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ADBMS Project Pearl

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Divya Tadi

The document describes a movie database project created by Team Pearl. The database allows users to search information about movies, directors, genres and theaters. It includes data on movie showtimes, theater locations and contact information. The database was designed with functional areas for movies, theaters, awards and ratings. Entities and attributes were defined in the logical design. The physical database design was then implemented using SQL statements to create the database structure based on the logical model.

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                              Team  Pearl   Arun Kumar Dash Divya Rajasri Tadi Rajeev Reddy Rachamalla Ramya Kirshna Reddy Vuyyuru Sophia Benjelloun Movies,  directors,  genres           The  movie  database  allows  users  to  search   information  regarding  movies  such  as  the  directors,   casts,  fan  ratings,  fans,  genres,  awards,  theaters,   MPAA  ratings,  shows,  price,  and  user  reviews.  In   addition,  the  database  provides  the  user  with   theater  information  including  the  number  of  screens   each  theater  occupies  per  location  and  providing   contact  information  of  the  theaters.  Management  at   local  theaters  will  be  able  to  track  a  movie  at  their   theater  based  on  the  price  of  the  ticket  by  time  of   day  the  movie  is  screened  and  its  type  of  viewers.                       Introduction Fall  2014   Dr.  McCart                          +  My  Favorites   Suggestions for You    
  2   TABLE OF CONTENTS Introduction:................................................................................................1 Requirements: .............................................................................................3 Assumptions: ...............................................................................................3 Restrictions:.................................................................................................4 Logical Design:.............................................................................................4 Logical Database Design................................................................6 Physical Design: ..........................................................................................6 Physical Database Design: ............................................................7 Data Generation and Loading:.................................................................21 Performance Tuning:................................................................................24 SQL Tuning:...................................................................................24 Querying:.......................................................................................27 Parallelizing Index:......................................................................30 Function Based Indexing: ...........................................................32 DBA Scripts:...............................................................................................34 Database Security: ....................................................................................41 Authentication:.............................................................................42 Users Privileges....................................................................43 Auditing:........................................................................................45 Data Backup and Recovery:.....................................................................46 Weightage Table: .......................................................................................47
  3   Requirements:     The  movie  database  should  include  the  name  and  location  of  multiple   movie  theaters.  The  data  will  be  focused  on  the  type  of  movie  and  type  of   theater  it  is  screened  at  along  with  the  time  of  day,  cost  per  ticket,  and  type  of   patron  in  particular  to  a  specific  movie,  whether  current  or  historical  records.   Even  additional  add-­‐ons  will  be  stored,  as  in  times;  the  cost  of  ticket  can  be   larger  than  an  original  movie  ticket.  Users  will  be  allowed  to  search  for  a   theater  screening  the  same  movie  and  providing  the  user  with  the  date  and   time  per  movie  and  theater  on  multiple  screens.  Additionally,  a  user  is  able  to   provide  a  theater  rating  more  than  once  with  the  option  to  write  a  description.   Assumptions:           • The  Theatre  review  is  about  the  theatre  and  not  about  the  screen.  (So,  if   a  user/reviewer  wants  to  review  a  particular  screen  of  a  specific   theatre,  there  is  no  mechanism  to  support  this).   • Ratings  are  given  in  the  range  from  (1to  5).  Five  means  excellent  and  1   means  poor.   • Each  theater  will  have  many  reviews.  It  is  One  to  Many  relation  between   theaters  and  reviews.     • Fans  or  anonymous  users  will  write  the  theater  ratings.  We  stored  all   anonymous  users  with  a  single  ID.   • In  each  theater  there  can  be  multiple  screens.  One  movie  can  be  shown   in  multiple  screens.  Many  to  Many  relations  between  movie  and   Theaters  (Screens).  
  4   • We  created  a  dummy  user  in  the  “fan”  table  to  incorporate  anonymous   users  within  the  database.      Restrictions:         • Users  cannot  give  review  about  individual  screens  in  a  Theater.   • There  is  no  provision  to  distinguish  between  anonymous  users.   Logical  Design:     The  database  is  divided  into  functional  areas.  These  functional  areas  include   Movies,  Theaters,  Awards  and  Ratings.  These  areas  are  discussed  further  in   the  database  decomposition  section.                                                                                                                                                                           Logical  Database  Design:     We  built  the  logical  model  after  the  requirements  were  clearly   identified.  The  logical  model  includes  the  specified  entities  and  the  relation   between  them.  We  detailed  the  attributes  in  each  and  every  entity/table.  The   logical  data  model  fully  explains  the  attributes  of  the  data  and  fulfills  the  data   Movies   Theaters   Ratings   Awards  
  5   requirements  from  a  business  point  of  view.  Data  attributes  define  the  data   types  and  lengths.  Some  data  types  include  the  null  ability  options.   We  created  our  logical  data  model  based  on  the  Movies  database   schema  using  oracle  data  modeler.   The  steps  involved  in  the  Oracle  Data  Modeler  for  Logical  Database  design  are:     File  -­‐>  Data  Modeler  -­‐>  Import  -­‐>  Data  Dictionary.   A  screen  shot  of  this  design  is  provided  below.                                                  
  6       Physical  Database  Design:   In  a  sense,  logical  design  is  what  you  draw  with  a  pencil  before  building   your  warehouse  and  physical  design  is  when  you  create  the  database  with   SQL  statements.  
  7   During  the  physical  design  process,  we  converted  the  data  gathered   during  the  logical  design  phase  into  a  description  of  the  physical  database,   including  tables  and  constraints.  Physical  design  decisions,  such  as  the  type  of   index  or  partitioning  have  a  large  impact  on  query  performance.   In  the  physical  database  design,  objects  such  as  tables  and  columns  are   created  based  on  the  entities  and  attributes  that  were  defined  during  logical   design  of  the  database  system.    Other  important  things  like  primary  keys,   foreign  keys,  other  unique  keys  and  indexes  are  also  defined.    All  these  parts   are  integrated  to  complete  the  Physical  design  of  the  database.     Tables:              
  8   AWARDS     CREATE  TABLE  "ADB_PEARL"."AWARDS"          (   "AWARD_ID"  NUMBER(10,0),       "AWARD_NAME"  VARCHAR2(30  BYTE),       "AWARD_YEAR"  NUMBER(5,0),       "AWARD_CATEGORY"  VARCHAR2(30  BYTE),       "FILM_ID"  NUMBER(10,0),       "AWARDEE_NAME"  VARCHAR2(50  BYTE),        PRIMARY  KEY  ("AWARD_ID")   )   CASTS     CREATE  TABLE  "ADB_PEARL"."CASTS"          (   "FILM_ID"  NUMBER(10,0),       "CAST_MEMBER"  VARCHAR2(50  BYTE),       "CAST_ROLE"  VARCHAR2(100  BYTE),        PRIMARY  KEY  ("FILM_ID",  "CAST_MEMBER",  "CAST_ROLE"),  
  9   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )     DIRECTORS        CREATE  TABLE  "ADB_PEARL"."DIRECTORS"          (   "FILM_ID"  NUMBER(10,0),       "DIRECTOR"  VARCHAR2(50  BYTE),        PRIMARY  KEY  ("FILM_ID",  "DIRECTOR"),                                  FOREIGN  KEY  ("FAN_ID")        REFERENCES  "ADB_PEARL"."FANS"  ("FAN_ID")  ENABLE,        FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )     FAN_RATINGS     CREATE  TABLE  "ADB_PEARL"."FAN_RATINGS"          (   "FAN_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,    
