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Entity-Relationship Model/3 — Transcript

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0:00[Music]
0:16welcome to
0:17module 15
0:18of database management systems
0:22we have been discussing about entity
0:24relationship model
0:27and this is the third
0:29and the closing module on this topic
0:36so in the last module we have discussed
0:38about er diagram and we have also seen
0:41how er model can be converted
0:44to a relational schema
0:48in this module we will try to
0:51go through
0:53a few extended features of er model try
0:57to show some of the
1:00more complicated situations how they can
1:02be modeled in the er model and along
1:05with that
1:07we will discuss a variety of design
1:10issues
1:11that will follow
1:13so these are the
1:14outline
1:17so we start with extended
1:20entity relationship features
1:23the first that we note is so far
1:26in the
1:27entity relationship model
1:30we have talked about relationships
1:32between two entity sets
1:36so we have talked about the student
1:38attending courses or instructors
1:40advising students and so on
1:43so such relationships are naturally
1:45called binary
1:47but it is possible that
1:50more than two entity sets let us say
1:52three entity sets could be involved in
1:56the same relation and we show an example
1:58here
2:00where
2:00we have three entity sets instructor
2:04student
2:05and project
2:07so the project entity set
2:09is a list of projects
2:11being done by the students or to be done
2:14by the students
2:16so the relationship project guide
2:20is a relationship between
2:23the guide who is an instructor
2:25the student
2:26who will do the project and
2:29the project that has to be performed so
2:32all three together define this
2:34relationship
2:37so
2:38in
2:39such cases
2:41it is
2:42possible
2:43in er model that we can represent it
2:46conveniently
2:47as a
2:48non-binary relationship
2:52now
2:54this is in ear diagram this is called a
2:56ternary relationship
3:00now
3:01we have talked about
3:02cardinality constraints on binary
3:06relationship one to one many to one
3:08one to many
3:10and many too many
3:11and
3:13we specified that
3:15if we have a binary relationship say
3:18this is one entity set and this is
3:20another entity set and we have a
3:22relationship so if we just
3:25connect them it means a many to many
3:27relation
3:28but if we have an arrow on
3:31one side
3:33entity set then it means on the arrow
3:35side is one
3:37so
3:38this is ah from
3:40entity set e one to e two this is one
3:44too many we could have arrow at both
3:46ends and that means one to one
3:49now the question is ah how will that ah
3:52work out what will be the meaning of
3:54arrow in terms of a
3:56ternary relationship
3:58now in the case of ternary relationship
4:02or this would generalize to
4:04relationships of higher degree whether
4:06where more than three entity sets may be
4:08involved
4:10we put a restriction that we will allow
4:13at most one
4:14arrow out
4:17of the ternary relationship
4:19so we could
4:20have only if we if we look at
4:24if we look at
4:26say this relationship
4:28then we could have an arrow only at this
4:31end
4:33but multiple arrows are not allowed and
4:36the reason is certainly to keep the
4:39semantics of the
4:42cardinality meaningful for example ah
4:46if we have
4:47a ternary relationship between a b and c
4:51lets say this is a a
4:54this is a b
4:56and this is c
4:58and we have a ternary relationship
5:00between
5:01them
5:02and let us say
5:04if we have
5:06a
5:08more than one arrow
5:10the for example ah suppose
5:13then
5:16we have say an arrow to b and an arrow
5:18to c the question is how should we
5:20interpret that should we interpret that
5:24an entity of entities at a
5:27is associated with
5:29unique entity from b
5:32and c
5:33together or
5:35should we associate should we interpret
5:38that the entities
5:41formed by the pair a b
5:44and
5:45the entity formed by the pair ac are
5:48uniquely related
5:50so there is multiplicity of
5:52interpretation if we allow more than one
5:55arrow in case of a ternary or higher
5:58degree relationship
5:59so what will follow for simplicity
6:02in this course and that is what is
6:04followed often in practice is in case of
6:07a ternary or higher order relationship
6:10only one arrow will be allowed in that
6:13in a
6:14in that relationship
6:18now let us talk about ah specialization
6:23ah those of you who have some background
6:26of object oriented systems would be
6:29familiar with
6:31the notion of specialization and
6:33generalization
6:35ah in object oriented systems we say
6:37that if we have a certain concept say we
6:40have a concept called person
6:42and then we say that
6:46a student is a person
6:48what you mean is a student is a
6:50specialization of person and person is a
6:52generalization of student and in that
6:54process student inherits
6:56all the attributes of person
6:59but
7:00in addition the student may have some
7:02specialized attributes
