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f5981606e1
Summary: Having CONTAINS be a class is a pain, undoing that mistake now Test Plan: none needed Reviewers: dsagal Reviewed By: dsagal Differential Revision: https://phab.getgrist.com/D2929
307 lines
12 KiB
Python
307 lines
12 KiB
Python
import itertools
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from abc import abstractmethod
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import six
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import column
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import depend
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import records
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import relation
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import twowaymap
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import usertypes
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from functions.lookup import _Contains
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import logger
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log = logger.Logger(__name__, logger.INFO)
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def _extract(cell_value):
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"""
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When cell_value is a Record, returns its rowId. Otherwise returns the value unchanged.
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This is to allow lookups to work with reference columns.
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"""
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if isinstance(cell_value, records.Record):
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return cell_value._row_id
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return cell_value
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class BaseLookupMapColumn(column.BaseColumn):
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"""
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Conceptually a LookupMapColumn is associated with a table ("target table") and maintains for
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each row a key (which is a tuple of values from the named columns), which is fast to look up.
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The lookup is generally performed in a formula in a different table ("referring table").
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LookupMapColumn is similar to a FormulaColumn in that it needs to do some computation whenever
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one of its dependencies changes: namely, it needs to update the index.
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Although it acts as a column, a LookupMapColumn isn't included among its table's columns, and
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doesn't have a column id.
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Compared to relational database, LookupMapColumn is analogous to a database index.
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"""
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def __init__(self, table, col_id, col_ids_tuple):
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# Note that self._recalc_rec_method is passed in as the formula's "method".
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col_info = column.ColInfo(usertypes.Any(), is_formula=True, method=self._recalc_rec_method)
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super(BaseLookupMapColumn, self).__init__(table, col_id, col_info)
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self._col_ids_tuple = col_ids_tuple
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self._engine = table._engine
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# Two-way map between rowIds of the target table (on the left) and key tuples (on the right).
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# Multiple rows can naturally map to the same key.
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# Multiple keys can map to the same row if CONTAINS() is used
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# The map is populated by engine's _recompute when this
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# node is brought up-to-date.
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self._row_key_map = self._make_row_key_map()
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self._engine.invalidate_column(self)
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# Map of referring Node to _LookupRelation. Different tables may do lookups using this
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# LookupMapColumn, and that creates a dependency from other Nodes to us, with a relation
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# between referring rows and the lookup keys. This map stores these relations.
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self._lookup_relations = {}
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@abstractmethod
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def _make_row_key_map(self):
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raise NotImplementedError
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@abstractmethod
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def _recalc_rec_method(self, rec, table):
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"""
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LookupMapColumn acts as a formula column, and this method is the "formula" called whenever
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a dependency changes. If LookupMapColumn indexes columns (A,B), then a change to A or B would
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cause the LookupMapColumn to be invalidated for the corresponding rows, and brought up to date
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during formula recomputation by calling this method. It shold take O(1) time per affected row.
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"""
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raise NotImplementedError
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@abstractmethod
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def _get_keys(self, target_row_id):
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"""
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Get the keys associated with the given target row id.
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"""
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raise NotImplementedError
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def unset(self, row_id):
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# This is called on record removal, and is necessary to deal with removed records.
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old_keys = self._get_keys(row_id)
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for old_key in old_keys:
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self._row_key_map.remove(row_id, old_key)
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self._invalidate_affected(old_keys)
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def _invalidate_affected(self, affected_keys):
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# For each known relation, figure out which referring rows are affected, and invalidate them.
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# The engine will notice that there have been more invalidations, and recompute things again.
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for node, rel in six.iteritems(self._lookup_relations):
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affected_rows = rel.get_affected_rows_by_keys(affected_keys)
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self._engine.invalidate_records(node.table_id, affected_rows, col_ids=(node.col_id,))
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def _get_relation(self, referring_node):
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"""
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Helper which returns an existing or new _LookupRelation object for the given referring Node.
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"""
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rel = self._lookup_relations.get(referring_node)
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if not rel:
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rel = _LookupRelation(self, referring_node)
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self._lookup_relations[referring_node] = rel
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return rel
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def _delete_relation(self, referring_node):
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self._lookup_relations.pop(referring_node, None)
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if not self._lookup_relations:
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self._engine.mark_lookupmap_for_cleanup(self)
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def do_lookup(self, key):
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"""
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Looks up key in the lookup map and returns a tuple with two elements: the set of matching
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records (as a set object, not ordered), and the Relation object for those records, relating
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the current frame to the returned records. Returns an empty set if no records match.
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"""
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key = tuple(_extract(val) for val in key)
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current_frame = self._engine.get_current_frame()
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if current_frame:
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rel = self._get_relation(current_frame.node)
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rel._add_lookup(current_frame.current_row_id, key)
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else:
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rel = None
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# The _use_node call both brings LookupMapColumn up-to-date, and creates a dependency on it.
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# Relation of None isn't valid, but it happens to be unused when there is no current_frame.
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row_ids = self._row_key_map.lookup_right(key, set())
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self._engine._use_node(self.node, rel, row_ids)
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if not row_ids:
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row_ids = self._row_key_map.lookup_right(key, set())
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return row_ids, rel
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# Override various column methods, since LookupMapColumn doesn't care to store any values. To
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# outside code, it looks like a column of None's.