  10     "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "IMDB_RATING"  NUMBER(10,1)  NOT  NULL  ENABLE,       "LAST_RATED"  DATE,       "FIRST_RATED"  DATE,        PRIMARY  KEY  ("FILM_ID",  "FAN_ID"),   FOREIGN  KEY  ("FAN_ID")        REFERENCES  "ADB_PEARL"."FANS"  ("FAN_ID")  ENABLE,        FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )   FANS     CREATE  TABLE  "ADB_PEARL"."FANS"          (   "FNAME"  VARCHAR2(50  BYTE),       "LNAME"  VARCHAR2(50  BYTE),       "GENDER"  VARCHAR2(10  BYTE),       "STREET"  VARCHAR2(100  BYTE),       "CITY"  VARCHAR2(50  BYTE),    
  11     "STATE"  VARCHAR2(20  BYTE),       "ZIP"  VARCHAR2(20  BYTE),       "BIRTH_DAY"  NUMBER,       "BIRTH_MONTH"  NUMBER,       "BIRTH_YEAR"  NUMBER,       "FAN_ID"  NUMBER(10,0),        PRIMARY  KEY  ("FAN_ID")   )   GENRES     CREATE  TABLE  "ADB_PEARL"."GENRES"          (   "FILM_ID"  NUMBER(10,0),       "GENRE"  VARCHAR2(20  BYTE),        PRIMARY  KEY  ("FILM_ID",  "GENRE"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )   KEYWORDS     CREATE  TABLE  "ADB_PEARL"."KEYWORDS"          (   "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "KEYWORD"  VARCHAR2(50  BYTE)  NOT  NULL  ENABLE,    
  12      PRIMARY  KEY  ("FILM_ID",  "KEYWORD"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )   LOCALES     CREATE  TABLE  "ADB_PEARL"."LOCALES"          (   "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "CITY"  VARCHAR2(50  BYTE),       "STATE"  VARCHAR2(50  BYTE),       "COUNTRY"  VARCHAR2(50  BYTE)  NOT  NULL  ENABLE,       "NOTE"  VARCHAR2(200  BYTE),        PRIMARY  KEY  ("FILM_ID",  "CITY",  "COUNTRY"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )              
  13         MOVIES     CREATE  TABLE  "ADB_PEARL"."MOVIES"          (   "IMDB_RANK"  NUMBER(10,0),       "IMDB_RATING"  NUMBER(10,1),       "FILM_TITLE"  VARCHAR2(100  BYTE)  NOT  NULL  ENABLE,       "IMDB_VOTES"  NUMBER(10,0),       "FILM_YEAR"  NUMBER(4,0),       "RUNTIME"  NUMBER(10,0),       "BUDGET"  NUMBER(12,0),       "WORLDWIDE_GROSS"  NUMBER(12,0),       "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "USA_GROSS"  NUMBER(12,0),    
  14     "AFI_RANK"  NUMBER(10,0),       "MPAA_RATING"  VARCHAR2(10  BYTE),       "RELEASE_DATE"  DATE,       "GROSS_DATE"  DATE,        PRIMARY  KEY  ("FILM_ID"),   FOREIGN  KEY  ("MPAA_RATING")        REFERENCES  "ADB_PEARL"."MPAA_RATINGS"  ("MPAA_RATING")   ENABLE        )   MPAA_RATINGS     CREATE  TABLE  "ADB_PEARL"."MPAA_RATINGS"          (   "MPAA_RATING"  VARCHAR2(10  BYTE)  NOT  NULL  ENABLE,       "RATING_DESCRIPTION"  VARCHAR2(100  BYTE),        PRIMARY  KEY  ("MPAA_RATING")   )   PATRON_TYPE     CREATE  TABLE  "ADB_PEARL"."PATRON_TYPE"          (   "TYPE_ID"  NUMBER(5,0),       "PATRON"  VARCHAR2(25  BYTE),    
  15     "MOVIE_TYPE"  VARCHAR2(25  BYTE),       "MOVIE_TIME"  VARCHAR2(25  BYTE),        PRIMARY  KEY  ("TYPE_ID")   )   PRICE     CREATE  TABLE  "ADB_PEARL"."PRICE"          (   "PRICE_DATE"  DATE  NOT  NULL  ENABLE,       "TYPE_ID"  NUMBER(10,0),       "FARE"  NUMBER(5,0),       "PRICE_ID"  NUMBER(10,0),        PRIMARY  KEY  ("PRICE_ID"),   CONSTRAINT  "PRICE_FK"  FOREIGN  KEY  ("TYPE_ID")        REFERENCES  "ADB_PEARL"."PATRON_TYPE"  ("TYPE_ID")  ENABLE        )   PRODUCERS     CREATE  TABLE  "ADB_PEARL"."PRODUCERS"          (   "FILM_ID"  NUMBER(10,0),       "PRODUCER"  VARCHAR2(50  BYTE),        PRIMARY  KEY  ("FILM_ID"),  
  16   CONSTRAINT  "PR_CONST"  FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )     SHOWS       CREATE  TABLE  "ADB_PEARL"."SHOWS"          (   "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "THEATRE_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "SCREEN_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "MOVIE_TIME"  TIMESTAMP  (6),       "SHOWS_DATE"  DATE  NOT  NULL  ENABLE,       "TICKETS_SOLD"  NUMBER(10,0),       "TYPE_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,        CONSTRAINT  "SHOWS_CONST"  PRIMARY  KEY  ("FILM_ID",   "THEATRE_ID",  "SCREEN_ID",  "MOVIE_TIME",  "SHOWS_DATE",  "TYPE_ID"),   CONSTRAINT  "SHOWS_FK"  FOREIGN  KEY  ("TYPE_ID")        REFERENCES  "ADB_PEARL"."PATRON_TYPE"  ("TYPE_ID")  ENABLE,        CONSTRAINT  "SHOWS_FK1"  FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE  
  17        )   TAGLINES     CREATE  TABLE  "ADB_PEARL"."TAGLINES"          (   "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "TAGLINE"  VARCHAR2(300  BYTE)  NOT  NULL  ENABLE,        PRIMARY  KEY  ("FILM_ID",  "TAGLINE"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )   TECHNICIANS     CREATE  TABLE  "ADB_PEARL"."TECHNICIANS"          (   "FILM_ID"  NUMBER(10,0),       "TECHNICIAN"  VARCHAR2(50  BYTE),        PRIMARY  KEY  ("FILM_ID"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )        
  18             THEATRE_INFO     CREATE  TABLE  "ADB_PEARL"."THEATRE_INFO"          (   "THEATRE_ID"  NUMBER(10,0),       "THEATRE_NAME"  VARCHAR2(50  BYTE)  NOT  NULL  ENABLE,       "THEATRE_TYPE"  VARCHAR2(30  BYTE),       "PHONE"  VARCHAR2(20  BYTE),       "EMAIL"  VARCHAR2(50  BYTE)  NOT  NULL  ENABLE,       "NUMBER_OF_SCREENS"  NUMBER(3,0)  NOT  NULL  ENABLE,       "STREET"  VARCHAR2(100  BYTE),       "CITY"  VARCHAR2(35  BYTE),       "STATE"  VARCHAR2(35  BYTE),       "ZIP"  VARCHAR2(15  BYTE),    
  19     "COUNTRY"  VARCHAR2(30  BYTE),        PRIMARY  KEY  ("THEATRE_ID")   )         THEATRE_MOVIE_INFO     CREATE  TABLE  "ADB_PEARL"."THEATRE_MOVIE_INFO"          (   "SCREEN_ID"  NUMBER(10,0),       "THEATRE_ID"  NUMBER(10,0),       "FILM_ID"  NUMBER(10,0),       "PRICE_ID"  NUMBER(10,0),       "MOVIE_TYPE"  VARCHAR2(20  BYTE),       "MOVIE_CLASS"  VARCHAR2(20  BYTE),       "CAPACITY"  NUMBER(4,0),        CONSTRAINT  "THEATRE_MOVIE_INFO_CONST1"  PRIMARY  KEY   ("SCREEN_ID",  "THEATRE_ID",  "FILM_ID",  "PRICE_ID"),   CONSTRAINT  "THEATRE_MOVIE_INFO_CONST2"  FOREIGN  KEY   ("THEATRE_ID")        REFERENCES  "ADB_PEARL"."THEATRE_INFO"  ("THEATRE_ID")   ENABLE,    
  20      CONSTRAINT  "THEATRE_MOVIE_INFO_CONST3"  FOREIGN  KEY   ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE,        CONSTRAINT  "THEATRE_MOVIE_INFO_CONST4"  FOREIGN  KEY   ("PRICE_ID")        REFERENCES  "ADB_PEARL"."PRICE"  ("PRICE_ID")  ENABLE        )   USER_REVIEWS     CREATE  TABLE  "ADB_PEARL"."USER_REVIEWS"          (   "REVIEW_ID"  NUMBER(10,0),       "THEATRE_ID"  NUMBER(10,0),       "FAN_ID"  NUMBER(10,0),       "RATING"  NUMBER(2,0),       "DESCRIPTION"  VARCHAR2(150  BYTE),       "REVIEW_DATE"  DATE,        CONSTRAINT  "USER_REVIEW_CONST1"  PRIMARY  KEY  ("REVIEW_ID",   "THEATRE_ID",  "FAN_ID"),   CONSTRAINT  "USER_REVIEW_CONST2"  FOREIGN  KEY  ("THEATRE_ID")        REFERENCES  "ADB_PEARL"."THEATRE_INFO"  ("THEATRE_ID")   ENABLE,        CONSTRAINT  "USER_REVIEW_CONST3"  FOREIGN  KEY  ("FAN_ID")  
  21        REFERENCES  "ADB_PEARL"."FANS"  ("FAN_ID")  ENABLE        )           Data  Generation  and  Loading:     For  this  section,  we  have  generated  appropriate  data  for  the  schema  of  the   database.  Apart  from  the  tables  already  existent  in  the  Movies  database,  we   have  created  6  additional  tables:   AWARDS   TECHNICIANS   THEATRE_INFO   THEATRE_MOVIE_INFO   USER_REVIEWS   PATRON_TYPE   Of  these  tables,  we  have  generated  data  for  the  AWARDS  and  the   TECHNICIANS  tables.  We  used  multiple  techniques  to  generate  the  data.  For   the  AWARDS  table,  we  gathered  data  from  Wikipedia.  We  assembled  the  data   into  an  Excel  table  and  then  loaded  the  data  using  the  import  feature  of   SQLDeveloper  into  our  AWARDS  table.   There  are  three  steps  in  the  import  process:  
  22   1.  Choose  the  import  method   2.  Select  the  columns   3.  Select  the  definitions  of  the  columns       For  propagating  data  into  the  TECHNICIANS  table,  we  first  gathered   some  data  about  the  technicians  from  Wikipedia.  Then,  we  assembled  the  data   into  an  Excel  table  and  then  imported  the  data  into  TECHNICIANS  table.      
  23         The  same  procedure  was  repeated  for  the  PRODUCERS  table.  We  began   assembling  the  data  about  the  respective  producers  from  Wikipedia,  then   assembled  them  into  an  Excel  table  and  finally  imported  that  into  our   PRODUCERS  table.      
  24       Performance  Tuning:     SQL  Tuning     Different  SQL  statements  are  used  to  retrieve  data  from  the  Movies   database.  We  can  get  the  same  results  by  writing  different  queries  but  using   the  best  query  is  always  important  to  improve  the  performance.  Therefore,  we   need  to  SQL  query  tuning  based  on  the  requirements.  The  list  of  queries  below   shows  how  queries  can  be  optimized  for  better  performance.     1. SQL  query  becomes  faster  if  you  use  the  actual  columns  in  SELECT   statement  instead  of  “  *  “.    
