ZooKeeper:
- For building distributed applications using Hadoop distributed coordination service
- When message is sent between two nodes and the network fails, sender does not know whether the receiver got the message.
- It have have gotten before network failed, or it may not have or perhaps the receivers process died.
- Only way sender can find out what happened is to reconnect to receiver and ask it.
- This is partial failure, when we dont even know whether operation failed.
-ZooKeeper gives you a set of tools to build distributed applications that can safely handle partial failures.
Zookeeper has following characteristics:
- It is simple: it is stripped down filesystem that exposes a few simple operations, and some extra abstractions such as ordering and notifications.
- It is expressive: can be used to build large class of coordination data structures and protocols. Ex: distributed queues distributed locks, and leader election among group of peers.
- Highly available: runs on collection of machines and is designed to be highly available, so applications can depend on it. It helps to avoid single point of failure in your system, so you can build a reliable application.
- Loosely coupled interactions: support participants who do not need to know about one another.
- It is library: provides open source, shared repository of implementations and recipes of common coordination patterns.
- High performance: throughput for ZooKeeper cluster has been benchmarked at over 10,000 operations per second.
Installing and Running ZooKeeper:
- When trying out ZooKeeper for the first time, it’s simplest to run it in standalone mode
with a single ZooKeeper server. You can do this on a development machine, for example.
ZooKeeper requires Java 6 to run, so make sure you have it installed first.
You don’t need Cygwin to run ZooKeeper on Windows, since there are Windows versions of the ZooKeeper scripts.
(Windows is supported only as a development platform, not as a
production platform.)
Download a stable release of ZooKeeper from the Apache ZooKeeper releases page at
http://zookeeper.apache.org/releases.html, and unpack the tarball in a suitable location:
% tar xzf zookeeper-x.y.z.tar.gz
ZooKeeper provides a few binaries to run and interact with the service, and it’s convenient
to put the directory containing the binaries on your command-line path:
% export ZOOKEEPER_INSTALL=/home/tom/zookeeper-x.y.z
% export PATH=$PATH:$ZOOKEEPER_INSTALL/bin
Before running the ZooKeeper service, we need to set up a configuration file. The configuration
file is conventionally called zoo.cfg and placed in the conf subdirectory (although you can also place it in /etc/zookeeper, or in the directory defined by the ZOOCFGDIR environment variable, if set). Here’s an example:
tickTime=2000
dataDir=/Users/tom/zookeeper
clientPort=2181
This is a standard Java properties file, and the three properties defined in this example
are the minimum required for running ZooKeeper in standalone mode. Briefly,
tickTime is the basic time unit in ZooKeeper (specified in milliseconds), dataDir is the
local filesystem location where ZooKeeper stores persistent data, and clientPort is the
port the ZooKeeper listens on for client connections (2181 is a common choice). You
should change dataDir to an appropriate setting for your system.
With a suitable configuration defined, we are now ready to start a local ZooKeeper
server:
% zkServer.sh start
To check whether ZooKeeper is running, send the ruok command (“Are you OK?”) to
the client port using nc (telnet works, too):
% echo ruok | nc localhost 2181
imok
The connect() method has now returned, and the next method to be invoked on the
CreateGroup is the create() method. In this method, we create a new ZooKeeper znode
using the create() method on the ZooKeeper instance. The arguments it takes are the
path (represented by a string), the contents of the znode (a byte array, null here), an
access control list (or ACL for short, which here is a completely open ACL, allowing
any client to read or write the znode), and the nature of the znode to be created.
Znodes may be ephemeral or persistent. An ephemeral znode will be deleted by the
ZooKeeper service when the client that created it disconnects, either by explicitly disconnecting
or if the client terminates for whatever reason. A persistent znode, on the other hand, is not deleted when the client disconnects. We want the znode representing a group to live longer than the lifetime of the program that creates it, so we create a persistent znode.
The return value of the create() method is the path that was created by ZooKeeper.
We use it to print a message that the path was successfully created. We will see how
the path returned by create() may differ from the one passed into the method when
we look at sequential znodes.
To see the program in action, we need to have ZooKeeper running on the local machine,
and then we can type:
% export CLASSPATH=ch14/target/classes/:$ZOOKEEPER_INSTALL/*:$ZOOKEEPER_INSTALL/lib/*:\
$ZOOKEEPER_INSTALL/conf
% java CreateGroup localhost zoo
Created /zoo
Joining a Group:
- The next part of the application is a program to register a member in a group. Each
member will run as a program and join a group. When the program exits, it should be
removed from the group, which we can do by creating an ephemeral znode that represents
it in the ZooKeeper namespace.
The JoinGroup program implements this idea, and its listing is in Example. The
logic for creating and connecting to a ZooKeeper instance has been refactored into a base
class, ConnectionWatcher, and appears in Example.
Example: A program that joins a group
public class JoinGroup extends ConnectionWatcher {
public void join(String groupName, String memberName) throws KeeperException,
InterruptedException {
String path = "/" + groupName + "/" + memberName;
String createdPath = zk.create(path, null/*data*/, Ids.OPEN_ACL_UNSAFE,
CreateMode.EPHEMERAL);
System.out.println("Created " + createdPath);
}
public static void main(String[] args) throws Exception {
JoinGroup joinGroup = new JoinGroup();
joinGroup.connect(args[0]);
joinGroup.join(args[1], args[2]);
// stay alive until process is killed or thread is interrupted
Thread.sleep(Long.MAX_VALUE);
}
}
Example: A helper class that waits for the connection to ZooKeeper to be established
public class ConnectionWatcher implements Watcher {
private static final int SESSION_TIMEOUT = 5000;
protected ZooKeeper zk;
private CountDownLatch connectedSignal = new CountDownLatch(1);
public void connect(String hosts) throws IOException, InterruptedException {
zk = new ZooKeeper(hosts, SESSION_TIMEOUT, this);
connectedSignal.await();
}
@Override
public void process(WatchedEvent event) {
if (event.getState() == KeeperState.SyncConnected) {
connectedSignal.countDown();
}
}
public void close() throws InterruptedException {
zk.close();
}
}
The code for JoinGroup is very similar to CreateGroup. It creates an ephemeral znode as
a child of the group znode in its join() method, then simulates doing work of some
kind by sleeping until the process is forcibly terminated. Later, you will see that upon
termination, the ephemeral znode is removed by ZooKeeper.
Listing Members in a Group:
- Example: A program to list the members in a group
public class ListGroup extends ConnectionWatcher {
public void list(String groupName) throws KeeperException,
InterruptedException {
String path = "/" + groupName;
try {
List<String> children = zk.getChildren(path, false);
if (children.isEmpty()) {
System.out.printf("No members in group %s\n", groupName);
System.exit(1);
}
for (String child : children) {
System.out.println(child);
}
} catch (KeeperException.NoNodeException e) {
System.out.printf("Group %s does not exist\n", groupName);
System.exit(1);
}
}
public static void main(String[] args) throws Exception {
ListGroup listGroup = new ListGroup();
listGroup.connect(args[0]);
listGroup.list(args[1]);
listGroup.close();
}
}
In the list() method, we call getChildren() with a znode path and a watch flag to
retrieve a list of child paths for the znode, which we print out. Placing a watch on a
znode causes the registered Watcher to be triggered if the znode changes state. Although
we’re not using it here, watching a znode’s children would permit a program to get
notifications of members joining or leaving the group, or of the group being deleted.
We catch KeeperException.NoNodeException, which is thrown in the case when the
group’s znode does not exist.
Let’s see ListGroup in action. As expected, the zoo group is empty, since we haven’t
added any members yet:
% java ListGroup localhost zoo
No members in group zoo
We can use JoinGroup to add some members. We launch them as background processes,
since they don’t terminate on their own (due to the sleep statement):
% java JoinGroup localhost zoo duck &
% java JoinGroup localhost zoo cow &
% java JoinGroup localhost zoo goat &
% goat_pid=$!
The last line saves the process ID of the Java process running the program that adds
goat as a member. We need to remember the ID so that we can kill the process in a
moment, after checking the members:
% java ListGroup localhost zoo
goat
duck
cow
To remove a member, we kill its process:
% kill $goat_pid
And a few seconds later, it has disappeared from the group because the process’s ZooKeeper
session has terminated (the timeout was set to 5 seconds) and its associated
ephemeral node has been removed:
% java ListGroup localhost zoo
duck
cow
Let’s stand back and see what we’ve built here. We have a way of building up a list of
a group of nodes that are participating in a distributed system. The nodes may have no
knowledge of each other. A client that wants to use the nodes in the list to perform
some work, for example, can discover the nodes without them being aware of the client’s
existence.
Finally, note that group membership is not a substitution for handling network errors
when communicating with a node. Even if a node is a group member, communications
with it may fail, and such failures must be handled in the usual ways (retrying, trying
a different member of the group, and so on).
ZooKeeper command-line tools:
ZooKeeper comes with a command-line tool for interacting with the ZooKeeper namespace.
We can use it to list the znodes under the /zoo znode as follows:
% zkCli.sh localhost ls /zoo
Processing ls
WatchedEvent: Server state change. New state: SyncConnected
[duck, cow]
Deleting a group:
- To round off the example, let’s see how to delete a group. The ZooKeeper class provides
a delete() method that takes a path and a version number. ZooKeeper will delete a
znode only if the version number specified is the same as the version number of the
znode it is trying to delete, an optimistic locking mechanism that allows clients to detect
conflicts over znode modification. You can bypass the version check, however, by using
a version number of –1 to delete the znode regardless of its version number.
There is no recursive delete operation in ZooKeeper, so you have to delete child znodes
before parents. This is what we do in the DeleteGroup class, which will remove a group
and all its members.
Example: A program to delete a group and its members
public class DeleteGroup extends ConnectionWatcher {
public void delete(String groupName) throws KeeperException,
InterruptedException {
String path = "/" + groupName;
try {
List<String> children = zk.getChildren(path, false);
for (String child : children) {
zk.delete(path + "/" + child, -1);
}
zk.delete(path, -1);
} catch (KeeperException.NoNodeException e) {
System.out.printf("Group %s does not exist\n", groupName);
System.exit(1);
}
}
public static void main(String[] args) throws Exception {
DeleteGroup deleteGroup = new DeleteGroup();
deleteGroup.connect(args[0]);
deleteGroup.delete(args[1]);
deleteGroup.close();
}
}
Finally, we can delete the zoo group that we created earlier:
% java DeleteGroup localhost zoo
% java ListGroup localhost zoo
Group zoo does not exist
ZooKeeper Service:
ZooKeeper is a highly available, high-performance coordination service. In this section,
we look at the nature of the service it provides: its model, operations, and
implementation.