7:04so what it means that if you look
7:07from
7:08ah
7:09from the
7:11perspective of
7:13such
7:15specialization
7:17say if i draw like this this is an
7:20entity set a
7:21and this entity set b
7:23and
7:24to mark the specialization we show
7:28an arrow head with a blank triangle at
7:31that end
7:33so
7:34if we by this what we mean is b
7:37is a a
7:39so
7:41b inherits all the properties of a but
7:44can have some more properties
7:46so if you look at all the entities that
7:49a may have
7:51you will find that a sub group of the
7:53entities in the entity set a
7:56have some additional common properties
7:59so if a is set of persons
8:02and b is a set of students
8:04then a may have
8:06entities who which represent
8:09people who are not students who are
8:11employees
8:12who could be retired and so on
8:14but there will be a number of entities
8:16who have the commonality of being
8:18student they are
8:20enrolled in certain course of certain
8:22university and so on so
8:25in terms of the er diagram er model what
8:28we do is we try to look at
8:31the entity a and
8:34move top down
8:36so that whenever we find a group of
8:38entities which have certain commonality
8:41we move them into a
8:43lower separate specialized
8:46entity set and relate these two entity
8:49sets to the specialization relation
8:52so this sub groups form lower level
8:55entity sets
8:56and
8:58as i said that it is designated in a
9:01certain way
9:02and
9:03as in the object oriented system the
9:06lower level entity set inherits all the
9:09attributes
9:10and relationships of participation of
9:12the higher level entity side so here is
9:15an example you can see the person at the
9:18so called root of this hierarchy of
9:20specialization
9:22it has a set of properties id name
9:24street city and employee is another
9:27relationship another entity set which is
9:30a specialization of person relation
9:33person entity set so employee inherits
9:37all attributes id name street and city
9:40but in addition the commonality of the
9:43entities in the employee entity set is a
9:45fact that all of them have a salary
9:48attribute
9:49a similar entity set student is a
9:51specialization of person where
9:54the again all attributes are inherited
9:57but there is a common attribute called
10:00total credits
10:01which is common for all the students but
10:04is not available or common for the
10:07persons in general
10:08and as you can see that it could be
10:10hierarchical it could go further down
10:12employee could be specialized into
10:14instructor and secretary again by the
10:19rule of specialization instructor will
10:22inherit all attributes of employee which
10:24means that it will inherit attributes of
10:27person which employee has inherited
10:30plus the employee specific attribute
10:33salary so it will inherit all five of
10:35those attributes and then it adds
10:38another attribute which is specific for
10:40the instructor which says the rank which
10:43is is another specific attribute that
10:45you have
10:46now
10:47when you specialize a certain entity set
10:50into
10:50two or more entity sets like we
10:53specialize person in employee and
10:54student then there could be different
10:57situations that
10:58could exist for example certain entity
11:02may be a member of both employee as well
11:06as
11:06student
11:08if that happens then we say that they
11:10are overlapping entity sets
11:13or they could be
11:14disjoint
11:16where
11:17no member of instructor
11:20would be a member of the secretary and
11:24vice versa so we say that
11:26this disjointness
11:28tell us that
11:31no instructor can be a secretary and no
11:33secretary can be an instructor whereas
11:35overlapping
11:37specialized sets denote that well an
11:41employee may or may not be a student but
11:43it is possible that some employee is
11:45also a student and vice versa and that
11:48is how we will represent this
11:55and we will see that when we specialize
11:57the
11:59specialized entity could be total or
12:02they could be partial
12:04we will talk about that totality and
12:06partial little little later
12:08let us look at how do we represent this
12:10information in the relational schema
12:13because as we have seen that whenever we
12:16have a
12:17er diagram it is important to find out
12:20what is the
12:22relational schema that will be
12:24corresponding to that
12:26e r diagram or er model
12:28so
12:29here we could do this in two ways one
12:32that we are showing here is form a
12:34schema for the higher level entity so
12:36form a schema for the person as you can
12:39see here
12:40that person is described in terms of
12:42four attributes
12:44and this form is schema for each of the
12:46lower level entity set
12:48where you include the primary key of the
12:52higher level entity set so when you are
12:53forming the schema of
12:55person of student
12:57which is a specialization of person you
13:00include the id which is the
13:03key of the higher level entity set
13:06person
13:07and along with that you include the so
