sqlglot.dialects.spark2
1from __future__ import annotations 2 3import typing as t 4 5from sqlglot import exp, parser 6from sqlglot.dialects.dialect import create_with_partitions_sql, rename_func, trim_sql 7from sqlglot.dialects.hive import Hive 8from sqlglot.helper import seq_get 9 10 11def _create_sql(self: Hive.Generator, e: exp.Create) -> str: 12 kind = e.args["kind"] 13 properties = e.args.get("properties") 14 15 if kind.upper() == "TABLE" and any( 16 isinstance(prop, exp.TemporaryProperty) 17 for prop in (properties.expressions if properties else []) 18 ): 19 return f"CREATE TEMPORARY VIEW {self.sql(e, 'this')} AS {self.sql(e, 'expression')}" 20 return create_with_partitions_sql(self, e) 21 22 23def _map_sql(self: Hive.Generator, expression: exp.Map) -> str: 24 keys = self.sql(expression.args["keys"]) 25 values = self.sql(expression.args["values"]) 26 return f"MAP_FROM_ARRAYS({keys}, {values})" 27 28 29def _parse_as_cast(to_type: str) -> t.Callable[[t.Sequence], exp.Expression]: 30 return lambda args: exp.Cast(this=seq_get(args, 0), to=exp.DataType.build(to_type)) 31 32 33def _str_to_date(self: Hive.Generator, expression: exp.StrToDate) -> str: 34 this = self.sql(expression, "this") 35 time_format = self.format_time(expression) 36 if time_format == Hive.date_format: 37 return f"TO_DATE({this})" 38 return f"TO_DATE({this}, {time_format})" 39 40 41def _unix_to_time_sql(self: Hive.Generator, expression: exp.UnixToTime) -> str: 42 scale = expression.args.get("scale") 43 timestamp = self.sql(expression, "this") 44 if scale is None: 45 return f"CAST(FROM_UNIXTIME({timestamp}) AS TIMESTAMP)" 46 if scale == exp.UnixToTime.SECONDS: 47 return f"TIMESTAMP_SECONDS({timestamp})" 48 if scale == exp.UnixToTime.MILLIS: 49 return f"TIMESTAMP_MILLIS({timestamp})" 50 if scale == exp.UnixToTime.MICROS: 51 return f"TIMESTAMP_MICROS({timestamp})" 52 53 raise ValueError("Improper scale for timestamp") 54 55 56class Spark2(Hive): 57 class Parser(Hive.Parser): 58 FUNCTIONS = { 59 **Hive.Parser.FUNCTIONS, # type: ignore 60 "MAP_FROM_ARRAYS": exp.Map.from_arg_list, 61 "TO_UNIX_TIMESTAMP": exp.StrToUnix.from_arg_list, 62 "LEFT": lambda args: exp.Substring( 63 this=seq_get(args, 0), 64 start=exp.Literal.number(1), 65 length=seq_get(args, 1), 66 ), 67 "SHIFTLEFT": lambda args: exp.BitwiseLeftShift( 68 this=seq_get(args, 0), 69 expression=seq_get(args, 1), 70 ), 71 "SHIFTRIGHT": lambda args: exp.BitwiseRightShift( 72 this=seq_get(args, 0), 73 expression=seq_get(args, 1), 74 ), 75 "RIGHT": lambda args: exp.Substring( 76 this=seq_get(args, 0), 77 start=exp.Sub( 78 this=exp.Length(this=seq_get(args, 0)), 79 expression=exp.Add(this=seq_get(args, 1), expression=exp.Literal.number(1)), 80 ), 81 length=seq_get(args, 1), 82 ), 83 "APPROX_PERCENTILE": exp.ApproxQuantile.from_arg_list, 84 "IIF": exp.If.from_arg_list, 85 "AGGREGATE": exp.Reduce.from_arg_list, 86 "DAYOFWEEK": lambda args: exp.DayOfWeek( 87 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 88 ), 89 "DAYOFMONTH": lambda args: exp.DayOfMonth( 90 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 91 ), 92 "DAYOFYEAR": lambda args: exp.DayOfYear( 93 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 94 ), 95 "WEEKOFYEAR": lambda args: exp.WeekOfYear( 96 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 97 ), 98 "DATE": lambda args: exp.Cast(this=seq_get(args, 0), to=exp.DataType.build("date")), 99 "DATE_TRUNC": lambda args: exp.TimestampTrunc( 100 this=seq_get(args, 1), 101 unit=exp.var(seq_get(args, 0)), 102 ), 103 "TRUNC": lambda args: exp.DateTrunc(unit=seq_get(args, 1), this=seq_get(args, 0)), 104 "BOOLEAN": _parse_as_cast("boolean"), 105 "DOUBLE": _parse_as_cast("double"), 106 "FLOAT": _parse_as_cast("float"), 107 "INT": _parse_as_cast("int"), 108 "STRING": _parse_as_cast("string"), 109 "TIMESTAMP": _parse_as_cast("timestamp"), 110 } 111 112 FUNCTION_PARSERS = { 113 **parser.Parser.FUNCTION_PARSERS, # type: ignore 114 "BROADCAST": lambda self: self._parse_join_hint("BROADCAST"), 115 "BROADCASTJOIN": lambda self: self._parse_join_hint("BROADCASTJOIN"), 116 "MAPJOIN": lambda self: self._parse_join_hint("MAPJOIN"), 117 "MERGE": lambda self: self._parse_join_hint("MERGE"), 118 "SHUFFLEMERGE": lambda self: self._parse_join_hint("SHUFFLEMERGE"), 119 "MERGEJOIN": lambda self: self._parse_join_hint("MERGEJOIN"), 120 "SHUFFLE_HASH": lambda self: self._parse_join_hint("SHUFFLE_HASH"), 121 "SHUFFLE_REPLICATE_NL": lambda self: self._parse_join_hint("SHUFFLE_REPLICATE_NL"), 122 } 123 124 def _parse_add_column(self) -> t.Optional[exp.Expression]: 125 return self._match_text_seq("ADD", "COLUMNS") and self._parse_schema() 126 127 def _parse_drop_column(self) -> t.Optional[exp.Expression]: 128 return self._match_text_seq("DROP", "COLUMNS") and self.expression( 129 exp.Drop, 130 this=self._parse_schema(), 131 kind="COLUMNS", 132 ) 133 134 def _pivot_column_names(self, pivot_columns: t.List[exp.Expression]) -> t.List[str]: 135 # Spark doesn't add a suffix to the pivot columns when there's a single aggregation 136 if len(pivot_columns) == 1: 137 return [""] 138 139 names = [] 140 for agg in pivot_columns: 141 if isinstance(agg, exp.Alias): 142 names.append(agg.alias) 143 else: 144 """ 145 This case corresponds to aggregations without aliases being used as suffixes 146 (e.g. col_avg(foo)). We need to unquote identifiers because they're going to 147 be quoted in the base parser's `_parse_pivot` method, due to `to_identifier`. 148 Otherwise, we'd end up with `col_avg(`foo`)` (notice the double quotes). 149 150 Moreover, function names are lowercased in order to mimic Spark's naming scheme. 151 """ 152 agg_all_unquoted = agg.transform( 153 lambda node: exp.Identifier(this=node.name, quoted=False) 154 if isinstance(node, exp.Identifier) 155 else node 156 ) 157 names.append(agg_all_unquoted.sql(dialect="spark", normalize_functions="lower")) 158 159 return names 160 161 class Generator(Hive.Generator): 162 TYPE_MAPPING = { 163 **Hive.Generator.TYPE_MAPPING, # type: ignore 164 exp.DataType.Type.TINYINT: "BYTE", 165 exp.DataType.Type.SMALLINT: "SHORT", 166 exp.DataType.Type.BIGINT: "LONG", 167 } 168 169 PROPERTIES_LOCATION = { 170 **Hive.Generator.PROPERTIES_LOCATION, # type: ignore 171 exp.EngineProperty: exp.Properties.Location.UNSUPPORTED, 172 exp.AutoIncrementProperty: exp.Properties.Location.UNSUPPORTED, 173 exp.CharacterSetProperty: exp.Properties.Location.UNSUPPORTED, 174 exp.CollateProperty: exp.Properties.Location.UNSUPPORTED, 175 } 176 177 TRANSFORMS = { 178 **Hive.Generator.TRANSFORMS, # type: ignore 179 exp.ApproxDistinct: rename_func("APPROX_COUNT_DISTINCT"), 180 exp.FileFormatProperty: lambda self, e: f"USING {e.name.upper()}", 181 exp.ArraySum: lambda self, e: f"AGGREGATE({self.sql(e, 'this')}, 0, (acc, x) -> acc + x, acc -> acc)", 182 exp.BitwiseLeftShift: rename_func("SHIFTLEFT"), 183 exp.BitwiseRightShift: rename_func("SHIFTRIGHT"), 184 exp.DateTrunc: lambda self, e: self.func("TRUNC", e.this, e.args.get("unit")), 185 exp.Hint: lambda self, e: f" /*+ {self.expressions(e).strip()} */", 