Data Model:
ZooKeeper maintains a hierarchical tree of nodes called znodes. A znode stores data
and has an associated ACL. ZooKeeper is designed for coordination (which typically
uses small data files), not high-volume data storage, so there is a limit of 1 MB on the
amount of data that may be stored in any znode.
Data access is atomic. A client reading the data stored at a znode will never receive only
some of the data; either the data will be delivered in its entirety, or the read will fail.
Similarly, a write will replace all the data associated with a znode. ZooKeeper guarantees
that the write will either succeed or fail; there is no such thing as a partial write, where only
someof the data written by the client is stored.
ZooKeeper does not support an append operation. These characteristics contrast with HDFS,
which is designed for high-volume data storage, with streaming data access, and provides an append
operation.
Znodes are referenced by paths, which in ZooKeeper are represented as slash-delimited
Unicode character strings, like filesystem paths in Unix. Paths must be absolute, so
they must begin with a slash character. Furthermore, they are canonical, which means
that each path has a single representation, and so paths do not undergo resolution. For
example, in Unix, a file with the path /a/b can equivalently be referred to by the
path /a/./b, since “.” refers to the current directory at the point it is encountered in the
path. In ZooKeeper, “.” does not have this special meaning and is actually illegal as a
path component (as is “..” for the parent of the current directory).
Path components are composed of Unicode characters, with a few restrictions (these
are spelled out in the ZooKeeper reference documentation). The string “zookeeper” is
a reserved word and may not be used as a path component. In particular, ZooKeeper
uses the /zookeeper subtree to store management information, such as information on
quotas.
Note that paths are not URIs, and they are represented in the Java API by a
java.lang.String, rather than the Hadoop Path class (or by the java.net.URI class, for
that matter).
Znodes have some properties that are very useful for building distributed applications,
which we discuss in the following sections.
Ephemeral Znodes:
Znodes can be one of two types: ephemeral or persistent. A znode’s type is set at creation
time and may not be changed later. An ephemeral znode is deleted by ZooKeeper when
the creating client’s session ends. By contrast, a persistent znode is not tied to the client’s
session and is deleted only when explicitly deleted by a client (not necessarily the one
that created it). An ephemeral znode may not have children, not even ephemeral ones.
Even though ephemeral nodes are tied to a client session, they are visible to all clients
(subject to their ACL policy, of course).
Ephemeral znodes are ideal for building applications that need to know when certain
distributed resources are available. The example earlier in this chapter uses ephemeral
znodes to implement a group membership service, so any process can discover the
members of the group at any particular time.
Sequence Numbers:
A sequential znode is given a sequence number by ZooKeeper as a part of its name. If
a znode is created with the sequential flag set, then the value of a monotonically increasing
counter (maintained by the parent znode) is appended to its name.
If a client asks to create a sequential znode with the name /a/b-, for example, then the
znode created may actually have the name /a/b-3.
If, later on, another sequential znode
with the name /a/b- is created, then it will be given a unique name with a larger value
of the counter—for example, /a/b-5. In the Java API, the actual path given to sequential
znodes is communicated back to the client as the return value of the create() call.
Sequence numbers can be used to impose a global ordering on events in a distributed
system, and may be used by the client to infer the ordering. In “A Lock Service”
you will learn how to use sequential znodes to build a shared lock.
Watches:
Watches allow clients to get notifications when a znode changes in some way. Watches
are set by operations on the ZooKeeper service, and are triggered by other operations
on the service. For example, a client might call the exists operation on a znode, placing
a watch on it at the same time. If the znode doesn’t exist, then the exists operation
will return false. If, some time later, the znode is created by a second client, then the
watch is triggered, notifying the first client of the znode’s creation. You will see precisely
which operations trigger others in the next section.
Watchers are triggered only once.
To receive multiple notifications, a client needs to
re register the watch. If the client in the previous example wishes to receive further
notifications for the znode’s existence (to be notified when it is deleted, for example),
it needs to call the exists operation again to set a new watch.
Operations:
- Nine basic operations in ZooKeeper:
Table: Operations in the ZooKeeper service
Operation Description
create Creates a znode (the parent znode must already exist)
delete Deletes a znode (the znode must not have any children)
exists Tests whether a znode exists and retrieves its metadata
getACL, setACL Gets/sets the ACL for a znode
getChildren Gets a list of the children of a znode
getData, setData Gets/sets the data associated with a znode
sync Synchronizes a client’s view of a znode with ZooKeeper
Update operations in ZooKeeper are conditional. A delete or setData operation has to
specify the version number of the znode that is being updated (which is found from a
previous exists call). If the version number does not match, the update will fail. Updates
are a nonblocking operation, so a client that loses an update (because another
process updated the znode in the meantime) can decide whether to try again or take
some other action, and it can do so without blocking the progress of any other process.
Although ZooKeeper can be viewed as a filesystem, there are some filesystem primitives
that it does away with in the name of simplicity. Because files are small and are written
and read in their entirety, there is no need to provide open, close, or seek operations.
Multi-update:
There is another ZooKeeper operation, called multi, which batches together multiple
primitive operations into a single unit that either succeeds or fails in its entirety. The
situation where some of the primitive operations succeed and some fail can never arise.
Multi-update is very useful for building structures in ZooKeeper that maintain some
global invariant. One example is an undirected graph. Each vertex in the graph is naturally
represented as a znode in ZooKeeper, and to add or remove an edge we need to update the two znodes corresponding to its vertices, since each has a reference to the other. If we only used primitive ZooKeeper operations, it would be possible for another client to observe the graph in an inconsistent state where one vertex is connected to another but the reverse connection is absent. Batching the updates on the two znodes into one multi operation ensures that the update is atomic, so a pair of vertices can
never have a dangling connection.
ACLs:
A znode is created with a list of ACLs, which determines who can perform certain
operations on it.
ACLs depend on authentication, the process by which the client identifies itself to
ZooKeeper. There are a few authentication schemes that ZooKeeper provides:
digest
The client is authenticated by a username and password.
sasl
The client is authenticated using Kerberos.
ip
The client is authenticated by its IP address.
Clients may authenticate themselves after establishing a ZooKeeper session. Authentication
is optional, although a znode’s ACL may require an authenticated client, in
which case the client must authenticate itself to access the znode. Here is an example
of using the digest scheme to authenticate with a username and password:
zk.addAuthInfo("digest", "tom:secret".getBytes());
An ACL is the combination of an authentication scheme, an identity for that scheme,
and a set of permissions. For example, if we wanted to give a client with the IP address
10.0.0.1 read access to a znode, we would set an ACL on the znode with the ip scheme,
an ID of 10.0.0.1, and READ permission. In Java, we would create the ACL object as
follows:
new ACL(Perms.READ,
new Id("ip", "10.0.0.1"));
The full set of permissions are listed in Table Note that the exists operation is
not governed by an ACL permission, so any client may call exists to find the Stat for
a znode or to discover that a znode does not in fact exist.
Table: ACL permissions
ACL permission Permitted operations
CREATE create (a child znode)
READ getChildren
getData
WRITE setData
DELETE delete (a child znode)
ADMIN setACL
There are a number of predefined ACLs defined in the ZooDefs.Ids class, including
OPEN_ACL_UNSAFE, which gives all permissions (except ADMIN permission) to everyone.
In addition, ZooKeeper has a pluggable authentication mechanism, which makes it
possible to integrate third-party authentication systems if needed.
Implementation:
The ZooKeeper service can run in two modes. In standalone mode, there is a single
ZooKeeper server, which is useful for testing due to its simplicity (it can even be
embedded in unit tests), but provides no guarantees of high-availability or resilience.
In production, ZooKeeper runs in replicated mode, on a cluster of machines called an
ensemble. ZooKeeper achieves high-availability through replication, and can provide a
service as long as a majority of the machines in the ensemble are up. For example, in a
five-node ensemble, any two machines can fail and the service will still work because
a majority of three remain. Note that a six-node ensemble can also tolerate only two
machines failing, since with three failures the remaining three do not constitute a majority
of the six. For this reason, it is usual to have an odd number of machines in an ensemble.
Conceptually, ZooKeeper is very simple: all it has to do is ensure that every modification
to the tree of znodes is replicated to a majority of the ensemble. If a minority of the
machines fail, then a minimum of one machine will survive with the latest state. The
other remaining replicas will eventually catch up with this state.
The implementation of this simple idea, however, is nontrivial. ZooKeeper uses a protocol
called Zab that runs in two phases, which may be repeated indefinitely:
Phase 1: Leader election
The machines in an ensemble go through a process of electing a distinguished
member, called the leader. The other machines are termed followers. This phase is
finished once a majority (or quorum) of followers have synchronized their state
with the leader.
Phase 2: Atomic broadcast
All write requests are forwarded to the leader, which broadcasts the update to the
followers. When a majority have persisted the change, the leader commits the update,
and the client gets a response saying the update succeeded. The protocol for achieving consensus is designed to be atomic, so a change either succeeds or fails. It resembles a two-phase commit.
Consistency:
Understanding the basis of ZooKeeper’s implementation helps in understanding the
consistency guarantees that the service makes. The terms “leader” and “follower” for
the machines in an ensemble are apt, for they make the point that a follower may lag
the leader by a number of updates. This is a consequence of the fact that only a majority
and not all of the ensemble needs to have persisted a change before it is committed. A
good mental model for ZooKeeper is of clients connected to ZooKeeper servers that
are following the leader. A client may actually be connected to the leader, but it has no
control over this, and cannot even know if this is the case.
Every update made to the znode tree is given a globally unique identifier, called a
zxid (which stands for “ZooKeeper transaction ID”). Updates are ordered, so if zxid
z1 is less than z 2 , then z1 happened before z, according to ZooKeeper, which is the
single authority on ordering in the distributed system.
Failover to another ZooKeeper server is handled automatically by the ZooKeeper client,
and, crucially, sessions (and associated ephemeral znodes) are still valid after another
server takes over from the failed one.
