CS 339 Lab 4: SimpleDB Transactions
Assigned: Tuesday, May 23, 2023 Due: Monday, June 5, 2023 11:59
PM Central
In this lab, you will implement a simple locking-based transaction system in
SimpleDB. You will need to add lock and unlock calls at the appropriate places
in your code, as well as code to track the locks held by each transaction and
grant locks to transactions as they are needed.
The remainder of this document describes what is involved in adding transaction
support and provides a basic outline of how you might add this support to your
database.
As with the previous lab, we recommend that you start as early as possible.
Locking and transactions can be quite tricky to debug!
1. Getting started
You should begin by downloading the starter code on Canvas: SimpleDB Lab 4.
Then set up your API - e.g., Ecipse or IntelliJ - as in the previous SimpleDB
labs.
2. Transactions, Locking, and Concurrency Control
Before starting, you should make sure you understand what a transaction is
and how strict two-phase locking (which you will use to ensure isolation and
atomicity of your transactions) works.
In the remainder of this section, we briefly overview these concepts and discuss
how they relate to SimpleDB.
2.1. Transactions
A transaction is a group of database actions (e.g., inserts, deletes, and reads)
that are executed atomically; that is, either all of the actions complete or none
of them do, and it is not apparent to an outside observer of the database that
these actions were not completed as a part of a single, indivisible action.
2.2. The ACID Properties
To help you understand how代写 CS 339 Lab 4 transaction management works in SimpleDB, we
briefly review how it ensures that the ACID properties are satisfied:
• Atomicity: Strict two-phase locking and careful buffer management ensure
atomicity.
• Consistency: The database is transaction consistent by virtue of atomicity. Other consistency issues (e.g., key constraints) are not addressed in
SimpleDB.
1
• Isolation: Strict two-phase locking provides isolation.
• Durability: A FORCE buffer management policy ensures durability (see
Section 2.3 below).
2.3. Recovery and Buffer Management
To simplify your job, we recommend that you implement a NO STEAL/FORCE
buffer management policy.
As we discussed in class, this means that:
• You shouldn’t evict dirty (updated) pages from the buffer pool if they are
locked by an uncommitted transaction (this is NO STEAL).
• On transaction commit, you should force dirty pages to disk (e.g., write
the pages out) (this is FORCE).
To further simplify your life, you may assume that SimpleDB will not crash while
processing a transactionComplete command. Note that these three points
mean that you do not need to implement log-based recovery in this lab, since
you will never need to undo any work (you never evict dirty pages) and you will
never need to redo any work (you force updates on commit and will not crash
during commit processing).
2.4. Granting Locks
You will need to add calls to SimpleDB (in BufferPool, for example), that allow
a caller to request or release a (shared or exclusive) lock on a specific object on
behalf of a specific transaction.
We recommend locking at page granularity; please do not implement table-level
locking (even though it is possible) for simplicity of testing. The rest of this
document and our unit tests assume page-level locking.
You will need to create data structures that keep track of which locks each
transaction holds and check to see if a lock should be granted to a transaction
when it is requested.
You will need to implement shared and exclusive locks; recall that these work as
follows:
• Before a transaction can read an object, it must have a shared lock on it.
• Before a transaction can write an object, it must have an exclusive lock on
it.
• Multiple transactions can have a shared lock on an object.
• Only one transaction may have an exclusive lock on an object.
• If transaction t is the only transaction holding a shared lock on an object
o, t may upgrade its lock on o to an exclusive lock.
If a transaction requests a lock that cannot be immediately granted, your code
should block, waiting for that lock to become available (i.e., be released by another
2
transaction running in a different thread). Be careful about race conditions in
your lock implementation — think about how concurrent invocations to your
lock may affect the behavior. (you way wish to read about Synchronization in
Java).
Exercise 1.
Write the methods that acquire and release locks in BufferPool. Assuming you
are using page-level locking, you will need to complete the following:
• Modify getPage() to block and acquire the desired lock before returning a
page.