13:10called local attributes or attributes
13:12which are specific to this low level
13:14entity set in this case total credit
13:16similar thing happens with employee
13:19now this representation is in a way
13:21optimized because
13:23you
13:24are in representing the information only
13:27once when it is needed
13:29but the drawback is if you have to find
13:31out information about say employee
13:34then you will not only have to access
13:36the employee entity set or the
13:39corresponding
13:41relation in the relational schema but
13:43you will also have to access the parent
13:46or higher level entity set to get the
13:48attribute values which are inherited and
13:51if you have a multi-level hierarchy as
13:53we have shown this could involve
13:55accessing multiple relations to find
13:58information about a single entity in an
14:01entity set
14:03so
14:04this is an
14:06in terms of data representation this is
14:08an optimized representation but it has
14:11the overhead of having to access
14:13multiple
14:14ah entity sets to get information about
14:18certain entities
14:20an alternate scheme would be that
14:23based on the hierarchy of specialization
14:25you assume all attributes as they are
14:28inherited and then represent every
14:30entity set in full so when you the
14:32representation of person does not change
14:35but when you represent student
14:37now earlier you are just having id and
14:40total credit now in you include all
14:43entities that are inherited
14:45similarly you do the same thing so you
14:47have the all entities of the parent all
14:50attributes of the parent entity set as
14:52well as the local attribute of that
14:54specific entity set
14:56now this naturally makes it easy to
14:58extract information from a
15:00for a single entity set but
15:03at the same time you are storing the
15:06same ah
15:08data redundantly for people who are
15:11having overlapped representation so if
15:15we have
15:16as we know student and employer
15:17overlapped so the same entity will
15:20happen in student as well as in employee
15:24so it will the information of the common
15:26attributes name street city etcetera
15:29they will occur in both these tables in
15:32the design so these are two methods and
15:35now we have just ah given you the
15:38relative
15:39advantages and its advantages of the
15:41same and based on a particular situation
15:43you have to choose what is a good method
15:46to represent
15:50you can look at
15:51now you know from the object based
15:52system that if you have a specialization
15:55hierarchy you can think of it as a
15:57generalization hierarchy also
15:59the generalization hierarchy goes in a
16:01bottom up manner so instead of
16:04actually
16:06starting with an entity set and finding
16:08out subsets of entities which have
16:10greater commonality between them and
16:12putting them as specialized you could
16:14actually group them
16:16in
16:18the terms of finding out what they share
16:20and create a higher level entities
16:24for example the way i am saying is let
16:26us say that i have one entity set
16:29which say
16:31ug
16:32student
16:33and have another entity set in the same
16:35university which is a pg student
16:39so there are
16:40both of them are students naturally they
16:42are
16:43disjoint a person cannot be ug as well
16:45as pg student at the same time
16:47and once you represent that you find
16:49that well there are lot of information
16:51which are common between these two
16:53entity sets like the student roll number
16:56name
16:57and so on so forth so you could choose
17:00that well you instead of having them as
17:03two separate
17:05entity sets
17:07you could
17:08extract out the common attributes and
17:10put them at a higher level entity so all
17:12that you are doing is
17:14instead of going top down you are going
17:16bottom up in the whole approach
17:18so if you
17:20do that then ah there you can easily see
17:23that specialization and generalization
17:25is are inverse of each other
17:28and they are used interchangeably in
17:31terms of the relational
17:34entity relationship design
17:37the other constraint that you can
17:40identify you should identify is the
17:43constraint of completeness
17:45we say that if i have an
17:48entity set
17:51say person
17:53and
17:54then we have specializations of
17:57employee and student the question is
17:59for a higher level entity set
18:01is it necessarily that every entity
18:05will be represented in
18:08one of the or more than one of the lower
18:11level entity sets
18:13if that is guaranteed that an entity
18:16must belong to one of the lower level
18:18entity sets we say that it is a complete
18:22specialization
18:24but if it is that a
18:26higher level entity
18:29is may or may not be featuring in a
18:34entity set which is at a lower level
18:36then will say it is a partially
18:39specialized hierarchy so they both of
18:42these are are possible depending on
18:44different situation that we have
18:46so
18:47by default we assume partial
18:50specialization and
18:53so if we want to say certain