  25   SELECT  FILM_TITLE,  FILM_ID  FROM  MOVIES   INSTEAD  OF   SELECT  *  FROM  MOVIES   2.  Sometimes  you  may  have  more  than  one  sub  queries  in  your  main  query.   Try  to  minimize  the  number  of  sub  query  blocks  in  your  query.   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  WHERE  (IMDB_VOTES,   USA_GROSS)  =  (SELECT  MAX  (IMDB_VOTES),  MAX  (USA_GROSS)  FROM   MOVIES)   INSTEAD  OF   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  WHERE  IMDB_VOTES=  (SELECT   MAX  (IMDB_VOTES)  FROM  MOVIES)  AND  USA_GROSS  =  (SELECT  MAX   (USA_GROSS)  FROM  MOVIES)   3.  Use  operator  EXISTS,  IN  and  table  joins  appropriately  in  your  query.       a)  Usually,  IN  has  the  slowest  performance.       b)  IN  is  efficient  when  most  of  the  filter  criteria  is  in  the  sub-­‐query.     c)  EXISTS  is  efficient  when  most  of  the  filter  criteria  is  in  the  main  query.      Example:  Write  the  Query  as  follows:   SELECT  FILM_ID  FROM  SHOWS  S  WHERE  EXISTS  (SELECT  *  FROM   THEATRE_INFO  T  WHERE  S.THEATRE_ID=T.THEATRE_ID)   INSTEAD  OF   SELECT  FILM_ID  FROM  SHOWS  WHERE  THEATRE_ID  IN  (SELECT   THEATRE_ID  FROM  THEATRE_INFO)  
  26       4.  Use  UNION  ALL  in  place  of  UNION      Example:  Write  the  Query  as  follows:   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  UNION  ALL  SELECT  AWARD_ID,   AWARD_NAME  FROM  AWARDS   INSTEAD  OF   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  UNION  SELECT  AWARD_ID,   AWARD_NAME  FROM  AWARDS   5.  Use  where  clause  appropriately       Example:  Write  the  Query  as  follows:   SELECT  *  FROM  MOVIES  WHERE  FILM_YEAR  BETWEEN  2000  AND  2014   INSTEAD  OF   SELECT  *  FROM  MOVIES  WHERE  FILM_YEAR>=2000  AND  FILM_YEAR<=2014   6.  HAVING  clause  is  used  to  filter  the  rows  after  all  the  rows  are  selected.  It  is   like  a  filter.  Do  not  use  the  HAVING  clause  for  any  other  purposes.   SELECT  MPAA_RATING,  COUNT  (M.FILM_TITLE)  AS  MOVIES  FROM  MOVIES  M   GROUP  BY  MPAA_RATING  HAVING  COUNT  (M.FILM_TITLE)>1   INSTEAD  OF   SELECT  MPAA_RATING,  COUNT  (M.FILM_TITLE)  AS  MOVIES  FROM  MOVIES   M  GROUP  BY  MPAA_RATING  HAVING  MPAA_RATING='R'        
  27   7.  Use  EXISTS  instead  of  DISTINCT  when  using  joins,  which  involves  tables   having  one-­‐to-­‐many  relationship.       Example:  Write  the  Query  as  follows:   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  M  WHERE  EXISTS  (SELECT   CAST_MEMBER  FROM  CASTS  C  WHERE  M.FILM_ID=C.FILM_ID)   INSTEAD  OF   SELECT  DISTINCT  C.CAST_MEMBER,  M.FILM_ID  FROM  MOVIES  M,  CASTS  C   WHERE  M.FILM_ID=C.FILM_ID   Querying   Interesting  queries  for  MOVIES  database:   1. Display  the  name  of  all  movies  that  have  an  IMDB  rating  of  at  least  8.0,   with  more  than  100,000  IMDB  votes,  and  were  released  from  2007  to   2013.    Show  the  movies  with  the  highest  IMDB  ratings  first.         SELECT  M.FILM_TITLE  AS  MOVIES  FROM  RELMDB.MOVIES  M  WHERE   M.IMDB_VOTES  >100000  AND  M.IMDB_RATING  >=8.0  AND   M.FILM_YEAR>=2007  AND  M.FILM_YEAR<=2013  ORDER  BY   M.IMDB_RATING  DESC;  
  28       2. Display  each  movie’s  title  and  total  gross,  where  total  gross  is  the  USA   gross  and  worldwide  gross  combined.  Exclude  any  movies  that  do  not   have  values  for  either  USA  gross  or  worldwide  gross.  Show  the  highest   grossing  movies  first.   SELECT  M.FILM_TITLE  AS  TITLE,  (M.USA_GROSS  +   M.WORLDWIDE_GROSS)  AS  TOTAL_GROSS  FROM  RELMDB.MOVIES  M   WHERE  M.USA_GROSS  IS  NOT  NULL  AND  M.WORLDWIDE_GROSS  IS   NOT  NULL  ORDER  BY  TOTAL_GROSS  DESC;      
  29   3. Display  how  many  movies  have  an  MPAA  rating  of  G,  PG,  PG-­‐13,  and  R.   Show  the  results  in  alphabetical  order  by  MPAA  rating.   SELECT  MPAA_RATING,  COUNT  (M.FILM_TITLE)  AS  MOVIES   FROMRELMDB.MOVIES  M  WHERE     MPAA_RATING  IN  ('G','PG','PG-­‐13','R')  GROUP  BY  MPAA_RATING   ORDER  BY  MPAA_RATING;     4. Display  the  titles  of  all  movies  where  Tom  Hanks  or  Tim  Allen  were  cast   members.  Each  movie  title  should  be  shown  only  once.   SELECT  DISTINCT  M.FILM_TITLE  AS  TITLE  FROM  RELMDB.MOVIES  M   INNER  JOIN  RELMDB.CASTS  C  ON     M.FILM_ID  =  C.FILM_ID  WHERE  C.CAST_MEMBER  IN  ('Tom  Hanks','Tim   Allen')       5. 5.  For  each  movie,  display  its  movie  title,  year,  and  how  many  cast   members  were  part  of  the  movie.  Exclude  movies  with  five  or  fewer  cast   members.  Display  movies  with  the  most  cast  members  first,  followed  by   movie  year  and  title.   SELECT  COUNT  (C.CAST_MEMBER)  AS  CASTCOUNT,  M.FILM_TITLE,   M.FILM_YEAR  FROM    
  30   RELMDB.CASTS  C  INNER  JOIN  RELMDB.MOVIES  M  ON  M.FILM_ID=   C.FILM_ID  GROUP  BY     M.FILM_TITLE,  M.FILM_YEAR  HAVING  COUNT  (C.CAST_MEMBER)  >5   ORDER  BY  COUNT     (C.CAST_MEMBER)  DESC,  FILM_YEAR  DESC,  FILM_TITLE  DESC  ;     6. Displays  the  movies  which  contain  the  keyword  “people”  in  tagline.   SELECT  movies.film_title         FROM  movies         INNER  JOIN  taglines  ON  movies.film_id  =  taglines.film_id       WHERE  taglines.tagline  LIKE  '%people%';       Parallelizing  Index     We  can  use  parallelizing  indexes  which  enable  the  database  to  use  multiple   processes  to  create  the  index  which  is  quicker  than  if  a  single  server  process  
  31   created  the  index    sequentially.  We  can  increase  the  degree  of  the  table  to  help   it  to  use  multiple  processes  which  improves  the  performance.     We  first  ran  a  query  which  displays  the  film  name  and  its  Fan  ID  where  the   film_year  is  greater  than  1990.     SELECT  MOVIES.FILM_TITLE,MOVIES.FILM_YEAR,FAN_RATINGS.FAN_ID     from  MOVIES  LEFT  JOIN  FAN_RATINGS  on  FAN_RATINGS.FILM_ID  =   MOVIES.Film_id  where  MOVIES.FILM_YEAR  >  1990       Now,  we  increased  the  degree  of  the  tables  to  allow  parallelism   ALTER  TABLE  MOVIES  PARALLEL(DEGREE  4)   ALTER  TABLE  FAN_RATINGS  PARALLEL(DEGREE  4)         We  can  see  the  reduction  in  the  cost  by  enabling  parallelism.         Conclusion:     We  can  notice  that  query  cost  has  reduced  from  7  to  5.  Hence,  the  use  of   parallelized  view  helped  in  the  improvement  of  performance.    Parallelism  also   helps  in  faster  access  of  data.  
  32     Function  Based  Indexing   The  ability  to  index  functions  and  use  these  indexes  in  a  query  is  called   function-­‐based  index.  This  capacity  allows  you  to  have  case  insensitive   searches  or  sorts,  search  on  complex  equations,  and  extend  the  SQL  Language   efficiently  by  implementing  your  own  functions  and  operators  and  then   searching  on  them.   • It  is  easy  and  provides  immediate  value.   • It  can  be  used  to  speed  up  existing  applications  without  changing  any  of   their  logic  or  queries.   • It  can  be  used  to  supply  additional  functionalities  to  applications  with   very  little  cost.   Query:     SELECT  FILM_TITLE,(WORLDWIDE_GROSS-­‐BUDGET)  AS  Earnings  FROM   MOVIES   WHERE  (WORLDWIDE_GROSS-­‐BUDGET)>1000000     Without  Index:        
  33   Index  Creation:     With  Index:     Here  we  observe  that  indexing  the  functional  attribute  not  only   increases  the  cost  but  also  the  performance.  In  the  query  above,  if  we  had   made  indexes  on  either  WORLDWIDE_GROSS  or  BUDGET,  it  wouldn’t  have   been  used  since  we  are  using  WORLDWIDE_GROSS-­‐BUDGET  as  the  filtering   criteria.    After  creating  indexes  ideally  STATS  should  be  gathered  since  the   spread  of  the  data  in  the  database  changes  the  statistics  of  the  database.  But   currently  we  do  not  have  the  privilege  to  execute  DBMS_STATS  package.  It   requires  DBA  privilege  since  it  will  impact  the  database  performance.      
  34     DBA  Scripts:     The  below  queries  will  display  the  critical  and  general  database  information.   SELECT  *  FROM  V$DATABASE;     SELECT    *  FROM  V$INSTANCE      
  35     SELECT  *  FROM  V$VERSION     ACTIVE  SESSIONS  IN  THE  DATABASE:   The  below  query  lists  out  the  sessions  which  are  presently  active  in  the   database:   SELECT  NVL(V$SESSION.USERNAME,  '(oracle)')  AS  USERNAME,   V$SESSION.OSUSER,  V$SESSION.SID,   V$SESSION.SERIAL#,V$PROCESS.SPID,  V$SESSION.LOCKWAIT,   V$SESSION.STATUS,V$SESSION.MODULE,     V$SESSION.MACHINE,V$SESSION.PROGRAM,   TO_CHAR(V$SESSION.LOGON_TIME,'DD-­‐MON-­‐YYYY  HH24:MI:SS')  AS     LOGON_TIME  FROM  V$SESSION,  V$PROCESS  WHERE  V$SESSION.PADDR  =   V$PROCESS.ADDR  AND    
  36   V$SESSION.STATUS  =  'ACTIVE'     ORDER  BY  V$SESSION.USERNAME,  V$SESSION.OSUSER;.         BLOCKING:   The  below  query  will  provide  the  list  of  user  id’s  who  have  blocked  a  session.   It  takes  into  account  the  V$SESSION  and  V$LOCKS  table.   SELECT  S.SID,  S.USERNAME,  B.BLOCKER,  B.WAITER  FROM  V$SESSION  s,       (SELECT    SID,  DECODE(BLOCK,  0,  'NO',  'YES'  )  BLOCKER,    DECODE(REQUEST,   0,  'NO','YES'  )  WAITER  FROM    V$LOCK       WHERE        REQUEST  >  0  OR  BLOCK  >  0  )    b       WHERE  S.SID  =  B.SID        
  37     There  were  perhaps  no  blocked  users,  therefore  resulting  into  the  above   output.     PROFILES:   The  below  query  lists  out  the  DBA  Profiles:   SELECT  *  FROM  DBA_PROFILES        
  38     USERS:   The  below  query  shows  the  list  of  users  in  the  database:   SELECT  USERNAME,  USER_ID,  ACCOUNT_STATUS,  LOCK_DATE,   EXPIRY_DATE,  DEFAULT_TABLESPACE,  PROFILE     FROM     DBA_USERS                  
  39     ROLES:   The  below  query  list  out  the  roles  in  the  database:   SELECT  *  FROM  DBA_ROLES       DISPLAYING  SYSTEM  PARAMETERS  ALONG  WITH  THEIR  DESCRIPTION     SET  LINESIZE  500       COLUMN  name    FORMAT  A30       COLUMN  value  FORMAT  A60      
  40     SELECT    SP.NAME,    SP.TYPE,    SP.VALUE,    SP.ISSES_MODIFIABLE,     SP.ISSYS_MODIFIABLE,  SP.ISINSTANCE_MODIFIABLE       FROM  V$SYSTEM_PARAMETER  SP     ORDER  BY  SP.NAME;       CACHE  MEMORY  USAGE:   To  improve  performance,  a  DBA  needs  to  constantly  monitor  the  cache   memory  usage.  Below  query  lists  out  the  same:     SELECT  OWNER,  NAMESPACE,  TYPW,  COUNT(*)  OBJECT_COUNT,   SUM(SHARABLE_MEM)  SHARABLE_MEM,     SUM(LOADS)  LOADS,  SUM(EXECUTIONS)  EXECUTIONS,  SUM(LOCKS)  LOCKS,   SUM(PINS)  PINS     FROM  V$DB_OBJECT_CACHE       GROUP  BY  OWNER,  NAMESPACE,  TYPE;    
  41         Database  Security:     Database  security  concerns  the  use  of  a  broad  range  of  information   security  controls  to  protect  databases  (potentially  including  the  data,  the   database  applications  or  stored  functions,  the  database  systems,  the  database   servers  and  the  associated  network  links)  against  compromises  of  their   confidentiality,  integrity  and  availability.  It  involves  various  types  or   categories  of  controls  such  as  technical,  procedural/administrative,  and   physical.     Security  risks  to  database  systems:   • Unauthorized  or  unintended  activity  or  misuse  by  authorized  database   users  
  42   • Data  corruption  and/or  loss  caused  by  the  entry  of  invalid  data  or   commands   • Malware  infections  causing  incidents  such  as  unauthorized  access   • Overloads,  performance  constraints,  and  capacity  issues     • Physical  damage  to  database  servers     • Design  flaws  and  programming  bugs  in  databases   Many  layers  and  types  of  information  security  controls  are  appropriate  to   databases,  including:   • Access  control   • Auditing   • Authentication   • Encryption   • Integrity  controls   • Backups   • Application  security   • Database  Security  applying  Statistical  Method   We  want  to  implement  authentication  and  auditing  of  the  database  in  our   project.   Authentication     A  basic  security  requirement  is  that  your  users  must  know.  You  must   identify  the  users  before  you  can  determine  their  privileges  and  access  rights;   so  that  you  can  audit  their  actions  upon  the  data.  