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def raw_get(self, value):
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return None
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def convert(self, value):
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return None
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def get_cell_value(self, row_id):
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return None
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def set(self, row_id, value):
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pass
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# For performance, prefer SimpleLookupMapColumn when no CONTAINS is used
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# in lookups, although the two implementations should be equivalent
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# See also table._add_update_summary_col
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class SimpleLookupMapColumn(BaseLookupMapColumn):
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def _make_row_key_map(self):
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return twowaymap.TwoWayMap(left=set, right="single")
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def _recalc_rec_method(self, rec, table):
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old_key = self._row_key_map.lookup_left(rec._row_id)
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# Note that rec._get_col(_col_id) is what creates the correct dependency, as well as ensures
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# that the columns used to index by are brought up-to-date (in case they are formula columns).
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new_key = tuple(_extract(rec._get_col(_col_id)) for _col_id in self._col_ids_tuple)
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try:
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self._row_key_map.insert(rec._row_id, new_key)
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except TypeError:
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# If key is not hashable, ignore it, just remove the old_key then.
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self._row_key_map.remove(rec._row_id, old_key)
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new_key = None
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# It's OK if None is one of the values, since None will just never be found as a key.
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self._invalidate_affected({old_key, new_key})
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def _get_keys(self, target_row_id):
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return {self._row_key_map.lookup_left(target_row_id)}
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class ContainsLookupMapColumn(BaseLookupMapColumn):
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def _make_row_key_map(self):
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return twowaymap.TwoWayMap(left=set, right=set)
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def _recalc_rec_method(self, rec, table):
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# Create a key in the index for every combination of values in columns
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# looked up with CONTAINS()
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new_keys_groups = []
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for col_id in self._col_ids_tuple:
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# Note that _get_col is what creates the correct dependency, as well as ensures
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# that the columns used to index by are brought up-to-date (in case they are formula columns).
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group = rec._get_col(extract_column_id(col_id))
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if isinstance(col_id, _Contains):
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# Check that the cell targeted by CONTAINS() has an appropriate type.
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# Don't iterate over characters of a string.
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# group = [] essentially means there are no new keys in this call
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if isinstance(group, (six.binary_type, six.text_type)):
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group = []
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else:
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group = [group]
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try:
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# We only care about the unique key values
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group = set(group)
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except TypeError:
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group = []
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new_keys_groups.append([_extract(v) for v in group])
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new_keys = set(itertools.product(*new_keys_groups))
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row_id = rec._row_id
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old_keys = self._get_keys(row_id)
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for old_key in old_keys - new_keys:
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self._row_key_map.remove(row_id, old_key)
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for new_key in new_keys - old_keys:
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self._row_key_map.insert(row_id, new_key)
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# Invalidate all keys which were either inserted or removed
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self._invalidate_affected(new_keys ^ old_keys)
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def _get_keys(self, target_row_id):
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# Need to copy the return value since it's the actual set
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# stored in the map and may be modified
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return set(self._row_key_map.lookup_left(target_row_id, ()))
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#----------------------------------------------------------------------
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class _LookupRelation(relation.Relation):
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"""
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_LookupRelation maintains a mapping between rows of a table doing a lookup to the rows getting
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returned from the lookup. Lookups are implemented using a LookupMapColumn, and a _LookupRelation
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with in conjunction with its LookupMapColumn.
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_LookupRelation are created and owned by LookupMapColumn, and should not be created directly by
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other code.
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"""
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def __init__(self, lookup_map, referring_node):
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super(_LookupRelation, self).__init__(referring_node.table_id, lookup_map.table_id)
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self._lookup_map = lookup_map
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self._referring_node = referring_node
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# Maps referring rows to keys, where multiple rows may map to the same key AND one row may
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# map to multiple keys (if a formula does multiple lookup calls).
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self._row_key_map = twowaymap.TwoWayMap(left=set, right=set)
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def __str__(self):
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return "_LookupRelation(%s->%s)" % (self._referring_node, self.target_table)
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def get_affected_rows(self, target_row_ids):
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if target_row_ids == depend.ALL_ROWS:
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return depend.ALL_ROWS
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# Each target row (result of a lookup by key)
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# is associated with a set of keys,and all rows that
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# looked up an affected key are affected by a change to any associated row. We remember which
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# rows looked up which key in self._row_key_map, so that when some target row changes to a new
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# key, we can know which referring rows need to be recomputed.
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return self.get_affected_rows_by_keys(
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set().union(*[self._lookup_map._get_keys(r) for r in target_row_ids])
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)
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def get_affected_rows_by_keys(self, keys):
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"""
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This is used by LookupMapColumn to know which rows got affected when a target row changed to
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have a different key. Keys can be any iterable. A key of None is allowed and affects nothing.
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"""
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affected_rows = set()
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for key in keys:
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if key is not None:
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affected_rows.update(self._row_key_map.lookup_right(key, default=()))
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return affected_rows
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def _add_lookup(self, referring_row_id, key):
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"""
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Helper used by LookupMapColumn to store the fact that the given key was looked up in the
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process of computing the given referring_row_id.
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"""
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self._row_key_map.insert(referring_row_id, key)
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def reset_rows(self, referring_rows):
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"""
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Called when starting to compute a formula, so that mappings for the given referring_rows can
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be cleared as they are about to be rebuilt.
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"""
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# Clear out references from referring_rows.
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if referring_rows == depend.ALL_ROWS:
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self._row_key_map.clear()
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else:
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for row_id in referring_rows:
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self._row_key_map.remove_left(row_id)
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def reset_all(self):
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"""
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Called when the dependency using this relation is reset, and this relation is no longer used.
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"""
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# In this case also, remove it from the LookupMapColumn. Once all relations are gone, the
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# lookup map can get cleaned up.
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self._row_key_map.clear()
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self._lookup_map._delete_relation(self._referring_node)
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def extract_column_id(c):
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if isinstance(c, _Contains):
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return c.value
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else:
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return c
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