Examine this table that contains over two million rows of data:

CREATE TABLE news_feed' ( .id'bigint (20) NOT NULL AUTO _INCREMENT, .news _sources_id'varchar (11) NOT NULL, .dataline' datetime NOT NULL, .headline' varchar (256) NOT NULL, .story' text NOT NULL,.tag varchar (32768) DEFAULT NULL, PRIMARY KEY (id') KEY dateline' ( dateline') ) Examine this query that returns 332 rows of date:

SELECT * FROM news_feed WHERE DATE(dateline)= `2013-01-01' Which change would show the greatest improvement in the response time of the query?

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Examine this table that contains over two million rows of data:

CREATE TABLE news_feed' ( .id'bigint (20) NOT NULL AUTO _INCREMENT, .news _sources_id'varchar (11) NOT NULL, .dataline' datetime NOT NULL, .headline' varchar (256) NOT NULL, .story' text NOT NULL,.tag varchar (32768) DEFAULT NULL, PRIMARY KEY (id') KEY dateline' ( dateline') ) Examine this query that returns 332 rows of date:

SELECT * FROM news_feed WHERE DATE(dateline)= `2013-01-01' Which change would show the greatest improvement in the response time of the query?

Accepted Answer

D. Use a date range comparison:

Answer

A. Use the LIKE operator:

Answer

B. USE the DATEDIFF function:

Answer

C. Use numeric equivalents for comparing the two dates:

Examine this table that contains over two million rows of data: CREATE TABLE news_feed' ( .id'bigint (20) NOT NULL AUTO _INCREMENT, .news _sources_id'varchar (11) NOT NULL, .dataline' datetime NOT…

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