  43   Users  can  be  authenticated  in  a  number  of  different  ways  before  they   are  allowed  to  create  a  database  session.  In  database  authentication,  you  can   define  users  such  that  the  database  performs  both  identification  and   authentication  of  users.  In  external  authentication,  you  can  define  users  such   that  authentication  is  performed  by  the  operating  system  or  network  service.   Alternatively,  you  can  identify  users  through  authentication  by  the  Secure   Sockets  Layer  (SSL).     For  enterprise  users,  an  enterprise  directory  can  be  used  to  authorize   their  access  to  the  database  through  enterprise  roles.  Finally,  you  can  specify   users  who  are  allowed  to  connect  through  a  middle-­‐tier  server.  The  middle-­‐ tier  server  authenticates  and  assumes  the  identity  of  the  user  and  is  allowed   to  enable  specific  roles  for  the  user.  This  is  called  proxy  authentication.   Different  privileges  are  given  to  different  users;  this  will  result  in  only   select  number  of  people  who  can  change  the  data  in  the  tables.  In  the  movies   database,  we  have  defined  a  set  of  actors  and  assigned  privileges.  The  list  of   some  of  the  users  and  their  privileges  are  listed  in  the  table  below.           Users  Privileges     A  user  privilege  is  a  right  to  execute  a  particular  type  of  SQL  statement   or  a  right  to  access  another  user's  object.  The  types  of  privileges  are  defined   by  DBMS.   Roles,  on  the  other  hand,  are  created  by  users  (usually  administrators)  and   are  used  to  group  together  privileges  or  other  roles.  They  are  a  means  of   facilitating  the  granting  of  multiple  privileges  or  roles  to  users.   User  Roles  
  44   • Database  Administrator     • Database  Programmers     • Moderators   • Users     We  set  authentication  rules  for  each  user.  Users  need  to  create  username  and   password  to  log  into  the  system  to  ensure  that  they  have  privileges.     Some  authentication  features  need  to  be  enabled  in  the  system:   • Password  has  to  be  changed  every  three  months.   • Make  the  password  between  10  and  30  characters  and  using  numbers.   • Use  mixed  case  letters  and  special  characters  in  the  password.     • Use  the  database  character  set  for  the  password's  characters,  which  can   include  the  underscore  (_),  dollar  ($),  and  number  sign  (#)  characters.   • Do  not  use  an  actual  word  for  the  entire  password.   • Entering  a  password  incorrectly  for  more  than  five  tries  will  lock  the   user  account.   • Password  encryption.   The  following  DBA  script  will  display  all  the  roles  and  the  privileges  granted:         SET  SERVEROUTPUT  ON       SET  VERIFY  OFF       SELECT  a.granted_role  "Role",                    a.admin_option  "Adm"       FROM      user_role_privs  a;       SELECT  a.privilege  "Privilege",      
  45                a.admin_option  "Adm"       FROM      user_sys_privs  a;       Auditing     Auditing  is  the  monitoring  and  recording  of  selected  user  database   actions.  It  can  be  based  on  individual  actions,  such  as  the  type  of  SQL   statement  executed  or  on  combinations  of  factors  that  can  include  user  name,   application,  time,  and  so  on.  Security  policies  can  trigger  auditing  when   specified  elements  in  an  Oracle  database  are  accessed  or  altered,  including  the   contents  within  a  specified  object.   Auditing  is  typically  used  to:   • Enable  future  accountability  for  current  actions  taken  in  a  particular   schema,  table,  or  row,  or  affecting  specific  content.   • Deter  users  (or  others)  from  inappropriate  actions  based  on  that   accountability.   • Investigate  suspicious  activity.   • Notify  an  auditor  that  an  unauthorized  user  is  manipulating  or  deleting   data  and  that  the  user  has  more  privileges  than  expected  which  can  lead   to  reassessing  user  authorizations.   • Monitor  and  gather  data  about  specific  database  activities.   • Detect  problems  with  an  authorization  or  access  control   implementation.   Types  of  auditing:   • Statement  auditing  
  46   • Privilege  auditing   • Schema  object  auditing   • Fine-­‐Grade  auditing   Auditing  can  also  be  used  to  monitor  data  about  certain  database  activities.  A   DBA  can  gather  data  about  all  the  logical  I/O’s  being  performed.  This  can  give   the  DBA  a  better  understanding  of  what  is  happening  in  the  system.   Data  backup  and  recovery     Data  backup  is  an  insurance  plan.  Important  files  are  accidentally   deleted  all  the  time.  Mission-­‐critical  data  can  become  corrupt.  Natural   disasters  can  leave  your  office  in  ruin.  With  a  solid  backup  and  recovery  plan,   you  can  recover  from  any  of  these.  Without  one,  you're  left  with  nothing  to  fall   back  on.     A  Recovery  manager  can  be  used  to  backup  data  and  restore  it  in  quick  time.       Recovery  Manager  (RMAN)  is  an  Oracle  utility  that  can  back  up,  restore,   and  recover  database  files.  The  product  is  a  feature  of  the  Oracle  database   server  and  does  not  require  separate  installation.  Recovery  Manager  is  a   client/server  application  that  uses  database  server  sessions  to  perform   backup  and  recovery.  It  stores  metadata  about  its  operations  in  the  control  file   of  the  target  database  and,  optionally,  in  a  recovery  catalog  schema  in  an   Oracle  database.   Below  is  an  example  query  to  back  up  a  database  to  an  image  copy:        
  47   connect  target  /  run  {  shutdown  immediate;  startup  force  DBA;  shutdown   immediate;  startup  mount;  allocate  channel  channel1  type  DISK;    backup  as   copy    format  '/backup/%U'  (database)  CURRENT  CONTROLFILE  SPFILE;         BACKUP  AS  COPY  CURRENT  CONTROLFILE  FORMAT  '/backup/control01.ctl';         release  channel  channel1;         shutdown  immediate;  startup;         SQL  "ALTER  DATABASE  BACKUP  CONTROLFILE  TO  TRACE";  }         Weightage  Table:     Topic  /   Section   Description   Evaluation   Logical   database   design   The  logical  design  section  should  include  entity-­‐ relationship  diagrams  (ERDs)  and  data   dictionaries  for  your  database  design,  as  well  as   any  design  assumptions.  You  might  include  a  few   high-­‐level  diagrams  that  highlight  interesting   sections  of  your  project  (include  textual   descriptions  with  these).  There  should  also  be  a   complete  ERD  for  your  entire  project.  There  is  no   expectation  that  you  implement  all  of  your  design,   just  indicate  the  areas  built.  You  are  expected  to   add  additional  design  work  as  part  of  the  project.   15   Physical   database   design   This  section  should  cover  implementation-­‐level   issues.  For  instance,  you  should  discuss  predicted   usage  and  indexing  strategies  that  support   expected  activities.  In  addition,  you  may  wish  to   discuss  architecture  issues,  including  distributed   database  issues  (even  though  you  may  not   implement  anything  in  these  areas).  Artifacts   could  include  capacity  planning,  storage   subsystems,  and  data  placement  (e.g.,  tablespace   /  file  system  arrangements),  indexing  strategies,   15  
  48   transaction  usage  maps,  etc.   Data   generation   and  loading   Though  some  data  was  provided,  there  may  have   been  interesting  queries,  stored  procedures,   desktop  tools  (e.g.,  MS  Excel)  that  were  used  to   populate  the  database.  You  may  have  used   queries  with  mod  function,  data  arithmetic,   number  sequences,  lookup  tables,  and  even  data   from  the  Web.  Any  /  all  of  these  are  interesting   additions  to  the  project.   15   Performance   tuning   In  this  section,  highlight  any  experiments  run  as   part  of  the  project  related  to  performance  tuning.   Experiments  with  different  indexing  strategies,   optimizer  changes,  transaction  isolation  levels,   function-­‐based  indexes,  and  table  partitioning  can   all  be  interesting.  Remember  to  look  at  different   types  of  queries  (e.g.,  point,  range,  scan),   execution  plans,  and  I/O  burden.   20   Querying   You  may  also  choose  to  focus  on  writing  SQL   queries  (analytic  SQL  extensions  can  also  be   explored).  Include  interesting  queries  that   highlight  the  types  of  questions  that  can  be   answered  by  the  database.  These  queries  may   also  be  used  to  illustrate  performance  tuning.   10   DBA  scripts   Throughout  the  semester,  we  looked  at  example   DBA  scripts  that  query  the  system  catalog  (a  good   way  to  explore  the  database  engine).  Provide  DBA   scripts,  and  an  explanation  of  how  the  scripts  can   be  used,  that  are  helpful  for  reporting  on  database   objects,  indexes,  constraints,  physical  storage,   data  files,  etc.   15   Database   security   Database  security  is  an  important  area  of  interest   that  can  also  be  investigated.  Though  you  are   limited  on  the  implementation  side,  you  can   develop  a  security  policy  and  discuss  how  you   might  implement  various  aspects  using   authentication  strategies,  roles,  profiles,  and  even   auditing  features.   10    

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ADBMS Project Pearl

  • 1.                               Team  Pearl   Arun Kumar Dash Divya Rajasri Tadi Rajeev Reddy Rachamalla Ramya Kirshna Reddy Vuyyuru Sophia Benjelloun Movies,  directors,  genres           The  movie  database  allows  users  to  search   information  regarding  movies  such  as  the  directors,   casts,  fan  ratings,  fans,  genres,  awards,  theaters,   MPAA  ratings,  shows,  price,  and  user  reviews.  In   addition,  the  database  provides  the  user  with   theater  information  including  the  number  of  screens   each  theater  occupies  per  location  and  providing   contact  information  of  the  theaters.  Management  at   local  theaters  will  be  able  to  track  a  movie  at  their   theater  based  on  the  price  of  the  ticket  by  time  of   day  the  movie  is  screened  and  its  type  of  viewers.                       Introduction Fall  2014   Dr.  McCart                          +  My  Favorites   Suggestions for You    
  • 2.   2   TABLE OF CONTENTS Introduction:................................................................................................1 Requirements: .............................................................................................3 Assumptions: ...............................................................................................3 Restrictions:.................................................................................................4 Logical Design:.............................................................................................4 Logical Database Design................................................................6 Physical Design: ..........................................................................................6 Physical Database Design: ............................................................7 Data Generation and Loading:.................................................................21 Performance Tuning:................................................................................24 SQL Tuning:...................................................................................24 Querying:.......................................................................................27 Parallelizing Index:......................................................................30 Function Based Indexing: ...........................................................32 DBA Scripts:...............................................................................................34 Database Security: ....................................................................................41 Authentication:.............................................................................42 Users Privileges....................................................................43 Auditing:........................................................................................45 Data Backup and Recovery:.....................................................................46 Weightage Table: .......................................................................................47
  • 3.   3   Requirements:     The  movie  database  should  include  the  name  and  location  of  multiple   movie  theaters.  The  data  will  be  focused  on  the  type  of  movie  and  type  of   theater  it  is  screened  at  along  with  the  time  of  day,  cost  per  ticket,  and  type  of   patron  in  particular  to  a  specific  movie,  whether  current  or  historical  records.   Even  additional  add-­‐ons  will  be  stored,  as  in  times;  the  cost  of  ticket  can  be   larger  than  an  original  movie  ticket.  Users  will  be  allowed  to  search  for  a   theater  screening  the  same  movie  and  providing  the  user  with  the  date  and   time  per  movie  and  theater  on  multiple  screens.  Additionally,  a  user  is  able  to   provide  a  theater  rating  more  than  once  with  the  option  to  write  a  description.   Assumptions:           • The  Theatre  review  is  about  the  theatre  and  not  about  the  screen.  (So,  if   a  user/reviewer  wants  to  review  a  particular  screen  of  a  specific   theatre,  there  is  no  mechanism  to  support  this).   • Ratings  are  given  in  the  range  from  (1to  5).  Five  means  excellent  and  1   means  poor.   • Each  theater  will  have  many  reviews.  It  is  One  to  Many  relation  between   theaters  and  reviews.     • Fans  or  anonymous  users  will  write  the  theater  ratings.  We  stored  all   anonymous  users  with  a  single  ID.   • In  each  theater  there  can  be  multiple  screens.  One  movie  can  be  shown   in  multiple  screens.  Many  to  Many  relations  between  movie  and   Theaters  (Screens).  
