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A working guide to kestrel

Kestrel is a very simple message queue that runs on the JVM and uses the memcache protocol (with some extensions) to talk to clients.

A single kestrel server has a set of queues identified by a name, which is also the filename of that queue's journal file (usually in /var/spool/kestrel). Each queue is a strictly-ordered FIFO of "items" of binary data. Usually this data is in some serialized format like JSON or ruby's marshal format.

Generally queue names should be limited to alphanumerics [A-Za-z0-9], dash (-) and underline (_). In practice, kestrel doesn't enforce any restrictions other than the name can't contain slash (/) because that can't be used in filenames, squiggle (~) because it's used for temporary files, plus (+) because it's used for fanout queues, and dot (.) because it's reserved for future use. Queue names are case-sensitive, but if you're running kestrel on OS X or Windows, you will want to refrain from taking advantage of this, since the journal filenames on those two platforms are not case-sensitive.

A cluster of kestrel servers is like a memcache cluster: the servers don't know about each other, and don't do any cross-communication, so you can add as many as you like. Clients have a list of all servers in the cluster, and pick one at random for each operation. In this way, each queue appears to be spread out across every server, with items in a loose ordering.

When kestrel starts up, it scans the journal folder and creates queues based on any journal files it finds there, to restore state to the way it was when it last shutdown (or was killed or died). New queues are created by referring to them (for example, adding or trying to remove an item). A queue can be deleted with the "delete" command.


The config files for kestrel are scala expressions loaded at runtime, usually from production.scala, although you can use development.scala by passing -Dstage=development to the java command line.

The config file evaluates to a KestrelConfig object that's used to configure the server as a whole, a default queue, and any overrides for specific named queues. The fields on KestrelConfig are documented here with their default values:

To confirm the current configuration of each queue, send "dump_config" to a server (which can be done over telnet).

To reload the config file on a running server, send "reload" the same way. You should immediately see the changes in "dump_config", to confirm. Reloading will only affect queue configuration, not global server configuration. To change the server configuration, restart the server.

Logging is configured according to util-logging. The logging configuration syntax is described here:

Per-queue configuration is documented here:

The journal file

The journal file is the only on-disk storage of a queue's contents, and it's just a sequential record of each add or remove operation that's happened on that queue. When kestrel starts up, it replays each queue's journal to build up the in-memory queue that it uses for client queries.

The journal file is rotated in one of two conditions:

  1. the queue is empty and the journal is larger than defaultJournalSize

  2. the journal is larger than maxJournalSize

For example, if defaultJournalSize is 16MB (the default), then if the queue is empty and the journal is larger than 16MB, it will be truncated into a new (empty) file. If the journal is larger than maxJournalSize (1GB by default), the journal will be rewritten periodically to contain just the live items.

You can turn the journal off for a queue (keepJournal = false) and the queue will exist only in memory. If the server restarts, all enqueued items are lost. You can also force a queue's journal to be sync'd to disk periodically, or even after every write operation, at a performance cost, using syncJournal.

If a queue grows past maxMemorySize bytes (128MB by default), only the first 128MB is kept in memory. The journal is used to track later items, and as items are removed, the journal is played forward to keep 128MB in memory. This is usually known as "read-behind" mode, but Twitter engineers sometimes refer to it as the "square snake" because of the diagram used to brainstorm the implementation. When a queue is in read-behind mode, removing an item will often cause 2 disk operations instead of one: one to record the remove, and one to read an item in from disk to keep 128MB in memory. This is the trade-off to avoid filling memory and crashing the JVM.

Item expiration

When they come from a client, expiration times are handled in the same way as memcache: if the number is small (less than one million), it's interpreted as a relative number of seconds from now. Otherwise it's interpreted as an absolute unix epoch time, in seconds since the beginning of 1 January 1970 GMT.

Expiration times are immediately translated into an absolute time, in milliseconds, and if it's further in the future than the queue's maxAge, the maxAge is used instead. An expiration of 0, which is usually the default, means an item never expires.

Expired items are flushed from a queue whenever a new item is added or removed. An idle queue won't have any items expired, but you can trigger a check by doing a "peek" on it.

