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NEW QUESTION: 1
Which version of Java will you use to develop a Java EE application on SAP Cloud Platform Cloud Foundry?
A. 0
B. 1
C. 2
D. 3
E. 4
Answer: A
Explanation:
Explanation/Reference:
See page 64 S4C80 Col17.

NEW QUESTION: 2
Automatic Undo Management is enabled for your database. You want a user to retrieve metadata and historical data for a given transaction or for transactions in a given time interval.
Which three are prerequisites to fulfill this requirement?
A. Minimal supplemental logging must be enabled.
B. The select any transaction privilege must be granted to the user.
C. The flashback any table privilegemust be granted to the user.
D. The recycle bin parameter must be set to on.
E. Flashback Data Archive must be created and the flashback archive administer system privilege must be granted to the user.
F. The database must be running in archivelog mode.
Answer: B,C,E

NEW QUESTION: 3
You have user profile records in your OLPT database, that you want to join with web logs you have already ingested into the Hadoop file system. How will you obtain these user records?
A. Ingest with Flume agents
B. Hive LOAD DATA command
C. Ingest with Hadoop Streaming
D. Sqoop import
E. HDFS command
F. Pig LOAD command
Answer: F
Explanation:
Apache Hadoop and Pig provide excellent tools for extracting and analyzing data
from very large Web logs.
We use Pig scripts for sifting through the data and to extract useful information from the Web logs.
We load the log file into Pig using the LOAD command.
raw_logs = LOAD 'apacheLog.log' USING TextLoader AS (line:chararray);
Note 1:
Data Flow and Components
*Content will be created by multiple Web servers and logged in local hard discs. This content will then be pushed to HDFS using FLUME framework. FLUME has agents running on Web servers; these are machines that collect data intermediately using collectors and finally push that data to HDFS.
*Pig Scripts are scheduled to run using a job scheduler (could be cron or any sophisticated batch job solution). These scripts actually analyze the logs on various dimensions and extract the results. Results from Pig are by default inserted into HDFS, but we can use storage
implementation for other repositories also such as HBase, MongoDB, etc. We have also tried the solution with HBase (please see the implementation section). Pig Scripts can either push this data to HDFS and then MR jobs will be required to read and push this data into HBase, or Pig scripts can push this data into HBase directly. In this article, we use scripts to push data onto HDFS, as we are showcasing the Pig framework applicability for log analysis at large scale.
*The database HBase will have the data processed by Pig scripts ready for reporting and further slicing and dicing.
*The data-access Web service is a REST-based service that eases the access and integrations with data clients. The client can be in any language to access REST-based API. These clients could be BI- or UI-based clients.
Note 2:
The Log Analysis Software Stack
*Hadoop is an open source framework that allows users to process very large data in parallel. It's based on the framework that supports Google search engine. The Hadoop core is mainly divided into two modules:
1.HDFS is the Hadoop Distributed File System. It allows you to store large amounts of data using multiple commodity servers connected in a cluster.
2.Map-Reduce (MR) is a framework for parallel processing of large data sets. The default implementation is bonded with HDFS.
*The database can be a NoSQL database such as HBase. The advantage of a NoSQL database is that it provides scalability for the reporting module as well, as we can keep historical processed data for reporting purposes. HBase is an open source columnar DB or NoSQL DB, which uses HDFS. It can also use MR jobs to process data. It gives real-time, random read/write access to very large data sets -- HBase can save very large tables having million of rows. It's a distributed database and can also keep multiple versions of a single row.
*The Pig framework is an open source platform for analyzing large data sets and is implemented as a layered language over the Hadoop Map-Reduce framework. It is built to ease the work of developers who write code in the Map-Reduce format, since code in Map-Reduce format needs to be written in Java. In contrast, Pig enables users to write code in a scripting language.
*Flume is a distributed, reliable and available service for collecting, aggregating and moving a large amount of log data (src flume-wiki). It was built to push large logs into Hadoop-HDFS for further processing. It's a data flow solution, where there is an originator and destination for each node and is divided into Agent and Collector tiers for collecting logs and pushing them to destination storage.
Reference: Hadoop and Pig for Large-Scale Web Log Analysis

NEW QUESTION: 4
You have an Exchange Server 2013 organization that has a hybrid deployment with Microsoft Office 365.
The hybrid deployment use Active Directory Federation Services (AD FS) 3.0.
You need to ensure that only Exchange ActiveSync devices are allowed to access Office 365 services from outside of the organization.
Which two actions should you perform? Each correct answer presents part of the solution.
A. Update the Office 365 Identify Platform relying party trust.
B. Add an Active Directory Identify Platform relying party trust.
C. Update the Office mobile device policy.
D. Add claims rules to the Active Directory claims provider trust.
E. Create a Mobile Device Mailbox Policy.
Answer: A,D
Explanation:
Explanation/Reference:
Explanation:
C: Step 1: Add claim rules to the Active Directory Claims Provider trust Block all external access to Office
365 except Exchange ActiveSync
The following example allows access to all Office 365 applications, including Exchange Online, from internal clients including Outlook. It blocks access from clients residing outside the corporate network, as indicated by the client IP address, except for Exchange ActiveSync clients such as smart phones. The rule set builds on the default Issuance Authorization rule titled Permit Access to All Users. Use the following steps to add an Issuance Authorization rule to the Office 365 relying party trust using the Claim Rule Wizard: (steps omitted).
B: Step 2: Update the Microsoft Office 365 Identity Platform relying party trust Reference: Limiting Access to Office 365 Services Based on the Location of the Client
https://technet.microsoft.com/en-us/library/hh526961(v=ws.10).aspx

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