Class Scheduling in Java
This tutorial provides a walkthrough of designing and building a simple application in Java using FoundationDB. In this tutorial, we use a few simple data modeling techniques. For a more in-depth discussion of data modeling in FoundationDB, see Data Modeling.
The concepts in this tutorial are applicable to all the languages supported by FoundationDB. If you prefer, you can see a version of this tutorial in Python, Ruby, or Go.
First steps
Let’s begin with “Hello world.”
If you have not yet installed FoundationDB, see Getting Started on macOS or Getting Started on Linux.
We’ll start by importing the basic FoundationDB package, as well as the Tuple class:
import com.apple.foundationdb.*;
import com.apple.foundationdb.tuple.Tuple;
Before using the API, we need to specify the API version. This allows programs to maintain compatibility even if the API is modified in future versions. Next, we open a FoundationDB database. The API will connect to the FoundationDB cluster indicated by the default cluster file.
private static final FDB fdb;
private static final Database db;
static {
fdb = FDB.selectAPIVersion(730);
db = fdb.open();
}
We’re ready to use the database. First, let’s write a key-value pair. We do this by executing a transaction with the run() method. We’ll also use methods of the Tuple class to pack() data for storage in the database:
db.run((Transaction tr) -> {
tr.set(Tuple.from("hello").pack(), Tuple.from("world").pack());
return null;
});
When run() returns without exception, the modification is durably stored in FoundationDB! This method creates a transaction with a single modification. We’ll see later how to do multiple operations in a single transaction. For now, let’s read back the data. We’ll use Tuple again to unpack the result as a string:
String hello = db.run((Transaction tr) -> {
byte[] result = tr.get(Tuple.from("hello").pack()).join();
return Tuple.fromBytes(result).getString(0);
});
System.out.println("Hello " + hello);
If this is all working, it looks like we are ready to start building a real application. For reference, here’s the full code for “hello world”:
import com.apple.foundationdb.*;
import com.apple.foundationdb.tuple.Tuple;
public class HelloWorld {
private static final FDB fdb;
private static final Database db;
static {
fdb = FDB.selectAPIVersion(730);
db = fdb.open();
}
public static void main(String[] args) {
// Run an operation on the database
db.run((Transaction tr) -> {
tr.set(Tuple.from("hello").pack(), Tuple.from("world").pack());
return null;
});
// Get the value of 'hello' from the database
String hello = db.run((Transaction tr) -> {
byte[] result = tr.get(Tuple.from("hello").pack()).join();
return Tuple.fromBytes(result).getString(0);
});
System.out.println("Hello " + hello);
}
}
Class scheduling application
Let’s say we’ve been asked to build a class scheduling system for students and administrators. We’ll walk through the design and implementation of this application. Instead of typing everything in as you follow along, look at the Appendix: ClassScheduling.java for a finished version of the program. You may want to refer to this code as we walk through the tutorial.
Requirements
We’ll need to let users list available classes and track which students have signed up for which classes. Here’s a first cut at the functions we’ll need to implement:
availableClasses() // returns list of classes
signup(studentID, class) // signs up a student for a class
drop(studentID, class) // drops a student from a class
Data model
First, we need to design a data model. A data model is just a method for storing our application data using keys and values in FoundationDB. We seem to have two main types of data: (1) a list of classes and (2) a record of which students will attend which classes. Let’s keep attending data like this:
// ("attends", student, class) = ""
We’ll just store the key with a blank value to indicate that a student is signed up for a particular class. For this application, we’re going to think about a key-value pair’s key as a tuple. Encoding a tuple of data elements into a key is a very common pattern for an ordered key-value store.
We’ll keep data about classes like this:
// ("class", class_name) = seatsAvailable
Similarly, each such key will represent an available class. We’ll use seatsAvailable to record the number of seats available.
Transactions
We’re going to rely on the powerful guarantees of transactions to help keep all of our modifications straight, so let’s look at how the FoundationDB Java API lets you write a transactional function. We use the run() method to execute a code block transactionally. Let’s write the simple addClass function we’ll use to populate the database’s class list:
private static void addClass(TransactionContext db, final String c) {
db.run((Transaction tr) -> {
tr.set(Tuple.from("class", c).pack(), encodeInt(100));
return null;
});
}
A function using this approach takes a TransactionContext parameter. When calling such a function, you can pass either a Database or Transaction, each of which are subclasses of TransactionContext. The function to be executed transactionally is parameterized by the Transaction it will use to do reads and writes.
