# sqlglot.optimizer.qualify_columns API documentation

Edit on GitHub

# sqlglot.optimizer.qualify_columns

View Source

       1from __future__ import annotations
       2
       3import itertools
       4import typing as t
       5
       6from sqlglot import alias, exp
       7from sqlglot.dialects.dialect import Dialect, DialectType
       8from sqlglot.errors import OptimizeError
       9from sqlglot.helper import seq_get, SingleValuedMapping
      10from sqlglot.optimizer.annotate_types import TypeAnnotator
      11from sqlglot.optimizer.scope import Scope, build_scope, traverse_scope, walk_in_scope
      12from sqlglot.optimizer.simplify import simplify_parens
      13from sqlglot.schema import Schema, ensure_schema
      14
      15if t.TYPE_CHECKING:
      16    from sqlglot._typing import E
      17
      18
      19def qualify_columns(
      20    expression: exp.Expression,
      21    schema: t.Dict | Schema,
      22    expand_alias_refs: bool = True,
      23    expand_stars: bool = True,
      24    infer_schema: t.Optional[bool] = None,
      25    allow_partial_qualification: bool = False,
      26    dialect: DialectType = None,
      27) -> exp.Expression:
      28    """
      29    Rewrite sqlglot AST to have fully qualified columns.
      30
      31    Example:
      32        >>> import sqlglot
      33        >>> schema = {"tbl": {"col": "INT"}}
      34        >>> expression = sqlglot.parse_one("SELECT col FROM tbl")
      35        >>> qualify_columns(expression, schema).sql()
      36        'SELECT tbl.col AS col FROM tbl'
      37
      38    Args:
      39        expression: Expression to qualify.
      40        schema: Database schema.
      41        expand_alias_refs: Whether to expand references to aliases.
      42        expand_stars: Whether to expand star queries. This is a necessary step
      43            for most of the optimizer's rules to work; do not set to False unless you
      44            know what you're doing!
      45        infer_schema: Whether to infer the schema if missing.
      46        allow_partial_qualification: Whether to allow partial qualification.
      47
      48    Returns:
      49        The qualified expression.
      50
      51    Notes:
      52        - Currently only handles a single PIVOT or UNPIVOT operator
      53    """
      54    schema = ensure_schema(schema, dialect=dialect)
      55    annotator = TypeAnnotator(schema)
      56    infer_schema = schema.empty if infer_schema is None else infer_schema
      57    dialect = Dialect.get_or_raise(schema.dialect)
      58    pseudocolumns = dialect.PSEUDOCOLUMNS
      59    bigquery = dialect == "bigquery"
      60
      61    for scope in traverse_scope(expression):
      62        scope_expression = scope.expression
      63        is_select = isinstance(scope_expression, exp.Select)
      64
      65        if is_select and scope_expression.args.get("connect"):
      66            # In Snowflake / Oracle queries that have a CONNECT BY clause, one can use the LEVEL
      67            # pseudocolumn, which doesn't belong to a table, so we change it into an identifier
      68            scope_expression.transform(
      69                lambda n: n.this if isinstance(n, exp.Column) and n.name == "LEVEL" else n,
      70                copy=False,
      71            )
      72            scope.clear_cache()
      73
      74        resolver = Resolver(scope, schema, infer_schema=infer_schema)
      75        _pop_table_column_aliases(scope.ctes)
      76        _pop_table_column_aliases(scope.derived_tables)
      77        using_column_tables = _expand_using(scope, resolver)
      78
      79        if (schema.empty or dialect.FORCE_EARLY_ALIAS_REF_EXPANSION) and expand_alias_refs:
      80            _expand_alias_refs(
      81                scope,
      82                resolver,
      83                dialect,
      84                expand_only_groupby=bigquery,
      85            )
      86
      87        _convert_columns_to_dots(scope, resolver)
      88        _qualify_columns(scope, resolver, allow_partial_qualification=allow_partial_qualification)
      89
      90        if not schema.empty and expand_alias_refs:
      91            _expand_alias_refs(scope, resolver, dialect)
      92
      93        if is_select:
      94            if expand_stars:
      95                _expand_stars(
      96                    scope,
      97                    resolver,
      98                    using_column_tables,
      99                    pseudocolumns,
     100                    annotator,
     101                )
     102            qualify_outputs(scope)
     103
     104        _expand_group_by(scope, dialect)
     105
     106        # DISTINCT ON and ORDER BY follow the same rules (tested in DuckDB, Postgres, ClickHouse)
     107        # https://www.postgresql.org/docs/current/sql-select.html#SQL-DISTINCT
     108        _expand_order_by_and_distinct_on(scope, resolver)
     109
     110        if bigquery:
     111            annotator.annotate_scope(scope)
     112
     113    return expression
     114
     115
     116def validate_qualify_columns(expression: E) -> E:
     117    """Raise an `OptimizeError` if any columns aren't qualified"""
     118    all_unqualified_columns = []
     119    for scope in traverse_scope(expression):
     120        if isinstance(scope.expression, exp.Select):
     121            unqualified_columns = scope.unqualified_columns
     122
     123            if scope.external_columns and not scope.is_correlated_subquery and not scope.pivots:
     124                column = scope.external_columns[0]
     125                for_table = f" for table: '{column.table}'" if column.table else ""
     126                raise OptimizeError(f"Column '{column}' could not be resolved{for_table}")
     127
     128            if unqualified_columns and scope.pivots and scope.pivots[0].unpivot:
     129                # New columns produced by the UNPIVOT can't be qualified, but there may be columns
     130                # under the UNPIVOT's IN clause that can and should be qualified. We recompute
     131                # this list here to ensure those in the former category will be excluded.