• Implement unsafeReleasePage(). This method is primarily used for testing,
and at the end of transactions.
• Implement holdsLock() so that logic in Exercise 2 can determine whether
a page is already locked by a transaction.
You may find it helpful to define a LockManager class that is responsible for
maintaining state about transactions and locks, but the design decision is up to
you.
You may need to implement the next exercise before your code passes the unit
tests in LockingTest.
2.5. Lock Lifetime
You will need to implement strict two-phase locking. This means that transactions
should acquire the appropriate type of lock on any object before accessing that
object and shouldn’t release any locks until after the transaction commits.
Fortunately, the SimpleDB design is such that it is possible to obtain locks on
pages in BufferPool.getPage() before you read or modify them. So, rather
than adding calls to locking routines in each of your operators, we recommend
acquiring locks in getPage(). Depending on your implementation, it is possible
that you may not have to acquire a lock anywhere else. It is up to you to verify
this!
You will need to acquire a shared lock on any page (or tuple) before you read
it, and you will need to acquire an exclusive lock on any page (or tuple) before
you write it. You will notice that we are already passing around Permissions
objects in the BufferPool; these objects indicate the type of lock that the caller
would like to have on the object being accessed (we have given you the code for
the Permissions class.)
Note that your implementation of HeapFile.insertTuple() and HeapFile.deleteTuple(),
as well as the implementation of the iterator returned by HeapFile.iterator()
should access pages using BufferPool.getPage(). Double check that
3
these different uses of getPage() pass the correct permissions object (e.g.,
Permissions.READ_WRITE or Permissions.READ_ONLY). You may also wish to
double check that your implementation of BufferPool.insertTuple() and
BufferPool.deleteTupe() call markDirty() on any of the pages they access
(you should have done this when you implemented this code in lab 2, but we did
not test for this case.)
After you have acquired locks, you will need to think about when to release them
as well. It is clear that you should release all locks associated with a transaction
after it has committed or aborted to ensure strict 2PL. However, it is possible
for there to be other scenarios in which releasing a lock before a transaction
ends might be useful. For instance, you may release a shared lock on a page
after scanning it to find empty slots (as described below).
Exercise 2.
Ensure that you acquire and release locks throughout SimpleDB. Some (but not
necessarily all) actions that you should verify work properly:
• Reading tuples off of pages during a SeqScan (if you implemented locking
in BufferPool.getPage(), this should work correctly as long as your
HeapFile.iterator() uses BufferPool.getPage().)
• Inserting and deleting tuples through BufferPool and HeapFile methods (if
you implemented locking in BufferPool.getPage(), this should work correctly as long as HeapFile.insertTuple() and HeapFile.deleteTuple()
use BufferPool.getPage().)
You will also want to think especially hard about acquiring and releasing locks
in the following situations:
• Adding a new page to a HeapFile. When do you physically write the
page to disk? Are there race conditions with other transactions (on other
threads) that might need special attention at the HeapFile level, regardless
of page-level locking?
• Looking for an empty slot into which you can insert tuples. Most implementations scan pages looking for an empty slot, and will need a READ_ONLY
lock to do this. Surprisingly, however, if a transaction t finds no free slot
on a page p, t may immediately release the lock on p. Although this
apparently contradicts the rules of two-phase locking, it is ok because t
did not use any data from the page, such that a concurrent transaction t’
which updated p cannot possibly effect the answer or outcome of t.
At this point, your code should pass the unit tests in LockingTest.
4
2.6. Implementing NO STEAL
Modifications from a transaction are written to disk only after it commits. This
means we can abort a transaction by discarding the dirty pages and rereading
them from disk. Thus, we must not evict dirty pages. This policy is called NO
STEAL.
You will need to modify the evictPage method in BufferPool. In particular, it
must never evict a dirty page. If your eviction policy prefers a dirty page for
eviction, you will have to find a way to evict an alternative page. In the case
where all pages in the buffer pool are dirty, you should throw a DbException. If
your eviction policy evicts a clean page, be mindful of any locks transactions
may already hold to the evicted page and handle them appropriately in your
implementation.