During failover, the application will receive notifications of disconnections and connections
to the service. Watch notifications will not be delivered while the client is disconnected, but they will be delivered when the client successfully reconnects. Also, if the application tries to perform an operation while the client is reconnecting to another server, the operation will fail. This underlines the importance of handling connection loss exceptions in real-world ZooKeeper applications.
Time:
There are several time parameters in ZooKeeper. The tick time is the fundamental period
of time in ZooKeeper and is used by servers in the ensemble to define the schedule on
which their interactions run. Other settings are defined in terms of tick time, or are at
least constrained by it. The session timeout, for example, may not be less than 2 ticks
or more than 20. If you attempt to set a session timeout outside this range, it will be
modified to fall within the range.
A common tick time setting is 2 seconds (2,000 milliseconds). This translates to an
allowable session timeout of between 4 and 40 seconds. There are a few considerations
in selecting a session timeout.
A low session timeout leads to faster detection of machine failure. In the group membership
example, the session timeout is the time it takes for a failed machine to be
removed from the group. Beware of setting the session timeout too low, however, since
a busy network can cause packets to be delayed and may cause inadvertent session
expiry. In such an event, a machine would appear to “flap”: leaving and then rejoining
the group repeatedly in a short space of time.
Applications that create more complex ephemeral state should favor longer session
timeouts, as the cost of reconstruction is higher. In some cases, it is possible to design
the application so it can restart within the session timeout period and avoid session
expiry. (This might be desirable to perform maintenance or upgrades.) Every session
is given a unique identity and password by the server, and if these are passed to ZooKeeper
while a connection is being made, it is possible to recover a session (as long as it hasn’t expired). An application can therefore arrange a graceful shutdown, whereby it stores the session identity and password to stable storage before restarting the process, retrieving the stored session identity and password and recovering the session. You should view this feature as an optimization, which can help avoid expire sessions. It does not remove the need to handle session expiry, which can still occur if a machine
fails unexpectedly, or even if an application is shut down gracefully but does not restart
before its session expires—for whatever reason.
As a general rule, the larger the ZooKeeper ensemble, the larger the session timeout
should be. Connection timeouts, read timeouts, and ping periods are all defined internally
as a function of the number of servers in the ensemble, so as the ensemble grows, these periods decrease. Consider increasing the timeout if you experience frequent connection loss. You can monitor ZooKeeper metrics—such as request latency statistics—using JMX.
States:
The ZooKeeper object transitions through different states in its lifecycle.
You can query its state at any time by using the getState() method:
public States getState()
States is an enum representing the different states that a ZooKeeper object may be in.
(Despite the enum’s name, an instance of ZooKeeper may only be in one state at a time.)
A newly constructed ZooKeeper instance is in the CONNECTING state, while it tries to
establish a connection with the ZooKeeper service. Once a connection is established,
it goes into the CONNECTED state.
We wrap the code up in a class called ActiveKeyValueStore:
public class ActiveKeyValueStore extends ConnectionWatcher {
private static final Charset CHARSET = Charset.forName("UTF-8");
public void write(String path, String value) throws InterruptedException,
KeeperException {
Stat stat = zk.exists(path, false);
if (stat == null) {
zk.create(path, value.getBytes(CHARSET), Ids.OPEN_ACL_UNSAFE,
CreateMode.PERSISTENT);
} else {
zk.setData(path, value.getBytes(CHARSET), -1);
}
}
}
The contract of the write() method is that a key with the given value is written to
ZooKeeper. It hides the difference between creating a new znode and updating an existing
znode with a new value, by testing first for the znode using the exists operation and then performing the
appropriate operation. The other detail worth mentioning is the need to convert the string value to a byte array, for which we just use the getBytes() method with a UTF-8 encoding.
To illustrate the use of the ActiveKeyValueStore, consider a ConfigUpdater class that
updates a configuration property with a value. The listing appears in Example 14-6.
Example: An application that updates a property in ZooKeeper at random times
public class ConfigUpdater {
public static final String PATH = "/config";
private ActiveKeyValueStore store;
private Random random = new Random();
public ConfigUpdater(String hosts) throws IOException, InterruptedException {
store = new ActiveKeyValueStore();
store.connect(hosts);
}
public void run() throws InterruptedException, KeeperException {
while (true) {
String value = random.nextInt(100) + "";
store.write(PATH, value);
System.out.printf("Set %s to %s\n", PATH, value);
TimeUnit.SECONDS.sleep(random.nextInt(10));
}
}
public static void main(String[] args) throws Exception {
ConfigUpdater configUpdater = new ConfigUpdater(args[0]);
configUpdater.run();
}
}
The program is simple. A ConfigUpdater has an ActiveKeyValueStore that connects to
ZooKeeper in ConfigUpdater’s constructor. The run() method loops forever, updating
the /config znode at random times with random values.
Next, let’s look at how to read the /config configuration property. First, we add a read
method to ActiveKeyValueStore:
public String read(String path, Watcher watcher) throws InterruptedException,
KeeperException {
byte[] data = zk.getData(path, watcher, null/*stat*/);
return new String(data, CHARSET);
}
The getData() method of ZooKeeper takes the path, a Watcher, and a Stat object. The
Stat object is filled in with values by getData(), and is used to pass information back
to the caller. In this way, the caller can get both the data and the metadata for a znode,
although in this case, we pass a null Stat because we are not interested in the metadata.
As a consumer of the service, ConfigWatcher (see Example 14-7) creates an ActiveKey
ValueStore, and after starting, calls the store’s read() method (in its displayConfig()
method) to pass a reference to itself as the watcher. It displays the initial value of the
configuration that it reads.
Example: An application that watches for updates of a property in ZooKeeper and prints them
to the console
public class ConfigWatcher implements Watcher {
private ActiveKeyValueStore store;
public ConfigWatcher(String hosts) throws IOException, InterruptedException {
store = new ActiveKeyValueStore();
store.connect(hosts);
}
public void displayConfig() throws InterruptedException, KeeperException {
String value = store.read(ConfigUpdater.PATH, this);
System.out.printf("Read %s as %s\n", ConfigUpdater.PATH, value);
}
@Override
public void process(WatchedEvent event) {
if (event.getType() == EventType.NodeDataChanged) {
try {
displayConfig();
} catch (InterruptedException e) {
System.err.println("Interrupted. Exiting.");
Thread.currentThread().interrupt();
} catch (KeeperException e) {
System.err.printf("KeeperException: %s. Exiting.\n", e);
}
}
}
public static void main(String[] args) throws Exception {
ConfigWatcher configWatcher = new ConfigWatcher(args[0]);
configWatcher.displayConfig();
// stay alive until process is killed or thread is interrupted
Thread.sleep(Long.MAX_VALUE);
}
}
When the ConfigUpdater updates the znode, ZooKeeper causes the watcher to fire with
an event type of EventType.NodeDataChanged. ConfigWatcher acts on this event in its
process() method by reading and displaying the latest version of the config.
Because watches are one-time signals, we tell ZooKeeper of the new watch each time
we call read() on ActiveKeyValueStore—this ensures we see future updates. Furthermore,
we are not guaranteed to receive every update, since between the receipt of the watch event and the next read, the znode may have been updated, possibly many times, and as the client has no watch registered during that period, it is not notified. For the configuration service, this is not a problem because clients care only about the latest value of a property, as it takes precedence over previous values, but in general you
should be aware of this potential limitation.
Let’s see the code in action. Launch the ConfigUpdater in one terminal window:
% java ConfigUpdater localhost
Set /config to 79
Set /config to 14
Set /config to 78
Then launch the ConfigWatcher in another window immediately afterward:
% java ConfigWatcher localhost
Read /config as 79
Read /config as 14
Read /config as 78
Resilient ZooKeeper Application
The first of the Fallacies of Distributed Computing states that “The network is reliable.”
As they stand, the programs so far have been assuming a reliable network, so when they run on a real network, they can fail in several ways. Let’s examine possible failure modes and what we can do to correct them so that our programs are resilient in the face of failure.
Every ZooKeeper operation in the Java API declares two types of exception in its throws
clause: InterruptedException and KeeperException.
InterruptedException
An InterruptedException is thrown if the operation is interrupted. There is a standard
Java mechanism for canceling blocking methods, which is to call interrupt() on the
thread from which the blocking method was called. A successful cancellation will result
in an InterruptedException. ZooKeeper adheres to this standard, so you can cancel a
ZooKeeper operation in this way. Classes or libraries that use ZooKeeper should usually
propagate the InterruptedException so that their clients can cancel their operations.
An InterruptedException does not indicate a failure, but rather that the operation has
been canceled, so in the configuration application example, it is appropriate to propagate
the exception, causing the application to terminate.
KeeperException
A KeeperException is thrown if the ZooKeeper server signals an error or if there is a
communication problem with the server. There are various subclasses of
KeeperException for different error cases. For example, KeeperException.NoNodeExcep
tion is a subclass of KeeperException that is thrown if you try to perform an operation
on a znode that doesn’t exist.
Every subclass of KeeperException has a corresponding code with information about
the type of error. For example, for KeeperException.NoNodeException the code is Keep
erException.Code.NONODE (an enum value).
There are two ways then to handle KeeperException: either catch KeeperException and
test its code to determine what remedying action to take, or catch the equivalent
KeeperException subclasses and perform the appropriate action in each catch block.
KeeperExceptions fall into three broad categories.
- For building distributed applications using Hadoop distributed coordination service
- When message is sent between two nodes and the network fails, sender does not know whether the receiver got the message.
- It have have gotten before network failed, or it may not have or perhaps the receivers process died.
- Only way sender can find out what happened is to reconnect to receiver and ask it.
- This is partial failure, when we dont even know whether operation failed.
-ZooKeeper gives you a set of tools to build distributed applications that can safely handle partial failures.
Zookeeper has following characteristics:
- It is simple: it is stripped down filesystem that exposes a few simple operations, and some extra abstractions such as ordering and notifications.
- It is expressive: can be used to build large class of coordination data structures and protocols. Ex: distributed queues distributed locks, and leader election among group of peers.
- Highly available: runs on collection of machines and is designed to be highly available, so applications can depend on it. It helps to avoid single point of failure in your system, so you can build a reliable application.
- Loosely coupled interactions: support participants who do not need to know about one another.
- It is library: provides open source, shared repository of implementations and recipes of common coordination patterns.