  • 4.   4   • We  created  a  dummy  user  in  the  “fan”  table  to  incorporate  anonymous   users  within  the  database.      Restrictions:         • Users  cannot  give  review  about  individual  screens  in  a  Theater.   • There  is  no  provision  to  distinguish  between  anonymous  users.   Logical  Design:     The  database  is  divided  into  functional  areas.  These  functional  areas  include   Movies,  Theaters,  Awards  and  Ratings.  These  areas  are  discussed  further  in   the  database  decomposition  section.                                                                                                                                                                           Logical  Database  Design:     We  built  the  logical  model  after  the  requirements  were  clearly   identified.  The  logical  model  includes  the  specified  entities  and  the  relation   between  them.  We  detailed  the  attributes  in  each  and  every  entity/table.  The   logical  data  model  fully  explains  the  attributes  of  the  data  and  fulfills  the  data   Movies   Theaters   Ratings   Awards  
  • 5.   5   requirements  from  a  business  point  of  view.  Data  attributes  define  the  data   types  and  lengths.  Some  data  types  include  the  null  ability  options.   We  created  our  logical  data  model  based  on  the  Movies  database   schema  using  oracle  data  modeler.   The  steps  involved  in  the  Oracle  Data  Modeler  for  Logical  Database  design  are:     File  -­‐>  Data  Modeler  -­‐>  Import  -­‐>  Data  Dictionary.   A  screen  shot  of  this  design  is  provided  below.                                                  
  • 6.   6       Physical  Database  Design:   In  a  sense,  logical  design  is  what  you  draw  with  a  pencil  before  building   your  warehouse  and  physical  design  is  when  you  create  the  database  with   SQL  statements.  
  • 7.   7   During  the  physical  design  process,  we  converted  the  data  gathered   during  the  logical  design  phase  into  a  description  of  the  physical  database,   including  tables  and  constraints.  Physical  design  decisions,  such  as  the  type  of   index  or  partitioning  have  a  large  impact  on  query  performance.   In  the  physical  database  design,  objects  such  as  tables  and  columns  are   created  based  on  the  entities  and  attributes  that  were  defined  during  logical   design  of  the  database  system.    Other  important  things  like  primary  keys,   foreign  keys,  other  unique  keys  and  indexes  are  also  defined.    All  these  parts   are  integrated  to  complete  the  Physical  design  of  the  database.     Tables:              
  • 8.   8   AWARDS     CREATE  TABLE  "ADB_PEARL"."AWARDS"          (   "AWARD_ID"  NUMBER(10,0),       "AWARD_NAME"  VARCHAR2(30  BYTE),       "AWARD_YEAR"  NUMBER(5,0),       "AWARD_CATEGORY"  VARCHAR2(30  BYTE),       "FILM_ID"  NUMBER(10,0),       "AWARDEE_NAME"  VARCHAR2(50  BYTE),        PRIMARY  KEY  ("AWARD_ID")   )   CASTS     CREATE  TABLE  "ADB_PEARL"."CASTS"          (   "FILM_ID"  NUMBER(10,0),       "CAST_MEMBER"  VARCHAR2(50  BYTE),       "CAST_ROLE"  VARCHAR2(100  BYTE),        PRIMARY  KEY  ("FILM_ID",  "CAST_MEMBER",  "CAST_ROLE"),  
  • 9.   9   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )     DIRECTORS        CREATE  TABLE  "ADB_PEARL"."DIRECTORS"          (   "FILM_ID"  NUMBER(10,0),       "DIRECTOR"  VARCHAR2(50  BYTE),        PRIMARY  KEY  ("FILM_ID",  "DIRECTOR"),                                  FOREIGN  KEY  ("FAN_ID")        REFERENCES  "ADB_PEARL"."FANS"  ("FAN_ID")  ENABLE,        FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )     FAN_RATINGS     CREATE  TABLE  "ADB_PEARL"."FAN_RATINGS"          (   "FAN_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,    
  • 10.   10     "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "IMDB_RATING"  NUMBER(10,1)  NOT  NULL  ENABLE,       "LAST_RATED"  DATE,       "FIRST_RATED"  DATE,        PRIMARY  KEY  ("FILM_ID",  "FAN_ID"),   FOREIGN  KEY  ("FAN_ID")        REFERENCES  "ADB_PEARL"."FANS"  ("FAN_ID")  ENABLE,        FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )   FANS     CREATE  TABLE  "ADB_PEARL"."FANS"          (   "FNAME"  VARCHAR2(50  BYTE),       "LNAME"  VARCHAR2(50  BYTE),       "GENDER"  VARCHAR2(10  BYTE),       "STREET"  VARCHAR2(100  BYTE),       "CITY"  VARCHAR2(50  BYTE),    
  • 11.   11     "STATE"  VARCHAR2(20  BYTE),       "ZIP"  VARCHAR2(20  BYTE),       "BIRTH_DAY"  NUMBER,       "BIRTH_MONTH"  NUMBER,       "BIRTH_YEAR"  NUMBER,       "FAN_ID"  NUMBER(10,0),        PRIMARY  KEY  ("FAN_ID")   )   GENRES     CREATE  TABLE  "ADB_PEARL"."GENRES"          (   "FILM_ID"  NUMBER(10,0),       "GENRE"  VARCHAR2(20  BYTE),        PRIMARY  KEY  ("FILM_ID",  "GENRE"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )   KEYWORDS     CREATE  TABLE  "ADB_PEARL"."KEYWORDS"          (   "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "KEYWORD"  VARCHAR2(50  BYTE)  NOT  NULL  ENABLE,    
  • 12.   12      PRIMARY  KEY  ("FILM_ID",  "KEYWORD"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )   LOCALES     CREATE  TABLE  "ADB_PEARL"."LOCALES"          (   "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "CITY"  VARCHAR2(50  BYTE),       "STATE"  VARCHAR2(50  BYTE),       "COUNTRY"  VARCHAR2(50  BYTE)  NOT  NULL  ENABLE,       "NOTE"  VARCHAR2(200  BYTE),        PRIMARY  KEY  ("FILM_ID",  "CITY",  "COUNTRY"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )              
  • 13.   13         MOVIES     CREATE  TABLE  "ADB_PEARL"."MOVIES"          (   "IMDB_RANK"  NUMBER(10,0),       "IMDB_RATING"  NUMBER(10,1),       "FILM_TITLE"  VARCHAR2(100  BYTE)  NOT  NULL  ENABLE,       "IMDB_VOTES"  NUMBER(10,0),       "FILM_YEAR"  NUMBER(4,0),       "RUNTIME"  NUMBER(10,0),       "BUDGET"  NUMBER(12,0),       "WORLDWIDE_GROSS"  NUMBER(12,0),       "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "USA_GROSS"  NUMBER(12,0),    
  • 14.   14     "AFI_RANK"  NUMBER(10,0),       "MPAA_RATING"  VARCHAR2(10  BYTE),       "RELEASE_DATE"  DATE,       "GROSS_DATE"  DATE,        PRIMARY  KEY  ("FILM_ID"),   FOREIGN  KEY  ("MPAA_RATING")        REFERENCES  "ADB_PEARL"."MPAA_RATINGS"  ("MPAA_RATING")   ENABLE        )   MPAA_RATINGS     CREATE  TABLE  "ADB_PEARL"."MPAA_RATINGS"          (   "MPAA_RATING"  VARCHAR2(10  BYTE)  NOT  NULL  ENABLE,       "RATING_DESCRIPTION"  VARCHAR2(100  BYTE),        PRIMARY  KEY  ("MPAA_RATING")   )   PATRON_TYPE     CREATE  TABLE  "ADB_PEARL"."PATRON_TYPE"          (   "TYPE_ID"  NUMBER(5,0),       "PATRON"  VARCHAR2(25  BYTE),    
