class_docstr: A metric data set along with the associated SQL query node that can be rendered to get those values.
docstr: Return a flattened iterable with all groupable column associations for the current data set.
docstr_tok: ["Return","a","flattened","iterable","with","all","groupable","column","associations","for","the","current","data","set","."]
code: def groupable_column_associations(
      self,
  ) -> Sequence[ColumnAssociation]:
      """Return a flattened iterable with all groupable column associations for the current data set."""
      instances = (
          self.instance_set.entity_instances
          + self.instance_set.dimension_instances
          + self.instance_set.time_dimension_instances
      )
      return tuple(
          more_itertools.flatten(
              [instance.associated_columns for instance in instances]
          )
      )
  
file_path: metricflow/metricflow/dataset/sql_dataset.py
imports: from __future__ import annotations
  from typing import Sequence
  import more_itertools
  from metricflow.dataset.dataset import DataSet
  from metricflow.instances import InstanceSet
  from metricflow.specs.column_assoc import ColumnAssociation
  from metricflow.specs.specs import DimensionSpec, EntitySpec, TimeDimensionSpec
  from metricflow.sql.sql_plan import SqlSelectStatementNode
label_desc: Use image node_id 6 for calling the SqlDataSet obj's underlying member method code with example usage: obj.groupable_column_associations() and returns: tuple