The global config option expirationTimerFrequency can be used to start a background thread that periodically removes expired items from the head of each queue. See file for more.

Fanout Queues

If a queue name has a + in it (like "orders+audit"), it's treated as a fanout queue, using the format <parent>+<child>. These queues belong to a parent queue -- in this example, the "orders" queue. Every item written into a parent queue will also be written into each of its children.

Fanout queues each have their own journal file (if the parent queue has a journal file) and otherwise behave exactly like any other queue. You can get and peek and even add items directly to a child queue if you want. It uses the parent queue's configuration instead of having independent child queue configuration blocks.

When a fanout queue is first referenced by a client, the journal file (if any) is created, and it will start receiving new items written to the parent queue. Existing items are not copied over. A fanout queue can be deleted to stop it from receiving new items.

Memcache commands

  • SET <queue-name> <flags (ignored)> <expiration> <# bytes>

    Add an item to a queue. It may fail if the queue has a size or item limit and it's full.

  • GET <queue-name>[options]

    Remove an item from a queue. It will return an empty response immediately if the queue is empty. The queue name may be followed by options separated by /:

    • /t=<milliseconds>

      Wait up to a given time limit for a new item to arrive. If an item arrives on the queue within this timeout, it's returned as normal. Otherwise, after that timeout, an empty response is returned.

    • /open

      Tentatively remove an item from the queue. The item is returned as usual but is also set aside in case the client disappears before sending a "close" request. (See "Reliable Reads" below.)

    • /close

      Close any existing open read. (See "Reliable Reads" below.)

    • /abort

      Cancel any existing open read, returing that item to the head of the queue. It will be the next item fetched. (See "Reliable Reads" below.)

    • /peek

      Return the first available item from the queue, if there is one, but don't remove it. You can't combine this with any of the reliable read options.

    For example, to open a new read, waiting up to 500msec for an item:

      GET work/t=500/open

    Or to close an existing read and open a new one:

      GET work/close/open
  • DELETE <queue-name>

    Drop a queue, discarding any items in it, and deleting any associated journal files.

  • FLUSH <queue-name>

    Discard all items remaining in this queue. The queue remains live and new items can be added. The time it takes to flush will be linear to the current queue size, and any other activity on this queue will block while it's being flushed.


    Discard all items remaining in all queues. The queues are flushed one at a time, as if kestrel received a FLUSH command for each queue.


    Display the kestrel version in a way compatible with memcache.


    Cleanly shutdown the server and exit.


    Reload the config file and reconfigure all queues. This should have no noticable effect on the server's responsiveness.


    Dump a list of each queue currently known to the server, and list the config values for each queue. The format is:

      queue 'master' {

    The last queue will be followed by END on a line by itself.


    Display server stats in memcache style. They're described below.


    Display server stats in a more readable style, grouped by queue. They're described below.

  • MONITOR <queue-name> <seconds>

    Monitor a queue for a time, fetching any new items that arrive. Clients are queued in a fair fashion, per-item, so many clients may monitor a queue at once. After the given timeout, a separate END response will signal the end of the monitor period. Any fetched items are open transactions (see "Reliable Reads" below), and should be closed with CONFIRM.

  • CONFIRM <queue-name> <count>

    Confirm receipt of count items from a queue. Usually this is the response to a MONITOR command, to confirm the items that arrived during the monitor period.

Reliable reads

Normally when a client removes an item from the queue, kestrel immediately discards the item and assumes the client has taken ownership. This isn't always safe, because a client could crash or lose the network connection before it gets the item. So kestrel also supports a "reliable read" that happens in two stages, using the /open and /close options to GET.

When /open is used, and an item is available, kestrel will remove it from the queue and send it to the client as usual. But it will also set the item aside. If a client disconnects while it has an open read, the item is put back into the queue, at the head, so it will be the next item fetched. Only one item can be "open" per client connection.

A previous open request is closed with /close. The server will reject any attempt to open another read when one is already open, but it will ignore /close if there's no open request, so that you can add /close to every GET request for convenience.

