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NEW QUESTION: 1
Can you use MapReduce to perform a relational join on two large tables sharing a key? Assume that the two tables are formatted as comma-separated file in HDFS.
A. Yes, so long as both tables fit into memory.
B. Yes.
C. No, MapReduce cannot perform relational operations.
D. Yes, but only if one of the tables fits into memory.
E. No, but it can be done with either Pig or Hive.
Answer: B
Explanation:
Note:
*Join Algorithms in MapReduce A) Reduce-side join B) Map-side join C) In-memory join / Striped Striped variant variant
/ Memcached variant
*Which join to use? / In-memory join > map-side join > reduce-side join / Limitations of each? In-memory join: memory Map-side join: sort order and partitioning Reduce-side join: general purpose
NEW QUESTION: 2
スイッチでイネーブルにするには、どのSPAN設定が必要ですか?
A. NA
B. 送信元および宛先ポートを設定する
C. SPANトラフィックにモニタVLANが作成されます。
D. トランクリンク上のVTPプルーニングをディセーブルにする
Answer: B
NEW QUESTION: 3
Your Amazon RDS MySQL DB instance runs on the largest available instance type. The DB instance runs at near capacity for CPU and network bandwidth. You expect traffic to increase and are looking for ways you can continue to scale your database. Which strategies allow you to continue to scale and take on more traffic?
A. Create additional database accounts in the DB instance; configure the app servers to make calls using different account credentials
B. Create a read replica of the master database in another Availability Zone; configure the app to send read-only calls to the replica.
C. Create an Amazon Elasticache cluster; configure the app to retrieve frequently accessed data and queries from the cache.
D. Create a cross-region read replica of the master database; configure the app to send read-only calls to the replica
E. Convert the DB instance to a m=Multi-AZ deployment; configure the app to send read- only calls to the standby
Answer: B,C