18:55specialization is total we will have to
18:58write the keyword total by the side of
19:00the arrow head that is representing the
19:03specialization hierarchy you can say
19:06that
19:06the example i talked of in uniting unite
19:10undergraduate and
19:12graduate or post graduate students into
19:15the entity set of students
19:17gives you a hierarchy which is
19:21total because every
19:23entity in the entity set student must be
19:26either a ug student or a pg student it
19:29is not possible that i have a student
19:31who is neither a ug student nor a pg
19:33student so every high entity the higher
19:35level entity set
19:37ah student must feature in one of these
19:39two specializations so therefore they
19:42are necessarily
19:45total in the relationship so this is the
19:47completeness constraint that you can
19:48think of
19:50moving on lets talk about
19:52another feature which is known as
19:53aggregation the situation is like this
19:56we have already talked about this part
19:59of the diagram
20:00which is a ternary relationship which
20:02relates project instructor and student
20:05now let us say once the project
20:07progresses you would need to add
20:09evaluation to that so here there is
20:11another entity set which represents
20:13evaluation i mean how you are grading or
20:16putting marks and so on so naturally the
20:18evaluation of
20:20a student will be dependent on the
20:24project the student and the supervisor
20:27and that will relate to the evaluation
20:29so evaluation
20:31eval for the relationship is necessarily
20:34a relationship between four entities
20:38or four entity sets so to say
20:41now the question is how do we represent
20:44this information
20:46the
20:47relationship
20:48sets eval for and project guide the two
20:51that we saw if we just want to recall
20:53once more the project guide involves
20:55three of the relation entity sets and
20:58the eval for
20:59relates to
21:00four of the entity sets
21:03now every eval for relationship
21:05corresponds to a
21:08project guide relationship that is if i
21:10have an entity individual for
21:11relationship
21:13i will have a corresponding entity in
21:15the project guide relationship which
21:16specifies the student project and the
21:18instructor
21:20so but
21:21it is other way it is possible that some
21:23project guide relationship may not
21:26correspond to any eval relationship that
21:28is it is possible that ah there is a
21:30allotted project by a student
21:33with a particular instructor which has
21:35yet not been evaluated the evaluation
21:37process is not complete or the time has
21:39not come
21:41so
21:42if we have to
21:43represent the information only for the
21:47eval for relationship we will get
21:49partial information because it is
21:52possible that some entities in eval 4
21:56does not have the evolve for information
21:58do not feature there but
22:00need to be preserved because i need to
22:03remember the project guide
22:06instructor the student and the project
22:09so we need to keep both duplicating the
22:12information
22:14so
22:15we can
22:16use aggregation to eliminate this ah
22:18duplication of information or redundancy
22:21of information
22:22so what we do is we treat the first
22:25entity first relationship the project
22:27gate relationship as if it is an
22:29abstract entity
22:31and then you allow relationship between
22:35two relationships this is something we
22:37did not do before relationship so far
22:40has always been between entity sets
22:42so what you can see that project guide
22:46relationship itself as if it is a
22:48virtual entity it is an abstract entity
22:51and then you allow the relationship
22:53between
22:54the project guide
22:56and the eval 4
22:58relationship which relates to the
23:01evaluation entity set
23:03ah this
23:04really this shows i mean i will just
23:06show you in the diagram so this is how
23:08it will
23:09now work out to be so this is the
23:15abstract
23:18project guide
23:20entity set which is an abstract entity
23:22set because it is actually relationship
23:25and that relates to eval for
23:27which on the other side has the
23:29evaluation so
23:31what will happen is a student is guided
23:33by a particular instructor in a
23:35particular project will feature in this
23:38abstract entity set
23:40which relates the three
23:41entity sets project student and
23:44instructor
23:45and
23:47if it has an evaluation then this
23:50through this
23:51relationship
23:52it will be represented
23:54and the evaluation
23:56value will exist so
23:58we know that if a project is evaluated
24:02then it certainly have a corresponding
24:04entity
24:05in the
24:06abstract entity set project guide but
24:09the reverse may not be true i may have
24:12an entity in the project guide entity
24:13set which does not have an evaluation so
24:16by using this aggregation model i can
24:19represent
24:20the information of
24:22this situation model this situation more
24:25accurately than i could do otherwise
24:30so this can be represented again how to