- High performance: throughput for ZooKeeper cluster has been benchmarked at over 10,000 operations per second.
Installing and Running ZooKeeper:
- When trying out ZooKeeper for the first time, it’s simplest to run it in standalone mode
with a single ZooKeeper server. You can do this on a development machine, for example.
ZooKeeper requires Java 6 to run, so make sure you have it installed first.
You don’t need Cygwin to run ZooKeeper on Windows, since there are Windows versions of the ZooKeeper scripts.
(Windows is supported only as a development platform, not as a
production platform.)
Download a stable release of ZooKeeper from the Apache ZooKeeper releases page at
http://zookeeper.apache.org/releases.html, and unpack the tarball in a suitable location:
% tar xzf zookeeper-x.y.z.tar.gz
ZooKeeper provides a few binaries to run and interact with the service, and it’s convenient
to put the directory containing the binaries on your command-line path:
% export ZOOKEEPER_INSTALL=/home/tom/zookeeper-x.y.z
% export PATH=$PATH:$ZOOKEEPER_INSTALL/bin
Before running the ZooKeeper service, we need to set up a configuration file. The configuration
file is conventionally called zoo.cfg and placed in the conf subdirectory (although you can also place it in /etc/zookeeper, or in the directory defined by the ZOOCFGDIR environment variable, if set). Here’s an example:
tickTime=2000
dataDir=/Users/tom/zookeeper
clientPort=2181
This is a standard Java properties file, and the three properties defined in this example
are the minimum required for running ZooKeeper in standalone mode. Briefly,
tickTime is the basic time unit in ZooKeeper (specified in milliseconds), dataDir is the
local filesystem location where ZooKeeper stores persistent data, and clientPort is the
port the ZooKeeper listens on for client connections (2181 is a common choice). You
should change dataDir to an appropriate setting for your system.
With a suitable configuration defined, we are now ready to start a local ZooKeeper
server:
% zkServer.sh start
To check whether ZooKeeper is running, send the ruok command (“Are you OK?”) to
the client port using nc (telnet works, too):
% echo ruok | nc localhost 2181
imok
Example:
- Imagine group of servers that provide some service to clients.
- We want clients to be able to locate one of the servers, so they can use the service.
- One of the challenges is to maintain list of servers in group.
Group Membership in ZooKeeper:
- One way of understanding ZooKeeper is to think of it as providing high availability filesystem.
- It does not have files and directories, but unified concept of a node, called znode which acts both as container of data(like a file) and container of other znodes( like a directory).
- Znodes form hierarchical namespace, and natural way to build a membership list is to create parent znode with name of the group and child znodes with name of the group members(Servers).
Creating a Group:
Example: A program to create a znode representing a group in ZooKeeper
public class CreateGroup implements Watcher {
private static final int SESSION_TIMEOUT = 5000;
private ZooKeeper zk;
private CountDownLatch connectedSignal = new CountDownLatch(1);
public void connect(String hosts) throws IOException, InterruptedException {
zk = new ZooKeeper(hosts, SESSION_TIMEOUT, this);
connectedSignal.await();
}
@Override
public void process(WatchedEvent event) { // Watcher interface
if (event.getState() == KeeperState.SyncConnected) {
connectedSignal.countDown();
}
}
public void create(String groupName) throws KeeperException,
InterruptedException {
String path = "/" + groupName;
String createdPath = zk.create(path, null/*data*/, Ids.OPEN_ACL_UNSAFE,
CreateMode.PERSISTENT);
System.out.println("Created " + createdPath);
}
public void close() throws InterruptedException {
zk.close();
}
public static void main(String[] args) throws Exception {
CreateGroup createGroup = new CreateGroup();
createGroup.connect(args[0]);
createGroup.create(args[1]);
createGroup.close();
}
}
When the main() method is run, it creates a CreateGroup instance and then calls its
connect() method. This method instantiates a new ZooKeeper object, the main class of
the client API and the one that maintains the connection between the client and the
ZooKeeper service. The constructor takes three arguments: the first is the host address
(and optional port, which defaults to 2181) of the ZooKeeper service;
the second is the session timeout in milliseconds (which we set to 5 seconds), explained in more
detail later; and the third is an instance of a Watcher object. The Watcher object receives
callbacks from ZooKeeper to inform it of various events. In this case, CreateGroup is a
Watcher, so we pass this to the ZooKeeper constructor.
When a ZooKeeper instance is created, it starts a thread to connect to the ZooKeeper
service. The call to the constructor returns immediately, so it is important to wait for
the connection to be established before using the ZooKeeper object. We make use of
Java’s CountDownLatch class (in the java.util.concurrent package) to block until the
ZooKeeper instance is ready. This is where the Watcher comes in. The Watcher interface
has a single method:
public void process(WatchedEvent event);
When the client has connected to ZooKeeper, the Watcher receives a call to its
process() method with an event indicating that it has connected. On receiving a connection
event (represented by the Watcher.Event.KeeperState enum, with value
SyncConnected), we decrement the counter in the CountDownLatch, using its count
Down() method. The latch was created with a count of one, representing the number of
events that need to occur before it releases all waiting threads. After calling count
Down() once, the counter reaches zero and the await() method returns.
CreateGroup is the create() method. In this method, we create a new ZooKeeper znode
using the create() method on the ZooKeeper instance. The arguments it takes are the
path (represented by a string), the contents of the znode (a byte array, null here), an
access control list (or ACL for short, which here is a completely open ACL, allowing
any client to read or write the znode), and the nature of the znode to be created.
Znodes may be ephemeral or persistent. An ephemeral znode will be deleted by the
ZooKeeper service when the client that created it disconnects, either by explicitly disconnecting
or if the client terminates for whatever reason. A persistent znode, on the other hand, is not deleted when the client disconnects. We want the znode representing a group to live longer than the lifetime of the program that creates it, so we create a persistent znode.
The return value of the create() method is the path that was created by ZooKeeper.
We use it to print a message that the path was successfully created. We will see how
the path returned by create() may differ from the one passed into the method when
we look at sequential znodes.
To see the program in action, we need to have ZooKeeper running on the local machine,
and then we can type:
% export CLASSPATH=ch14/target/classes/:$ZOOKEEPER_INSTALL/*:$ZOOKEEPER_INSTALL/lib/*:\
$ZOOKEEPER_INSTALL/conf
% java CreateGroup localhost zoo
Created /zoo
Joining a Group:
- The next part of the application is a program to register a member in a group. Each
member will run as a program and join a group. When the program exits, it should be
removed from the group, which we can do by creating an ephemeral znode that represents
it in the ZooKeeper namespace.
The JoinGroup program implements this idea, and its listing is in Example. The
logic for creating and connecting to a ZooKeeper instance has been refactored into a base
class, ConnectionWatcher, and appears in Example.
Example: A program that joins a group
public class JoinGroup extends ConnectionWatcher {
public void join(String groupName, String memberName) throws KeeperException,
InterruptedException {
String path = "/" + groupName + "/" + memberName;
String createdPath = zk.create(path, null/*data*/, Ids.OPEN_ACL_UNSAFE,
CreateMode.EPHEMERAL);
System.out.println("Created " + createdPath);
}
public static void main(String[] args) throws Exception {
JoinGroup joinGroup = new JoinGroup();
joinGroup.connect(args[0]);
joinGroup.join(args[1], args[2]);
// stay alive until process is killed or thread is interrupted
Thread.sleep(Long.MAX_VALUE);
}
}
Example: A helper class that waits for the connection to ZooKeeper to be established
public class ConnectionWatcher implements Watcher {
private static final int SESSION_TIMEOUT = 5000;
protected ZooKeeper zk;
private CountDownLatch connectedSignal = new CountDownLatch(1);
public void connect(String hosts) throws IOException, InterruptedException {
zk = new ZooKeeper(hosts, SESSION_TIMEOUT, this);
connectedSignal.await();
}
@Override
public void process(WatchedEvent event) {
if (event.getState() == KeeperState.SyncConnected) {
connectedSignal.countDown();
}
}
public void close() throws InterruptedException {
zk.close();
}
}
The code for JoinGroup is very similar to CreateGroup. It creates an ephemeral znode as
a child of the group znode in its join() method, then simulates doing work of some
kind by sleeping until the process is forcibly terminated. Later, you will see that upon
termination, the ephemeral znode is removed by ZooKeeper.
Listing Members in a Group:
- Example: A program to list the members in a group
public class ListGroup extends ConnectionWatcher {
public void list(String groupName) throws KeeperException,
InterruptedException {
String path = "/" + groupName;
try {
List<String> children = zk.getChildren(path, false);
if (children.isEmpty()) {
System.out.printf("No members in group %s\n", groupName);
System.exit(1);
}
for (String child : children) {
System.out.println(child);
}
} catch (KeeperException.NoNodeException e) {
System.out.printf("Group %s does not exist\n", groupName);
System.exit(1);
}
}
public static void main(String[] args) throws Exception {
ListGroup listGroup = new ListGroup();
listGroup.connect(args[0]);
listGroup.list(args[1]);
listGroup.close();
}
}
In the list() method, we call getChildren() with a znode path and a watch flag to
retrieve a list of child paths for the znode, which we print out. Placing a watch on a
znode causes the registered Watcher to be triggered if the znode changes state. Although
we’re not using it here, watching a znode’s children would permit a program to get
notifications of members joining or leaving the group, or of the group being deleted.
We catch KeeperException.NoNodeException, which is thrown in the case when the
group’s znode does not exist.
Let’s see ListGroup in action. As expected, the zoo group is empty, since we haven’t
added any members yet:
% java ListGroup localhost zoo
No members in group zoo
We can use JoinGroup to add some members. We launch them as background processes,
since they don’t terminate on their own (due to the sleep statement):
% java JoinGroup localhost zoo duck &
% java JoinGroup localhost zoo cow &
% java JoinGroup localhost zoo goat &
% goat_pid=$!
The last line saves the process ID of the Java process running the program that adds
goat as a member. We need to remember the ID so that we can kill the process in a
moment, after checking the members:
% java ListGroup localhost zoo
goat
duck
cow
To remove a member, we kill its process:
% kill $goat_pid
And a few seconds later, it has disappeared from the group because the process’s ZooKeeper
session has terminated (the timeout was set to 5 seconds) and its associated
ephemeral node has been removed:
% java ListGroup localhost zoo
duck
cow
Let’s stand back and see what we’ve built here. We have a way of building up a list of
a group of nodes that are participating in a distributed system. The nodes may have no
knowledge of each other. A client that wants to use the nodes in the list to perform
some work, for example, can discover the nodes without them being aware of the client’s
existence.
