Data Sources

Metarank has two data processing stages:

• import: consume historical visitor interaction events and produce latest point-in-time snapshot of the system and all the ML features.

• inference: continues processing live events that come realtime.

An overview diagram of event flow during inference/bootstrap is shown below:

Metarank supports the following list of connectors:

Name	Import	Inference
Apache Kafka	yes	yes
Apache Pulsar	yes	yes
AWS Kinesis Streams	yes, but actually no *	yes
RESTful API	yes	yes
Files	yes	no

* AWS Kinesis has a strict max 7 days retention period, so if you want to store more than 7 days of historical clickthrough events, choose something else (for example, add AWS Kinesis Firehose to write events from Kinesis topic to S3 files to pick them with Files connector).

Common options for bootstrapping connectors

All supported connectors have some shared options:

• offset: a time window in which events are read

  • earliest - start from the first stored message in the topic

  • latest - consume only events that came recently (after Metarank connection)

  • ts=<timestamp> - start from a specific absolute timestamp in the past

  • last=<duration> - consume only events that happened within a defined relative duration (duration supports the following patterns: 1s, 1m, 1h, 1d)

• format: event record encoding format, possible options:

  • json: Both Json-line (newline separated records) and Json-array ([{event:1}, {event:2}]) formats are supported.

  • snowplow:tsv|snowplow:json - Snowplow-native format, see Snowplow integration for details on how to set it up

File

Config file definition example:

type: file
path: /home/user/ranklens/events/
offset: earliest|latest|ts=<unixtime>|last=<duration>
format: <json|snowplow:tsv|snowplow:json>
sort: <name|time> # optional, default name

The path parameter is a node-local file or directory with the input dataset.

The file data source supports:

• compression, auto-detected based on file extension: ZStandard and GZip are supported

• directories with multiple input files. Metarank sorts files by the specified sort method to read them in a proper sequence.

Apache Kafka

Apache Kafka is an open source distributed event streaming platform.

If you already use Kafka in your project, Metarank can connect to an existing Kafka topic to read incoming and stored events both for import (with an offset set to some time in the past) and inference (when offset is set to latest) stages.

Kafka connector is configured in the following way:

type: kafka
brokers: [broker1, broker2]
topic: events
groupId: metarank
offset: earliest|latest|ts=<unixtime>|last=<duration>
format: <json|snowplow:tsv|snowplow:json>
options: # optional connector raw parameters, map<string,string>

Extra connector options can be taken from ConsumerConfig in the following way:

type: kafka
options:
  client.id: 'helloworld'
  enable.auto.commit: 'false'

Apache Pulsar

Apache Pulsar is an open source distributed messaging and streaming platform.

If you already use Pulsar in your project, Metarank can connect to an existing Pulsar topic to read incoming and stored events both for import (with an offset set to some time in the past) and inference (when offset is set to latest) stages.

Metarank supports Pulsar 2.8+, but using 2.9+ is recommended.

Pulsar connector is configured in the following way:

type: pulsar
serviceUrl: <pulsar service URL>
adminUrl: <pulsar service HTTP admin URL>
topic: events
subscriptionName: metarank
subscriptionType: exclusive # options are exclusive, shared, failover
offset: earliest|latest|ts=<unixtime>|last=<duration>
format: <json|snowplow:tsv|snowplow:json>
options: # optional connector parameters, map<string,string>

Extra connector options can be taken from Configuring Pulsar consumer in the following way:

type: pulsar
options:
  receiverQueueSize: 10
  acknowledgementsGroupTimeMicros: 50000

AWS Kinesis Streams

AWS Kinesis Streams is a fully-managed event streaming platform. Metarank uses a connector for Apache Flink which is well-maintained and feature complete.

To configure the connector, use this reference YAML block:

type: kinesis
region: us-east-1
topic: events
offset: earliest|latest|ts=<unixtime>|last=<duration>
format: <json|snowplow:tsv|snowplow:json>

Important things to note when using AWS Kinesis connector for bootstrap:

• AWS Kinesis has a hard limit on max retention time of 7 days. If you want to store more data there, use AWS Firehose to offload these events to S3 and pick them with the File connector.
• AWS limits max throughput per shard to 2Mb/s, so it may take some time to pull large dataset from kinesis. You may need to consider using an EFO consumer for a dedicated throughput.

AWS Authentication

Kinesis source uses a default auth chain from the AWS SDK, so all the possible ways of AWS SDK authentication methods are supported, but in short:

• Use IAM roles when possible

• add AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY env vars to manually supply the keys.

REST API

It's possible to ingest real-time feedback events directly using the REST API of Metarank:

• POST /feedback - push feedback events to Metarank

The /feedback endpoint is always enabled and there is no need to configure it explicitly.

You can read more about Metarank REST API in the API Documentation. You can bundle multiple events in a single batch using batch payloads, so REST API can be used for batch dataset import instead of a separate import step:

$ java -jar metarank serve --config conf.yaml
$ curl -d @events.json http://localhost:8080/feedback