24:32represent this in terms of the schema so
24:35what we do we represent the aggregation
24:37we create a schema containing the
24:39primary key of the aggregated
24:42relationship
24:43the primary key of the associated entity
24:45set and all the other descriptive
24:48attributes and put them together
24:55so in our example
24:57the schema would be eval for and that
25:00schema will have
25:03these are
25:05entities these are attributes of the
25:08aggregated
25:10or abstract
25:12entity set which is coming from the
25:15student
25:16project and the instructor entities and
25:20this is for the
25:21evaluation id so we put this together so
25:25now you can see that all of these are
25:28related
25:31representing who is the guide of which
25:34student in what project
25:36and if this exists then this gives you
25:39the evaluation
25:41so naturally once this has been
25:42represented the project guide schema by
25:45itself
25:46becomes redundant and therefore it can
25:49be removed so this is a process through
25:51which we come to the
25:53the decision of actually having the
25:56schema to represent all the required
25:58information naturally if the evaluation
26:01is not done then the evaluation id ah
26:04for in eval for will not exist
26:08and that will be a null showing that it
26:11is not
26:12present right now
26:15ok now ah given
26:17these
26:18basic features as well as the extended
26:20features let me talk about a few design
26:23issues which will ah
26:26be
26:26required to see what kind of information
26:30that ah
26:32the the different challenges that we
26:34have seen so far
26:36for example we have seen the case of
26:38multi valued attributes
26:41so
26:42and
26:43the way we can represent that is
26:47using that multivalued attribute as a
26:49separate entity set like the phone
26:52number which also has the advantage of
26:54having its own
26:57added information for example
26:59once we do this then not only i can
27:02have against the same instructor id i
27:05can have multiple phone numbers but i
27:07can have location for each one of these
27:09phone numbers and i make use of
27:13this
27:14relation
27:15relationship that i create
27:17which allow me to ah represent this
27:21multivalued attribute so this is a
27:23common technique that will be used
27:25frequently in such cases
27:28you can have entities versus
27:30relationship for example ah if we
27:34have
27:35ah info we need to keep information
27:37about ah registration
27:40how students register to different
27:42sections then we could represent
27:44registration as an entity set and have
27:47different
27:49relationships of section registration
27:51which specify how registration is
27:53related to section
27:55and student dredge which specify how
27:58registration is related to student to
28:00represent that kind of information
28:03we can have placement of relationship
28:05attributes also attribute date we talked
28:07about as an attribute of advisor
28:10to designate
28:13as
28:14when that particular instructor became
28:17advisor of a student is a common ah
28:20situation that we have already seen
28:23there is also question of ah the choice
28:25being made between the binary and
28:27non-binary relationship ternary or
28:30higher degree
28:31now as it turns out that it is possible
28:34that you could represent
28:36ternary relationships directly or you
28:38can decompose that for example a ternary
28:40relationship can be decomposed in terms
28:42of two binary relationship
28:45for example let us say if we talk about
28:47ah persons then person every person has
28:50parents so
28:53he or she has a father and a mother
28:56now if we represent this as a ternary
28:59relationship
29:00then the one difficulty that we have
29:03that
29:04a person must have both the father and
29:08mother to be represented there for
29:10example if we can come to a situation
29:12where only the mother is known the
29:14father is not known i will not be able
29:16to represent that because it will always
29:18have to come
29:19as a triplet of
29:21three persons the the person under
29:23consideration
29:25her father and her mother but if i
29:27represent the person and the father in
29:30one relationship
29:32the person and the mother in another
29:34relationship then i can take care of the
29:36situation where
29:38when one of the parents are known i can
29:41still represent this
29:43so there are certain tradeoffs which can
29:45be done between the choice of binary and
29:47non-binary relationships but obviously
29:50there are certain relationships which
29:51are
29:52inherently non-binary for example the
29:54project guide example we have seen the
29:56project guide information cannot be
29:58decomposed
30:00ah without certain loss of information
30:02to be represented by say the instructor
30:04and the project and another relationship
30:06between the student and the project it
30:09really that does not represent the same
30:12information
30:13so
30:14ah in general you can
30:17convert a non-binary relationship by in