Finally, note that group membership is not a substitution for handling network errors
when communicating with a node. Even if a node is a group member, communications
with it may fail, and such failures must be handled in the usual ways (retrying, trying
a different member of the group, and so on).
ZooKeeper command-line tools:
ZooKeeper comes with a command-line tool for interacting with the ZooKeeper namespace.
We can use it to list the znodes under the /zoo znode as follows:
% zkCli.sh localhost ls /zoo
Processing ls
WatchedEvent: Server state change. New state: SyncConnected
[duck, cow]
Deleting a group:
- To round off the example, let’s see how to delete a group. The ZooKeeper class provides
a delete() method that takes a path and a version number. ZooKeeper will delete a
znode only if the version number specified is the same as the version number of the
znode it is trying to delete, an optimistic locking mechanism that allows clients to detect
conflicts over znode modification. You can bypass the version check, however, by using
a version number of –1 to delete the znode regardless of its version number.
There is no recursive delete operation in ZooKeeper, so you have to delete child znodes
before parents. This is what we do in the DeleteGroup class, which will remove a group
and all its members.
Example: A program to delete a group and its members
public class DeleteGroup extends ConnectionWatcher {
public void delete(String groupName) throws KeeperException,
InterruptedException {
String path = "/" + groupName;
try {
List<String> children = zk.getChildren(path, false);
for (String child : children) {
zk.delete(path + "/" + child, -1);
}
zk.delete(path, -1);
} catch (KeeperException.NoNodeException e) {
System.out.printf("Group %s does not exist\n", groupName);
System.exit(1);
}
}
public static void main(String[] args) throws Exception {
DeleteGroup deleteGroup = new DeleteGroup();
deleteGroup.connect(args[0]);
deleteGroup.delete(args[1]);
deleteGroup.close();
}
}
Finally, we can delete the zoo group that we created earlier:
% java DeleteGroup localhost zoo
% java ListGroup localhost zoo
Group zoo does not exist
ZooKeeper Service:
ZooKeeper is a highly available, high-performance coordination service. In this section,
we look at the nature of the service it provides: its model, operations, and
implementation.
Data Model:
ZooKeeper maintains a hierarchical tree of nodes called znodes. A znode stores data
and has an associated ACL. ZooKeeper is designed for coordination (which typically
uses small data files), not high-volume data storage, so there is a limit of 1 MB on the
amount of data that may be stored in any znode.
Data access is atomic. A client reading the data stored at a znode will never receive only
some of the data; either the data will be delivered in its entirety, or the read will fail.
Similarly, a write will replace all the data associated with a znode. ZooKeeper guarantees
that the write will either succeed or fail; there is no such thing as a partial write, where only
someof the data written by the client is stored.
ZooKeeper does not support an append operation. These characteristics contrast with HDFS,
which is designed for high-volume data storage, with streaming data access, and provides an append
operation.
Znodes are referenced by paths, which in ZooKeeper are represented as slash-delimited
Unicode character strings, like filesystem paths in Unix. Paths must be absolute, so
they must begin with a slash character. Furthermore, they are canonical, which means
that each path has a single representation, and so paths do not undergo resolution. For
example, in Unix, a file with the path /a/b can equivalently be referred to by the
path /a/./b, since “.” refers to the current directory at the point it is encountered in the
path. In ZooKeeper, “.” does not have this special meaning and is actually illegal as a
path component (as is “..” for the parent of the current directory).
Path components are composed of Unicode characters, with a few restrictions (these
are spelled out in the ZooKeeper reference documentation). The string “zookeeper” is
a reserved word and may not be used as a path component. In particular, ZooKeeper
uses the /zookeeper subtree to store management information, such as information on
quotas.
Note that paths are not URIs, and they are represented in the Java API by a
java.lang.String, rather than the Hadoop Path class (or by the java.net.URI class, for
that matter).
Znodes have some properties that are very useful for building distributed applications,
which we discuss in the following sections.
Ephemeral Znodes:
Znodes can be one of two types: ephemeral or persistent. A znode’s type is set at creation
time and may not be changed later. An ephemeral znode is deleted by ZooKeeper when
the creating client’s session ends. By contrast, a persistent znode is not tied to the client’s
session and is deleted only when explicitly deleted by a client (not necessarily the one
that created it). An ephemeral znode may not have children, not even ephemeral ones.
Even though ephemeral nodes are tied to a client session, they are visible to all clients
(subject to their ACL policy, of course).
Ephemeral znodes are ideal for building applications that need to know when certain
distributed resources are available. The example earlier in this chapter uses ephemeral
znodes to implement a group membership service, so any process can discover the
members of the group at any particular time.
Sequence Numbers:
A sequential znode is given a sequence number by ZooKeeper as a part of its name. If
a znode is created with the sequential flag set, then the value of a monotonically increasing
counter (maintained by the parent znode) is appended to its name.
If a client asks to create a sequential znode with the name /a/b-, for example, then the
znode created may actually have the name /a/b-3.
If, later on, another sequential znode
with the name /a/b- is created, then it will be given a unique name with a larger value
of the counter—for example, /a/b-5. In the Java API, the actual path given to sequential
znodes is communicated back to the client as the return value of the create() call.
Sequence numbers can be used to impose a global ordering on events in a distributed
system, and may be used by the client to infer the ordering. In “A Lock Service”
you will learn how to use sequential znodes to build a shared lock.
Watches:
Watches allow clients to get notifications when a znode changes in some way. Watches
are set by operations on the ZooKeeper service, and are triggered by other operations
on the service. For example, a client might call the exists operation on a znode, placing
a watch on it at the same time. If the znode doesn’t exist, then the exists operation
will return false. If, some time later, the znode is created by a second client, then the
watch is triggered, notifying the first client of the znode’s creation. You will see precisely
which operations trigger others in the next section.
Watchers are triggered only once.
To receive multiple notifications, a client needs to
re register the watch. If the client in the previous example wishes to receive further
notifications for the znode’s existence (to be notified when it is deleted, for example),
it needs to call the exists operation again to set a new watch.
Operations:
- Nine basic operations in ZooKeeper:
Table: Operations in the ZooKeeper service
Operation Description
create Creates a znode (the parent znode must already exist)
delete Deletes a znode (the znode must not have any children)
exists Tests whether a znode exists and retrieves its metadata
getACL, setACL Gets/sets the ACL for a znode
getChildren Gets a list of the children of a znode
getData, setData Gets/sets the data associated with a znode
sync Synchronizes a client’s view of a znode with ZooKeeper
Update operations in ZooKeeper are conditional. A delete or setData operation has to
specify the version number of the znode that is being updated (which is found from a
previous exists call). If the version number does not match, the update will fail. Updates
are a nonblocking operation, so a client that loses an update (because another
process updated the znode in the meantime) can decide whether to try again or take
some other action, and it can do so without blocking the progress of any other process.
Although ZooKeeper can be viewed as a filesystem, there are some filesystem primitives
that it does away with in the name of simplicity. Because files are small and are written
and read in their entirety, there is no need to provide open, close, or seek operations.
Multi-update:
There is another ZooKeeper operation, called multi, which batches together multiple
primitive operations into a single unit that either succeeds or fails in its entirety. The
situation where some of the primitive operations succeed and some fail can never arise.
Multi-update is very useful for building structures in ZooKeeper that maintain some
global invariant. One example is an undirected graph. Each vertex in the graph is naturally
represented as a znode in ZooKeeper, and to add or remove an edge we need to update the two znodes corresponding to its vertices, since each has a reference to the other. If we only used primitive ZooKeeper operations, it would be possible for another client to observe the graph in an inconsistent state where one vertex is connected to another but the reverse connection is absent. Batching the updates on the two znodes into one multi operation ensures that the update is atomic, so a pair of vertices can
never have a dangling connection.
ACLs:
A znode is created with a list of ACLs, which determines who can perform certain
operations on it.
ACLs depend on authentication, the process by which the client identifies itself to
ZooKeeper. There are a few authentication schemes that ZooKeeper provides:
digest
The client is authenticated by a username and password.
sasl
The client is authenticated using Kerberos.
ip
The client is authenticated by its IP address.
Clients may authenticate themselves after establishing a ZooKeeper session. Authentication
is optional, although a znode’s ACL may require an authenticated client, in
which case the client must authenticate itself to access the znode. Here is an example
of using the digest scheme to authenticate with a username and password:
zk.addAuthInfo("digest", "tom:secret".getBytes());
An ACL is the combination of an authentication scheme, an identity for that scheme,
and a set of permissions. For example, if we wanted to give a client with the IP address
10.0.0.1 read access to a znode, we would set an ACL on the znode with the ip scheme,
an ID of 10.0.0.1, and READ permission. In Java, we would create the ACL object as
follows:
new ACL(Perms.READ,
new Id("ip", "10.0.0.1"));
The full set of permissions are listed in Table Note that the exists operation is
not governed by an ACL permission, so any client may call exists to find the Stat for
a znode or to discover that a znode does not in fact exist.
Table: ACL permissions
ACL permission Permitted operations
CREATE create (a child znode)
READ getChildren
getData
WRITE setData
DELETE delete (a child znode)
ADMIN setACL
There are a number of predefined ACLs defined in the ZooDefs.Ids class, including
OPEN_ACL_UNSAFE, which gives all permissions (except ADMIN permission) to everyone.
In addition, ZooKeeper has a pluggable authentication mechanism, which makes it
possible to integrate third-party authentication systems if needed.
Implementation:
The ZooKeeper service can run in two modes. In standalone mode, there is a single
ZooKeeper server, which is useful for testing due to its simplicity (it can even be
embedded in unit tests), but provides no guarantees of high-availability or resilience.
In production, ZooKeeper runs in replicated mode, on a cluster of machines called an
ensemble. ZooKeeper achieves high-availability through replication, and can provide a
service as long as a majority of the machines in the ensemble are up. For example, in a
five-node ensemble, any two machines can fail and the service will still work because
a majority of three remain. Note that a six-node ensemble can also tolerate only two
machines failing, since with three failures the remaining three do not constitute a majority
of the six. For this reason, it is usual to have an odd number of machines in an ensemble.