186 exp.StrToDate: _str_to_date, 187 exp.StrToTime: lambda self, e: f"TO_TIMESTAMP({self.sql(e, 'this')}, {self.format_time(e)})", 188 exp.UnixToTime: _unix_to_time_sql, 189 exp.Create: _create_sql, 190 exp.Map: _map_sql, 191 exp.Reduce: rename_func("AGGREGATE"), 192 exp.StructKwarg: lambda self, e: f"{self.sql(e, 'this')}: {self.sql(e, 'expression')}", 193 exp.TimestampTrunc: lambda self, e: self.func( 194 "DATE_TRUNC", exp.Literal.string(e.text("unit")), e.this 195 ), 196 exp.Trim: trim_sql, 197 exp.VariancePop: rename_func("VAR_POP"), 198 exp.DateFromParts: rename_func("MAKE_DATE"), 199 exp.LogicalOr: rename_func("BOOL_OR"), 200 exp.LogicalAnd: rename_func("BOOL_AND"), 201 exp.DayOfWeek: rename_func("DAYOFWEEK"), 202 exp.DayOfMonth: rename_func("DAYOFMONTH"), 203 exp.DayOfYear: rename_func("DAYOFYEAR"), 204 exp.WeekOfYear: rename_func("WEEKOFYEAR"), 205 exp.AtTimeZone: lambda self, e: f"FROM_UTC_TIMESTAMP({self.sql(e, 'this')}, {self.sql(e, 'zone')})", 206 } 207 TRANSFORMS.pop(exp.ArraySort) 208 TRANSFORMS.pop(exp.ILike) 209 210 WRAP_DERIVED_VALUES = False 211 CREATE_FUNCTION_RETURN_AS = False 212 213 def cast_sql(self, expression: exp.Cast) -> str: 214 if isinstance(expression.this, exp.Cast) and expression.this.is_type( 215 exp.DataType.Type.JSON 216 ): 217 schema = f"'{self.sql(expression, 'to')}'" 218 return self.func("FROM_JSON", expression.this.this, schema) 219 if expression.to.is_type(exp.DataType.Type.JSON): 220 return self.func("TO_JSON", expression.this) 221 222 return super(Hive.Generator, self).cast_sql(expression) 223 224 class Tokenizer(Hive.Tokenizer): 225 HEX_STRINGS = [("X'", "'")]
57class Spark2(Hive): 58 class Parser(Hive.Parser): 59 FUNCTIONS = { 60 **Hive.Parser.FUNCTIONS, # type: ignore 61 "MAP_FROM_ARRAYS": exp.Map.from_arg_list, 62 "TO_UNIX_TIMESTAMP": exp.StrToUnix.from_arg_list, 63 "LEFT": lambda args: exp.Substring( 64 this=seq_get(args, 0), 65 start=exp.Literal.number(1), 66 length=seq_get(args, 1), 67 ), 68 "SHIFTLEFT": lambda args: exp.BitwiseLeftShift( 69 this=seq_get(args, 0), 70 expression=seq_get(args, 1), 71 ), 72 "SHIFTRIGHT": lambda args: exp.BitwiseRightShift( 73 this=seq_get(args, 0), 74 expression=seq_get(args, 1), 75 ), 76 "RIGHT": lambda args: exp.Substring( 77 this=seq_get(args, 0), 78 start=exp.Sub( 79 this=exp.Length(this=seq_get(args, 0)), 80 expression=exp.Add(this=seq_get(args, 1), expression=exp.Literal.number(1)), 81 ), 82 length=seq_get(args, 1), 83 ), 84 "APPROX_PERCENTILE": exp.ApproxQuantile.from_arg_list, 85 "IIF": exp.If.from_arg_list, 86 "AGGREGATE": exp.Reduce.from_arg_list, 87 "DAYOFWEEK": lambda args: exp.DayOfWeek( 88 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 89 ), 90 "DAYOFMONTH": lambda args: exp.DayOfMonth( 91 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 92 ), 93 "DAYOFYEAR": lambda args: exp.DayOfYear( 94 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 95 ), 96 "WEEKOFYEAR": lambda args: exp.WeekOfYear( 97 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 98 ), 99 "DATE": lambda args: exp.Cast(this=seq_get(args, 0), to=exp.DataType.build("date")), 100 "DATE_TRUNC": lambda args: exp.TimestampTrunc( 101 this=seq_get(args, 1), 102 unit=exp.var(seq_get(args, 0)), 103 ), 104 "TRUNC": lambda args: exp.DateTrunc(unit=seq_get(args, 1), this=seq_get(args, 0)), 105 "BOOLEAN": _parse_as_cast("boolean"), 106 "DOUBLE": _parse_as_cast("double"), 107 "FLOAT": _parse_as_cast("float"), 108 "INT": _parse_as_cast("int"), 109 "STRING": _parse_as_cast("string"), 110 "TIMESTAMP": _parse_as_cast("timestamp"), 111 } 112 113 FUNCTION_PARSERS = { 114 **parser.Parser.FUNCTION_PARSERS, # type: ignore 115 "BROADCAST": lambda self: self._parse_join_hint("BROADCAST"), 116 "BROADCASTJOIN": lambda self: self._parse_join_hint("BROADCASTJOIN"), 117 "MAPJOIN": lambda self: self._parse_join_hint("MAPJOIN"), 118 "MERGE": lambda self: self._parse_join_hint("MERGE"), 119 "SHUFFLEMERGE": lambda self: self._parse_join_hint("SHUFFLEMERGE"), 120 "MERGEJOIN": lambda self: self._parse_join_hint("MERGEJOIN"), 121 "SHUFFLE_HASH": lambda self: self._parse_join_hint("SHUFFLE_HASH"), 122 "SHUFFLE_REPLICATE_NL": lambda self: self._parse_join_hint("SHUFFLE_REPLICATE_NL"), 123 } 124 125 def _parse_add_column(self) -> t.Optional[exp.Expression]: 126 return self._match_text_seq("ADD", "COLUMNS") and self._parse_schema() 127 128 def _parse_drop_column(self) -> t.Optional[exp.Expression]: 129 return self._match_text_seq("DROP", "COLUMNS") and self.expression( 130 exp.Drop, 131 this=self._parse_schema(), 132 kind="COLUMNS", 133 ) 134 135 def _pivot_column_names(self, pivot_columns: t.List[exp.Expression]) -> t.List[str]: 136 # Spark doesn't add a suffix to the pivot columns when there's a single aggregation 137 if len(pivot_columns) == 1: 138 return [""] 139 140 names = [] 141 for agg in pivot_columns: 142 if isinstance(agg, exp.Alias): 143 names.append(agg.alias) 144 else: 145 """ 146 This case corresponds to aggregations without aliases being used as suffixes 147 (e.g. col_avg(foo)). We need to unquote identifiers because they're going to 148 be quoted in the base parser's `_parse_pivot` method, due to `to_identifier`. 149 Otherwise, we'd end up with `col_avg(`foo`)` (notice the double quotes). 150 151 Moreover, function names are lowercased in order to mimic Spark's naming scheme. 152 """ 153 agg_all_unquoted = agg.transform( 154 lambda node: exp.Identifier(this=node.name, quoted=False) 155 if isinstance(node, exp.Identifier) 156 else node 157 ) 158 names.append(agg_all_unquoted.sql(dialect="spark", normalize_functions="lower")) 159 160 return names 161 162 class Generator(Hive.Generator): 163 TYPE_MAPPING = { 164 **Hive.Generator.TYPE_MAPPING, # type: ignore 165 exp.DataType.Type.TINYINT: "BYTE", 166 exp.DataType.Type.SMALLINT: "SHORT", 167 exp.DataType.Type.BIGINT: "LONG", 168 } 169 170 PROPERTIES_LOCATION = { 171 **Hive.Generator.PROPERTIES_LOCATION, # type: ignore 172 exp.EngineProperty: exp.Properties.Location.UNSUPPORTED, 173 exp.AutoIncrementProperty: exp.Properties.Location.UNSUPPORTED, 174 exp.CharacterSetProperty: exp.Properties.Location.UNSUPPORTED, 175 exp.CollateProperty: exp.Properties.Location.UNSUPPORTED, 176 } 177 178 TRANSFORMS = { 179 **Hive.Generator.TRANSFORMS, # type: ignore 180 exp.ApproxDistinct: rename_func("APPROX_COUNT_DISTINCT"), 181 exp.FileFormatProperty: lambda self, e: f"USING {e.name.upper()}", 182 exp.ArraySum: lambda self, e: f"AGGREGATE({self.sql(e, 'this')}, 0, (acc, x) -> acc + x, acc -> acc)", 183 exp.BitwiseLeftShift: rename_func("SHIFTLEFT"), 184 exp.BitwiseRightShift: rename_func("SHIFTRIGHT"), 185 exp.DateTrunc: lambda self, e: self.func("TRUNC", e.this, e.args.get("unit")), 186 exp.Hint: lambda self, e: f" /*+ {self.expressions(e).strip()} */", 187 exp.StrToDate: _str_to_date, 188 exp.StrToTime: lambda self, e: f"TO_TIMESTAMP({self.sql(e, 'this')}, {self.format_time(e)})", 189 exp.UnixToTime: _unix_to_time_sql, 190 exp.Create: _create_sql, 191 exp.Map: _map_sql, 192 exp.Reduce: rename_func("AGGREGATE"), 193 exp.StructKwarg: lambda