30:20the binary form by doing this so this is
30:22a ternary relationship being shown
30:24and for doing that these are the three
30:27entity sets
30:29involving the ternary relationship and
30:32to make decomposite into a ternary
30:34relationship what we do is into binary
30:37relationships we inject
30:40a new
30:41entity artificial entity set e
30:45and then we define three different
30:48relations between them so which
30:51individually relates to the entity sets
30:54a b and c so this is a standard
30:56decomposition and you can easily
30:58understand that ah
31:01a b and c in our earlier example could
31:03all be persons and
31:06r a
31:07could
31:08mean that father of
31:11r b could mean mother of and so on so i
31:13can do do it in decompose it in this
31:16manner and represent that
31:21now
31:23while we do this decomposition we will
31:25also have to remember in
31:26that we need to translate all
31:29constraints
31:30that are present for the ternary
31:33relationship
31:34and oftentimes it may become difficult
31:37to translate all constraints it may not
31:40be possible and there may be instances
31:42in the translated schema that cannot
31:44correspond to an instance of the
31:47original
31:48relationship so we will have to
31:51ah avoid
31:52we can we will have to take care of this
31:55situation by identifying attributes
31:59and making
32:00use of the weak entity sets which we
32:03have already
32:05seen in our earlier discussions so if we
32:08summarize the discussions on the year
32:11design decisions we see that the first
32:14decision that
32:16we need to take in case of design is the
32:19use of an attribute or entity set to
32:21represent the object so that is the
32:23first modeling that what is the concept
32:25and what is what are the attributes
32:28or what is the representing entity set
32:31for the object that we are trying to
32:33deal with instructor student
32:36project and so on
32:38and
32:39we will also have to see whether in the
32:41real world this actually is an entity
32:44set or it is a relationship set that it
32:47is ah not an concept by itself but is a
32:51concept which relates
32:53two or more entity sets and thereby
32:57becomes a set of representation
33:00the use of ternary relationship versus
33:03the pair of binary relationship this
33:04tradeoff will have to be weighed as a
33:07design consideration
33:08we have to look into the use of strong
33:11or weak entity set so we will have to
33:13identify the weak entity sets and see if
33:16they should be represented through the
33:18identifying relation
33:20ah
33:21as against a strong entity set
33:24we have to identify
33:26the specialization generalization
33:28situation where so that we can get more
33:31specific information
33:32and create
33:34appropriate modularity in the design
33:37we have to look at ah aggregation which
33:41where we can aggregate entity sets bound
33:44by a
33:45ah relationship
33:47and create an abstract single unit which
33:50can play a role of an independent entity
33:54set in the whole design
33:57so these are
33:58the basic
34:00so these are the basic design
34:03decisions that you need to make and we
34:06will certainly come up with lot more of
34:08design decisions as we go along
34:11and
34:12before i close
34:13in the presentation i have summarized
34:16the different symbols that are used in
34:18the er notation so i will not these have
34:21already been discussed in depth so i
34:23will not go through them one by one but
34:24i have put them as a list in
34:27the couple of slides there is a next
34:29slide in that which
34:31will be
34:33a quick reference for you while you are
34:35initially doing the er diagram so that
34:37you know exactly which symbol to pick up
34:39for what situation
34:41and at the end also there are few slides
34:44which show you that the ear notation
34:47itself is not a unique one there are
34:49multiple
34:50ways to represent similar things for
34:52example this is one which is showing you
34:55different composite attributes ah the
34:59generalization relationship is shown
35:01differently so there are these are all
35:04different styles of
35:05showing
35:07the
35:09constraints that that apply to a
35:11particular
35:13relationship
35:14and
35:15we will i mean we have included this ah
35:18not because we will use these alternate
35:20notations but i haven't quit them
35:22because
35:23it is possible that you come across some
35:25ear
35:27diagram where these notations are used
35:29and if you come across and you are not
35:31able to identify then please refer to
35:33this slides and you will be able to
35:35recognize what is ah what is
35:38corresponding symbol that you already
35:40know
35:40so in this module we have discussed the
35:42extended features of your model and we
35:44have
35:46deliberated on certain design issues and
35:49we will close our discussion on the
35:51entity relationship model here and move
35:54on to discuss the
35:56actual relational design

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