The run() method automatically creates a transaction and implements a retry loop to ensure that the transaction eventually commits.
For a database db:
addClass(db, "class1")
is equivalent to something like:
Transaction t = db.createTransaction();
while (true) {
try {
tr.set(Tuple.from("class", "class1").pack(), encodeInt(100));
t.commit().join();
} catch (RuntimeException e) {
t = t.onError(e).join();
}
}
If instead you pass a Transaction for the TransactionContext parameter, the transaction will be used directly, and it is assumed that the caller implements appropriate retry logic for errors. This permits functions using this pattern to be composed into larger transactions.
Note that by default, the operation will be retried an infinite number of times and the transaction will never time out. It is therefore recommended that the client choose a default transaction retry limit or timeout value that is suitable for their application. This can be set either at the transaction level using the setRetryLimit or setTimeout transaction options or at the database level with the setTransactionRetryLimit or setTransactionTimeout database options. For example, one can set a one minute timeout on each transaction and a default retry limit of 100 by calling:
db.options().setTransactionTimeout(60000); // 60,000 ms = 1 minute
db.options().setTransactionRetryLimit(100);
Making some sample classes
Let’s make some sample classes and put them in the classNames variable. We’ll make individual classes from combinations of class types, levels, and times:
// Generate 1,620 classes like '9:00 chem for dummies'
private static List<String> levels = Arrays.asList("intro", "for dummies",
"remedial", "101", "201", "301", "mastery", "lab", "seminar");
private static List<String> types = Arrays.asList("chem", "bio", "cs",
"geometry", "calc", "alg", "film", "music", "art", "dance");
private static List<String> times = Arrays.asList("2:00", "3:00", "4:00",
"5:00", "6:00", "7:00", "8:00", "9:00", "10:00", "11:00", "12:00", "13:00",
"14:00", "15:00", "16:00", "17:00", "18:00", "19:00");
private static List<String> classNames = initClassNames();
private static List<String> initClassNames() {
List<String> classNames = new ArrayList<String>();
for (String level: levels)
for (String type: types)
for (String time: times)
classNames.add(time + " " + type + " " + level);
return classNames;
}
Initializing the database
We initialize the database with our class list:
private static void init(Database db) {
db.run((Transaction tr) -> {
tr.clear(Tuple.from("attends").range());
tr.clear(Tuple.from("class").range());
for (String className: classNames)
addClass(tr, className);
return null;
});
}
After init() is run, the database will contain all of the sample classes we created above.
Listing available classes
Before students can do anything else, they need to be able to retrieve a list of available classes from the database. Because FoundationDB sorts its data by key and therefore has efficient range-read capability, we can retrieve all of the classes in a single database call. We find this range of keys with getRange():
private static List<String> availableClasses(TransactionContext db) {
return db.run((Transaction tr) -> {
List<String> classNames = new ArrayList<String>();
for(KeyValue kv: tr.getRange(Tuple.from("class").range()))
classNames.add(Tuple.fromBytes(kv.getKey()).getString(1));
return classNames;
});
}
In general, the Tuple.range() method returns a Range representing all the key-value pairs starting with the specified tuple. In this case, we want all classes, so we call Tuple.range() with the tuple ("class"). The getRange() method returns an iterable of the key-values specified by its range. To extract the class name, we unpack the key using Tuple.fromBytes() and take its second part. (The first part is the prefix "class".)
Signing up for a class
We finally get to the crucial function. A student has decided on a class (by name) and wants to sign up. The signup function will take a student (s) and a class (c):
private static void signup(TransactionContext db, final String s, final String c) {
db.run((Transaction tr) -> {
byte[] rec = Tuple.from("attends", s, c).pack();
tr.set(rec, Tuple.from("").pack());
return null;
});
}
We simply insert the appropriate record (with a blank value).
Dropping a class
Dropping a class is similar to signing up:
private static void drop(TransactionContext db, final String s, final String c) {
db.run((Transaction tr) -> {
byte[] rec = Tuple.from("attends", s, c).pack();
tr.clear(rec);
return null;
});
}
Of course, to actually drop the student from the class, we need to be able to delete a record from the database. We do this with the clear() method.
Done?
We report back to the project leader that our application is done—students can sign up for, drop, and list classes. Unfortunately, we learn that a new problem has been discovered: popular classes are being over-subscribed. Our application now needs to enforce the class size constraint as students add and drop classes.
