Streams in GDN is built on the publish-subscribe pattern, aka pub-sub. In this pattern, producers publish messages to streams. Consumers can then subscribe to those streams, process incoming messages, and send an acknowledgement when processing is complete.
Once a subscription has been created, all messages will be retained by GDN streams, even if the consumer gets disconnected. Retained messages will be discarded only when a consumer acknowledges that they've been successfully processed.
As in other pub-sub systems, streams in GDN are named channels for transmitting messages from producers to consumers. Stream names are URLs that have a well-defined structure:
|Stream name component||Description|
||This identifies the type of stream. GDN currently supports only persistent streams. With persistent streams, all messages are durably persistedon disk (that means on multiple disks).|
||The stream tenant within the instance. Tenants are essential to multi-tenancy in GDN|
||The administrative unit of the stream, which acts as a grouping and geo-fencing mechanism for related streams. Stream configuration is performed at the geofabric level. Each tenant can have multiple geofabrics.|
||The final part of the name. Stream names are freeform.|
Every collection within a geofabric is also a stream with same name.
A geofabric is a geo-fenced grouping within a tenant. A tenant can create multiple geofabrics. For instance, a tenant with different applications can create a separate geofabric for each application. A geofabric allows the application to create and manage a hierarchy of streams. The stream
my-tenant/app1 is a geofabric for the application
my-tenant. You can create any number of
streams under the geofabric.
Messages are the basic
unit of GDN streams. They're what producers publish to streams and what consumers then consume from streams (and acknowledge when the message has been processed). Messages are the analogue of letters in a postal service system.
|Value / data payload||The data carried by the message. All GDN stream messages carry raw bytes, although message data can also conform to data schemas in future|
|Key||Messages can optionally be tagged with keys, which can be useful for things like stream compaction|
|Properties||An optional key/value map of user-defined properties|
|Producer name||The name of the producer that produced the message (producers are automatically given default names, but you can apply your own explicitly as well)|
|Sequence ID||Each GDN stream message belongs to an ordered sequence on its stream. A message's sequence ID is its ordering in that sequence.|
|Publish time||The timestamp of when the message was published (automatically applied by the producer)|
|Event time||An optional timestamp that applications can attach to the message representing when something happened, e.g. when the message was processed. The event time of a message is 0 if none is explicitly set.|
A producer is a process that attaches to a stream and publishes messages to a C8 for processing.
Producers can send messages to GDN either synchronously (sync) or asynchronously (async).
|Sync send||The producer will wait for acknowledgement from the broker after sending each message. If acknowledgment isn't received then the producer will consider the send operation a failure.|
|Async send||The producer will put the message in a blocking queue and return immediately. The client library will then send the message to the broker in the background. If the queue is full, the producer could be blocked or fail immediately when calling the API, depending on arguments passed to the producer.|
Messages published by producers can be compressed during transportation in order to save bandwidth. C8 streams currently supports two types of compression:
If batching is enabled, the producer will accumulate and send a batch of messages in a single request. Batching size is defined by the maximum number of messages and maximum publish latency.
A consumer is a process that attaches to a stream via a subscription and then receives messages.
Messages can be received from C8 either synchronously (sync) or asynchronously (async).
|Sync receive||A sync receive will be blocked until a message is available.|
|Async receive||An async receive will return immediately with a future value|
When a consumer has successfully processed a message, it needs to send an acknowledgement to the GDN so that GDN can discard the message (otherwise it stores the message).
Messages can be acknowledged either one by one or cumulatively. With cumulative acknowledgement, the consumer only needs to acknowledge the last message it received. All messages in the stream up to (and including) the provided message will not be re-delivered to that consumer.
Cumulative acknowledgement cannot be used with
shared subscription mode, because shared mode involves multiple consumers having access to the same subscription.
Client libraries can provide their own listener implementations for consumers. In this interface, the
received method is called whenever a new message is received.
A subscription is a named configuration rule that determines how messages are delivered to consumers. There are three available subscription modes in GDN streams: exclusive, shared, and failover. These modes are illustrated in the figure below.
exclusive mode, only a single consumer is allowed to attach to the subscription. If more than one consumer attempts to subscribe to a stream using the same subscription, the consumer receives an error.
In the diagram above, only Consumer-A is allowed to consume messages.
