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Create Index Based on Query Plan

You use Query Store to optimize a query in a database. The query has two execution plans: ✑ Plan 2 is shown in the Plan 2 Execution Plan exhibit.

✑ Plan 10 is shown in the Plan 10 Execution Plan exhibit.

You create an index at 22:24 based on the missing index suggestion in Plan 2. The average duration statistics for the query is shown in the Tracked Queries exhibit.

You need to analyze the operators in the two execution plans.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

 

Answer Given:

 

Discussion:

Zikato

I see no clustered index scan there. Also the hash match operator didn't process morerows. By making the index seek more effective the percentage moved to other operator - number of rows is the same.

Bartek

Yes, in addition I think query throughpull II increase in plan 10. Just we can see it on Query Store diagram

Kuratko

NO (same or less -> smaller data & less data pages in NCI);

YES (Icons says "we are scans"; labels says: "we are seeks" -> seeks are *mostly* effec.)

YES ("same data" in shortest duration)


aboutME

I am John Fan Zhang, a data analyst and finance researcher. I hold a PhD in finance, CFA charter and full membership of CFA New Zealand Society. I have fifteen-year experience in corporate investment and eight-year experience in advanced data analysis. My research focuses on the effect of social psychology (culture) on financial decisions. Finance research involves heaps of data analyses that lead me to the data field. I am a Microsoft Certified Solutions Expert (MCSE): Data Management and Analytics (Excel, Power BI, and SQL). Aside from Excel, Power BI and SQL, I am also familiar with econometric tools such as Stata, Eviews, and MATLAB. I use OX and Python for programming. I am an active data community event participant, volunteer, speaker, moderator, program reviewer, including PASS Marathon 2020, Global AI BootCamp Auckland 2019, SQL Saturday Auckland (2017, 2018, 2019), and Definity Conference (2018, 2019, 2020, Auckland, New Zealand).

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