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NEW QUESTION: 1
Why should you run "clusterXL_admin down -p" command?
A. With the -p option, monitoring of critical devices will continue
B. This option is required with clusterXL_admin command
C. You want to keep the peers in sync during the failover testing
D. This option allows automatic failover if the active member experiences a problem
Answer: B
NEW QUESTION: 2
Case Study: 6 - TerramEarth
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About
80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second.
Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced.
The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second with 22 hours of operation per day, TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a single U.S. west coast based data center. These systems gzip CSV files from the field and upload via FTP, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
Decrease unplanned vehicle downtime to less than 1 week.
* Support the dealer network with more data on how their customers use their equipment to better
* position new products and services
Have the ability to partner with different companies - especially with seed and fertilizer suppliers
* in the fast-growing agricultural business - to create compelling joint offerings for their customers.
Technical Requirements
Expand beyond a single datacenter to decrease latency to the American Midwest and east
* coast.
Create a backup strategy.
* Increase security of data transfer from equipment to the datacenter.
* Improve data in the data warehouse.
* Use customer and equipment data to anticipate customer needs.
* Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
Windows Server 2008 R2
* - 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair. Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
Off the shelf application. License tied to number of physical CPUs
* - Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
A single PostgreSQL server
* - RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in the manufacturing process, with our ability to build better vehicles for lower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?
A. Replace the existing data warehouse with BigQuery. Use federated data sources.
B. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.
C. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.
D. Replace the existing data warehouse with BigQuery. Use table partitioning.
Answer: D
Explanation:
1. BigQuery does not guarantee data consistency for external data sources. Changes to the underlying data while a query is running can result in unexpected behavior.
2. Query performance for external data sources may not be as high as querying data in a native BigQuery table.
NEW QUESTION: 3
Which information/report is part of the Service Level Agreement report?
A. Percent Downtime
B. Transfer Speed
C. Consistency Groups
D. Chargeback
Answer: A
NEW QUESTION: 4
データベースの最新の自動ワークロード・リポジトリ（AWR）レポートでは、バッファビジー待機の数が多いであることに気づきます。データベースはフリーリストで管理セグメントを持つローカル管理表領域で構成されています。
更なる調査では、ビジー待機をバッファリングすることで、データ・ブロックの競合によって引き起こされることがわかります。
どのオプションはすぐに待機イベントを減少させるために最初に検討する必要がありますか。
A. PCTUSEDを下げます。
B. V$DB_CACHE_ADVICEの勧告に基づいてdb_buffer_cacheを増やします。
C. 自動セグメント領域管理（ASSM）を使用します。
D. PCTFREEを下げます。
E. DBWNプロセスの数を増加させます。
Answer: C
Explanation:
Explanation
* Automatic segment space management (ASSM) is a simpler and more efficient way of managing space within a segment. It completely eliminates any need to specify and tune the pctused,freelists, and freelist groups storage parameters for schema objects created in the tablespace. If any of these attributes are specified, they are ignored.
* Oracle introduced Automatic Segment Storage Management (ASSM) as a replacement for traditional freelists management which used one-way linked-lists to manage free blocks with tables and indexes. ASSM is commonly called "bitmap freelists" because that is how Oracle implement the internal data structures for free block management.
Note:
* Buffer busy waits are most commonly associated with segment header contention onside the data buffer pool (db_cache_size, etc.).
* The most common remedies for high buffer busy waits include database writer (DBWR) contention tuning, adding freelists (or ASSM), and adding missing indexes.