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NEW QUESTION: 1
You need to analyze 60,000,000 images stored in JPEG format, each of which is approximately 25 KB. Because you Hadoop cluster isn't optimized for storing and processing many small files, you decide to do the following actions:
1.Group the individual images into a set of larger files
2.Use the set of larger files as input for a MapReduce job that processes them directly with python using Hadoop streaming.
Which data serialization system gives the flexibility to do this?
A. SequenceFiles
B. JSON
C. HTML
D. CSV
E. Avro
F. XML
Answer: A
Explanation:
Sequence files are block-compressed and provide direct serialization and deserialization of several arbitrary data types (not just text). Sequence files can be generated as the output of other MapReduce tasks and are an efficient intermediate representation for data that is passing from one MapReduce job to anther.
NEW QUESTION: 2
展示を表示し、ORDERSおよびORDER_ITEMSテーブルの構造を調べます。
ORDER_ID、ORDER_DATE、および各注文のアイテムの総数を表示するビューを作成する必要があります。
どのCREATE VIEWステートメントがビューを正常に作成しますか？
A. CREATE OR REPLACE VIEW ord_vuAS SELECT o.order_id、o.order_date、COUNT（i.line_item_id） "NO OF ITEMS" FROM orders o JOIN order_items iON（o.order_id = i.order_id）GROUP BY o.order_id、 o.order_date;
B. CREATE OR REPLACE VIEW ord_vuAS SELECT o.order_id、o.order_date、COUNT（i.line_item_id）FROM orders o JOIN order_items iON（o.order_id = i.order_id）GROUP BY o.order_id、o.order_date;
C. CREATE OR REPLACE VIEW ord_vuAS SELECT o.order_id、o.order_date、COUNT（i.line_item_id）|| 'NO OF ITEMS'FROM orders o JOIN order_items iON（o.order_id = i.order_id）GROUP BY o。 order_id、o.order_dateWHITH CHECK OPTION;
D. CREATE OR REPLACE VIEW ord_vu（order_id、order_date）AS SELECT o.order_id、o.order_date、COUNT（i.line_item_id） "NO OF ITEMS" FROM orders o JOIN order_items iON（o.order_id = i.order_id） GROUP BY o.order_id、o.order_date;
Answer: A
NEW QUESTION: 3
You are developing a SQL Server Integration Services (SSIS) package to implement an incremental data load strategy.
The package reads data from a source system. Depending on the value in a source column, the package redirects rows
to one of five different data flow paths.
You need to add a data flow transformation to support the package redirection.
Which data flow transformation should you use?
A. Conditional Split
B. Multicast
C. Pivot
D. Lookup
Answer: A