Exclusive mode is the default subscription mode.
round robin mode, multiple consumers can attach to the same subscription. Messages are delivered in a round robin distribution across consumers, and any given message is delivered to only one consumer. When a consumer disconnects, all the messages that were sent to it and not acknowledged will be rescheduled for sending to the remaining consumers.
In the diagram above, Consumer-B-1 and Consumer-B-2 are able to subscribe to the stream, but Consumer-C-1 and others could as well.
Limitations of shared mode:
There are two important things to be aware of when using shared mode:
- Message ordering is not guaranteed.
- You cannot use cumulative acknowledgment with shared mode.
failover mode, multiple consumers can attach to the same subscription. The consumers will be lexically sorted by the consumer's name and the first consumer will initially be the only one receiving messages. This consumer is called the
When the master consumer disconnects, all (non-acked and subsequent) messages will be delivered to the next consumer in line.
In the diagram above, Consumer-C-1 is the master consumer while Consumer-C-2 would be the next in line to receive messages if Consumer-C-1 disconnected.
When a consumer subscribes to a GDN stream, by default it subscribes to one specific stream, such as
persistent://tenant1/fabric1/my-stream. GDN stream consumers can simultaneously subscribe to multiple streams. You can define a list of streams in two ways:
- On the basis of a **reg**ular **ex**pression (regex), for example
- By explicitly defining a list of streams
When subscribing to multiple streams by regex, all streams must be in the same
When subscribing to multiple streams, the GDN stream client will automatically make a call to the GDN API to discover the streams that match the regex pattern/list and then subscribe to all of them. If any of the streams don't currently exist, the consumer will auto-subscribe to them once the streams are created.
No ordering guarantees:
When a consumer subscribes to multiple streams, all ordering guarantees normally provided by GDN on single stream do not hold. If your use case for GDN involves any strict ordering requirements, we would strongly recommend against using this feature.
Stream as Message Queue¶
Message queues are essential components of many large-scale data architectures. If every single work object that passes through your system absolutely
must be processed in spite of the slowness or downright failure of this or that system component, there's a good chance that you'll need a message queue to step in and ensure that unprocessed data is retained---with correct ordering---until the required actions are taken.
GDN Streams is a great choice for a message queue because:
- it was built with persistent storage in mind
- it offers automatic load balancing across consumers for messages on a stream
You can use the same GDN stream to act as a real-time message bus and as a message queue if you wish (or just one or the other)
You can set aside some streams for real-time purposes and other streams for message queue purposes (or use specific geofabrics for either purpose if you wish).
Client configuration changes:
To use a stream as a message queue, you should distribute the receiver load on that topic across several consumers (the optimal number of consumers will depend on the load).
Each consumer must:
Establish a shared subscription and use the same subscription name as the other consumers (otherwise the subscription is not shared and the consumers can't act as a processing ensemble)
If you'd like to have tight control over message dispatching across consumers, set the consumers' receiver queue size very low (potentially even to 0 if necessary).
Each Stream has a receiver queue that determines how many messages the consumer will attempt to fetch at a time. A receiver queue of 1000 (the default), for example, means that the consumer will attempt to process 1000 messages from the stream's backlog upon connection. Setting the receiver queue to zero essentially means ensuring that each consumer is only doing one thing at a time.
The downside to restricting the receiver queue size of consumers is that that limits the potential throughput of those consumers. Whether the performance/control trade-off is worthwhile will depend on your use case.
Message Retention and Expiry¶
By default, GDN:
- immediately delete
allmessages that have been acknowledged by a consumer, and
- persistently store all unacknowledged messages in a message backlog for upto 3 days.
GDN streams has two features, however, that enable you to override this default behavior:
- Message retention enables you to store messages that have been acknowledged by a consumer
- Message expiry enables you to set a time to live (TTL) for messages that have not yet been acknowledged
All message retention and expiry is managed at the
The diagram below illustrates both concepts:
With message retention, shown at the top, a
retention policy applied to all streams in a database dicates that some messages are durably stored in GDN even though they've already been acknowledged. Acknowledged messages that are not covered by the retention policy are
deleted. Without a retention policy,
all of the
acknowledged messages would be deleted.
With message expiry, shown at the bottom, some messages are
deleted, even though they
haven't been acknowledged, because they've expired according to the
TTL applied to the namespace (for example because a TTL of 5 minutes has been applied and the messages haven't been acknowledged but are 10 minutes old).