In this section we will give an overview of the database schema and more specifically, we will focus on the SQLAlchemy specific schema.
In the following image you can see the tables of a fairly empty and new AiiDA database.
The database table names are marked at the top of every table (in deep green), the names of the the columns are below. The primary key of every table is highlighted with light green and the columns that participate to an index (apart from the index of the primary key) are highlighted with yellow color.
We will now briefly describe some of the database tables.
Note
the kombu_queue
and the kombu_message
tables are generated by the celery and not by the AiiDA. In AiiDA the celery is used by daemon to handle the distributed task queue and real-time messaging. To know more about celery please refer celery documentation.
This table contains the information about all the Node instances stored in AiiDA. Since the Node class has various sub-classes, there is a column (named type
) at the db_dbnode
table that indicates the type of the node.
Other columns are the ctime
andmtime
that correspond to the creation time and the modification time of the node. There are foreign keys that link this table with the db_dbcomputer
and the db_dbuser
tables.
It is also worth noting the attributes
and extras
columns that are of type JSONB. This type allows to store directly JSON snippets in such columns while they can be indexed for fast searching.
The db_dbuser table contains user related information. It is worth noting that the stored password column contained hashed information.
The AiiDA nodes are connected with links and form a graph. The links are stored in the db_dblink
table. The columns of that table contain the name of the link, the id of the input & output nodes and the type of the node.
The db_dbpath
table is the transitive closure of the above table and it is populated automatically. The purpose of this table is to speed up graph-traversal queries. Unfortunately, there is a space penalty that is paid for that speed increase.
Please note that the db_dblink
table stores only the direct links between the nodes where as the db_dbpath
table stores all links that is direct and indirect between the nodes.
The nodes can be grouped into groups. In the db_dbgroup
table contains information about the group like the name, the type and the description of the group. The nodes that are contained in the group are stored in db_dbgroup_dbnodes
table.
The calculations have a specific state which is needed for the user to verify their status but also for the daemon to submit them and/or fetch the results. This table contains the calculation id, the state that the calculation had and the timestamp of that state.
In the db_dbcomment
table comments made by users to specific nodes are stored.
In the db_dbworkflow
table various information of the workflow are stored. These are (among others) the name and the id of the workflow as well as various metadata.
The data related to each workflow is stored at the db_dbworkflowdata
table. This data could be the input or output of the workflow and can be stored as a JSON value in database or in a text file.
The workflow is divided into multiple steps. Each step could be the new calculation or the subworkplow. The general information like parent workflow id, status, name is stored at db_dbworkflowstep
table.
If the workflow step contains the calculation(s), the ids of the workflow step and the calculation node are stored at db_dbworkflowstep_calculations
table.
If the workflow step contains the subworkflow(s), the ids of the workflow step and the subworkflow are stored at db_dbworkflowstep_sub_workflows
table.