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iLAB OVERVIEW Scenario and Summary EXPLAIN shows information about the database: the number of tables; how tables are joined; how data is looked up (full table scan, full index scan or partial index scan); the presence of subqueries, sorts, and unions; DISTINCT and WHERE clauses are used; indexes used and their length (longer index – longer search); number of records examinedDeliverables Grading of the lab assignment will be based on the following. Assignment Step Description Points Step 1 EXPLAIN #1 – describe Output of EXPLAIN6Step 2 EXPLAIN #2  to have type as partial index scan6Step 3 EXPLAIN #3 to have type as index_merge6Step 4 EXPLAIN #4 to have type = fulltext6Step 5 EXPLAIN #5  to have type as const6Step 6 EXPLAIN #6 Sample subquery example 6Step 7 EXPLAIN #7 – describe Output of EXPLAIN with join6Step 8 EXPLAIN #8 – EXPLAIN EXTENDED6Step 9Explain warnings using SHOW WARNINGS6Step 10Explain UPDATE statement6Total iLab Points60 PointsSubmit your lab session–showing any queries, and other SQL code, and the resulting return from the database–to the Dropbox for the Week 5 iLab.  iLAB STEPS 1)      STEP 1: EXPLAIN Output – test EXPLAIN #1Mysql> EXPLAIN select column from database.tablename where column = valueGG – capital letter G  places the result set verticallyExplain the meaning and values of result columns (id, table, type, possible_keys, key, key_len, ref, rows, Extra) Save the screenshot.2)      STEP 2: Modify EXPLAIN in step #1  – test EXPLAIN #2  to have type as partial index scan by including one of the following:<, <=, >, >=, IS NULL, BETWEEN, INExplain output of EXPLAIN. Save the screenshot.3)      STEP 3: Modify EXPLAIN in step #1 – test EXPLAIN #3 to have type as index_merge by including LIKE statementExplain

output of EXPLAIN. Save the screenshot.4)      STEP 4: Modify EXPLAIN #1  – test  EXPLAIN #4 to have type = fulltext data accessTo write SELECT which causes fulltext data access –select job_category and job_title of the job with  title or description which include the word ‘programmer’.Example:EXPLAIN select job_category, job_title from bonus where MATCH (job_title, job_description) AGAINST (‘programmer’)G Explain output of EXPLAIN. Save the screenshot.5)      STEP 5:  Modify EXPLAIN #1 – test EXPLAIN #5  to have type as const by joining/looking up unique index values (index fields compared with =)Example:EXPLAIN select hire_date from employee where employee_id = 1234;Explain output of EXPLAIN. Save the screenshot.6)      STEP 6: Sample subquery example – test EXPLAIN #6Write EXPLAIN select statement using subquery. Example:EXPLAIN select employee_id, employee_name IN (select job_category from bonus AS bonus_subquery where bon_comm IS NULL) from employee AS outerGExplain output of EXPLAIN. Save the screenshot.7)      STEP 7: Turn subquery in #6 to join – test EXPLAIN #7. Explain output of EXPLAIN. Save the screenshot.8)      STEP 8: To know the approximate number of examined rows to be returned,  modify EXPLAIN #1 to EXPLAIN EXTENDED – test EXPLAIN #8Mysql> EXPLAIN  EXTENDED select column from database.tablename where column = valueGExplain output of EXPLAIN EXTENDED (values of rows and filtered columns)9)      STEP  9: Explain warnings received in step #8 by using command:Mysql>SHOW WARNINGSG10)  STEP 10: Explain UPDATE statement – test EXPLAIN #9Example:Explain update table_name set column_name = valueGExplain update mis561.employee set table1col = ‘val’G Explain output of EXPLAIN. Save the screenshot.