Exercise 3.
Implement the necessary logic for page eviction without evicting dirty pages in
the evictPage method in BufferPool.
2.7. Transactions
In SimpleDB, a TransactionId object is created at the beginning of each query.
This object is passed to each of the operators involved in the query. When the
query is complete, the BufferPool method transactionComplete is called.
Calling this method either commits or aborts the transaction, specified by the
parameter flag commit. At any point during its execution, an operator may
throw a TransactionAbortedException exception, which indicates an internal
error or deadlock has occurred. The test cases we have provided you with create
the appropriate TransactionId objects, pass them to your operators in the
appropriate way, and invoke transactionComplete when a query is finished.
We have also implemented TransactionId.
Exercise 4.
Implement the transactionComplete() method in BufferPool. Note that
there are two versions of transactionComplete, one which accepts an additional
boolean commit argument, and one which does not. The version without the
additional argument should always commit and so can simply be implemented
by calling transactionComplete(tid, true).
When you commit, you should flush dirty pages associated to the transaction to
disk. When you abort, you should revert any changes made by the transaction
by restoring the page to its on-disk state.
5
Whether the transaction commits or aborts, you should also release any state
the BufferPool keeps regarding the transaction, including releasing any locks
that the transaction held.
At this point, your code should pass the TransactionTest unit test and the
AbortEvictionTest system test. You may find the TransactionTest system
test illustrative, but it will likely fail until you complete the next exercise.
2.8. Deadlocks and Aborts
It is possible for transactions in SimpleDB to deadlock (if you do not understand
why, we recommend reading about deadlocks in Ramakrishnan & Gehrke). You
will need to detect this situation and throw a TransactionAbortedException.
There are many possible ways to detect deadlock. A strawman example would
be to implement a simple timeout policy that aborts a transaction if it has not
completed after a given period of time. For a real solution, you may implement
cycle-detection in a dependency graph data structure as shown in lecture. In
this scheme, you would check for cycles in a dependency graph periodically
or whenever you attempt to grant a new lock, and abort something if a cycle
exists. After you have detected that a deadlock exists, you must decide how to
improve the situation. Assume you have detected a deadlock while transaction t
is waiting for a lock. If you’re feeling homicidal, you might abort all transactions
that t is waiting for; this may result in a large amount of work being undone,
but you can guarantee that t will make progress. Alternately, you may decide to
abort t to give other transactions a chance to make progress. This means that
the end-user will have to retry transaction t.
Another approach is to use global orderings of transactions to avoid building
the wait-for graph. This is sometimes preferred for performance reasons, but
transactions that could have succeeded can be aborted by mistake under this
scheme. Examples include the WAIT-DIE and WOUND-WAIT schemes.
Exercise 5.
Implement deadlock detection or prevention in src/simpledb/BufferPool.java.
You have many design decisions for your deadlock handling system, but it is not
necessary to do something highly sophisticated. We expect you to do better
than a simple timeout on each transaction. A good starting point will be to
implement cycle-detection in a wait-for graph before every lock request, and you
will receive full credit for such an implementation. Please describe your choices
in the lab writeup and list the pros and cons of your choice compared to the
alternatives.
You should ensure that your code aborts transactions properly when a
deadlock occurs, by throwing a TransactionAbortedException exception.
This exception will be caught by the code executing the transaction (e.g.,
6
TransactionTest.java), which should call transactionComplete() to
cleanup after the transaction. You are not expected to automatically restart a
transaction which fails due to a deadlock – you can assume that higher level
code will take care of this.
We have provided some (not-so-unit) tests in test/simpledb/DeadlockTest.java.
They are actually a bit involved, so they may take more than a few seconds to
run (depending on your policy). If they seem to hang indefinitely, then you
probably have an unresolved deadlock. These tests construct simple deadlock
situations that your code should be able to escape.
