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1# This file is part of daf_butler. 

2# 

3# Developed for the LSST Data Management System. 

4# This product includes software developed by the LSST Project 

5# (http://www.lsst.org). 

6# See the COPYRIGHT file at the top-level directory of this distribution 

7# for details of code ownership. 

8# 

9# This program is free software: you can redistribute it and/or modify 

10# it under the terms of the GNU General Public License as published by 

11# the Free Software Foundation, either version 3 of the License, or 

12# (at your option) any later version. 

13# 

14# This program is distributed in the hope that it will be useful, 

15# but WITHOUT ANY WARRANTY; without even the implied warranty of 

16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

17# GNU General Public License for more details. 

18# 

19# You should have received a copy of the GNU General Public License 

20# along with this program. If not, see <http://www.gnu.org/licenses/>. 

21from __future__ import annotations 

22 

23__all__ = ["TableDimensionRecordStorage"] 

24 

25from typing import Optional 

26 

27import sqlalchemy 

28 

29from ...core import ( 

30 DataCoordinate, 

31 DimensionElement, 

32 DimensionRecord, 

33 makeDimensionElementTableSpec, 

34 Timespan, 

35 TIMESPAN_FIELD_SPECS, 

36) 

37from ...core.utils import NamedKeyDict 

38from ..interfaces import Database, DimensionRecordStorage, StaticTablesContext 

39from ..queries import QueryBuilder 

40 

41 

42class TableDimensionRecordStorage(DimensionRecordStorage): 

43 """A record storage implementation uses a regular database table. 

44 

45 For spatial dimension elements, use `SpatialDimensionRecordStorage` 

46 instead. 

47 

48 Parameters 

49 ---------- 

50 db : `Database` 

51 Interface to the database engine and namespace that will hold these 

52 dimension records. 

53 element : `DimensionElement` 

54 The element whose records this storage will manage. 

55 table : `sqlalchemy.schema.Table` 

56 The logical table for the element. 

57 """ 

58 def __init__(self, db: Database, element: DimensionElement, *, table: sqlalchemy.schema.Table): 

59 self._db = db 

60 self._table = table 

61 self._element = element 

62 

63 @classmethod 

64 def initialize(cls, db: Database, element: DimensionElement, *, 

65 context: Optional[StaticTablesContext] = None) -> DimensionRecordStorage: 

66 # Docstring inherited from DimensionRecordStorage. 

67 spec = makeDimensionElementTableSpec(element) 

68 if context is not None: 68 ↛ 71line 68 didn't jump to line 71, because the condition on line 68 was never false

69 table = context.addTable(element.name, spec) 

70 else: 

71 table = db.ensureTableExists(element.name, spec) 

72 return cls(db, element, table=table) 

73 

74 @property 

75 def element(self) -> DimensionElement: 

76 # Docstring inherited from DimensionRecordStorage.element. 

77 return self._element 

78 

79 def clearCaches(self): 

80 # Docstring inherited from DimensionRecordStorage.clearCaches. 

81 pass 

82 

83 def join( 

84 self, 

85 builder: QueryBuilder, *, 

86 regions: Optional[NamedKeyDict[DimensionElement, sqlalchemy.sql.ColumnElement]] = None, 

87 timespans: Optional[NamedKeyDict[DimensionElement, Timespan[sqlalchemy.sql.ColumnElement]]] = None, 

88 ): 

89 # Docstring inherited from DimensionRecordStorage. 

90 assert regions is None, "This implementation does not handle spatial joins." 

91 joinDimensions = list(self.element.required) 

92 joinDimensions.extend(self.element.implied) 

93 joinOn = builder.startJoin(self._table, joinDimensions, self.element.RecordClass.__slots__) 

94 if timespans is not None: 

95 timespanInTable = Timespan( 

96 begin=self._table.columns[TIMESPAN_FIELD_SPECS.begin.name], 

97 end=self._table.columns[TIMESPAN_FIELD_SPECS.end.name], 

98 ) 

99 for timespanInQuery in timespans.values(): 99 ↛ 100line 99 didn't jump to line 100, because the loop on line 99 never started

100 joinOn.append(timespanInQuery.overlaps(timespanInTable, ops=sqlalchemy.sql)) 

101 timespans[self.element] = timespanInTable 

102 builder.finishJoin(self._table, joinOn) 

103 return self._table 

104 

105 def fetch(self, dataId: DataCoordinate) -> Optional[DimensionRecord]: 

106 # Docstring inherited from DimensionRecordStorage.fetch. 

107 RecordClass = self.element.RecordClass 

108 # I don't know how expensive it is to construct the query below, and 

109 # hence how much gain there might be to caching it, so I'm going to 

110 # wait for it to appear as a hotspot in a profile before trying that. 

111 whereTerms = [self._table.columns[fieldName] == dataId[dimension.name] 

112 for fieldName, dimension in zip(RecordClass.__slots__, self.element.required)] 

113 query = sqlalchemy.sql.select( 

114 [self._table.columns[name] for name in RecordClass.__slots__] 

115 ).select_from( 

116 self._table 

117 ).where(sqlalchemy.sql.and_(*whereTerms)) 

118 row = self._db.query(query).fetchone() 

119 if row is None: 

120 return None 

121 return RecordClass(*row) 

122 

123 def insert(self, *records: DimensionRecord): 

124 # Docstring inherited from DimensionRecordStorage.insert. 

125 elementRows = [record.toDict() for record in records] 

126 with self._db.transaction(): 

127 self._db.insert(self._table, *elementRows) 

128 

129 def sync(self, record: DimensionRecord) -> bool: 

130 # Docstring inherited from DimensionRecordStorage.sync. 

131 n = len(self.element.required) 

132 _, inserted = self._db.sync( 

133 self._table, 

134 keys={k: getattr(record, k) for k in record.__slots__[:n]}, 

135 compared={k: getattr(record, k) for k in record.__slots__[n:]}, 

136 ) 

137 return inserted