BCO Persistence

This section introduces how InfluxDBopen in new window and the BCO Influxdb Connector app can be used to store the history of unit service state changes. This can for example be useful to persist and monitor the current economy level of your smart environment.

How to setup InfluxDB via docker

Download and run the docker container via:

sudo docker run \
  --name influxdb \
  --network=bco-net \
  --publish 8086:8086 \
  --volume influx_data:/var/lib/influxdb2 \
  --volume influx_config:/etc/influxdb2 \
  --restart=always \
  --log-driver=local \
  --detach \


Choose openbase as organization name and bco-persistence as bucket name to simplify this setup.

add_unit After the container spins up, please follow the onboarding via homecubeopen in new window by setup your initial user, bucket and organization. add_unit Once done, influxdb is up and running and you can press Configure Later to continue with the bco setup. add_unit

How to setup the BCO Influxdb Connector App.

The BCO Influxdb Connector is a BCO app that persists all unit changes into influxdb.

1. Register the new App via the UnitRegistry

To install the InfluxDbConnector you need to register it by using the bco-registry-editor. So please make sure you are connected to your BCO instance and start the bco-registry-editor --host homecube. Than, you need to navigate to: UnitRegistry → App


Now add a new unit with right click → Add

To add the InfluxDB connector class to the new unit, select InfluxDB Connector as AppClassId and press apply.


2. Authenticate and Configure the App via Meta Configs

Switch to the token overview and create a new (READ/WRITE) API token to grant BCO write access.


Don't forget to select the bco-persistence buckets.


Finally open the token menu...


... and copy the key

influxdb_copy_token Transfer the token to a new MetaConfig entry of the BCO Influxdb Connector via the bco-registry-editor e.g. INFLUXDB_TOKEN = <PASTE_TOKEN_HERE>


In case you choose the default values during the influxdb setup and you run influxdb on the same host as influxdb is running, all values except INFLUXDB_TOKEN are optionally.

Further configurable meta config entries are:

  • INFLUXDB_URL → Url of your InfluxDB
    DEFAULT: INFLUXDB_URL = http://influxdb:8086
  • INFLUXDB_BUCKET → Name of the bucket where your data will be stored
    DEFAULT: INFLUXDB_BUCKET = bco-persistence
  • INFLUXDB_BATCH_TIME → Time limit(ms) after your batch is written to the database
  • INFLUXDB_BATCH_LIMIT → Max size of your batch
  • INFLUXDB_ORG → Org for the bucket
    DEFAULT: INFLUXDB_ORG = openbase
  • INFLUXDB_TOKEN → Token with read and write access to your database

How to query influx db.

InfluxDB 2 uses Flux as a functional data scripting language. A good guide how to get started with Flux is provided by the official Influxdb Documentationopen in new window.

How to create a Query

Chronograf is the user interface and administrative component of the InfluxDB platform. It is already included in influxdb 2 With Chronograf you can quickly see your data and build dashboards.

Therefore, you need to log in into the Chronograf webview and select the Data Explorer.

If you have run bco-test --simulate and collected some data in your bucket, you should see some measurements. query_data

This query selects from the measurement power_consumption_state_service the field consumption data from the tag alias PowerConsumptionSensor-11.
It creates this query in Flux (you can see the query when you select the 'Script Editor'): flux-query

There are more options to visualize the data like raw_data, histogram table etc. You can also save your graphs into dashboards.

If you want know about the possibilities of chronograf you can have a look at the official documentation here Chronograf Documentationopen in new window


The database contains a measurement 'heartbeat' with the field 'alive'. If the influxdb connector app is started, the value one is written into this field. Every 15 minutes the value one is written into the field again. When the app is closed a zero value is written into the field. This can be used to check whether the database was functional and stored data. So you can consider possible downtimes during queries and calculations.

Source Codeopen in new window

Service Aggregation

It is possible to perform a service aggregation via the function queryAggregatedServiceState of a unit. This function needs a QueryType as a parameter. Important attributes of the QueryType for the service aggregation are:

  • measurement
  • service_type
  • time_range_stop
  • time_range_stop
  • aggregation_window

To get an overview of the QueryType look here: Queryopen in new window

The method returns an AggregatedServiceStateopen in new window. Which contains the service_type, the query and the aggregated_service_type. Depending on whether the requested service_type is an enum or not, the aggregated_service_type consists of percentages of how often which status was active, or of the average values.

// Query for continuous data
Query query = Query.newBuilder()
     .setTimeRangeStart(TimestampType.Timestamp.newBuilder().setTime(time - 3600).build())
AggregatedServiceStateType.AggregatedServiceState aggregatedServiceState = testLocation.queryAggregatedServiceState(query).get();
// Query for enum data
Query enumQuery = Query.newBuilder()
     .setTimeRangeStart(TimestampType.Timestamp.newBuilder().setTime(time - 3600).build())

AggregatedServiceStateType.AggregatedServiceState aggregatedEnumServiceState = testLocation.queryAggregatedServiceState(enumQuery).ge();

The full example how to query an aggregated service state is available over here: HowToQueryAggregatedStateopen in new window

Query Database

You can also send raw queries to the database via the units with the queryRecord function. This function needs also a QueryTypeopen in new window as a parameter. However, the only attribute that must be filled is the raw_query. The method returns an RecordCollectionopen in new window which consists of Recordsopen in new window. In the Chronograf and the Query-Section it is explained how a raw query looks like and how it can be built.

An example request looks like:

String query = "from(bucket: \"bco-persistence\")\n" +
     "  |> range(start:" + (time - 3600) + ", stop: " + time + ")\n" +
     "  |> filter(fn: (r) => r._measurement == \"power_consumption_state_service\")";
RecordCollectionType.RecordCollection recordCollection = testLocation.queryRecord(Query.newBuilder().setRawQuery(query).build()).get();

The full example how to query a database record is available over here: HowToQueryUnitLongTermStateUpdatesopen in new window.