from __future__ import annotations import typing as t from sqlglot import exp, transforms from sqlglot.dialects.dialect import ( NormalizationStrategy, concat_to_dpipe_sql, concat_ws_to_dpipe_sql, date_delta_sql, generatedasidentitycolumnconstraint_sql, json_extract_segments, no_tablesample_sql, rename_func, map_date_part, ) from sqlglot.dialects.postgres import Postgres from sqlglot.helper import seq_get from sqlglot.tokens import TokenType from sqlglot.parser import build_convert_timezone if t.TYPE_CHECKING: from sqlglot._typing import E def _build_date_delta(expr_type: t.Type[E]) -> t.Callable[[t.List], E]: def _builder(args: t.List) -> E: expr = expr_type( this=seq_get(args, 2), expression=seq_get(args, 1), unit=map_date_part(seq_get(args, 0)), ) if expr_type is exp.TsOrDsAdd: expr.set("return_type", exp.DataType.build("TIMESTAMP")) return expr return _builder class Redshift(Postgres): # https://docs.aws.amazon.com/redshift/latest/dg/r_names.html NORMALIZATION_STRATEGY = NormalizationStrategy.CASE_INSENSITIVE SUPPORTS_USER_DEFINED_TYPES = False INDEX_OFFSET = 0 COPY_PARAMS_ARE_CSV = False HEX_LOWERCASE = True HAS_DISTINCT_ARRAY_CONSTRUCTORS = True # ref: https://docs.aws.amazon.com/redshift/latest/dg/r_FORMAT_strings.html TIME_FORMAT = "'YYYY-MM-DD HH24:MI:SS'" TIME_MAPPING = {**Postgres.TIME_MAPPING, "MON": "%b", "HH24": "%H", "HH": "%I"} class Parser(Postgres.Parser): FUNCTIONS = { **Postgres.Parser.FUNCTIONS, "ADD_MONTHS": lambda args: exp.TsOrDsAdd( this=seq_get(args, 0), expression=seq_get(args, 1), unit=exp.var("month"), return_type=exp.DataType.build("TIMESTAMP"), ), "CONVERT_TIMEZONE": lambda args: build_convert_timezone(args, "UTC"), "DATEADD": _build_date_delta(exp.TsOrDsAdd), "DATE_ADD": _build_date_delta(exp.TsOrDsAdd), "DATEDIFF": _build_date_delta(exp.TsOrDsDiff), "DATE_DIFF": _build_date_delta(exp.TsOrDsDiff), "GETDATE": exp.CurrentTimestamp.from_arg_list, "LISTAGG": exp.GroupConcat.from_arg_list, "SPLIT_TO_ARRAY": lambda args: exp.StringToArray( this=seq_get(args, 0), expression=seq_get(args, 1) or exp.Literal.string(",") ), "STRTOL": exp.FromBase.from_arg_list, } NO_PAREN_FUNCTION_PARSERS = { **Postgres.Parser.NO_PAREN_FUNCTION_PARSERS, "APPROXIMATE": lambda self: self._parse_approximate_count(), "SYSDATE": lambda self: self.expression(exp.CurrentTimestamp, sysdate=True), } SUPPORTS_IMPLICIT_UNNEST = True def _parse_table( self, schema: bool = False, joins: bool = False, alias_tokens: t.Optional[t.Collection[TokenType]] = None, parse_bracket: bool = False, is_db_reference: bool = False, parse_partition: bool = False, ) -> t.Optional[exp.Expression]: # Redshift supports UNPIVOTing SUPER objects, e.g. `UNPIVOT foo.obj[0] AS val AT attr` unpivot = self._match(TokenType.UNPIVOT) table = super()._parse_table( schema=schema, joins=joins, alias_tokens=alias_tokens, parse_bracket=parse_bracket, is_db_reference=is_db_reference, ) return self.expression(exp.Pivot, this=table, unpivot=True) if unpivot else table def _parse_convert( self, strict: bool, safe: t.Optional[bool] = None ) -> t.Optional[exp.Expression]: to = self._parse_types() self._match(TokenType.COMMA) this = self._parse_bitwise() return self.expression(exp.TryCast, this=this, to=to, safe=safe) def _parse_approximate_count(self) -> t.Optional[exp.ApproxDistinct]: index = self._index - 1 func = self._parse_function() if isinstance(func, exp.Count) and isinstance(func.this, exp.Distinct): return self.expression(exp.ApproxDistinct, this=seq_get(func.this.expressions, 0)) self._retreat(index) return None class Tokenizer(Postgres.Tokenizer): BIT_STRINGS = [] HEX_STRINGS = [] STRING_ESCAPES = ["\\", "'"] KEYWORDS = { **Postgres.Tokenizer.KEYWORDS, "(+)": TokenType.JOIN_MARKER, "HLLSKETCH": TokenType.HLLSKETCH, "MINUS": TokenType.EXCEPT, "SUPER": TokenType.SUPER, "TOP": TokenType.TOP, "UNLOAD": TokenType.COMMAND, "VARBYTE": TokenType.VARBINARY, "BINARY VARYING": TokenType.VARBINARY, } KEYWORDS.pop("VALUES") # Redshift allows # to appear as a table identifier prefix SINGLE_TOKENS = Postgres.Tokenizer.SINGLE_TOKENS.copy() SINGLE_TOKENS.pop("#") class Generator(Postgres.Generator): LOCKING_READS_SUPPORTED = False QUERY_HINTS = False VALUES_AS_TABLE = False TZ_TO_WITH_TIME_ZONE = True NVL2_SUPPORTED = True LAST_DAY_SUPPORTS_DATE_PART = False CAN_IMPLEMENT_ARRAY_ANY = False MULTI_ARG_DISTINCT = True COPY_PARAMS_ARE_WRAPPED = False HEX_FUNC = "TO_HEX" PARSE_JSON_NAME = "JSON_PARSE" ARRAY_CONCAT_IS_VAR_LEN = False SUPPORTS_CONVERT_TIMEZONE = True EXCEPT_INTERSECT_SUPPORT_ALL_CLAUSE = False SUPPORTS_MEDIAN = True # Redshift doesn't have `WITH` as part of their with_properties so we remove it WITH_PROPERTIES_PREFIX = " " TYPE_MAPPING = { **Postgres.Generator.TYPE_MAPPING, exp.DataType.Type.BINARY: "VARBYTE", exp.DataType.Type.INT: "INTEGER", exp.DataType.Type.TIMETZ: "TIME", exp.DataType.Type.TIMESTAMPTZ: "TIMESTAMP", exp.DataType.Type.VARBINARY: "VARBYTE", exp.DataType.Type.ROWVERSION: "VARBYTE", } TRANSFORMS = { **Postgres.Generator.TRANSFORMS, exp.ArrayConcat: lambda self, e: self.arrayconcat_sql(e, name="ARRAY_CONCAT"), exp.Concat: concat_to_dpipe_sql, exp.ConcatWs: concat_ws_to_dpipe_sql, exp.ApproxDistinct: lambda self, e: f"APPROXIMATE COUNT(DISTINCT {self.sql(e, 'this')})", exp.CurrentTimestamp: lambda self, e: ( "SYSDATE" if e.args.get("sysdate") else "GETDATE()" ), exp.DateAdd: date_delta_sql("DATEADD"), exp.DateDiff: date_delta_sql("DATEDIFF"), exp.DistKeyProperty: lambda self, e: self.func("DISTKEY", e.this), exp.DistStyleProperty: lambda self, e: self.naked_property(e), exp.Explode: lambda self, e: self.explode_sql(e), exp.FromBase: rename_func("STRTOL"), exp.GeneratedAsIdentityColumnConstraint: generatedasidentitycolumnconstraint_sql, exp.JSONExtract: json_extract_segments("JSON_EXTRACT_PATH_TEXT"), exp.JSONExtractScalar: json_extract_segments("JSON_EXTRACT_PATH_TEXT"), exp.GroupConcat: rename_func("LISTAGG"), exp.Hex: lambda self, e: self.func("UPPER", self.func("TO_HEX", self.sql(e, "this"))), exp.Select: transforms.preprocess( [ transforms.eliminate_distinct_on, transforms.eliminate_semi_and_anti_joins, transforms.unqualify_unnest, transforms.unnest_generate_date_array_using_recursive_cte, ] ), exp.SortKeyProperty: lambda self, e: f"{'COMPOUND ' if e.args['compound'] else ''}SORTKEY({self.format_args(*e.this)})", exp.StartsWith: lambda self, e: f"{self.sql(e.this)} LIKE {self.sql(e.expression)} || '%'", exp.StringToArray: rename_func("SPLIT_TO_ARRAY"), exp.TableSample: no_tablesample_sql, exp.TsOrDsAdd: date_delta_sql("DATEADD"), exp.TsOrDsDiff: date_delta_sql("DATEDIFF"), exp.UnixToTime: lambda self, e: f"(TIMESTAMP 'epoch' + {self.sql(e.this)} * INTERVAL '1 SECOND')", } # Postgres maps exp.Pivot to no_pivot_sql, but Redshift support pivots TRANSFORMS.pop(exp.Pivot) # Postgres doesn't support JSON_PARSE, but Redshift does TRANSFORMS.pop(exp.ParseJSON) # Redshift uses the POW | POWER (expr1, expr2) syntax instead of expr1 ^ expr2 (postgres) TRANSFORMS.pop(exp.Pow) # Redshift supports these functions TRANSFORMS.pop(exp.AnyValue) TRANSFORMS.pop(exp.LastDay) TRANSFORMS.pop(exp.SHA2) RESERVED_KEYWORDS = { "aes128", "aes256", "all", "allowoverwrite", "analyse", "analyze", "and", "any", "array", "as", "asc", "authorization", "az64", "backup", "between", "binary", "blanksasnull", "both", "bytedict", "bzip2", "case", "cast", "check", "collate", "column", "constraint", "create", "credentials", "cross", "current_date", "current_time", "current_timestamp", "current_user", "current_user_id", "default", "deferrable", "deflate", "defrag", "delta", "delta32k", "desc", "disable", "distinct", "do", "else", "emptyasnull", "enable", "encode", "encrypt ", "encryption", "end", "except", "explicit", "false", "for", "foreign", "freeze", "from", "full", "globaldict256", "globaldict64k", "grant", "group", "gzip", "having", "identity", "ignore", "ilike", "in", "initially", "inner", "intersect", "interval", "into", "is", "isnull", "join", "leading", "left", "like", "limit", "localtime", "localtimestamp", "lun", "luns", "lzo", "lzop", "minus", "mostly16", "mostly32", "mostly8", "natural", "new", "not", "notnull", "null", "nulls", "off", "offline", "offset", "oid", "old", "on", "only", "open", "or", "order", "outer", "overlaps", "parallel", "partition", "percent", "permissions", "pivot", "placing", "primary", "raw", "readratio", "recover", "references", "rejectlog", "resort", "respect", "restore", "right", "select", "session_user", "similar", "snapshot", "some", "sysdate", "system", "table", "tag", "tdes", "text255", "text32k", "then", "timestamp", "to", "top", "trailing", "true", "truncatecolumns", "type", "union", "unique", "unnest", "unpivot", "user", "using", "verbose", "wallet", "when", "where", "with", "without", } def unnest_sql(self, expression: exp.Unnest) -> str: args = expression.expressions num_args = len(args) if num_args != 1: self.unsupported(f"Unsupported number of arguments in UNNEST: {num_args}") return "" if isinstance(expression.find_ancestor(exp.From, exp.Join, exp.Select), exp.Select): self.unsupported("Unsupported UNNEST when not used in FROM/JOIN clauses") return "" arg = self.sql(seq_get(args, 0)) alias = self.expressions(expression.args.get("alias"), key="columns", flat=True) return f"{arg} AS {alias}" if alias else arg def cast_sql(self, expression: exp.Cast, safe_prefix: t.Optional[str] = None) -> str: if expression.is_type(exp.DataType.Type.JSON): # Redshift doesn't support a JSON type, so casting to it is treated as a noop return self.sql(expression, "this") return super().cast_sql(expression, safe_prefix=safe_prefix) def datatype_sql(self, expression: exp.DataType) -> str: """ Redshift converts the `TEXT` data type to `VARCHAR(255)` by default when people more generally mean VARCHAR of max length which is `VARCHAR(max)` in Redshift. Therefore if we get a `TEXT` data type without precision we convert it to `VARCHAR(max)` and if it does have precision then we just convert `TEXT` to `VARCHAR`. """ if expression.is_type("text"): expression.set("this", exp.DataType.Type.VARCHAR) precision = expression.args.get("expressions") if not precision: expression.append("expressions", exp.var("MAX")) return super().datatype_sql(expression) def alterset_sql(self, expression: exp.AlterSet) -> str: exprs = self.expressions(expression, flat=True) exprs = f" TABLE PROPERTIES ({exprs})" if exprs else "" location = self.sql(expression, "location") location = f" LOCATION {location}" if location else "" file_format = self.expressions(expression, key="file_format", flat=True, sep=" ") file_format = f" FILE FORMAT {file_format}" if file_format else "" return f"SET{exprs}{location}{file_format}" def array_sql(self, expression: exp.Array) -> str: if expression.args.get("bracket_notation"): return super().array_sql(expression) return rename_func("ARRAY")(self, expression) def explode_sql(self, expression: exp.Explode) -> str: self.unsupported("Unsupported EXPLODE() function") return ""