What is RMI? Discuss stub and skeleton. Explain its role in creating distributed applications.

-

 The RMI (Remote Method Invocation) is an API that provides a mechanism to create distributed application in java. The RMI allows an object to invoke methods on an object running in another JVM. The RMI provides remote communication between the applications using two objects stub and skeleton. RMI applications often comprise two separate programs, a server and a client. A typical server program creates some remote objects, makes references to these objects accessible, and waits for clients to invoke methods on these objects. A typical client program obtains a remote reference to one or more remote objects on a server and then invokes methods on them. 

RMI provides the mechanism by which the server and the client communicate and pass information back and forth. A primary goal for the RMI designers was to allow programmers to develop distributed Java programs with the same syntax and semantics used for non-distributed programs. To do this, they had to carefully map how Java classes and objects work in a single Java Virtual Machine (JVM) to a new model of how classes and objects would work in a distributed (multiple JVM) computing environment.


Stub and Skeleton Layer

The stub/skeleton layer is the interface between the application layer and the rest of the RMI system. This layer does not deal with specifics of any transport, but transmits data to the remote reference layer by using marshaling. It also takes data from remote reference layer by using unmarshalling or demarshalling.

During communication between two machines through RPC or RMI, parameters are packed into a message and then sent over the network. This packing of parameters into a message is called marshalling. On the other side these packed parameters are unpacked from the message which is called unmarshalling.

A stub for a remote object is the client-side proxy for the remote object. Such a stub implements all the interfaces that are supported by the remote object implementation. A client-side stub is responsible for:

- Initiating a call to the remote object

- Marshaling arguments

- Informing the remote reference layer that the call should be invoked

- Unmarshaling the return value or exception from a marshal stream.

-  Informing the remote reference layer that the call is complete. -

- A skeleton for a remote object is a server-side entity that contains a method which dispatches calls to the actual remote object implementation. 

The skeleton is responsible for:

- Unmarshaling arguments.

- Making the up-call to the actual remote object implementation. 

- Marshaling the return value of the call or an exception.

Comments

Post a Comment

Popular posts from this blog

Suppose that a data warehouse consists of the four dimensions; date, spectator, location, and game, and the two measures, count and charge, where charge is the fee that a spectator pays when watching a game on a given date. Spectators may be students, adults, or seniors, with each category having its own charge rate. a) Draw a star schema diagram for the data b) Starting with the base cuboid [date; spectator; location; game], what specific OLAP operations should perform in order to list the total charge paid by student spectators at GM Place in 2004?

-
Image
  b) The specific OLAP operations to be performed are: 1. Roll-up on date from date id to year. 2. Roll-up on spectator from spectator id to status. 3. Roll-up on location from location id to location name. 4. Roll-up on the game from game id to all. 5. Dice with status= “students”, location name= “GM Place”, and year=2004
Read more

Suppose that a data warehouse consists of the three dimensions time, doctor, and patient, and the two measures count and charge, where a charge is the fee that a doctor charges a patient for a visit. a) Draw a schema diagram for the above data warehouse using one of the schemas. [star, snowflake, fact constellation] b) Starting with the base cuboid [day, doctor, patient], what specific OLAP operations should be performed in order to list the total fee collected by each doctor in 2004? c) To obtain the same list, write an SQL query assuming the data are stored in a relational database with the schema fee (day, month, year, doctor, hospital, patient, count, charge)

-
Image
Solution: a) Star Schema is shown in the figure below: b) First, we should use the roll-up operation to get the year 2004(rolling-up from the day then month to a year). After getting that, we need to use the slice operation to select (2004). Second, we should use roll-up operation again to get all patients. Then, we need to use the slice operation to select (all). Finally, we get a list of the total fee collected by each doctor in 2004. So, 1. roll up from day to month to year 2. slice for year = “2004” 3. roll up on patient from the individual patient to all 4. slice for patient = “all” 5. get the list of the total fees collected by each doctor in 2004 c) Select doctor, Sum(charge) From fee Where year = 2004 Group by doctor
Read more

Suppose that a data warehouse for Big-University consists of the following four dimensions: student, course, semester, and instructor, and two measures count and avg_grade. When at the lowest conceptual level (e.g., for a given student, course, semester, and instructor combination), the avg_grade measure stores the actual course grade of the student. At higher conceptual levels, avg_grade stores the average grade for the given combination. a) Draw a snowflake schema diagram for the data warehouse. b) Starting with the base cuboid [student, course, semester, instructor], what specific OLAP operations (e.g., roll-up from semester to year) should one perform in order to list the average grade of CS courses for each BigUniversity student. c) If each dimension has five levels (including all), such as “student < major < status < university < all”, how many cuboids will this cube contain (including the base and apex cuboids)?

-
Image
a) A Snowflake Shema is shown in figure below: b) The specific OLAP operations to be performed: 1. Roll-up on course from course_id to department. 2. Roll-up on a student from student_id to university. 3. Dice on course, student with department ="CS" and university = "biguniversity" 4. Drill-down on a student from the university to student_name. c) N = 4 dimensions The cube will contain 54 = 625 cuboids.
Read more