Note that there are two timing parameters near the top of DeadLockTest.java;
these determine the frequency at which the test checks if locks have been acquired and the waiting time before an aborted transaction is restarted. You
may observe different performance characteristics by tweaking these parameters if you use a timeout-based detection method. The tests will output
TransactionAbortedExceptions corresponding to resolved deadlocks to the
console.
Your code should now should pass the TransactionTest system test (which
may also run for quite a long time depending on your implementation).
At this point, you should have a recoverable database, in the sense that if the
database system crashes (at a point other than transactionComplete()) or if
the user explicitly aborts a transaction, the effects of any running transaction
will not be visible after the system restarts (or the transaction aborts.) You
may wish to verify this by running some transactions and explicitly killing the
database server.
2.9. Design alternatives
During the course of this lab, we have identified some substantial design choices
that you have to make:
• Locking granularity: page-level versus tuple-level
• Deadlock handling: detection vs. prevention, aborting yourself vs. others.
Bonus Exercise 6. (20% extra credit)
For one or more of these choices, implement both alternatives and experimentally
compare their performance charateristics. Include your benchmarking code and
a brief evaluation (possibly with graphs) in your writeup.
You have now completed this lab. Good work!
7
3. Logistics
You must submit your code (see below) as well as a short (2 pages, maximum)
writeup describing your approach. This writeup should:
• Describe any design decisions you made in deadlock handling, and list the
pros and cons of your approach.
• Discuss and justify any changes you made to the API.
• Describe any missing or incomplete elements of your code.
• Describe how long you spent on the lab, and whether there was anything
you found particularly difficult or confusing.
• Describe any extra credit implementation you have done.
3.1. Collaboration
This lab should be manageable for a single person, but if you prefer to work
with a partner, this is also OK. Larger groups are not allowed. Please indicate
clearly who you worked with, if anyone, on your writeup.
3.2. Submitting your assignment
Zip up your code and upload it to Canvas. Place your write-up in a file called
lab4-writeup.txt with your submission in your main source directory (the one
that contains your build.xml). On Linux/MacOS, you can create your hand-in
file by running the following command:
$ zip -r mylabgroup_lab4.zip cs339-lab4
### 3.3. Submitting a bug
SimpleDB is a relatively complex piece of code. It is very possible you are going
to find bugs, inconsistencies, and bad, outdated, or incorrect documentation,
etc.
We ask you, therefore, to do this lab with an adventurous mindset. Don’t get
mad if something is not clear, or even wrong; rather, try to figure it out yourself
or send us a friendly email.
Please submit (friendly!) bug reports to [email protected]. When you
do, please try to include:
• A description of the bug.
• A .java file we can drop in the test/simpledb directory, compile, and run.
• A .txt file with the data that reproduces the bug. We should be able to
convert it to a .dat file using HeapFileEncoder.
You can also post on the class page on Piazza if you feel you have run into a bug.
8
3.4 Grading
75% of your grade will be based on whether or not your code passes the system
test suite we will run over it. These tests will be a superset of the tests we have
provided. Before handing in your code, you should make sure it produces no
errors (passes all of the tests) from both ant test and ant systemtest.
• Given that this lab deals with concurrency, we will rerun the autograder
after the due date to discourage trying buggy code until lucky. It is your
responsibility to ensure that your code reliably passes the tests.
• This lab has a higher percentage of manual grading compared to previous
labs. Specifically, we will be very unhappy if your concurrency handling is
bogus (e.g., inserting Thread.sleep(1000) until a race disappears).
Important: before testing, we will replace your build.xml, HeapFileEncoder.java
and the entire contents of the test directory with our version of these files. This
means you cannot change the format of .dat files! You should also be careful
changing our APIs. You should test that your code compiles the unmodified
tests.
The first 75% of your grade will be based on how your hand-in performs with
our unit tests. An additional 25% of your grade will be based on the quality of
your writeup and our subjective evaluation of your code.
We had a lot of fun designing this assignment, and we hope you enjoy hacking
on it!
WX：codehelp