Seats are limited!
Let’s go back to the data model. Remember that we stored the number of seats in the class in the value of the key-value entry in the class list. Let’s refine that a bit to track the remaining number of seats in the class. The initialization can work the same way (in our example, all classes initially have 100 seats), but the availableClasses, signup, and drop functions are going to have to change. Let’s start with availableClasses:
private static List<String> availableClasses(TransactionContext db) {
return db.run((Transaction tr) -> {
List<String> classNames = new ArrayList<String>();
for(KeyValue kv: tr.getRange(Tuple.from("class").range())) {
if (decodeInt(kv.getValue()) > 0)
classNames.add(Tuple.fromBytes(kv.getKey()).getString(1));
}
return classNames;
});
}
This is easy – we simply add a condition to check that the value is non-zero. Let’s check out signup next:
private static void signup(TransactionContext db, final String s, final String c) {
db.run((Transaction tr) -> {
byte[] rec = Tuple.from("attends", s, c).pack();
if (tr.get(rec).join() != null)
return null; // already signed up
int seatsLeft = decodeInt(tr.get(Tuple.from("class", c).pack()).join());
if (seatsLeft == 0)
throw new IllegalStateException("No remaining seats");
tr.set(Tuple.from("class", c).pack(), encodeInt(seatsLeft - 1));
tr.set(rec, Tuple.from("").pack());
return null;
});
}
We now have to check that we aren’t already signed up, since we don’t want a double sign up to decrease the number of seats twice. Then we look up how many seats are left to make sure there is a seat remaining so we don’t push the counter into the negative. If there is a seat remaining, we decrement the counter.
Concurrency and consistency
The signup function is starting to get a bit complex; it now reads and writes a few different key-value pairs in the database. One of the tricky issues in this situation is what happens as multiple clients/students read and modify the database at the same time. Couldn’t two students both see one remaining seat and sign up at the same time?
These are tricky issues without simple answers—unless you have transactions! Because these functions are defined as FoundationDB transactions, we can have a simple answer: Each transactional function behaves as if it is the only one modifying the database. There is no way for a transaction to ‘see’ another transaction change the database, and each transaction ensures that either all of its modifications occur or none of them do.
Looking deeper, it is, of course, possible for two transactions to conflict. For example, if two people both see a class with one seat and sign up at the same time, FoundationDB must allow only one to succeed. This causes one of the transactions to fail to commit (which can also be caused by network outages, crashes, etc.). To ensure correct operation, applications need to handle this situation, usually via retrying the transaction. In this case, the conflicting transaction will be retried automatically by the run() method and will eventually lead to the correct result, a ‘No remaining seats’ exception.
Idempotence
Occasionally, a transaction might be retried even after it succeeds (for example, if the client loses contact with the cluster at just the wrong moment). This can cause problems if transactions are not written to be idempotent, i.e. to have the same effect if committed twice as if committed once. There are generic design patterns for making any transaction idempotent, but many transactions are naturally idempotent. For example, all of the transactions in this tutorial are idempotent.
Dropping with limited seats
Let’s finish up the limited seats feature by modifying the drop function:
private static void drop(TransactionContext db, final String s, final String c) {
db.run((Transaction tr) -> {
byte[] rec = Tuple.from("attends", s, c).pack();
if (tr.get(rec).join() == null)
return null; // not taking this class
byte[] classKey = Tuple.from("class", c).pack();
tr.set(classKey, encodeInt(decodeInt(tr.get(classKey).join()) + 1));
tr.clear(rec);
return null;
});
}
This case is easier than signup because there are no constraints we can hit. We just need to make sure the student is in the class and to “give back” one seat when the student drops.
More features?!
Of course, as soon as our new version of the system goes live, we hear of a trick that certain students are using. They are signing up for all classes immediately, and only later dropping those that they don’t want to take. This has led to an unusable system, and we have been asked to fix it. We decide to limit students to five classes:
private static void signup(TransactionContext db, final String s, final String c) {
db.run((Transaction tr) -> {
byte[] rec = Tuple.from("attends", s, c).pack();
if (tr.get(rec).join() != null)
return null; // already signed up
int seatsLeft = decodeInt(tr.get(Tuple.from("class", c).pack()).join());
if (seatsLeft == 0)
throw new IllegalStateException("No remaining seats");
List<KeyValue> classes = tr.getRange(Tuple.from("attends", s).range()).asList().join();
if (classes.size() == 5)
throw new IllegalStateException("Too many classes");
tr.set(Tuple.from("class", c).pack(), encodeInt(seatsLeft - 1));
tr.set(rec, Tuple.from("").pack());
return null;
});
}
Fortunately, we decided on a data model that keeps all of the attending records for a single student together. With this approach, we can use a single range read to retrieve all the classes that a student attends. We simply throw an exception if the number of classes has reached the limit of five.
