answer
Question 1
Overall code organization
interface directory contains the interface definition for Cart , CartItem , Item ,
Supermarket and SupermarketSerializer . Business directory contains the
implementation for the Cart and Supermarket interface. It also contains both mutable and
immutable version of CartItem and Item interfaces. The client directory contains client
HTTP proxy classes for Cart and Supermarket . The JUnit tests are in tests subdirectory.
The wordloads contains the code for experiment. Directory server contains HTTP Server
classes for Cart and Supermarket . The utils directory contains classes utility classes used
in implementation such as serializer classes, HTTP request and response class and exception
classes.
RPC semantics
At-most-once is imlemented between clients and the Cart or Supermarket, and between the
Cart and the Supermarket.
Failure containment
When supermarket fails, the exception is catched in the cart instance and the exception object
is stored in
the response class and sent to client. Thus when Supermarket instance fails, Cart instances
should still be able to respond to queries on the state of shopping carts, but will raise
exceptions when some operations, namely, item additions or checkout, are invoked.
All-or-nothing atomicity
For Cart , only method add and checkout invoked the supermarket method. When
Supermarket fails, add will not add new item to cart, nothing happens. In checkout
method, the Cart is cleared only when the invoke of updateStocks success. For
Supermarket , the actual operations are conducted only when all the ids of the input are valid.
Thus, if one of id is invalid, exception throwed and nothing happens.
Question 2
Method
In CartImp , I define following instance variable.
private Map
new HashMap<>();
1
Each cart is a ConcurrentHashMap mapping cart item id to cart item. The
ConcurrentHashMap ensures the atomicity of adding or removing cart items. The atomicity of
change cart item is achieved by using ReentrantReadWriteLock in MutableCartItem class.
A single ReentrantReadWriteLock is used in the MutableCartItem class. When reading
quantity , readlock is used. When chaning quantity , the writelock is used.
Correctness
Hashmap level atomicity is achieved due to the fact of the implementation of
ConcurrentHashMap in the library. MutableCartItem level atomicity is achieved using the
ReentrantReadWriteLock . The overall effect is equivalent to a single global lock.
Issue of reads on predicates vs. multi-granularity locking
We don’t need to consider multi-granularity locking. There are just two level of hierarchy: cart
contains items. It is not necessary to use the more complex multi-granularity locking. Predicates
locking is not considered either. Because it is expensive to implement.
Performance
My method will allow multiple threads to get the cart items. It even allows multiple threads to
updates of different cart items. It has high concurrency.
Question 3
Method
In SupermarketImp , I define following instance variable.
It is a ConcurrentHashMap mapping item id to item. The ConcurrentHashMap ensures the
atomicity of adding or removing items. The atomicity of updating item is achieved by using
ReentrantReadWriteLock in MutableItem class. A single ReentrantReadWriteLock is
used in the MutableItem class. When reading the fields, readlock is used. When chaning
the fields, the writelock is used.
Correctness
Hashmap level atomicity is achieved due to the implementation of ConcurrentHashMap is
thread-safe. MutableCartItem level atomicity is achieved using the
ReentrantReadWriteLock . The overall effect is equivalent to a single global lock.
Issue of reads on predicates vs. multi-granularity locking
ConcurrentHashMap
We don’t need to consider multi-granularity locking. There are just two level of hierarchy:
supermarket contains items. It is not necessary to use the more complex multi-granularity
locking. Predicates locking is not considered either. Because it is expensive to implement.
Performance
My method will allow multiple threads to retrive the items. It even allows multiple threads to
updates of different items. It has high concurrency.
Question 4
There are two test classes CartTest and SupermarketTest to test for Cart and
Supermarket both for local test and RPC test. The localTest indicates which kind of test is
performed. There are two kind of tests. One kind is for testing the basic correctness of
implementation in single thread. It tests both the normal cases and cases where exceptions are
expected to be thrown.
Another is to test before-or-after atomicity. In the test testForConcurrency1 in
SupermarketTest , thread 1 repeatedly adds items to one cart and check out which will
update the corresponding items’ stock in the supermarket. thread 2 repeatedly calls the
updateStocks to replenish the corresponding items. The amount of stocks thread 1
consumes eqaul to the amount thread 2 increases. The test method runs the two threads at
the same time, when they finish, assert that the amount of stocks don’t change. In the test
testForConcurrency2 in SupermarketTest , thread 1 repeatedly call updateStocks
that increase the stocks and then updateStocks that decreases the stocks , thread 2
repeatedly call getItems , assert that the getItems returns the amount of stocks either after
decrease or after increase. In the test testForConcurrency1 in CartTest , thread 1
repeatedly adds items to one cart . thread 2 repeatedly remove the same items from the
same cart. The amount of items thread 1 adds eqaul to the amount thread 2 removes. The
test method runs the two threads at the same time, when they finish, assert that the quantity of
the item doesn’t change. In the test testForConcurrency2 in CartTest , thread 1
repeatedly call add and then remove , thread 2 repeatedly call getCartItems , assert that
the getCartItems returns the quantity of cart item either after add or after remove .
Question 5
Workload Design
There are two kinds of access to Supermarket service: one is by Cart and another is by
Admin Client . For Cart , the getItems call is invoked when Stock Client add a Cart
Item to the Cart and updateStocks is invoked when Mobile Client checkout. Assuming
on average, custom add 10 different items before checkout. Thus in runCartInteraction , it
calls updateStocks with probability of 0.1 and calls getItems with probability 0.9. For
Admin Client , it mainly uses updateStocks to replenish items. It calls updateStocks with
probability 0.8 and calls getItems with probability 0.2. Since Cart interaction is much more
frequent than Admin Client interaction. runAdminClientInteraction is called with
probability 0.01 and runCartInteraction is called with probability 0.99.
Experimental Setup
Hardware: MacBook Pro (15-inch, 2016) with processor 2.7 GHz Intel Core i7 and memory 16
GB 2133 MHz LPDDR3. With more powerful hardware, the throughput is expected to increase.
Data: 100000 items are generated in the supermarket initially.
Configuration: Use binary serialization in RPC. Worker with 5000 warm up runs and 20000
actual runs. Max thread pool set to 100 and min thread pool set to 10 in
SupermarketHTTPServer .
Each worker thread records the successful interactions and the time taken. Total successful
interactions divided by total time taken to get the throughput.
Discussion of Results
Above graph shows the throughput changes with number of client threads. We can see that the
throughput tends to decrease when we increase the number of clients. This maches my
expectations. More clients will compete for the computation resources, and each client will take
more time, thus the throughput decreases.
Question 1
Overall code organization
RPC semantics
Failure containment
All-or-nothing atomicity
Question 2
Method
Correctness
Issue of reads on predicates vs. multi-granularity locking
Performance
Question 3
Method
Correctness
Issue of reads on predicates vs. multi-granularity locking
Performance
Question 4
Question 5
Workload Design
Experimental Setup
Discussion of Results