self, e: f"{self.sql(e, 'this')}: {self.sql(e, 'expression')}", 194 exp.TimestampTrunc: lambda self, e: self.func( 195 "DATE_TRUNC", exp.Literal.string(e.text("unit")), e.this 196 ), 197 exp.Trim: trim_sql, 198 exp.VariancePop: rename_func("VAR_POP"), 199 exp.DateFromParts: rename_func("MAKE_DATE"), 200 exp.LogicalOr: rename_func("BOOL_OR"), 201 exp.LogicalAnd: rename_func("BOOL_AND"), 202 exp.DayOfWeek: rename_func("DAYOFWEEK"), 203 exp.DayOfMonth: rename_func("DAYOFMONTH"), 204 exp.DayOfYear: rename_func("DAYOFYEAR"), 205 exp.WeekOfYear: rename_func("WEEKOFYEAR"), 206 exp.AtTimeZone: lambda self, e: f"FROM_UTC_TIMESTAMP({self.sql(e, 'this')}, {self.sql(e, 'zone')})", 207 } 208 TRANSFORMS.pop(exp.ArraySort) 209 TRANSFORMS.pop(exp.ILike) 210 211 WRAP_DERIVED_VALUES = False 212 CREATE_FUNCTION_RETURN_AS = False 213 214 def cast_sql(self, expression: exp.Cast) -> str: 215 if isinstance(expression.this, exp.Cast) and expression.this.is_type( 216 exp.DataType.Type.JSON 217 ): 218 schema = f"'{self.sql(expression, 'to')}'" 219 return self.func("FROM_JSON", expression.this.this, schema) 220 if expression.to.is_type(exp.DataType.Type.JSON): 221 return self.func("TO_JSON", expression.this) 222 223 return super(Hive.Generator, self).cast_sql(expression) 224 225 class Tokenizer(Hive.Tokenizer): 226 HEX_STRINGS = [("X'", "'")]
58 class Parser(Hive.Parser): 59 FUNCTIONS = { 60 **Hive.Parser.FUNCTIONS, # type: ignore 61 "MAP_FROM_ARRAYS": exp.Map.from_arg_list, 62 "TO_UNIX_TIMESTAMP": exp.StrToUnix.from_arg_list, 63 "LEFT": lambda args: exp.Substring( 64 this=seq_get(args, 0), 65 start=exp.Literal.number(1), 66 length=seq_get(args, 1), 67 ), 68 "SHIFTLEFT": lambda args: exp.BitwiseLeftShift( 69 this=seq_get(args, 0), 70 expression=seq_get(args, 1), 71 ), 72 "SHIFTRIGHT": lambda args: exp.BitwiseRightShift( 73 this=seq_get(args, 0), 74 expression=seq_get(args, 1), 75 ), 76 "RIGHT": lambda args: exp.Substring( 77 this=seq_get(args, 0), 78 start=exp.Sub( 79 this=exp.Length(this=seq_get(args, 0)), 80 expression=exp.Add(this=seq_get(args, 1), expression=exp.Literal.number(1)), 81 ), 82 length=seq_get(args, 1), 83 ), 84 "APPROX_PERCENTILE": exp.ApproxQuantile.from_arg_list, 85 "IIF": exp.If.from_arg_list, 86 "AGGREGATE": exp.Reduce.from_arg_list, 87 "DAYOFWEEK": lambda args: exp.DayOfWeek( 88 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 89 ), 90 "DAYOFMONTH": lambda args: exp.DayOfMonth( 91 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 92 ), 93 "DAYOFYEAR": lambda args: exp.DayOfYear( 94 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 95 ), 96 "WEEKOFYEAR": lambda args: exp.WeekOfYear( 97 this=exp.TsOrDsToDate(this=seq_get(args, 0)), 98 ), 99 "DATE": lambda args: exp.Cast(this=seq_get(args, 0), to=exp.DataType.build("date")), 100 "DATE_TRUNC": lambda args: exp.TimestampTrunc( 101 this=seq_get(args, 1), 102 unit=exp.var(seq_get(args, 0)), 103 ), 104 "TRUNC": lambda args: exp.DateTrunc(unit=seq_get(args, 1), this=seq_get(args, 0)), 105 "BOOLEAN": _parse_as_cast("boolean"), 106 "DOUBLE": _parse_as_cast("double"), 107 "FLOAT": _parse_as_cast("float"), 108 "INT": _parse_as_cast("int"), 109 "STRING": _parse_as_cast("string"), 110 "TIMESTAMP": _parse_as_cast("timestamp"), 111 } 112 113 FUNCTION_PARSERS = { 114 **parser.Parser.FUNCTION_PARSERS, # type: ignore 115 "BROADCAST": lambda self: self._parse_join_hint("BROADCAST"), 116 "BROADCASTJOIN": lambda self: self._parse_join_hint("BROADCASTJOIN"), 117 "MAPJOIN": lambda self: self._parse_join_hint("MAPJOIN"), 118 "MERGE": lambda self: self._parse_join_hint("MERGE"), 119 "SHUFFLEMERGE": lambda self: self._parse_join_hint("SHUFFLEMERGE"), 120 "MERGEJOIN": lambda self: self._parse_join_hint("MERGEJOIN"), 121 "SHUFFLE_HASH": lambda self: self._parse_join_hint("SHUFFLE_HASH"), 122 "SHUFFLE_REPLICATE_NL": lambda self: self._parse_join_hint("SHUFFLE_REPLICATE_NL"), 123 } 124 125 def _parse_add_column(self) -> t.Optional[exp.Expression]: 126 return self._match_text_seq("ADD", "COLUMNS") and self._parse_schema() 127 128 def _parse_drop_column(self) -> t.Optional[exp.Expression]: 129 return self._match_text_seq("DROP", "COLUMNS") and self.expression( 130 exp.Drop, 131 this=self._parse_schema(), 132 kind="COLUMNS", 133 ) 134 135 def _pivot_column_names(self, pivot_columns: t.List[exp.Expression]) -> t.List[str]: 136 # Spark doesn't add a suffix to the pivot columns when there's a single aggregation 137 if len(pivot_columns) == 1: 138 return [""] 139 140 names = [] 141 for agg in pivot_columns: 142 if isinstance(agg, exp.Alias): 143 names.append(agg.alias) 144 else: 145 """ 146 This case corresponds to aggregations without aliases being used as suffixes 147 (e.g. col_avg(foo)). We need to unquote identifiers because they're going to 148 be quoted in the base parser's `_parse_pivot` method, due to `to_identifier`. 149 Otherwise, we'd end up with `col_avg(`foo`)` (notice the double quotes). 150 151 Moreover, function names are lowercased in order to mimic Spark's naming scheme. 152 """ 153 agg_all_unquoted = agg.transform( 154 lambda node: exp.Identifier(this=node.name, quoted=False) 155 if isinstance(node, exp.Identifier) 156 else node 157 ) 158 names.append(agg_all_unquoted.sql(dialect="spark", normalize_functions="lower")) 159 160 return names
Parser consumes a list of tokens produced by the sqlglot.tokens.Tokenizer
and produces
a parsed syntax tree.
Arguments:
- error_level: the desired error level. Default: ErrorLevel.RAISE
- error_message_context: determines the amount of context to capture from a query string when displaying the error message (in number of characters). Default: 50.
- index_offset: Index offset for arrays eg ARRAY[0] vs ARRAY[1] as the head of a list. Default: 0
- alias_post_tablesample: If the table alias comes after tablesample. Default: False
- max_errors: Maximum number of error messages to include in a raised ParseError. This is only relevant if error_level is ErrorLevel.RAISE. Default: 3
- null_ordering: Indicates the default null ordering method to use if not explicitly set. Options are "nulls_are_small", "nulls_are_large", "nulls_are_last". Default: "nulls_are_small"
Inherited Members
162 class Generator(Hive.Generator): 163 TYPE_MAPPING = { 164 **Hive.Generator.TYPE_MAPPING, # type: ignore 165 exp.DataType.Type.TINYINT: "BYTE", 166 exp.DataType.Type.SMALLINT: "SHORT", 167 exp.DataType.Type.BIGINT: "LONG", 168 } 169 170 PROPERTIES_LOCATION = { 171 **Hive.Generator.PROPERTIES_LOCATION, # type: ignore 172 exp.EngineProperty: exp.Properties.Location.UNSUPPORTED, 173 exp.AutoIncrementProperty: exp.Properties.Location.UNSUPPORTED, 174 exp.CharacterSetProperty: exp.Properties.Location.UNSUPPORTED, 175 exp.CollateProperty: exp.Properties.Location.UNSUPPORTED, 176 } 177 178 TRANSFORMS = { 179 **Hive.Generator.TRANSFORMS, # type: ignore 180 exp.ApproxDistinct: rename_func("APPROX_COUNT_DISTINCT"), 181 exp.FileFormatProperty: lambda self, e: f"USING {e.name.upper()}", 182 exp.ArraySum: lambda self, e: f"AGGREGATE({self.sql(e, 'this')}, 0, (acc, x) -> acc + x, acc -> acc)", 183 exp.BitwiseLeftShift: rename_func("SHIFTLEFT"), 184 exp.BitwiseRightShift: rename_func("SHIFTRIGHT"), 185 exp.DateTrunc: lambda self, e: self.func("TRUNC", e.this, e.args.get("unit")), 186 exp.Hint: lambda self, e: f" /*+ {self.expressions(e).strip()} */", 187 exp.StrToDate: _str_to_date, 188 exp.StrToTime: lambda self, e: f"TO_TIMESTAMP({self.sql(e, 'this')}, {self.format_time(e)})", 189 exp.UnixToTime: _unix_to_time_sql, 190 exp.Create: _create_sql, 191 exp.Map: _map_sql, 192 exp.Reduce: rename_func("AGGREGATE"), 193 exp.StructKwarg: lambda self, e: f"{self.sql(e, 'this')}: {self.sql(e, 'expression')}", 194 exp.TimestampTrunc: lambda self, e: self.func( 195 "DATE_TRUNC", exp.Literal.string(e.text("unit")), e.this 196 ), 197 exp.Trim: trim_sql, 198 exp.VariancePop: rename_func("VAR_POP"), 199 exp.DateFromParts: rename_func("MAKE_DATE"), 200 exp.LogicalOr: rename_func("BOOL_OR"), 201 exp.LogicalAnd: rename_func("BOOL_AND"), 202 exp.DayOfWeek: rename_func("DAYOFWEEK"), 203 exp.DayOfMonth: rename_func("DAYOFMONTH"), 204 exp.DayOfYear: rename_func("DAYOFYEAR"), 205 exp.WeekOfYear: rename_func("WEEKOFYEAR"), 206 exp.AtTimeZone: lambda self, e: f"FROM_UTC_TIMESTAMP({self.sql(e, 'this')}, {self.sql(e, 'zone')})", 207 } 208 TRANSFORMS.pop(exp.ArraySort) 209 TRANSFORMS.pop(exp.ILike) 210 211 WRAP_DERIVED_VALUES = False 212 CREATE_FUNCTION_RETURN_AS = False 213 214 def cast_sql(self, expression: exp.Cast) -> str: 215 if isinstance(expression.this, exp.Cast) and expression.this.is_type( 216 exp.DataType.Type.JSON 217 ): 218 schema = f"'{self.sql(expression, 'to')}'" 219 return self.func("FROM_JSON", expression.this.this, schema) 220 if expression.to.is_type(exp.DataType.Type.JSON): 221 return self.func("TO_JSON", expression.this) 222 223 return super(Hive.Generator, self).cast_sql(expression)
Generator interprets the given syntax tree and produces a SQL string as an output.
Arguments:
- time_mapping (dict): the dictionary of custom time mappings in which the key represents a python time format and the output the target time format
- time_trie (trie): a trie of the time_mapping keys
- pretty (bool): if set to True the returned string will be formatted. Default: False.
- quote_start (str): specifies which starting character to use to delimit quotes. Default: '.
- quote_end (str): specifies which ending character to use to delimit quotes. Default: '.
- identifier_start (str): specifies which starting character to use to delimit identifiers. Default: ".
- identifier_end (str): specifies which ending character to use to delimit identifiers. Default: ".
- identify (bool | str): 'always': always quote, 'safe': quote identifiers if they don't contain an upcase, True defaults to always.
- normalize (bool): if set to True all identifiers will lower cased
- string_escape (str): specifies a string escape character. Default: '.
- identifier_escape (str): specifies an identifier escape character. Default: ".
- pad (int): determines padding in a formatted string. Default: 2.
- indent (int): determines the size of indentation in a formatted string. Default: 4.
- unnest_column_only (bool): if true unnest table aliases are considered only as column aliases
- normalize_functions (str): normalize function names, "upper", "lower", or None Default: "upper"
- alias_post_tablesample (bool): if the table alias comes after tablesample Default: False
- unsupported_level (ErrorLevel): determines the generator's behavior when it encounters unsupported expressions. Default ErrorLevel.WARN.