  • 15.   15     "MOVIE_TYPE"  VARCHAR2(25  BYTE),       "MOVIE_TIME"  VARCHAR2(25  BYTE),        PRIMARY  KEY  ("TYPE_ID")   )   PRICE     CREATE  TABLE  "ADB_PEARL"."PRICE"          (   "PRICE_DATE"  DATE  NOT  NULL  ENABLE,       "TYPE_ID"  NUMBER(10,0),       "FARE"  NUMBER(5,0),       "PRICE_ID"  NUMBER(10,0),        PRIMARY  KEY  ("PRICE_ID"),   CONSTRAINT  "PRICE_FK"  FOREIGN  KEY  ("TYPE_ID")        REFERENCES  "ADB_PEARL"."PATRON_TYPE"  ("TYPE_ID")  ENABLE        )   PRODUCERS     CREATE  TABLE  "ADB_PEARL"."PRODUCERS"          (   "FILM_ID"  NUMBER(10,0),       "PRODUCER"  VARCHAR2(50  BYTE),        PRIMARY  KEY  ("FILM_ID"),  
  • 16.   16   CONSTRAINT  "PR_CONST"  FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )     SHOWS       CREATE  TABLE  "ADB_PEARL"."SHOWS"          (   "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "THEATRE_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "SCREEN_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "MOVIE_TIME"  TIMESTAMP  (6),       "SHOWS_DATE"  DATE  NOT  NULL  ENABLE,       "TICKETS_SOLD"  NUMBER(10,0),       "TYPE_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,        CONSTRAINT  "SHOWS_CONST"  PRIMARY  KEY  ("FILM_ID",   "THEATRE_ID",  "SCREEN_ID",  "MOVIE_TIME",  "SHOWS_DATE",  "TYPE_ID"),   CONSTRAINT  "SHOWS_FK"  FOREIGN  KEY  ("TYPE_ID")        REFERENCES  "ADB_PEARL"."PATRON_TYPE"  ("TYPE_ID")  ENABLE,        CONSTRAINT  "SHOWS_FK1"  FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE  
  • 17.   17        )   TAGLINES     CREATE  TABLE  "ADB_PEARL"."TAGLINES"          (   "FILM_ID"  NUMBER(10,0)  NOT  NULL  ENABLE,       "TAGLINE"  VARCHAR2(300  BYTE)  NOT  NULL  ENABLE,        PRIMARY  KEY  ("FILM_ID",  "TAGLINE"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )   TECHNICIANS     CREATE  TABLE  "ADB_PEARL"."TECHNICIANS"          (   "FILM_ID"  NUMBER(10,0),       "TECHNICIAN"  VARCHAR2(50  BYTE),        PRIMARY  KEY  ("FILM_ID"),   FOREIGN  KEY  ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE        )        
  • 18.   18             THEATRE_INFO     CREATE  TABLE  "ADB_PEARL"."THEATRE_INFO"          (   "THEATRE_ID"  NUMBER(10,0),       "THEATRE_NAME"  VARCHAR2(50  BYTE)  NOT  NULL  ENABLE,       "THEATRE_TYPE"  VARCHAR2(30  BYTE),       "PHONE"  VARCHAR2(20  BYTE),       "EMAIL"  VARCHAR2(50  BYTE)  NOT  NULL  ENABLE,       "NUMBER_OF_SCREENS"  NUMBER(3,0)  NOT  NULL  ENABLE,       "STREET"  VARCHAR2(100  BYTE),       "CITY"  VARCHAR2(35  BYTE),       "STATE"  VARCHAR2(35  BYTE),       "ZIP"  VARCHAR2(15  BYTE),    
  • 19.   19     "COUNTRY"  VARCHAR2(30  BYTE),        PRIMARY  KEY  ("THEATRE_ID")   )         THEATRE_MOVIE_INFO     CREATE  TABLE  "ADB_PEARL"."THEATRE_MOVIE_INFO"          (   "SCREEN_ID"  NUMBER(10,0),       "THEATRE_ID"  NUMBER(10,0),       "FILM_ID"  NUMBER(10,0),       "PRICE_ID"  NUMBER(10,0),       "MOVIE_TYPE"  VARCHAR2(20  BYTE),       "MOVIE_CLASS"  VARCHAR2(20  BYTE),       "CAPACITY"  NUMBER(4,0),        CONSTRAINT  "THEATRE_MOVIE_INFO_CONST1"  PRIMARY  KEY   ("SCREEN_ID",  "THEATRE_ID",  "FILM_ID",  "PRICE_ID"),   CONSTRAINT  "THEATRE_MOVIE_INFO_CONST2"  FOREIGN  KEY   ("THEATRE_ID")        REFERENCES  "ADB_PEARL"."THEATRE_INFO"  ("THEATRE_ID")   ENABLE,    
  • 20.   20      CONSTRAINT  "THEATRE_MOVIE_INFO_CONST3"  FOREIGN  KEY   ("FILM_ID")        REFERENCES  "ADB_PEARL"."MOVIES"  ("FILM_ID")  ENABLE,        CONSTRAINT  "THEATRE_MOVIE_INFO_CONST4"  FOREIGN  KEY   ("PRICE_ID")        REFERENCES  "ADB_PEARL"."PRICE"  ("PRICE_ID")  ENABLE        )   USER_REVIEWS     CREATE  TABLE  "ADB_PEARL"."USER_REVIEWS"          (   "REVIEW_ID"  NUMBER(10,0),       "THEATRE_ID"  NUMBER(10,0),       "FAN_ID"  NUMBER(10,0),       "RATING"  NUMBER(2,0),       "DESCRIPTION"  VARCHAR2(150  BYTE),       "REVIEW_DATE"  DATE,        CONSTRAINT  "USER_REVIEW_CONST1"  PRIMARY  KEY  ("REVIEW_ID",   "THEATRE_ID",  "FAN_ID"),   CONSTRAINT  "USER_REVIEW_CONST2"  FOREIGN  KEY  ("THEATRE_ID")        REFERENCES  "ADB_PEARL"."THEATRE_INFO"  ("THEATRE_ID")   ENABLE,        CONSTRAINT  "USER_REVIEW_CONST3"  FOREIGN  KEY  ("FAN_ID")  
  • 21.   21        REFERENCES  "ADB_PEARL"."FANS"  ("FAN_ID")  ENABLE        )           Data  Generation  and  Loading:     For  this  section,  we  have  generated  appropriate  data  for  the  schema  of  the   database.  Apart  from  the  tables  already  existent  in  the  Movies  database,  we   have  created  6  additional  tables:   AWARDS   TECHNICIANS   THEATRE_INFO   THEATRE_MOVIE_INFO   USER_REVIEWS   PATRON_TYPE   Of  these  tables,  we  have  generated  data  for  the  AWARDS  and  the   TECHNICIANS  tables.  We  used  multiple  techniques  to  generate  the  data.  For   the  AWARDS  table,  we  gathered  data  from  Wikipedia.  We  assembled  the  data   into  an  Excel  table  and  then  loaded  the  data  using  the  import  feature  of   SQLDeveloper  into  our  AWARDS  table.   There  are  three  steps  in  the  import  process:  
  • 22.   22   1.  Choose  the  import  method   2.  Select  the  columns   3.  Select  the  definitions  of  the  columns       For  propagating  data  into  the  TECHNICIANS  table,  we  first  gathered   some  data  about  the  technicians  from  Wikipedia.  Then,  we  assembled  the  data   into  an  Excel  table  and  then  imported  the  data  into  TECHNICIANS  table.      
  • 23.   23         The  same  procedure  was  repeated  for  the  PRODUCERS  table.  We  began   assembling  the  data  about  the  respective  producers  from  Wikipedia,  then   assembled  them  into  an  Excel  table  and  finally  imported  that  into  our   PRODUCERS  table.      
  • 24.   24       Performance  Tuning:     SQL  Tuning     Different  SQL  statements  are  used  to  retrieve  data  from  the  Movies   database.  We  can  get  the  same  results  by  writing  different  queries  but  using   the  best  query  is  always  important  to  improve  the  performance.  Therefore,  we   need  to  SQL  query  tuning  based  on  the  requirements.  The  list  of  queries  below   shows  how  queries  can  be  optimized  for  better  performance.     1. SQL  query  becomes  faster  if  you  use  the  actual  columns  in  SELECT   statement  instead  of  “  *  “.    