Conceptually, ZooKeeper is very simple: all it has to do is ensure that every modification
to the tree of znodes is replicated to a majority of the ensemble. If a minority of the
machines fail, then a minimum of one machine will survive with the latest state. The
other remaining replicas will eventually catch up with this state.
The implementation of this simple idea, however, is nontrivial. ZooKeeper uses a protocol
called Zab that runs in two phases, which may be repeated indefinitely:
Phase 1: Leader election
The machines in an ensemble go through a process of electing a distinguished
member, called the leader. The other machines are termed followers. This phase is
finished once a majority (or quorum) of followers have synchronized their state
with the leader.
Phase 2: Atomic broadcast
All write requests are forwarded to the leader, which broadcasts the update to the
followers. When a majority have persisted the change, the leader commits the update,
and the client gets a response saying the update succeeded. The protocol for achieving consensus is designed to be atomic, so a change either succeeds or fails. It resembles a two-phase commit.
Consistency:
Understanding the basis of ZooKeeper’s implementation helps in understanding the
consistency guarantees that the service makes. The terms “leader” and “follower” for
the machines in an ensemble are apt, for they make the point that a follower may lag
the leader by a number of updates. This is a consequence of the fact that only a majority
and not all of the ensemble needs to have persisted a change before it is committed. A
good mental model for ZooKeeper is of clients connected to ZooKeeper servers that
are following the leader. A client may actually be connected to the leader, but it has no
control over this, and cannot even know if this is the case.
Every update made to the znode tree is given a globally unique identifier, called a
zxid (which stands for “ZooKeeper transaction ID”). Updates are ordered, so if zxid
z1 is less than z 2 , then z1 happened before z, according to ZooKeeper, which is the
single authority on ordering in the distributed system.
The following guarantees for data consistency flow from ZooKeeper’s design:
Sequential consistency
Updates from any particular client are applied in the order that they are sent. This
means that if a client updates the znode z to the value a, and in a later operation,
it updates z to the value b, then no client will ever see z with value a after it has
seen it with value b (if no other updates are made to z).
Atomicity
Updates either succeed or fail. This means that if an update fails, no client will ever
see it.
Single system image
A client will see the same view of the system regardless of the server it connects to.
This means that if a client connects to a new server during the same session, it will
not see an older state of the system than the one it saw with the previous server.
When a server fails and a client tries to connect to another in the ensemble, a server
that is behind the one that failed will not accept connections from the client until
it has caught up with the failed server.
Durability
Once an update has succeeded, it will persist and will not be undone. This means
updates will survive server failures.
Timeliness
The lag in any client’s view of the system is bounded, so it will not be out of date
by more than some multiple of tens of seconds. This means that rather than allow
a client to see data that is very stale, a server will shut down, forcing the client to
switch to a more up-to-date server.
For performance reasons, reads are satisfied from a ZooKeeper server’s memory and
do not participate in the global ordering of writes. This property can lead to the appearance
of inconsistent ZooKeeper states from clients that communicate through a
mechanism outside ZooKeeper.
For example, client A updates znode z from a to a’, A tells B to read z, B reads the value
of z as a, not a’. This is perfectly compatible with the guarantees that ZooKeeper makes
(this condition that it does not promise is called “Simultaneously Consistent CrossClient
Views”). To prevent this condition from happening, B should call sync on z,
before reading z’s value. The sync operation forces the ZooKeeper server to which B is
connected to “catch up” with the leader, so that when B reads z’s value it will be the
one that A set (or a later value).
Sessions:
A ZooKeeper client is configured with the list of servers in the ensemble. On startup,
it tries to connect to one of the servers in the list. If the connection fails, it tries another
server in the list, and so on, until it either successfully connects to one of them or fails
if all ZooKeeper servers are unavailable.
Once a connection has been made with a ZooKeeper server, the server creates a new
session for the client. A session has a timeout period that is decided on by the application
that creates it. If the server hasn’t received a request within the timeout period, it may expire the session. Once a session has expired, it may not be reopened, and any ephemeral nodes associated with the session will be lost. Although session expiry is a comparatively rare event, since sessions are long-lived, it is important for applications to handle it.
Sessions are kept alive by the client sending ping requests (also known as heartbeats)
whenever the session is idle for longer than a certain period. (Pings are automatically
sent by the ZooKeeper client library, so your code doesn’t need to worry about maintaining
the session.) The period is chosen to be low enough to detect server failure
(manifested by a read timeout) and reconnect to another server within the session
timeout period.
Failover to another ZooKeeper server is handled automatically by the ZooKeeper client,
and, crucially, sessions (and associated ephemeral znodes) are still valid after another
server takes over from the failed one.
During failover, the application will receive notifications of disconnections and connections
to the service. Watch notifications will not be delivered while the client is disconnected, but they will be delivered when the client successfully reconnects. Also, if the application tries to perform an operation while the client is reconnecting to another server, the operation will fail. This underlines the importance of handling connection loss exceptions in real-world ZooKeeper applications.
Time:
There are several time parameters in ZooKeeper. The tick time is the fundamental period
of time in ZooKeeper and is used by servers in the ensemble to define the schedule on
which their interactions run. Other settings are defined in terms of tick time, or are at
least constrained by it. The session timeout, for example, may not be less than 2 ticks
or more than 20. If you attempt to set a session timeout outside this range, it will be
modified to fall within the range.
A common tick time setting is 2 seconds (2,000 milliseconds). This translates to an
allowable session timeout of between 4 and 40 seconds. There are a few considerations
in selecting a session timeout.
A low session timeout leads to faster detection of machine failure. In the group membership
example, the session timeout is the time it takes for a failed machine to be
removed from the group. Beware of setting the session timeout too low, however, since
a busy network can cause packets to be delayed and may cause inadvertent session
expiry. In such an event, a machine would appear to “flap”: leaving and then rejoining
the group repeatedly in a short space of time.
Applications that create more complex ephemeral state should favor longer session
timeouts, as the cost of reconstruction is higher. In some cases, it is possible to design
the application so it can restart within the session timeout period and avoid session
expiry. (This might be desirable to perform maintenance or upgrades.) Every session
is given a unique identity and password by the server, and if these are passed to ZooKeeper
while a connection is being made, it is possible to recover a session (as long as it hasn’t expired). An application can therefore arrange a graceful shutdown, whereby it stores the session identity and password to stable storage before restarting the process, retrieving the stored session identity and password and recovering the session. You should view this feature as an optimization, which can help avoid expire sessions. It does not remove the need to handle session expiry, which can still occur if a machine
fails unexpectedly, or even if an application is shut down gracefully but does not restart
before its session expires—for whatever reason.
As a general rule, the larger the ZooKeeper ensemble, the larger the session timeout
should be. Connection timeouts, read timeouts, and ping periods are all defined internally
as a function of the number of servers in the ensemble, so as the ensemble grows, these periods decrease. Consider increasing the timeout if you experience frequent connection loss. You can monitor ZooKeeper metrics—such as request latency statistics—using JMX.
States:
The ZooKeeper object transitions through different states in its lifecycle.
You can query its state at any time by using the getState() method:
public States getState()
States is an enum representing the different states that a ZooKeeper object may be in.
(Despite the enum’s name, an instance of ZooKeeper may only be in one state at a time.)
A newly constructed ZooKeeper instance is in the CONNECTING state, while it tries to
establish a connection with the ZooKeeper service. Once a connection is established,
it goes into the CONNECTED state.
A client using the ZooKeeper object can receive notifications of the state transitions by
registering a Watcher object. On entering the CONNECTED state, the watcher receives a
WatchedEvent whose KeeperState value is SyncConnected.
The ZooKeeper instance may disconnect and reconnect to the ZooKeeper service, moving
between the CONNECTED and CONNECTING states. If it disconnects, the watcher receives a
Disconnected event. Note that these state transitions are initiated by the ZooKeeper
instance itself, and it will automatically try to reconnect if the connection is lost.
The ZooKeeper instance may transition to a third state, CLOSED, if either the close()
method is called or the session times out as indicated by a KeeperState of type
Expired. Once in the CLOSED state, the ZooKeeper object is no longer considered to be
alive (this can be tested using the isAlive() method on States) and cannot be reused.
To reconnect to the ZooKeeper service, the client must construct a new ZooKeeper
instance.
Building Applications using ZooKeeper:
A configuration service:
One of the most basic services that a distributed application needs is a configuration
service so that common pieces of configuration information can be shared by machines
in a cluster. At the simplest level, ZooKeeper can act as a highly available store for
configuration, allowing application participants to retrieve or update configuration
files. Using ZooKeeper watches, it is possible to create an active configuration service,
where interested clients are notified of changes in configuration.
Let’s write such a service. We make a couple of assumptions that simplify the implementation
(they could be removed with a little more work). First, the only configuration values we need to store are strings, and keys are just znode paths, so we use a znode to store each key-value pair. Second, there is a single client that performs updates at any one time.
Among other things, this model fits with the idea of a master (such as the namenode in HDFS) that wishes to update information that its workers need to follow.
We wrap the code up in a class called ActiveKeyValueStore:
public class ActiveKeyValueStore extends ConnectionWatcher {
private static final Charset CHARSET = Charset.forName("UTF-8");
public void write(String path, String value) throws InterruptedException,
KeeperException {
Stat stat = zk.exists(path, false);
if (stat == null) {
zk.create(path, value.getBytes(CHARSET), Ids.OPEN_ACL_UNSAFE,
CreateMode.PERSISTENT);
} else {
zk.setData(path, value.getBytes(CHARSET), -1);
}
}
}
The contract of the write() method is that a key with the given value is written to
ZooKeeper. It hides the difference between creating a new znode and updating an existing
znode with a new value, by testing first for the znode using the exists operation and then performing the
appropriate operation. The other detail worth mentioning is the need to convert the string value to a byte array, for which we just use the getBytes() method with a UTF-8 encoding.
To illustrate the use of the ActiveKeyValueStore, consider a ConfigUpdater class that
updates a configuration property with a value. The listing appears in Example 14-6.
