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NEW QUESTION: 1
Given:
And given the code fragment:
What is the result?
A. Read E-Book
B. Read Book
C. Compilation fails at line n2.
D. Compilation fails at line n3.
E. Compilation fails at line n1.
Answer: D
NEW QUESTION: 2
You have not run apt-get on a system for some time, but it has been run on the system before. What apt-get command would you run to download the latest list of packages, but not the packages themselves?
A. apt-get upgrade
B. apt-getupdate
C. apt-get dist-upgrade
D. apt-get mirror-select
E. apt-get build-dep
Answer: B
NEW QUESTION: 3
When using AJAX, what is the purpose of the XMLHttpRequest object?
A. To request either XML data or plaintext data from the Web server
B. To read and write to an XML file stored on the local machine
C. To request data from the Web server strictly in XML format
D. To transfer an XML document to the Web server
Answer: A
NEW QUESTION: 4
A company named Fabrikam, Inc. has a Microsoft Azure web app. Billions of users visit the app daily.
The web app logs all user activity by using text files in Azure Blob storage. Each day, approximately 200 GB of text files are created.
Fabrikam uses the log files from an Apache Hadoop cluster on Azure DHlnsight.
You need to recommend a solution to optimize the storage of the log files for later Hive use.
What is the best property to recommend adding to the Hive table definition to achieve the goal? More than one answer choice may achieve the goal. Select the BEST answer.
A. STORED AS TEXTFILE
B. STORED AS RCFILE
C. STORED AS GZIP
D. STORED AS ORC
Answer: D
Explanation:
Explanation
The Optimized Row Columnar (ORC) file format provides a highly efficient way to store Hive data. It was designed to overcome limitations of the other Hive file formats. Using ORC files improves performance when Hive is reading, writing, and processing data.
Compared with RCFile format, for example, ORC file format has many advantages such as:
a single file as the output of each task, which reduces the NameNode's load Hive type support including datetime, decimal, and the complex types (struct, list, map, and union) light-weight indexes stored within the file skip row groups that don't pass predicate filtering seek to a given row block-mode compression based on data type run-length encoding for integer columns dictionary encoding for string columns concurrent reads of the same file using separate RecordReaders ability to split files without scanning for markers bound the amount of memory needed for reading or writing metadata stored using Protocol Buffers, which allows addition and removal of fields
