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NEW QUESTION: 1
A client application creates an HDFS file named foo.txt with a replication factor of 3. Identify which best describes the file access rules in HDFS if the file has a single block that is stored on data nodes A, B and C?
A. The file can be accessed if at least one of the data nodes storing the file is available.
B. Each data node stores a copy of the file in the local file system with the same name as the HDFS file.
C. Each data node locks the local file to prohibit concurrent readers and writers of the file.
D. The file will be marked as corrupted if data node B fails during the creation of the file.
Answer: A
Explanation:
HDFS keeps three copies of a block on three different datanodes to protect against true data corruption. HDFS also tries to distribute these three replicas on more than one rack to protect against data availability issues. The fact that HDFS actively monitors any failed datanode(s) and upon failure detection immediately schedules re-replication of blocks (if needed) implies that three copies of data on three different nodes is sufficient to avoid corrupted files. Note: HDFS is designed to reliably store very large files across machines in a large cluster. It stores each file as a sequence of blocks; all blocks in a file except the last block are the same size. The blocks of a file are replicated for fault tolerance. The block size and replication factor are configurable per file. An application can specify the number of replicas of a file. The replication factor can be specified at file creation time and can be changed later. Files in HDFS are write-once and have strictly one writer at any time. The NameNode makes all decisions regarding replication of blocks. HDFS uses rack-aware replica placement policy. In default configuration there are total 3 copies of a datablock on HDFS, 2 copies are stored on datanodes on same rack and 3rd copy on a different rack.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers , How the HDFS Blocks are replicated?

NEW QUESTION: 2
Drag and Drop Question
Drag and drop the MAC address types from the left onto the correct descriptions on the right?

Answer:
Explanation:

NEW QUESTION: 3
DRAG DROP
You are analyzing the performance of a database environment.
You suspect there are several missing indexes in the current database.
You need to return a prioritized list of the missing indexes on the current database.
How should you complete the Transact-SQL statement? To answer, drag the appropriate Transact-SQL segments to the correct locations. Each Transact-SQL segment may be used once, more than once or not at all. You may need to drag the split bar between panes or scroll to view content.

Answer:
Explanation:

Box 1: sys.db_db_missing_index_group_stats
The sys.db_db_missing_index_group_stats table include the required columns for the main query:
avg_total_user_cost, avg_user_impact, user_seeks, and user scans.
Box 2: group_handle
Example: The following query determines which missing indexes comprise a particular missing index group, and displays their column details. For the sake of this example, the missing index group handle is
24.
SELECT migs.group_handle, mid.*
FROM sys.dm_db_missing_index_group_stats AS migs
INNER JOIN sys.dm_db_missing_index_groups AS mig
ON (migs.group_handle = mig.index_group_handle)
INNER JOIN sys.dm_db_missing_index_details AS mid
ON (mig.index_handle = mid.index_handle)
WHERE migs.group_handle = 24;
Box 3: sys.db_db_missing_index_group_stats
The sys.db_db_missing_index_group_stats table include the required columns for the subquery:
avg_total_user_cost and avg_user_impact.
Example: Find the 10 missing indexes with the highest anticipated improvement for user queries The following query determines which 10 missing indexes would produce the highest anticipated cumulative improvement, in descending order, for user queries.
SELECT TOP 10 *
FROM sys.dm_db_missing_index_group_stats
ORDER BY avg_total_user_cost * avg_user_impact * (user_seeks + user_scans)DESC;