- null_ordering (str): Indicates the default null ordering method to use if not explicitly set. Options are "nulls_are_small", "nulls_are_large", "nulls_are_last". Default: "nulls_are_small"
- max_unsupported (int): Maximum number of unsupported messages to include in a raised UnsupportedError. This is only relevant if unsupported_level is ErrorLevel.RAISE. Default: 3
- leading_comma (bool): if the the comma is leading or trailing in select statements Default: False
- max_text_width: The max number of characters in a segment before creating new lines in pretty mode. The default is on the smaller end because the length only represents a segment and not the true line length. Default: 80
- comments: Whether or not to preserve comments in the output SQL code. Default: True
214 def cast_sql(self, expression: exp.Cast) -> str: 215 if isinstance(expression.this, exp.Cast) and expression.this.is_type( 216 exp.DataType.Type.JSON 217 ): 218 schema = f"'{self.sql(expression, 'to')}'" 219 return self.func("FROM_JSON", expression.this.this, schema) 220 if expression.to.is_type(exp.DataType.Type.JSON): 221 return self.func("TO_JSON", expression.this) 222 223 return super(Hive.Generator, self).cast_sql(expression)
Inherited Members
- sqlglot.generator.Generator
- Generator
- generate
- unsupported
- sep
- seg
- pad_comment
- maybe_comment
- wrap
- no_identify
- normalize_func
- indent
- sql
- uncache_sql
- cache_sql
- characterset_sql
- column_sql
- columnposition_sql
- columndef_sql
- columnconstraint_sql
- autoincrementcolumnconstraint_sql
- compresscolumnconstraint_sql
- generatedasidentitycolumnconstraint_sql
- notnullcolumnconstraint_sql
- primarykeycolumnconstraint_sql
- uniquecolumnconstraint_sql
- create_sql
- describe_sql
- prepend_ctes
- with_sql
- cte_sql
- tablealias_sql
- bitstring_sql
- hexstring_sql
- bytestring_sql
- directory_sql
- delete_sql
- drop_sql
- except_sql
- except_op
- fetch_sql
- filter_sql
- hint_sql
- index_sql
- identifier_sql
- inputoutputformat_sql
- national_sql
- partition_sql
- properties_sql
- root_properties
- properties
- locate_properties
- property_sql
- likeproperty_sql
- fallbackproperty_sql
- journalproperty_sql
- freespaceproperty_sql
- afterjournalproperty_sql
- checksumproperty_sql
- mergeblockratioproperty_sql
- datablocksizeproperty_sql
- blockcompressionproperty_sql
- isolatedloadingproperty_sql
- lockingproperty_sql
- withdataproperty_sql
- insert_sql
- intersect_sql
- intersect_op
- introducer_sql
- pseudotype_sql
- onconflict_sql
- returning_sql
- rowformatdelimitedproperty_sql
- table_sql
- tablesample_sql
- pivot_sql
- tuple_sql
- update_sql
- values_sql
- var_sql
- into_sql
- from_sql
- group_sql
- having_sql
- join_sql
- lambda_sql
- lateral_sql
- limit_sql
- offset_sql
- setitem_sql
- set_sql
- pragma_sql
- lock_sql
- literal_sql
- loaddata_sql
- null_sql
- boolean_sql
- order_sql
- cluster_sql
- distribute_sql
- sort_sql
- ordered_sql
- matchrecognize_sql
- query_modifiers
- select_sql
- schema_sql
- star_sql
- structkwarg_sql
- parameter_sql
- sessionparameter_sql
- placeholder_sql
- subquery_sql
- qualify_sql
- union_sql
- union_op
- unnest_sql
- where_sql
- window_sql
- partition_by_sql
- windowspec_sql
- withingroup_sql
- between_sql
- bracket_sql
- all_sql
- any_sql
- exists_sql
- case_sql
- constraint_sql
- nextvaluefor_sql
- extract_sql
- trim_sql
- concat_sql
- check_sql
- foreignkey_sql
- primarykey_sql
- unique_sql
- if_sql
- matchagainst_sql
- jsonkeyvalue_sql
- jsonobject_sql
- in_sql
- in_unnest_op
- interval_sql
- return_sql
- reference_sql
- anonymous_sql
- paren_sql
- neg_sql
- not_sql
- alias_sql
- aliases_sql
- attimezone_sql
- add_sql
- and_sql
- connector_sql
- bitwiseand_sql
- bitwiseleftshift_sql
- bitwisenot_sql
- bitwiseor_sql
- bitwiserightshift_sql
- bitwisexor_sql
- currentdate_sql
- collate_sql
- command_sql
- comment_sql
- transaction_sql
- commit_sql
- rollback_sql
- altercolumn_sql
- renametable_sql
- altertable_sql
- droppartition_sql
- addconstraint_sql
- distinct_sql
- ignorenulls_sql
- respectnulls_sql
- intdiv_sql
- dpipe_sql
- div_sql
- overlaps_sql
- distance_sql
- dot_sql
- eq_sql
- escape_sql
- glob_sql
- gt_sql
- gte_sql
- ilike_sql
- ilikeany_sql
- is_sql
- like_sql
- likeany_sql
- similarto_sql
- lt_sql
- lte_sql
- mod_sql
- mul_sql
- neq_sql
- nullsafeeq_sql
- nullsafeneq_sql
- or_sql
- slice_sql
- sub_sql
- trycast_sql
- use_sql
- binary
- function_fallback_sql
- func
- format_args
- text_width
- format_time
- expressions
- op_expressions
- naked_property
- set_operation
- tag_sql
- token_sql
- userdefinedfunction_sql
- joinhint_sql
- kwarg_sql
- when_sql
- merge_sql
- tochar_sql