Example: An application that updates a property in ZooKeeper at random times
public class ConfigUpdater {
public static final String PATH = "/config";
private ActiveKeyValueStore store;
private Random random = new Random();
public ConfigUpdater(String hosts) throws IOException, InterruptedException {
store = new ActiveKeyValueStore();
store.connect(hosts);
}
public void run() throws InterruptedException, KeeperException {
while (true) {
String value = random.nextInt(100) + "";
store.write(PATH, value);
System.out.printf("Set %s to %s\n", PATH, value);
TimeUnit.SECONDS.sleep(random.nextInt(10));
}
}
public static void main(String[] args) throws Exception {
ConfigUpdater configUpdater = new ConfigUpdater(args[0]);
configUpdater.run();
}
}
The program is simple. A ConfigUpdater has an ActiveKeyValueStore that connects to
ZooKeeper in ConfigUpdater’s constructor. The run() method loops forever, updating
the /config znode at random times with random values.
Next, let’s look at how to read the /config configuration property. First, we add a read
method to ActiveKeyValueStore:
public String read(String path, Watcher watcher) throws InterruptedException,
KeeperException {
byte[] data = zk.getData(path, watcher, null/*stat*/);
return new String(data, CHARSET);
}
The getData() method of ZooKeeper takes the path, a Watcher, and a Stat object. The
Stat object is filled in with values by getData(), and is used to pass information back
to the caller. In this way, the caller can get both the data and the metadata for a znode,
although in this case, we pass a null Stat because we are not interested in the metadata.
As a consumer of the service, ConfigWatcher (see Example 14-7) creates an ActiveKey
ValueStore, and after starting, calls the store’s read() method (in its displayConfig()
method) to pass a reference to itself as the watcher. It displays the initial value of the
configuration that it reads.
Example: An application that watches for updates of a property in ZooKeeper and prints them
to the console
public class ConfigWatcher implements Watcher {
private ActiveKeyValueStore store;
public ConfigWatcher(String hosts) throws IOException, InterruptedException {
store = new ActiveKeyValueStore();
store.connect(hosts);
}
public void displayConfig() throws InterruptedException, KeeperException {
String value = store.read(ConfigUpdater.PATH, this);
System.out.printf("Read %s as %s\n", ConfigUpdater.PATH, value);
}
@Override
public void process(WatchedEvent event) {
if (event.getType() == EventType.NodeDataChanged) {
try {
displayConfig();
} catch (InterruptedException e) {
System.err.println("Interrupted. Exiting.");
Thread.currentThread().interrupt();
} catch (KeeperException e) {
System.err.printf("KeeperException: %s. Exiting.\n", e);
}
}
}
public static void main(String[] args) throws Exception {
ConfigWatcher configWatcher = new ConfigWatcher(args[0]);
configWatcher.displayConfig();
// stay alive until process is killed or thread is interrupted
Thread.sleep(Long.MAX_VALUE);
}
}
When the ConfigUpdater updates the znode, ZooKeeper causes the watcher to fire with
an event type of EventType.NodeDataChanged. ConfigWatcher acts on this event in its
process() method by reading and displaying the latest version of the config.
Because watches are one-time signals, we tell ZooKeeper of the new watch each time
we call read() on ActiveKeyValueStore—this ensures we see future updates. Furthermore,
we are not guaranteed to receive every update, since between the receipt of the watch event and the next read, the znode may have been updated, possibly many times, and as the client has no watch registered during that period, it is not notified. For the configuration service, this is not a problem because clients care only about the latest value of a property, as it takes precedence over previous values, but in general you
should be aware of this potential limitation.
Let’s see the code in action. Launch the ConfigUpdater in one terminal window:
% java ConfigUpdater localhost
Set /config to 79
Set /config to 14
Set /config to 78
Then launch the ConfigWatcher in another window immediately afterward:
% java ConfigWatcher localhost
Read /config as 79
Read /config as 14
Read /config as 78
Resilient ZooKeeper Application
The first of the Fallacies of Distributed Computing states that “The network is reliable.”
As they stand, the programs so far have been assuming a reliable network, so when they run on a real network, they can fail in several ways. Let’s examine possible failure modes and what we can do to correct them so that our programs are resilient in the face of failure.
Every ZooKeeper operation in the Java API declares two types of exception in its throws
clause: InterruptedException and KeeperException.
InterruptedException
An InterruptedException is thrown if the operation is interrupted. There is a standard
Java mechanism for canceling blocking methods, which is to call interrupt() on the
thread from which the blocking method was called. A successful cancellation will result
in an InterruptedException. ZooKeeper adheres to this standard, so you can cancel a
ZooKeeper operation in this way. Classes or libraries that use ZooKeeper should usually
propagate the InterruptedException so that their clients can cancel their operations.
An InterruptedException does not indicate a failure, but rather that the operation has
been canceled, so in the configuration application example, it is appropriate to propagate
the exception, causing the application to terminate.
KeeperException
A KeeperException is thrown if the ZooKeeper server signals an error or if there is a
communication problem with the server. There are various subclasses of
KeeperException for different error cases. For example, KeeperException.NoNodeExcep
tion is a subclass of KeeperException that is thrown if you try to perform an operation
on a znode that doesn’t exist.
Every subclass of KeeperException has a corresponding code with information about
the type of error. For example, for KeeperException.NoNodeException the code is Keep
erException.Code.NONODE (an enum value).
There are two ways then to handle KeeperException: either catch KeeperException and
test its code to determine what remedying action to take, or catch the equivalent
KeeperException subclasses and perform the appropriate action in each catch block.
KeeperExceptions fall into three broad categories.
A state exception occurs when the operation fails because it cannot be
State exceptions.
applied to the znode tree. State exceptions usually happen because another process is
mutating a znode at the same time. For example, a setData operation with a version
number will fail with a KeeperException.BadVersionException if the znode is updated
by another process first, since the version number does not match. The programmer is
usually aware that this kind of conflict is possible and will code to deal with it.
Some state exceptions indicate an error in the program, such as KeeperExcep
tion.NoChildrenForEphemeralsException, which is thrown when trying to create a child
znode of an ephemeral znode.
Recoverable exceptions.
Recoverable exceptions are those from which the application can
recover within the same ZooKeeper session. A recoverable exception is manifested by
KeeperException.ConnectionLossException, which means that the connection to
ZooKeeper has been lost. ZooKeeper will try to reconnect, and in most cases the reconnection
will succeed and ensure that the session is intact.
However, ZooKeeper cannot tell whether the operation that failed with KeeperExcep
tion.ConnectionLossException was applied. This is an example of partial failure (which
we introduced at the beginning of the chapter). The onus is therefore on the programmer
to deal with the uncertainty, and the action that should be taken depends on the application.
At this point, it is useful to make a distinction between idempotent and nonidempotent operations.
An idempotent operation is one that may be applied one or more times with the same result, such as a read request or an unconditional setData. These can simply be retried.
A nonidempotent operation cannot be indiscriminately retried, as the effect of applying
it multiple times is not the same as applying it once. The program needs a way of
detecting whether its update was applied by encoding information in the znode’s path
name or its data. We shall discuss how to deal with failed nonidempotent operations
in “Recoverable exceptions” on page 518, when we look at the implementation of a
lock service.
Unrecoverable exceptions.
In some cases, the ZooKeeper session becomes invalid—
perhaps because of a timeout or because the session was closed (both get a KeeperEx
ception.SessionExpiredException), or perhaps because authentication failed (Keeper
Exception.AuthFailedException). In any case, all ephemeral nodes associated with the
session will be lost, so the application needs to rebuild its state before reconnecting to
ZooKeeper.
A reliable configuration service
Going back to the write() method in ActiveKeyValueStore, recall that it is composed
of an exists operation followed by either a create or a setData:
public void write(String path, String value) throws InterruptedException,
KeeperException {
Stat stat = zk.exists(path, false);
if (stat == null) {
zk.create(path, value.getBytes(CHARSET), Ids.OPEN_ACL_UNSAFE,
CreateMode.PERSISTENT);
} else {
zk.setData(path, value.getBytes(CHARSET), -1);
}
}
Taken as a whole, the write() method is idempotent, so we can afford to unconditionally
retry it. Here’s a modified version of the write() method that retries in a loop.
It is set to try a maximum number of retries (MAX_RETRIES) and sleeps for
RETRY_PERIOD_SECONDS between each attempt:
public void write(String path, String value) throws InterruptedException,
KeeperException {
int retries = 0;
while (true) {
try {
Stat stat = zk.exists(path, false);
if (stat == null) {
zk.create(path, value.getBytes(CHARSET), Ids.OPEN_ACL_UNSAFE,
CreateMode.PERSISTENT);
} else {
zk.setData(path, value.getBytes(CHARSET), stat.getVersion());
}
} catch (KeeperException.SessionExpiredException e) {
throw e;
} catch (KeeperException e) {
if (retries++ == MAX_RETRIES) {
throw e;
}
// sleep then retry
TimeUnit.SECONDS.sleep(RETRY_PERIOD_SECONDS);
}
}
}
The code is careful not to retry KeeperException.SessionExpiredException, since when
a session expires, the ZooKeeper object enters the CLOSED state, from which it can never
reconnect (refer to Figure 14-3). We simply rethrow the exception
and let the caller create a new ZooKeeper instance, so that the whole write() method can be retried. A
simple way to create a new instance is to create a new ConfigUpdater (which we’ve
actually renamed ResilientConfigUpdater) to recover from an expired session:
public static void main(String[] args) throws Exception {
while (true) {
try {
ResilientConfigUpdater configUpdater =
new ResilientConfigUpdater(args[0]);
configUpdater.run();
} catch (KeeperException.SessionExpiredException e) {
// start a new session
} catch (KeeperException e) {
// already retried, so exit
e.printStackTrace();
break;
}
}
}
An alternative way of dealing with session expiry would be to look for a KeeperState
of type Expired in the watcher (that would be the ConnectionWatcher in the example
here), and create a new connection when this is detected. This way, we would just keep
retrying in the write() method, even if we got a KeeperException.SessionExpiredExcep
tion, since the connection should eventually be reestablished. Regardless of the precise
mechanics of how we recover from an expired session, the important point is that it is
a different kind of failure from connection loss and needs to be handled differently.
This is just one strategy for retry handling—there are many others, such as using exponential
backoff where the period between retries is multiplied by a constant each
time. The org.apache.hadoop.io.retry package in Hadoop Core is a set of utilities for
adding retry logic into your code in a reusable way, and it may be helpful for building
ZooKeeper applications.