Composing transactions
Oh, just one last feature, we’re told. We have students that are trying to switch from one popular class to another. By the time they drop one class to free up a slot for themselves, the open slot in the other class is gone. By the time they see this and try to re-add their old class, that slot is gone too! So, can we make it so that a student can switch from one class to another without this worry?
Fortunately, we have FoundationDB, and this sounds an awful lot like the transactional property of atomicity—the all-or-nothing behavior that we already rely on. All we need to do is to compose the drop and signup functions into a new switchClasses function. This makes the switchClasses function exceptionally easy:
private static void switchClasses(TransactionContext db, final String s, final String oldC, final String newC) {
db.run((Transaction tr) -> {
drop(tr, s, oldC);
signup(tr, s, newC);
return null;
});
}
The simplicity of this implementation belies the sophistication of what FoundationDB is taking care of for us.
By dropping the old class and signing up for the new one inside a single transaction, we ensure that either both steps happen, or that neither happens. The first notable thing about the switchClasses function is that it is transactional, but it also calls the transactional functions signup and drop. Because these transactional functions can accept either a database or an existing transaction as their db parameter, the switchClass function can be called with a database by a simple client, and a new transaction will be automatically created. However, once this transaction is created and passed in as tr, the calls to drop and signup both share the same tr. This ensures that they see each other’s modifications to the database, and all of the changes that both of them make in sequence are made transactionally when the switchClass function returns. This compositional capability is very powerful.
Also note that, if an exception is raised, for example, in signup, the exception is not caught by switchClasses and so will be thrown to the calling function. In this case, the transaction object (owned by the run() method) is destroyed, automatically rolling back all database modifications, leaving the database completely unchanged by the half-executed function.
Are we done?
Yep, we’re done and ready to deploy. If you want to see this entire application in one place plus some multithreaded testing code to simulate concurrency, look at the Appendix: ClassScheduling.java, below.
Deploying and scaling
Since we store all state for this application in FoundationDB, deploying and scaling this solution up is impressively painless. Just run a web server, the UI, this back end, and point the whole thing at FoundationDB. We can run as many computers with this setup as we want, and they can all hit the database at the same time because of the transactional integrity of FoundationDB. Also, since all of the state in the system is stored in the database, any of these computers can fail without any lasting consequences.
Next steps
See Data Modeling for guidance on using tuple and subspaces to enable effective storage and retrieval of data.
See Developer Guide for general guidance on development using FoundationDB.
See the API References for detailed API documentation.
Appendix: ClassScheduling.java
Here’s the code for the scheduling tutorial:
import java.nio.ByteBuffer;
import java.util.Arrays;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import com.apple.foundationdb.*;
import com.apple.foundationdb.tuple.Tuple;
// Data model:
// ("attends", student, class) = ""
// ("class", class_name) = seatsLeft
public class ClassScheduling {
private static final FDB fdb;
private static final Database db;
static {
fdb = FDB.selectAPIVersion(730);
db = fdb.open();
db.options().setTransactionTimeout(60000); // 60,000 ms = 1 minute
db.options().setTransactionRetryLimit(100);
}
// Generate 1,620 classes like '9:00 chem for dummies'
private static List<String> levels = Arrays.asList("intro", "for dummies",
"remedial", "101", "201", "301", "mastery", "lab", "seminar");
private static List<String> types = Arrays.asList("chem", "bio", "cs",
"geometry", "calc", "alg", "film", "music", "art", "dance");
private static List<String> times = Arrays.asList("2:00", "3:00", "4:00",
"5:00", "6:00", "7:00", "8:00", "9:00", "10:00", "11:00", "12:00", "13:00",
