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# sqlglot.dialects.spark2

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      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'", "'")]

class Spark2(sqlglot.dialects.hive.Hive): View Source

     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'", "'")]

##### Inherited Members

sqlglot.dialects.dialect.Dialect
  get_or_raise
  format_time
  parse
  parse_into
  generate
  transpile
  tokenize
  parser
  generator

class Spark2.Parser(sqlglot.dialects.hive.Hive.Parser): View Source

     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

sqlglot.parser.Parser
  Parser
  reset
  parse
  parse_into
  check_errors
  raise_error
  expression
  validate_expression

class Spark2.Generator(sqlglot.dialects.hive.Hive.Generator): View Source

    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

def cast_sql(self, expression: sqlglot.expressions.Cast) -> str: View Source

    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
sqlglot.dialects.hive.Hive.Generator
  arrayagg_sql
  with_properties
  datatype_sql

class Spark2.Tokenizer(sqlglot.dialects.hive.Hive.Tokenizer): View Source

    225    class Tokenizer(Hive.Tokenizer):
    226        HEX_STRINGS = [("X'", "'")]

##### Inherited Members

sqlglot.tokens.Tokenizer
  reset
  tokenize