Lock Service:
A distributed lock is a mechanism for providing mutual exclusion between a collection
of processes. At any one time, only a single process may hold the lock. Distributed locks
can be used for leader election in a large distributed system, where the leader is the
process that holds the lock at any point in time.
To implement a distributed lock using ZooKeeper, we use sequential znodes to impose
an order on the processes vying for the lock. The idea is simple: first designate a lock
znode, typically describing the entity being locked on, say /leader; then clients that want
to acquire the lock create sequential ephemeral znodes as children of the lock znode.
At any point in time, the client with the lowest sequence number holds the lock. For
example, if two clients create znodes at around the same time, /leader/lock-1
and /leader/lock-2, then the client that created /leader/lock-1 holds the lock, since its
znode has the lowest sequence number. The ZooKeeper service is the arbiter of order,
since it assigns the sequence numbers.
The lock may be released simply by deleting the znode /leader/lock-1; alternatively, if
the client process dies, it will be deleted by virtue of it being an ephemeral znode. The
client that created /leader/lock-2 will then hold the lock, since it has the next lowest
sequence number. It will be notified that it has the lock by creating a watch that fires
when znodes go away.
The pseudocode for lock acquisition is as follows:
1. Create an ephemeral sequential znode named lock- under the lock znode and re-
member its actual path name (the return value of the create operation).
2. Get the children of the lock znode and set a watch.
3. If the path name of the znode created in 1 has the lowest number of the children
returned in 2, then the lock has been acquired. Exit.
4. Wait for the notification from the watch set in 2 and go to step 2.
The herd effect
Although this algorithm is correct, there are some problems with it. The first problem
is that this implementation suffers from the herd effect. Consider hundreds or thousands
of clients, all trying to acquire the lock. Each client places a watch on the lock znode
for changes in its set of children. Every time the lock is released, or another
process starts the lock acquisition process, the watch fires and every client receives a
notification. The “herd effect” refers to a large number of clients being notified of the
same event, when only a small number of them can actually proceed. In this case, only
one client will successfully acquire the lock, and the process of maintaining and sending
watch events to all clients causes traffic spikes, which put pressure on the ZooKeeper
servers.
To avoid the herd effect, the condition for notification needs to be refined. The key
observation for implementing locks is that a client needs to be notified only when the
child znode with the previous sequence number goes away, not when any child znode
is deleted (or created). In our example, if clients have created the znodes /leader/
lock-1, /leader/lock-2, and /leader/lock-3, then the client holding /leader/lock-3 only
needs to be notified when /leader/lock-2 disappears. It does not need to be notified
when /leader/lock-1 disappears or when a new znode /leader/lock-4 is added.
Recoverable exceptions
Another problem with the lock algorithm as it stands is that it doesn’t handle the case
when the create operation fails due to connection loss. Recall that in this case we do
not know if the operation succeeded or failed. Creating a sequential znode is a
nonidempotent operation, so we can’t simply retry, since if the first create had
succeeded, we would have an orphaned znode that would never be deleted (until the
client session ended, at least). Deadlock would be the unfortunate result.
The problem is that after reconnecting, the client can’t tell whether it created any of
the child znodes. By embedding an identifier in the znode name, if it suffers a connection
loss, it can check to see whether any of the children of the lock node have its identifier
in their name. If a child contains its identifier, it knows that the create operation succeeded,
and it shouldn’t create another child znode. If no child has the identifier in its name, then the client can safely create a new sequential child znode.
The client’s session identifier is a long integer that is unique for the ZooKeeper service
and therefore ideal for the purpose of identifying a client across connection loss events.
The session identifier can be obtained by calling the getSessionId() method on the
ZooKeeper Java class.
The ephemeral sequential znode should be created with a name of the form lock-
<sessionId>-, so that when the sequence number is appended by ZooKeeper, the name
becomes lock-<sessionId>-<sequenceNumber>. The sequence numbers are unique to the
parent, not to the name of the child, so this technique allows the child znodes to identify
their creators as well as impose an order of creation.
Unrecoverable exceptions
If a client’s ZooKeeper session expires, the ephemeral znode created by the client will
be deleted, effectively relinquishing the lock or at least forfeiting the client’s turn to
acquire the lock. The application using the lock should realize that it no longer holds
the lock, clean up its state, and then start again by creating a new lock object and trying
to acquire it. Notice that it is the application that controls this process, not the lock
implementation, since it cannot second-guess how the application needs to clean up
its state.
Implementation
Implementing a distributed lock correctly is a delicate matter, since accounting for all
of the failure modes is nontrivial. ZooKeeper comes with a production-quality lock
implementation in Java called WriteLock that is very easy for clients to use.
BookKeeper and Hedwig
BookKeeper is a highly-available and reliable logging service. It can be used to provide
write-ahead logging, which is a common technique for ensuring data integrity in storage
systems. In a system using write-ahead logging, every write operation is written to the
transaction log before it is applied. Using this procedure, we don’t have to write the
data to permanent storage after every write operation because in the event of a system
failure, the latest state may be recovered by replaying the transaction log for any writes
that had not been applied.
BookKeeper clients create logs called ledgers, and each record appended to a ledger is
called a ledger entry, which is simply a byte array. Ledgers are managed by bookies,
which are servers that replicate the ledger data. Note that ledger data is not stored in
ZooKeeper, only metadata is.
Traditionally, the challenge has been to make systems that use write-ahead logging
robust in the face of failure of the node writing the transaction log. This is usually done
by replicating the transaction log in some manner. Hadoop’s HDFS namenode, for
instance, writes its edit log to multiple disks, one of which is typically an NFS mounted
disk. However, in the event of failure of the primary, failover is still manual. By providing
logging as a highly available service, BookKeeper promises to make failover
transparent, since it can tolerate the loss of bookie servers. (In the case of HDFS HighAvailability, described on 50, a BookKeeper-based edit log will remove the requirement
for using NFS for shared storage.)
Hedwig is a topic-based publish-subscribe system built on BookKeeper. Thanks to its
ZooKeeper underpinnings, Hedwig is a highly available service and guarantees message
delivery even if subscribers are offline for extended periods of time.
BookKeeper is a ZooKeeper subproject, and you can find more information on how to
use it, and Hedwig, at http://zookeeper.apache.org/bookkeeper/.
ZooKeeper in Production:
In production, you should run ZooKeeper in replicated mode. Here we will cover some
of the considerations for running an ensemble of ZooKeeper servers. However, this
section is not exhaustive, so you should consult the ZooKeeper Administrator’s
Guide for detailed up-to-date instructions, including supported platforms, recommended
hardware, maintenance procedures, and configuration properties.
Resilience and Performance:
ZooKeeper machines should be located to minimize the impact of machine and network
failure. In practice, this means that servers should be spread across racks, power supplies,
and switches, so that the failure of any one of these does not cause the ensemble to lose a majority of its servers.
For applications that require low-latency service (on the order of a few milliseconds),
it is important to run all the servers in an ensemble in a single data center. Some use
cases don’t require low-latency responses, however, which makes it feasible to spread
servers across data centers (at least two per data center) for extra resilience. Example
applications in this category are leader election and distributed coarse-grained locking,
both of which have relatively infrequent state changes so the overhead of a few tens of
milliseconds that inter-data center messages incurs is not significant to the overall
functioning of the service.
ZooKeeper is a highly available system, and it is critical that it can perform its functions
in a timely manner. Therefore, ZooKeeper should run on machines that are dedicated
to ZooKeeper alone. Having other applications contend for resources can cause ZooKeeper’s
performance to degrade significantly.
Configure ZooKeeper to keep its transaction log on a different disk drive from its snapshots.
By default, both go in the directory specified by the dataDir property, but by
specifying a location for dataLogDir, the transaction log will be written there. By having
its own dedicated device (not just a partition), a ZooKeeper server can maximize the
rate at which it writes log entries to disk, which it does sequentially, without seeking.
Since all writes go through the leader, write throughput does not scale by adding servers,
so it is crucial that writes are as fast as possible.
If the process swaps to disk, performance will be adversely affected. This can be avoided
by setting the Java heap size to less than the amount of unused physical memory on
the machine. The ZooKeeper scripts will source a file called java.env from its configu-
ration directory, and this can be used to set the JVMFLAGS environment variable to set
the heap size (and any other desired JVM arguments).
Configuration
Each server in the ensemble of ZooKeeper servers has a numeric identifier that is unique
within the ensemble, and must fall between 1 and 255. The server number is specified
in plain text in a file named myid in the directory specified by the dataDir property.
Setting each server number is only half of the job. We also need to give all the servers
all the identities and network locations of the others in the ensemble. The ZooKeeper
configuration file must include a line for each server, of the form:
server.n=hostname:port:port
The value of n is replaced by the server number. There are two port settings: the first
is the port that followers use to connect to the leader, and the second is used for leader
election. Here is a sample configuration for a three-machine replicated ZooKeeper
ensemble:
tickTime=2000
dataDir=/disk1/zookeeper
dataLogDir=/disk2/zookeeper
clientPort=2181
initLimit=5
syncLimit=2
server.1=zookeeper1:2888:3888
server.2=zookeeper2:2888:3888
server.3=zookeeper3:2888:3888
Servers listen on three ports: 2181 for client connections; 2888 for follower connections,
if they are the leader; and 3888 for other server connections during the leader election
phase. When a ZooKeeper server starts up, it reads the myid file to determine which
server it is, then reads the configuration file to determine the ports it should listen on,
as well as the network addresses of the other servers in the ensemble.
Clients connecting to this ZooKeeper ensemble should use zookeeper1:2181,zoo
keeper2:2181,zookeeper3:2181 as the host string in the constructor for the ZooKeeper
object.
In replicated mode, there are two extra mandatory properties: initLimit and
syncLimit, both measured in multiples of tickTime.
initLimit is the amount of time to allow for followers to connect to and sync with the
leader. If a majority of followers fail to sync within this period, then the leader renounces
its leadership status and another leader election takes place. If this happens often (and
you can discover if this is the case because it is logged), it is a sign that the setting is too
low.
syncLimit is the amount of time to allow a follower to sync with the leader. If a follower
fails to sync within this period, it will restart itself. Clients that were attached to this
follower will connect to another one.
These are the minimum settings needed to get up and running with a cluster of ZooKeeper
servers.
There are, however, more configuration options, particularly for tuning performance, documented in the ZooKeeper Administrator’s Guide.
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