If for some reason you want to abort a read without disconnecting, you can use /abort. But because aborted items are placed back at the head of the queue, this isn't a good way to deal with client errors. Since the error-causing item will always be the next one available, you'll end up bouncing the same item around between clients instead of making progress.

There's always a trade-off: either potentially lose items or potentially receive the same item multiple times. Reliable reads choose the latter option. To use this tactic successfully, work items should be idempotent, meaning the work could be done 2 or 3 times and have the same effect as if it had been done only once (except wasting some resources).


GET dirty_jobs/close/open
(receives job 1)
GET dirty_jobs/close/open
(closes job 1, receives job 2)

Server stats

Global stats reported by kestrel are:

  • uptime - seconds the server has been online
  • time - current time in unix epoch
  • version - version string, like "1.2"
  • curr_items - total of items waiting in all queues
  • total_itmes - total of items that have ever been added in this server's lifetime
  • bytes - total byte size of items waiting in all queues
  • curr_connections - current open connections from clients
  • total_connections - total connections that have been opened in this server's lifetime
  • cmd_get - total GET requests
  • cmd_set - total SET requests
  • cmd_peek - total GET/peek requests
  • get_hits - total GET requests that received an item
  • get_misses - total GET requests on an empty queue
  • bytes_read - total bytes read from clients
  • bytes_written - total bytes written to clients

For each queue, the following stats are also reported:

  • items - items waiting in this queue
  • bytes - total byte size of items waiting in this queue
  • total_items - total items that have been added to this queue in this server's lifetime
  • logsize - byte size of the queue's journal file
  • expired_items - total items that have been expired from this queue in this server's lifetime
  • mem_items - items in this queue that are currently in memory
  • mem_bytes - total byte size of items in this queue that are currently in memory (will always be less than or equal to max_memory_size config for the queue)
  • age - time, in milliseconds, that the last item to be fetched from this queue had been waiting; that is, the time between SET and GET; if the queue is empty, this will always be zero
  • discarded - number of items discarded because the queue was too full
  • waiters - number of clients waiting for an item from this queue (using GET/t)
  • open_transactions - items read with /open but not yet confirmed

Kestrel as a library

You can use kestrel as a library by just sticking the jar on your classpath. It's a cheap way to get a durable work queue for inter-process or inter-thread communication. Each queue is represented by a PersistentQueue object:

class PersistentQueue(val name: String, persistencePath: String,
                      @volatile var config: QueueConfig, timer: Timer,
                      queueLookup: Option[(String => Option[PersistentQueue])]) {

and must be initialized before using:

def setup(): Unit

specifying the path for the journal files (if the queue will be journaled), the name of the queue, a QueueConfig object (derived from QueueBuilder), a timer for handling timeout reads, and optionally a way to find other named queues (for expireToQueue support).

To add an item to a queue:

def add(value: Array[Byte], expiry: Option[Time]): Boolean

It will return false if the item was rejected because the queue was full.

Queue items are represented by a case class:

case class QItem(addTime: Time, expiry: Option[Time], data: Array[Byte], var xid: Int)

and several operations exist to remove or peek at the head item:

def peek(): Option[QItem]
def remove(): Option[QItem]

To open a reliable read, set transaction true, and later confirm or unremove the item by its xid:

def remove(transaction: Boolean): Option[QItem]
def unremove(xid: Int)
def confirmRemove(xid: Int)

You can also asynchronously remove or peek at items using futures.

def waitRemove(deadline: Option[Time], transaction: Boolean): Future[Option[QItem]]
def waitPeek(deadline: Option[Time]): Future[Option[QItem]]

When done, you should close the queue:

def close(): Unit
def isClosed: Boolean

Here's a short example:

var queue = new PersistentQueue("work", "/var/spool/kestrel", config, timer, None)

// add an item with no expiration:
queue.add("hello".getBytes, 0)

// start to remove it, then back out:
val item = queue.remove(true)

// remove an item with a 500msec timeout, and confirm it:
queue.waitRemove(500.milliseconds.fromNow, true)() match {
  case None =>
    println("nothing. :(")
  case Some(item) =>
    println("got: " + new String(

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