce tasks sequentially (one reduce task at a time) Specifications of the MapReduce Application to be run: Input data: 100GB split into 100 shards of 1GB each Number of map tasks: 100 (one per shard) Number of reduce tasks: 10 (the desired number of outputs from the Map-Reduce Application) Each map task produces 100MB of intermediate data Each reduce task gets equal of amount of intermediate data from each of the map tasks to process for generating the final output Simplifying assumptions: Ignore local disk I/O time All network paths between server nodes have same bandwidth. Parallel network transfers don’t affect each other (no bandwidth contention). All data transfers occur ONLY after ALL the map tasks have completed execution Perfect load balancing (work distributed evenly to all reduce tasks) All server nodes in a given configuration have identical performance Compare two different cluster configurations: Configuration A (High-Performance Server Nodes): 5 server nodes Processing speed: 1 minute per GB (for either map or reduce task) Network transfer speed: 2GB per minute between server nodes Configuration B (Commodity Nodes): 10 server nodes Processing speed: 1.5 minutes per GB (for either map or reduce task) Network transfer speed: 1GB per minute between server nodes   (c) [1 point] Which configuration is faster in this example – configuration A (smaller number of high-performance nodes) or configuration B (larger number of commodity nodes)? 

Internet_Scale_Computing_1a Giant-Scale Services   1. You are building a planetary store, where:  The key is a unique sensor ID for each sensor deployed across the world. The value is information collected by the sensor such as environmental conditions (temperature, humidity, pollution levels), industrial data (machine status, output), and more. Your design aims to provide high availability and fast access time to process real-time queries to the sensor data store.   You have 5 data centers, each with an identical replica of the store.  Each data center has 100,000 servers.  The store is partitioned into 10,000 equal shards and stored on 10,000 servers .  Each shard is replicated in 10 servers.  You intend to provide “full harvest” for each query and fully exploit the available parallelism for processing each query.  A server assigned to a query is dedicated to that query for the duration of the query processing.   (a) [3 points] Assuming no failures, how many simultaneous queries can you process in each data center? Justify your answer. 

Internet_Scale_Computing_1c Giant-Scale Services   The context for this question is the same as the previous question. 1. You are building a planetary  store, where:  The key is a unique sensor ID for each sensor deployed across the world. The value is information collected by the sensor such as environmental conditions (temperature, humidity, pollution levels), industrial data (machine status, output), and more. Your design aims to provide high availability and fast access time to process real-time queries to the sensor data store.   You have 5 data centers, each with an identical replica of the store.  Each data center has 100,000 servers.  The store is partitioned into 10,000 equal shards and stored on 10,000 servers .  Each shard is replicated in 10 servers.  You intend to provide “full harvest” for each query and fully exploit the available parallelism for processing each query.  A server assigned to a query is dedicated to that query for the duration of the query processing.   (c) [2 points] Assume that you perform rolling upgrade whenever there is a hardware upgrade. The rolling upgrade takes down 10% of the servers at a time in each phase. What will be the yield during every upgrade phase? Explain.