Internal database schema

The following tables are used internally by DeepDive. There can not be tables with the same name in the database:

                            List of relations
 Schema |                     Name                     |   Type
--------+----------------------------------------------+----------
 public | dd_graph_variables_holdout                   | table
 public | dd_graph_variables_observation               | table
 public | dd_graph_weights                             | table
 public | dd_inference_result_variables                | table
 public | dd_inference_result_weights                  | table
 public | dd_inference_result_weights_mapping          | view
 public | dd_factors_[RULE_NAME]                       | table
 public | dd_weights_[RULE_NAME]                       | table
 public | [TABLE]_[VARIABLE]_inference                 | view
 public | [TABLE]_[VARIABLE]_calibration               | view
 public | dd_categories_[TABLE]                        | view

where [RULE_NAME] is the name of an inference rule, [TABLE] is the name of a table that contains variables, and [VARIABLE] is the name of a variable in the corresponding table.

Description of each schema:

  • dd_graph_variables_holdout: a table that contains all variable ids that are used for holdout. Can be used for custom holdout by a holdout query.

  • dd_graph_variables_observation: a table that contains all variable ids that are evidence that will not be fitted during learning. An usage example of this table can be found here.

  • dd_graph_weights: a table that contains all the materialized weights.

  • dd_inference_result_variables: a table that contains the inference results (expectation) for all query variables.

  • dd_inference_result_weights: a table that shows factor weight ids and learned weight values.

  • dd_inference_result_weights_mapping: a view that maps all distinct factor weights to their description and their learned values. It is a commonly used view that shows the learned weight value of a factor as well as the number of occurences of a factor.

  • dd_factors_[RULE_NAME]: a table that is defined by the input query of an inference rule. You can use it as a feature table in BrainDump.

  • dd_weight_[RULE_NAME]: a table that stores initial weights for factors, used internally.

  • [TABLE]_[VARIABLE]_inference: a view that maps variables with their inference results. It is commonly used for error analysis.

  • [TABLE]_[VARIABLE]_inference_bucketed: a table that maps variables with their inference results, with expectations separated into 10 buckets. It is used for generating calibration plots.

  • [TABLE]_[VARIABLE]_calibration: a view that has calibration statistics of a variable. Used in generating calibration plots.

  • dd_categories_[TABLE]: a view that records the cardinality series of given variable. For example if the domain of a variable is {1,2,3} the cardinality is 3.