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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 DataCoordinate, DimensionElement, DimensionRecord, Timespan, TIMESPAN_FIELD_SPECS 

30from ...core.dimensions.schema import makeElementTableSpec 

31from ...core.utils import NamedKeyDict 

32from ..interfaces import Database, DimensionRecordStorage, StaticTablesContext 

33from ..queries import QueryBuilder 

34 

35 

36class TableDimensionRecordStorage(DimensionRecordStorage): 

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

38 

39 For spatial dimension elements, use `SpatialDimensionRecordStorage` 

40 instead. 

41 

42 Parameters 

43 ---------- 

44 db : `Database` 

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

46 dimension records. 

47 element : `DimensionElement` 

48 The element whose records this storage will manage. 

49 table : `sqlalchemy.schema.Table` 

50 The logical table for the element. 

51 """ 

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

53 self._db = db 

54 self._table = table 

55 self._element = element 

56 

57 @classmethod 

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

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

60 # Docstring inherited from DimensionRecordStorage. 

61 spec = makeElementTableSpec(element) 

62 if context is not None: 62 ↛ 65line 62 didn't jump to line 65, because the condition on line 62 was never false

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

64 else: 

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

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

67 

68 @property 

69 def element(self) -> DimensionElement: 

70 # Docstring inherited from DimensionRecordStorage.element. 

71 return self._element 

72 

73 def clearCaches(self): 

74 # Docstring inherited from DimensionRecordStorage.clearCaches. 

75 pass 

76 

77 def join( 

78 self, 

79 builder: QueryBuilder, *, 

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

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

82 ): 

83 # Docstring inherited from DimensionRecordStorage. 

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

85 joinDimensions = list(self.element.graph.required) 

86 joinDimensions.extend(self.element.implied) 

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

88 if timespans is not None: 

89 timespanInTable = Timespan( 

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

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

92 ) 

93 for timespanInQuery in timespans.values(): 93 ↛ 94line 93 didn't jump to line 94, because the loop on line 93 never started

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

95 timespans[self.element] = timespanInTable 

96 builder.finishJoin(self._table, joinOn) 

97 return self._table 

98 

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

100 # Docstring inherited from DimensionRecordStorage.fetch. 

101 RecordClass = self.element.RecordClass 

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

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

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

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

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

107 query = sqlalchemy.sql.select( 

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

109 ).select_from( 

110 self._table 

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

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

113 if row is None: 

114 return None 

115 return RecordClass(*row) 

116 

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

118 # Docstring inherited from DimensionRecordStorage.insert. 

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

120 with self._db.transaction(): 

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