Data Layout

The data layouts specifies how is the data and its metadata store in the database. Since we use Mongodb for the database, we will also explain the data layout using Mongobd’s terminology.

Properties collections

The following schema defines how the properties are stored:

# Unique identifier
_id: Integer

# Name to which the property belongs. e.g. Theory level
collection_name: String

# Metadata associated with the given property
metadata: String

# Properties values as JSON
data: Optional[String]

# Input with which the property was computed encoded as JSON
input: Optional[String]

Notice that the previous schema mirros the GraphQL definition of Property in the server.

Jobs collections

The following schema defines how jobs are defined:

# Unique identifier
id: Integer

# compute Properties
property: Ref[Property]

# Input to perform the computation
settings: String

# Job status
status: Status

# User who es executing the job
user: Optional[String]

# Timestamp = datatime.timestamp()
schedule_time: Optional[Float]

# Timestamp = datatime.timestamp()
report_time: Optional[Float]

# platform where the job was run: platform.platform()
platform: Optional[String]

Notice that the previous schema mirros the GraphQL definition of Job in the server.

Note

• Optional[T] is a type that could be either None or some T.

• References ref are implemented as Mongodb DBRefs.

• Jobs are stored in a collections named like jobs_<property_collection_name>.