"14:00", "15:00", "16:00", "17:00", "18:00", "19:00");
private static List<String> classNames = initClassNames();
private static List<String> initClassNames() {
List<String> classNames = new ArrayList<String>();
for (String level: levels)
for (String type: types)
for (String time: times)
classNames.add(time + " " + type + " " + level);
return classNames;
}
private static void addClass(TransactionContext db, final String c) {
db.run((Transaction tr) -> {
tr.set(Tuple.from("class", c).pack(), encodeInt(100));
return null;
});
}
private static byte[] encodeInt(int value) {
byte[] output = new byte[4];
ByteBuffer.wrap(output).putInt(value);
return output;
}
private static int decodeInt(byte[] value) {
if (value.length != 4)
throw new IllegalArgumentException("Array must be of size 4");
return ByteBuffer.wrap(value).getInt();
}
private static void init(Database db) {
db.run((Transaction tr) -> {
tr.clear(Tuple.from("attends").range());
tr.clear(Tuple.from("class").range());
for (String className: classNames)
addClass(tr, className);
return null;
});
}
private static List<String> availableClasses(TransactionContext db) {
return db.run((Transaction tr) -> {
List<String> classNames = new ArrayList<String>();
for(KeyValue kv: tr.getRange(Tuple.from("class").range())) {
if (decodeInt(kv.getValue()) > 0)
classNames.add(Tuple.fromBytes(kv.getKey()).getString(1));
}
return classNames;
});
}
private static void drop(TransactionContext db, final String s, final String c) {
db.run((Transaction tr) -> {
byte[] rec = Tuple.from("attends", s, c).pack();
if (tr.get(rec).join() == null)
return null; // not taking this class
byte[] classKey = Tuple.from("class", c).pack();
tr.set(classKey, encodeInt(decodeInt(tr.get(classKey).join()) + 1));
tr.clear(rec);
return null;
});
}
private static void signup(TransactionContext db, final String s, final String c) {
db.run((Transaction tr) -> {
byte[] rec = Tuple.from("attends", s, c).pack();
if (tr.get(rec).join() != null)
return null; // already signed up
int seatsLeft = decodeInt(tr.get(Tuple.from("class", c).pack()).join());
if (seatsLeft == 0)
throw new IllegalStateException("No remaining seats");
List<KeyValue> classes = tr.getRange(Tuple.from("attends", s).range()).asList().join();
if (classes.size() == 5)
throw new IllegalStateException("Too many classes");
tr.set(Tuple.from("class", c).pack(), encodeInt(seatsLeft - 1));
tr.set(rec, Tuple.from("").pack());
return null;
});
}
private static void switchClasses(TransactionContext db, final String s, final String oldC, final String newC) {
db.run((Transaction tr) -> {
drop(tr, s, oldC);
signup(tr, s, newC);
return null;
});
}
//
// Testing
//
private static void simulateStudents(int i, int ops) {
String studentID = "s" + Integer.toString(i);
List<String> allClasses = classNames;
List<String> myClasses = new ArrayList<String>();
String c;
String oldC;
String newC;
Random rand = new Random();
for (int j=0; j<ops; j++) {
int classCount = myClasses.size();
List<String> moods = new ArrayList<String>();
if (classCount > 0) {
moods.add("drop");
moods.add("switch");
}
if (classCount < 5)
moods.add("add");
String mood = moods.get(rand.nextInt(moods.size()));
try {
if (allClasses.isEmpty())
allClasses = availableClasses(db);
if (mood.equals("add")) {
c = allClasses.get(rand.nextInt(allClasses.size()));
signup(db, studentID, c);
myClasses.add(c);
} else if (mood.equals("drop")) {
c = myClasses.get(rand.nextInt(myClasses.size()));
drop(db, studentID, c);
myClasses.remove(c);
} else if (mood.equals("switch")) {
oldC = myClasses.get(rand.nextInt(myClasses.size()));
newC = allClasses.get(rand.nextInt(allClasses.size()));
switchClasses(db, studentID, oldC, newC);
myClasses.remove(oldC);
myClasses.add(newC);
}
} catch (Exception e) {
System.out.println(e.getMessage() + "Need to recheck available classes.");
allClasses.clear();
}
}
}
private static void runSim(int students, final int ops_per_student) throws InterruptedException {
List<Thread> threads = new ArrayList<Thread>(students);//Thread[students];
for (int i = 0; i < students; i++) {
final int j = i;
threads.add(new Thread(() -> simulateStudents(j, ops_per_student)) );
}
for (Thread thread: threads)
thread.start();
for (Thread thread: threads)
thread.join();
System.out.format("Ran %d transactions%n", students * ops_per_student);
}
public static void main(String[] args) throws InterruptedException {
init(db);
System.out.println("Initialized");
runSim(10,10);
}
}