  • 25.   25   SELECT  FILM_TITLE,  FILM_ID  FROM  MOVIES   INSTEAD  OF   SELECT  *  FROM  MOVIES   2.  Sometimes  you  may  have  more  than  one  sub  queries  in  your  main  query.   Try  to  minimize  the  number  of  sub  query  blocks  in  your  query.   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  WHERE  (IMDB_VOTES,   USA_GROSS)  =  (SELECT  MAX  (IMDB_VOTES),  MAX  (USA_GROSS)  FROM   MOVIES)   INSTEAD  OF   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  WHERE  IMDB_VOTES=  (SELECT   MAX  (IMDB_VOTES)  FROM  MOVIES)  AND  USA_GROSS  =  (SELECT  MAX   (USA_GROSS)  FROM  MOVIES)   3.  Use  operator  EXISTS,  IN  and  table  joins  appropriately  in  your  query.       a)  Usually,  IN  has  the  slowest  performance.       b)  IN  is  efficient  when  most  of  the  filter  criteria  is  in  the  sub-­‐query.     c)  EXISTS  is  efficient  when  most  of  the  filter  criteria  is  in  the  main  query.      Example:  Write  the  Query  as  follows:   SELECT  FILM_ID  FROM  SHOWS  S  WHERE  EXISTS  (SELECT  *  FROM   THEATRE_INFO  T  WHERE  S.THEATRE_ID=T.THEATRE_ID)   INSTEAD  OF   SELECT  FILM_ID  FROM  SHOWS  WHERE  THEATRE_ID  IN  (SELECT   THEATRE_ID  FROM  THEATRE_INFO)  
  • 26.   26       4.  Use  UNION  ALL  in  place  of  UNION      Example:  Write  the  Query  as  follows:   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  UNION  ALL  SELECT  AWARD_ID,   AWARD_NAME  FROM  AWARDS   INSTEAD  OF   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  UNION  SELECT  AWARD_ID,   AWARD_NAME  FROM  AWARDS   5.  Use  where  clause  appropriately       Example:  Write  the  Query  as  follows:   SELECT  *  FROM  MOVIES  WHERE  FILM_YEAR  BETWEEN  2000  AND  2014   INSTEAD  OF   SELECT  *  FROM  MOVIES  WHERE  FILM_YEAR>=2000  AND  FILM_YEAR<=2014   6.  HAVING  clause  is  used  to  filter  the  rows  after  all  the  rows  are  selected.  It  is   like  a  filter.  Do  not  use  the  HAVING  clause  for  any  other  purposes.   SELECT  MPAA_RATING,  COUNT  (M.FILM_TITLE)  AS  MOVIES  FROM  MOVIES  M   GROUP  BY  MPAA_RATING  HAVING  COUNT  (M.FILM_TITLE)>1   INSTEAD  OF   SELECT  MPAA_RATING,  COUNT  (M.FILM_TITLE)  AS  MOVIES  FROM  MOVIES   M  GROUP  BY  MPAA_RATING  HAVING  MPAA_RATING='R'        
  • 27.   27   7.  Use  EXISTS  instead  of  DISTINCT  when  using  joins,  which  involves  tables   having  one-­‐to-­‐many  relationship.       Example:  Write  the  Query  as  follows:   SELECT  FILM_ID,  FILM_TITLE  FROM  MOVIES  M  WHERE  EXISTS  (SELECT   CAST_MEMBER  FROM  CASTS  C  WHERE  M.FILM_ID=C.FILM_ID)   INSTEAD  OF   SELECT  DISTINCT  C.CAST_MEMBER,  M.FILM_ID  FROM  MOVIES  M,  CASTS  C   WHERE  M.FILM_ID=C.FILM_ID   Querying   Interesting  queries  for  MOVIES  database:   1. Display  the  name  of  all  movies  that  have  an  IMDB  rating  of  at  least  8.0,   with  more  than  100,000  IMDB  votes,  and  were  released  from  2007  to   2013.    Show  the  movies  with  the  highest  IMDB  ratings  first.         SELECT  M.FILM_TITLE  AS  MOVIES  FROM  RELMDB.MOVIES  M  WHERE   M.IMDB_VOTES  >100000  AND  M.IMDB_RATING  >=8.0  AND   M.FILM_YEAR>=2007  AND  M.FILM_YEAR<=2013  ORDER  BY   M.IMDB_RATING  DESC;  
  • 28.   28       2. Display  each  movie’s  title  and  total  gross,  where  total  gross  is  the  USA   gross  and  worldwide  gross  combined.  Exclude  any  movies  that  do  not   have  values  for  either  USA  gross  or  worldwide  gross.  Show  the  highest   grossing  movies  first.   SELECT  M.FILM_TITLE  AS  TITLE,  (M.USA_GROSS  +   M.WORLDWIDE_GROSS)  AS  TOTAL_GROSS  FROM  RELMDB.MOVIES  M   WHERE  M.USA_GROSS  IS  NOT  NULL  AND  M.WORLDWIDE_GROSS  IS   NOT  NULL  ORDER  BY  TOTAL_GROSS  DESC;      
  • 29.   29   3. Display  how  many  movies  have  an  MPAA  rating  of  G,  PG,  PG-­‐13,  and  R.   Show  the  results  in  alphabetical  order  by  MPAA  rating.   SELECT  MPAA_RATING,  COUNT  (M.FILM_TITLE)  AS  MOVIES   FROMRELMDB.MOVIES  M  WHERE     MPAA_RATING  IN  ('G','PG','PG-­‐13','R')  GROUP  BY  MPAA_RATING   ORDER  BY  MPAA_RATING;     4. Display  the  titles  of  all  movies  where  Tom  Hanks  or  Tim  Allen  were  cast   members.  Each  movie  title  should  be  shown  only  once.   SELECT  DISTINCT  M.FILM_TITLE  AS  TITLE  FROM  RELMDB.MOVIES  M   INNER  JOIN  RELMDB.CASTS  C  ON     M.FILM_ID  =  C.FILM_ID  WHERE  C.CAST_MEMBER  IN  ('Tom  Hanks','Tim   Allen')       5. 5.  For  each  movie,  display  its  movie  title,  year,  and  how  many  cast   members  were  part  of  the  movie.  Exclude  movies  with  five  or  fewer  cast   members.  Display  movies  with  the  most  cast  members  first,  followed  by   movie  year  and  title.   SELECT  COUNT  (C.CAST_MEMBER)  AS  CASTCOUNT,  M.FILM_TITLE,   M.FILM_YEAR  FROM    
  • 30.   30   RELMDB.CASTS  C  INNER  JOIN  RELMDB.MOVIES  M  ON  M.FILM_ID=   C.FILM_ID  GROUP  BY     M.FILM_TITLE,  M.FILM_YEAR  HAVING  COUNT  (C.CAST_MEMBER)  >5   ORDER  BY  COUNT     (C.CAST_MEMBER)  DESC,  FILM_YEAR  DESC,  FILM_TITLE  DESC  ;     6. Displays  the  movies  which  contain  the  keyword  “people”  in  tagline.   SELECT  movies.film_title         FROM  movies         INNER  JOIN  taglines  ON  movies.film_id  =  taglines.film_id       WHERE  taglines.tagline  LIKE  '%people%';       Parallelizing  Index     We  can  use  parallelizing  indexes  which  enable  the  database  to  use  multiple   processes  to  create  the  index  which  is  quicker  than  if  a  single  server  process  
  • 31.   31   created  the  index    sequentially.  We  can  increase  the  degree  of  the  table  to  help   it  to  use  multiple  processes  which  improves  the  performance.     We  first  ran  a  query  which  displays  the  film  name  and  its  Fan  ID  where  the   film_year  is  greater  than  1990.     SELECT  MOVIES.FILM_TITLE,MOVIES.FILM_YEAR,FAN_RATINGS.FAN_ID     from  MOVIES  LEFT  JOIN  FAN_RATINGS  on  FAN_RATINGS.FILM_ID  =   MOVIES.Film_id  where  MOVIES.FILM_YEAR  >  1990       Now,  we  increased  the  degree  of  the  tables  to  allow  parallelism   ALTER  TABLE  MOVIES  PARALLEL(DEGREE  4)   ALTER  TABLE  FAN_RATINGS  PARALLEL(DEGREE  4)         We  can  see  the  reduction  in  the  cost  by  enabling  parallelism.         Conclusion:     We  can  notice  that  query  cost  has  reduced  from  7  to  5.  Hence,  the  use  of   parallelized  view  helped  in  the  improvement  of  performance.    Parallelism  also   helps  in  faster  access  of  data.  
  • 32.   32     Function  Based  Indexing   The  ability  to  index  functions  and  use  these  indexes  in  a  query  is  called   function-­‐based  index.  This  capacity  allows  you  to  have  case  insensitive   searches  or  sorts,  search  on  complex  equations,  and  extend  the  SQL  Language   efficiently  by  implementing  your  own  functions  and  operators  and  then   searching  on  them.   • It  is  easy  and  provides  immediate  value.   • It  can  be  used  to  speed  up  existing  applications  without  changing  any  of   their  logic  or  queries.   • It  can  be  used  to  supply  additional  functionalities  to  applications  with   very  little  cost.   Query:     SELECT  FILM_TITLE,(WORLDWIDE_GROSS-­‐BUDGET)  AS  Earnings  FROM   MOVIES   WHERE  (WORLDWIDE_GROSS-­‐BUDGET)>1000000     Without  Index:        
  • 33.   33   Index  Creation:     With  Index:     Here  we  observe  that  indexing  the  functional  attribute  not  only   increases  the  cost  but  also  the  performance.  In  the  query  above,  if  we  had   made  indexes  on  either  WORLDWIDE_GROSS  or  BUDGET,  it  wouldn’t  have   been  used  since  we  are  using  WORLDWIDE_GROSS-­‐BUDGET  as  the  filtering   criteria.    After  creating  indexes  ideally  STATS  should  be  gathered  since  the   spread  of  the  data  in  the  database  changes  the  statistics  of  the  database.  But   currently  we  do  not  have  the  privilege  to  execute  DBMS_STATS  package.  It   requires  DBA  privilege  since  it  will  impact  the  database  performance.      
  • 34.   34     DBA  Scripts:     The  below  queries  will  display  the  critical  and  general  database  information.   SELECT  *  FROM  V$DATABASE;     SELECT    *  FROM  V$INSTANCE      
  • 35.   35     SELECT  *  FROM  V$VERSION     ACTIVE  SESSIONS  IN  THE  DATABASE:   The  below  query  lists  out  the  sessions  which  are  presently  active  in  the   database:   SELECT  NVL(V$SESSION.USERNAME,  '(oracle)')  AS  USERNAME,   V$SESSION.OSUSER,  V$SESSION.SID,   V$SESSION.SERIAL#,V$PROCESS.SPID,  V$SESSION.LOCKWAIT,   V$SESSION.STATUS,V$SESSION.MODULE,     V$SESSION.MACHINE,V$SESSION.PROGRAM,   TO_CHAR(V$SESSION.LOGON_TIME,'DD-­‐MON-­‐YYYY  HH24:MI:SS')  AS     LOGON_TIME  FROM  V$SESSION,  V$PROCESS  WHERE  V$SESSION.PADDR  =   V$PROCESS.ADDR  AND    
  • 36.   36   V$SESSION.STATUS  =  'ACTIVE'     ORDER  BY  V$SESSION.USERNAME,  V$SESSION.OSUSER;.         BLOCKING:   The  below  query  will  provide  the  list  of  user  id’s  who  have  blocked  a  session.   It  takes  into  account  the  V$SESSION  and  V$LOCKS  table.   SELECT  S.SID,  S.USERNAME,  B.BLOCKER,  B.WAITER  FROM  V$SESSION  s,       (SELECT    SID,  DECODE(BLOCK,  0,  'NO',  'YES'  )  BLOCKER,    DECODE(REQUEST,   0,  'NO','YES'  )  WAITER  FROM    V$LOCK       WHERE        REQUEST  >  0  OR  BLOCK  >  0  )    b       WHERE  S.SID  =  B.SID        
  • 37.   37     There  were  perhaps  no  blocked  users,  therefore  resulting  into  the  above   output.     PROFILES:   The  below  query  lists  out  the  DBA  Profiles:   SELECT  *  FROM  DBA_PROFILES        
  • 38.   38     USERS:   The  below  query  shows  the  list  of  users  in  the  database:   SELECT  USERNAME,  USER_ID,  ACCOUNT_STATUS,  LOCK_DATE,   EXPIRY_DATE,  DEFAULT_TABLESPACE,  PROFILE     FROM     DBA_USERS                  
  • 39.   39     ROLES:   The  below  query  list  out  the  roles  in  the  database:   SELECT  *  FROM  DBA_ROLES       DISPLAYING  SYSTEM  PARAMETERS  ALONG  WITH  THEIR  DESCRIPTION     SET  LINESIZE  500       COLUMN  name    FORMAT  A30       COLUMN  value  FORMAT  A60      
  • 40.   40     SELECT    SP.NAME,    SP.TYPE,    SP.VALUE,    SP.ISSES_MODIFIABLE,     SP.ISSYS_MODIFIABLE,  SP.ISINSTANCE_MODIFIABLE       FROM  V$SYSTEM_PARAMETER  SP     ORDER  BY  SP.NAME;       CACHE  MEMORY  USAGE:   To  improve  performance,  a  DBA  needs  to  constantly  monitor  the  cache   memory  usage.  Below  query  lists  out  the  same:     SELECT  OWNER,  NAMESPACE,  TYPW,  COUNT(*)  OBJECT_COUNT,   SUM(SHARABLE_MEM)  SHARABLE_MEM,     SUM(LOADS)  LOADS,  SUM(EXECUTIONS)  EXECUTIONS,  SUM(LOCKS)  LOCKS,   SUM(PINS)  PINS     FROM  V$DB_OBJECT_CACHE       GROUP  BY  OWNER,  NAMESPACE,  TYPE;    
  • 41.   41         Database  Security:     Database  security  concerns  the  use  of  a  broad  range  of  information   security  controls  to  protect  databases  (potentially  including  the  data,  the   database  applications  or  stored  functions,  the  database  systems,  the  database   servers  and  the  associated  network  links)  against  compromises  of  their   confidentiality,  integrity  and  availability.  It  involves  various  types  or   categories  of  controls  such  as  technical,  procedural/administrative,  and   physical.     Security  risks  to  database  systems:   • Unauthorized  or  unintended  activity  or  misuse  by  authorized  database   users  
  • 42.   42   • Data  corruption  and/or  loss  caused  by  the  entry  of  invalid  data  or   commands   • Malware  infections  causing  incidents  such  as  unauthorized  access   • Overloads,  performance  constraints,  and  capacity  issues     • Physical  damage  to  database  servers     • Design  flaws  and  programming  bugs  in  databases   Many  layers  and  types  of  information  security  controls  are  appropriate  to   databases,  including:   • Access  control   • Auditing   • Authentication   • Encryption   • Integrity  controls   • Backups   • Application  security   • Database  Security  applying  Statistical  Method   We  want  to  implement  authentication  and  auditing  of  the  database  in  our   project.   Authentication     A  basic  security  requirement  is  that  your  users  must  know.  You  must   identify  the  users  before  you  can  determine  their  privileges  and  access  rights;   so  that  you  can  audit  their  actions  upon  the  data.  
