Hive Mock Test

This section presents you various set of Mock Tests related to Hive. You can download these sample mock tests at your local machine and solve offline at your convenience. Every mock test is supplied with a mock test key to let you verify the final score and grade yourself.

Hive Mock Test III

Q 1 - In case of one large table and 2 small tables, for an optimized query performance

A - The largest one should be cached to memory and small ones should be streamed

B - The small Ones should be cached and large one should be streamed

C - All of the table should be cached

D - All the tables should be streamed.

Answer : B

Explanation

When the small one is cached, each row from the larger table can be efficiently compared with each row of the small table.

Q 2 - The DISTRIBUTED BY clause in hive

A - comes Before the sort by clause

B - comes after the sort by clause

C - does not depend on position of sort by clause

D - cannot be present along with the sort by clause

Answer : A

Explanation

Sorting as the last clause will be efficient as that is also the last step in the reduce job producing the output.

Q 3 - The DISTRIBUTED by clause is used to ensure that

B - similar values go to same mapper

Answer : A

Explanation

The DISTRIBUTED BY clause send a range of values to the same reducer.

Q 4 - A view in Hive can be seen by using

Answer : A

Explanation

There is no separate clause for viewing views. It is shown using show tables.

Q 5 - A View in Hive can be dropped by using

Answer : B

Explanation

DROP view drops the view.

Q 6 - The name of a view in Hive

A - can be same as the name of another table in the same database

B - cannot be same as the name of another table in the same database

C - cannot contain a number

D - cannot be more than 10 character long

Answer : B

Explanation

Views and tables are treated similarly in the hive metadata

Q 7 - The query

Create table TABLE_NAME LIKE VIEW_NAME

A - creates a table which is copy of the view

B - is invalid

C - runs only if the view has data

D - runs only if the view is in same directory as the table

Answer : A

Explanation

A table can be created form a view

Q 8 - what can be altered about a view

A - its name

B - its location

C - its TBLPROPERTIES

D - The query it is based on

Answer : C

Explanation

TBLPROPERTIES stores some documentation about the table like created date time etc.

Q 9 - Which kind of keys(CONSTRAINTS) Hive can have?

Answer : D

Explanation

Hive is schema on read and unlike RDBMS it does not have a way to enforce the existence of keys.

Q 10 - The Index in Hive can be seen by

Answer : B

Explanation

Similar to show tables, Indexes can be queried by SHOW Index.

Q 11 - If an Index is dropped then

A - The underlying table is also dropped

B - The underlying table is not dropped

C - the directory containing the index is deleted

D - Error is thrown by hive

Answer : D

Explanation

AN index can be dropped only after dropping the table on which index is created.

Q 12 - Indexes can be created

A - only on managed tables

B - only on views

C - Only on external tables

D - only on views with partitions

Answer : A

Explanation

As external table data is managed by other applications hive does not create index on them.

Q 13 - The clause " WITH DEFERRED REBUILD" while creating an index

A - creates index on a table which is yet to be created

B - creates index on a table which has no data

C - creates index only on a table which has data

D - creates an index which is empty

Answer : D

Explanation

It is about creating index on an empty table.

Q 14 - If the data on the table on which an index is defined changes then,

A - The Index becomes invalid

B - The index rebuilds automatically

C - The Index has to be rebuilt manually

D - The index must be dropped

Answer : C

Explanation

Hive does not manage the Index like RDBMS. SO it has to be built manually.

Q 15 - The identifiers in HiveQL are

A - case sensitive

B - case insensitive

C - sometimes case sensitive

D - Depends on the Hadoop environment

Answer : A

Explanation

Hive is case insensitive

Q 16 - What is the disadvantage of using too many partitions in Hive tables?

A - It slows down the namenode

B - Storage space is wasted

C - Join quires become slow

D - All of these

Answer : D

Explanation

Too many partitions create too many files and too much metadata to be stored by namenode.

Q 17 - When importing data to using SerDe, if a row is found to have more columns than expected then

A - The extra columns are replaced with NULL

B - The row is skipped

C - The import halts with error

D - The Columns are ignored.

Answer : D

Explanation

Hive is schema on Read and It does not throw error for mismatch between schema and actual data.

Q 18 - Consider the below two sets of queries.

Query A:
hive> INSERT OVERWRITE TABLE sales
	SELECT * FROM history WHERE action = 'purchased';
hive> INSERT OVERWRITE TABLE credits
	 SELECT * FROM history WHERE action = 'returned';

and 
Query B:

hive> FROM history
 INSERT OVERWRITE sales SELECT * WHERE action = 'purchased'
 INSERT OVERWRITE credits SELECT * WHERE action = 'returned'

Which of them will make a single pass through?