Event Hubs Connector
EventHubs I/O: QuickStart
The Samza EventHubs connector provides access to Azure EventHubs, Microsoft’s data streaming service on Azure. An eventhub is similar to a Kafka topic and can have multiple partitions with producers and consumers. Each message produced or consumed from an event hub is an instance of EventData.
Samza refers to any IO source (eg: Kafka) it interacts with as a system, whose properties are set using a corresponding
EventHubsSystemDescriptor allows you to configure various properties for the
EventHubsClient used by Samza.
The EventHubsInputDescriptor allows you to specify the properties of each EventHubs stream your application should read from. For each of your input streams, you should create a corresponding instance of EventHubsInputDescriptor by providing a topic-name and a serializer.
By default, messages are sent and received as byte arrays. Samza then de-serializes them to typed objects using your provided Serde. For example, the above uses a
StringSerde to de-serialize messages.
EventHubsOutputDescriptor allows you to specify the output streams for your application. For each output stream you write to in EventHubs, you should create an instance of
Each EventHubs stream is scoped to a container called a namespace, which uniquely identifies an EventHubs in a region. EventHubs’s security model is based on Shared Access Signatures(SAS). Hence, you should also provide your SAS keys and tokens to access the stream. You can generate your SAS tokens using the
Each event produced and consumed from an EventHubs stream is an instance of EventData, which wraps a byte-array payload. When producing to EventHubs, Samza serializes your object into an
EventData payload before sending it over the wire. Likewise, when consuming messages from EventHubs, messages are de-serialized into typed objects using the provided Serde.
You can use
#withPartitioningMethod to control how outgoing messages are partitioned. The following partitioning schemes are supported:
EVENT_HUB_HASHING: By default, Samza computes the partition for an outgoing message based on the hash of its partition-key. This ensures that events with the same key are sent to the same partition. If this option is chosen, the partition key should be a string. If the partition key is not set, the key in the message is used for partitioning.
PARTITION_KEY_AS_PARTITION: In this method, each message is sent to the partition specified by its partition key. This requires the partition key to be an integer. If the key is greater than the number of partitions, a modulo operation will be performed on the key. Similar to EVENT_HUB_HASHING, the key in the message is used if the partition key is not specified.
ROUND_ROBIN: In this method, outgoing messages are distributed in a round-robin across all partitions. The key and the partition key in the message are ignored.
Event Hubs supports the notion of consumer groups which enable multiple applications to have their own view of the event stream. Each partition is exclusively consumed by one consumer in the group. Each event hub stream has a pre-defined consumer group named $Default. You can define your own consumer group for your job using
Consumer buffer size
When the consumer reads a message from EventHubs, it appends them to a shared producer-consumer queue corresponding to its partition. This config determines the per-partition queue size. Setting a higher value for this config typically achieves a higher throughput at the expense of increased on-heap memory.
In this section, we will walk through a simple pipeline that reads from one EventHubs stream and copies each message to another output stream.
-Line 1 instantiates an
EventHubsSystemDescriptor configuring an EventHubsClient with 5 threads. To consume from other input sources like Kafka, you can define their corresponding descriptors.
-Line 2 creates an
EventHubsInputDescriptor with a String serde for its values. Recall that Samza follows a KV data-model for input messages. In the case of EventHubs, the key is a string which is set to the partitionKey in the message. Hence, no separate key serde is required.
-Line 3 creates an
EventHubsOutputDescriptor to write to an EventHubs stream with the given credentials.
-Line 4 obtains a
MessageStream from the input descriptor that you can later chain operations on.
-Line 5 creates an
OutputStream with the previously defined
EventHubsOutputDescriptor that you can send messages to.
-Line 7-12 define a simple pipeline that copies message from one EventHubs stream to another