  • 43.   43   Users  can  be  authenticated  in  a  number  of  different  ways  before  they   are  allowed  to  create  a  database  session.  In  database  authentication,  you  can   define  users  such  that  the  database  performs  both  identification  and   authentication  of  users.  In  external  authentication,  you  can  define  users  such   that  authentication  is  performed  by  the  operating  system  or  network  service.   Alternatively,  you  can  identify  users  through  authentication  by  the  Secure   Sockets  Layer  (SSL).     For  enterprise  users,  an  enterprise  directory  can  be  used  to  authorize   their  access  to  the  database  through  enterprise  roles.  Finally,  you  can  specify   users  who  are  allowed  to  connect  through  a  middle-­‐tier  server.  The  middle-­‐ tier  server  authenticates  and  assumes  the  identity  of  the  user  and  is  allowed   to  enable  specific  roles  for  the  user.  This  is  called  proxy  authentication.   Different  privileges  are  given  to  different  users;  this  will  result  in  only   select  number  of  people  who  can  change  the  data  in  the  tables.  In  the  movies   database,  we  have  defined  a  set  of  actors  and  assigned  privileges.  The  list  of   some  of  the  users  and  their  privileges  are  listed  in  the  table  below.           Users  Privileges     A  user  privilege  is  a  right  to  execute  a  particular  type  of  SQL  statement   or  a  right  to  access  another  user's  object.  The  types  of  privileges  are  defined   by  DBMS.   Roles,  on  the  other  hand,  are  created  by  users  (usually  administrators)  and   are  used  to  group  together  privileges  or  other  roles.  They  are  a  means  of   facilitating  the  granting  of  multiple  privileges  or  roles  to  users.   User  Roles  
  • 44.   44   • Database  Administrator     • Database  Programmers     • Moderators   • Users     We  set  authentication  rules  for  each  user.  Users  need  to  create  username  and   password  to  log  into  the  system  to  ensure  that  they  have  privileges.     Some  authentication  features  need  to  be  enabled  in  the  system:   • Password  has  to  be  changed  every  three  months.   • Make  the  password  between  10  and  30  characters  and  using  numbers.   • Use  mixed  case  letters  and  special  characters  in  the  password.     • Use  the  database  character  set  for  the  password's  characters,  which  can   include  the  underscore  (_),  dollar  ($),  and  number  sign  (#)  characters.   • Do  not  use  an  actual  word  for  the  entire  password.   • Entering  a  password  incorrectly  for  more  than  five  tries  will  lock  the   user  account.   • Password  encryption.   The  following  DBA  script  will  display  all  the  roles  and  the  privileges  granted:         SET  SERVEROUTPUT  ON       SET  VERIFY  OFF       SELECT  a.granted_role  "Role",                    a.admin_option  "Adm"       FROM      user_role_privs  a;       SELECT  a.privilege  "Privilege",      
  • 45.   45                a.admin_option  "Adm"       FROM      user_sys_privs  a;       Auditing     Auditing  is  the  monitoring  and  recording  of  selected  user  database   actions.  It  can  be  based  on  individual  actions,  such  as  the  type  of  SQL   statement  executed  or  on  combinations  of  factors  that  can  include  user  name,   application,  time,  and  so  on.  Security  policies  can  trigger  auditing  when   specified  elements  in  an  Oracle  database  are  accessed  or  altered,  including  the   contents  within  a  specified  object.   Auditing  is  typically  used  to:   • Enable  future  accountability  for  current  actions  taken  in  a  particular   schema,  table,  or  row,  or  affecting  specific  content.   • Deter  users  (or  others)  from  inappropriate  actions  based  on  that   accountability.   • Investigate  suspicious  activity.   • Notify  an  auditor  that  an  unauthorized  user  is  manipulating  or  deleting   data  and  that  the  user  has  more  privileges  than  expected  which  can  lead   to  reassessing  user  authorizations.   • Monitor  and  gather  data  about  specific  database  activities.   • Detect  problems  with  an  authorization  or  access  control   implementation.   Types  of  auditing:   • Statement  auditing  
  • 46.   46   • Privilege  auditing   • Schema  object  auditing   • Fine-­‐Grade  auditing   Auditing  can  also  be  used  to  monitor  data  about  certain  database  activities.  A   DBA  can  gather  data  about  all  the  logical  I/O’s  being  performed.  This  can  give   the  DBA  a  better  understanding  of  what  is  happening  in  the  system.   Data  backup  and  recovery     Data  backup  is  an  insurance  plan.  Important  files  are  accidentally   deleted  all  the  time.  Mission-­‐critical  data  can  become  corrupt.  Natural   disasters  can  leave  your  office  in  ruin.  With  a  solid  backup  and  recovery  plan,   you  can  recover  from  any  of  these.  Without  one,  you're  left  with  nothing  to  fall   back  on.     A  Recovery  manager  can  be  used  to  backup  data  and  restore  it  in  quick  time.       Recovery  Manager  (RMAN)  is  an  Oracle  utility  that  can  back  up,  restore,   and  recover  database  files.  The  product  is  a  feature  of  the  Oracle  database   server  and  does  not  require  separate  installation.  Recovery  Manager  is  a   client/server  application  that  uses  database  server  sessions  to  perform   backup  and  recovery.  It  stores  metadata  about  its  operations  in  the  control  file   of  the  target  database  and,  optionally,  in  a  recovery  catalog  schema  in  an   Oracle  database.   Below  is  an  example  query  to  back  up  a  database  to  an  image  copy:        
  • 47.   47   connect  target  /  run  {  shutdown  immediate;  startup  force  DBA;  shutdown   immediate;  startup  mount;  allocate  channel  channel1  type  DISK;    backup  as   copy    format  '/backup/%U'  (database)  CURRENT  CONTROLFILE  SPFILE;         BACKUP  AS  COPY  CURRENT  CONTROLFILE  FORMAT  '/backup/control01.ctl';         release  channel  channel1;         shutdown  immediate;  startup;         SQL  "ALTER  DATABASE  BACKUP  CONTROLFILE  TO  TRACE";  }         Weightage  Table:     Topic  /   Section   Description   Evaluation   Logical   database   design   The  logical  design  section  should  include  entity-­‐ relationship  diagrams  (ERDs)  and  data   dictionaries  for  your  database  design,  as  well  as   any  design  assumptions.  You  might  include  a  few   high-­‐level  diagrams  that  highlight  interesting   sections  of  your  project  (include  textual   descriptions  with  these).  There  should  also  be  a   complete  ERD  for  your  entire  project.  There  is  no   expectation  that  you  implement  all  of  your  design,   just  indicate  the  areas  built.  You  are  expected  to   add  additional  design  work  as  part  of  the  project.   15   Physical   database   design   This  section  should  cover  implementation-­‐level   issues.  For  instance,  you  should  discuss  predicted   usage  and  indexing  strategies  that  support   expected  activities.  In  addition,  you  may  wish  to   discuss  architecture  issues,  including  distributed   database  issues  (even  though  you  may  not   implement  anything  in  these  areas).  Artifacts   could  include  capacity  planning,  storage   subsystems,  and  data  placement  (e.g.,  tablespace   /  file  system  arrangements),  indexing  strategies,   15  
  • 48.   48   transaction  usage  maps,  etc.   Data   generation   and  loading   Though  some  data  was  provided,  there  may  have   been  interesting  queries,  stored  procedures,   desktop  tools  (e.g.,  MS  Excel)  that  were  used  to   populate  the  database.  You  may  have  used   queries  with  mod  function,  data  arithmetic,   number  sequences,  lookup  tables,  and  even  data   from  the  Web.  Any  /  all  of  these  are  interesting   additions  to  the  project.   15   Performance   tuning   In  this  section,  highlight  any  experiments  run  as   part  of  the  project  related  to  performance  tuning.   Experiments  with  different  indexing  strategies,   optimizer  changes,  transaction  isolation  levels,   function-­‐based  indexes,  and  table  partitioning  can   all  be  interesting.  Remember  to  look  at  different   types  of  queries  (e.g.,  point,  range,  scan),   execution  plans,  and  I/O  burden.   20   Querying   You  may  also  choose  to  focus  on  writing  SQL   queries  (analytic  SQL  extensions  can  also  be   explored).  Include  interesting  queries  that   highlight  the  types  of  questions  that  can  be   answered  by  the  database.  These  queries  may   also  be  used  to  illustrate  performance  tuning.   10   DBA  scripts   Throughout  the  semester,  we  looked  at  example   DBA  scripts  that  query  the  system  catalog  (a  good   way  to  explore  the  database  engine).  Provide  DBA   scripts,  and  an  explanation  of  how  the  scripts  can   be  used,  that  are  helpful  for  reporting  on  database   objects,  indexes,  constraints,  physical  storage,   data  files,  etc.   15   Database   security   Database  security  is  an  important  area  of  interest   that  can  also  be  investigated.  Though  you  are   limited  on  the  implementation  side,  you  can   develop  a  security  policy  and  discuss  how  you   might  implement  various  aspects  using   authentication  strategies,  roles,  profiles,  and  even   auditing  features.   10