     132                unpivot_columns = set(_unpivot_columns(scope.pivots[0]))
     133                unqualified_columns = [c for c in unqualified_columns if c not in unpivot_columns]
     134
     135            all_unqualified_columns.extend(unqualified_columns)
     136
     137    if all_unqualified_columns:
     138        raise OptimizeError(f"Ambiguous columns: {all_unqualified_columns}")
     139
     140    return expression
     141
     142
     143def _unpivot_columns(unpivot: exp.Pivot) -> t.Iterator[exp.Column]:
     144    name_columns = [
     145        field.this
     146        for field in unpivot.fields
     147        if isinstance(field, exp.In) and isinstance(field.this, exp.Column)
     148    ]
     149    value_columns = (c for e in unpivot.expressions for c in e.find_all(exp.Column))
     150
     151    return itertools.chain(name_columns, value_columns)
     152
     153
     154def _pop_table_column_aliases(derived_tables: t.List[exp.CTE | exp.Subquery]) -> None:
     155    """
     156    Remove table column aliases.
     157
     158    For example, `col1` and `col2` will be dropped in SELECT ... FROM (SELECT ...) AS foo(col1, col2)
     159    """
     160    for derived_table in derived_tables:
     161        if isinstance(derived_table.parent, exp.With) and derived_table.parent.recursive:
     162            continue
     163        table_alias = derived_table.args.get("alias")
     164        if table_alias:
     165            table_alias.args.pop("columns", None)
     166
     167
     168def _expand_using(scope: Scope, resolver: Resolver) -> t.Dict[str, t.Any]:
     169    columns = {}
     170
     171    def _update_source_columns(source_name: str) -> None:
     172        for column_name in resolver.get_source_columns(source_name):
     173            if column_name not in columns:
     174                columns[column_name] = source_name
     175
     176    joins = list(scope.find_all(exp.Join))
     177    names = {join.alias_or_name for join in joins}
     178    ordered = [key for key in scope.selected_sources if key not in names]
     179
     180    if names and not ordered:
     181        raise OptimizeError(f"Joins {names} missing source table {scope.expression}")
     182
     183    # Mapping of automatically joined column names to an ordered set of source names (dict).
     184    column_tables: t.Dict[str, t.Dict[str, t.Any]] = {}
     185
     186    for source_name in ordered:
     187        _update_source_columns(source_name)
     188
     189    for i, join in enumerate(joins):
     190        source_table = ordered[-1]
     191        if source_table:
     192            _update_source_columns(source_table)
     193
     194        join_table = join.alias_or_name
     195        ordered.append(join_table)
     196
     197        using = join.args.get("using")
     198        if not using:
     199            continue
     200
     201        join_columns = resolver.get_source_columns(join_table)
     202        conditions = []
     203        using_identifier_count = len(using)
     204        is_semi_or_anti_join = join.is_semi_or_anti_join
     205
     206        for identifier in using:
     207            identifier = identifier.name
     208            table = columns.get(identifier)
     209
     210            if not table or identifier not in join_columns:
     211                if (columns and "*" not in columns) and join_columns:
     212                    raise OptimizeError(f"Cannot automatically join: {identifier}")
     213
     214            table = table or source_table
     215
     216            if i == 0 or using_identifier_count == 1:
     217                lhs: exp.Expression = exp.column(identifier, table=table)
     218            else:
     219                coalesce_columns = [
     220                    exp.column(identifier, table=t)
     221                    for t in ordered[:-1]
     222                    if identifier in resolver.get_source_columns(t)
     223                ]
     224                if len(coalesce_columns) > 1:
     225                    lhs = exp.func("coalesce", *coalesce_columns)
     226                else:
     227                    lhs = exp.column(identifier, table=table)
     228
     229            conditions.append(lhs.eq(exp.column(identifier, table=join_table)))
     230
     231            # Set all values in the dict to None, because we only care about the key ordering
     232            tables = column_tables.setdefault(identifier, {})
     233
     234            # Do not update the dict if this was a SEMI/ANTI join in
     235            # order to avoid generating COALESCE columns for this join pair
     236            if not is_semi_or_anti_join:
     237                if table not in tables:
     238                    tables[table] = None
     239                if join_table not in tables:
     240                    tables[join_table] = None
     241
     242        join.args.pop("using")
     243        join.set("on", exp.and_(*conditions, copy=False))
     244
     245    if column_tables:
     246        for column in scope.columns:
     247            if not column.table and column.name in column_tables:
     248                tables = column_tables[column.name]
     249                coalesce_args = [exp.column(column.name, table=table) for table in tables]
     250                replacement: exp.Expression = exp.func("coalesce", *coalesce_args)
     251
     252                if isinstance(column.parent, exp.Select):
     253                    # Ensure the USING column keeps its name if it's projected
     254                    replacement = alias(replacement, alias=column.name, copy=False)
     255                elif isinstance(column.parent, exp.Struct):
     256                    # Ensure the USING column keeps its name if it's an anonymous STRUCT field
     257                    replacement = exp.PropertyEQ(
     258                        this=exp.to_identifier(column.name), expression=replacement
     259                    )
     260
     261                scope.replace(column, replacement)
     262
     263    return column_tables
     264
     265
     266def _expand_alias_refs(
     267    scope: Scope, resolver: Resolver, dialect: Dialect, expand_only_groupby: bool = False
     268) -> None:
     269    """
     270    Expand references to aliases.
     271    Example:
     272        SELECT y.foo AS bar, bar * 2 AS baz FROM y
     273     => SELECT y.foo AS bar, y.foo * 2 AS baz FROM y
     274    """
     275    expression = scope.expression
     276
     277    if not isinstance(expression, exp.Select) or dialect == "oracle":
     278        return
     279
     280    alias_to_expression: t.Dict[str, t.Tuple[exp.Expression, int]] = {}
     281    projections = {s.alias_or_name for s in expression.selects}
     282
     283    def replace_columns(
     284        node: t.Optional[exp.Expression], resolve_table: bool = False, literal_index: bool = False
     285    ) -> None:
     286        is_group_by = isinstance(node, exp.Group)
     287        is_having = isinstance(node, exp.Having)
     288        if not node or (expand_only_groupby and not is_group_by):
     289            return
     290
     291        for column in walk_in_scope(node, prune=lambda node: node.is_star):
     292            if not isinstance(column, exp.Column):
     293                continue
     294
     295            # BigQuery's GROUP BY allows alias expansion only for standalone names, e.g:
     296            #   SELECT FUNC(col) AS col FROM t GROUP BY col --> Can be expanded
     297            #   SELECT FUNC(col) AS col FROM t GROUP BY FUNC(col)  --> Shouldn't be expanded, will result to FUNC(FUNC(col))
     298            # This not required for the HAVING clause as it can evaluate expressions using both the alias & the table columns
     299            if expand_only_groupby and is_group_by and column.parent is not node:
     300                continue
     301
     302            skip_replace = False
     303            table = resolver.get_table(column.name) if resolve_table and not column.table else None
     304            alias_expr, i = alias_to_expression.get(column.name, (None, 1))
     305
     306            if alias_expr:
     307                skip_replace = bool(
     308                    alias_expr.find(exp.AggFunc)
     309                    and column.find_ancestor(exp.AggFunc)
     310                    and not isinstance(column.find_ancestor(exp.Window, exp.Select), exp.Window)
     311                )
     312
     313                # BigQuery's having clause gets confused if an alias matches a source.
     314                # SELECT x.a, max(x.b) as x FROM x GROUP BY 1 HAVING x > 1;
     315                # If HAVING x is expanded to max(x.b), bigquery treats x as the new projection x instead of the table
     316                if is_having and dialect == "bigquery":
     317                    skip_replace = skip_replace or any(
     318                        node.parts[0].name in projections
     319                        for node in alias_expr.find_all(exp.Column)
     320                    )
     321
     322            if table and (not alias_expr or skip_replace):
     323                column.set("table", table)
     324            elif not column.table and alias_expr and not skip_replace:
     325                if isinstance(alias_expr, exp.Literal) and (literal_index or resolve_table):
     326                    if literal_index:
     327                        column.replace(exp.Literal.number(i))
     328                else:
     329                    column = column.replace(exp.paren(alias_expr))
     330                    simplified = simplify_parens(column)
     331                    if simplified is not column:
     332                        column.replace(simplified)
     333
     334    for i, projection in enumerate(expression.selects):
     335        replace_columns(projection)
     336        if isinstance(projection, exp.Alias):
     337            alias_to_expression[projection.alias] = (projection.this, i + 1)
     338
     339    parent_scope = scope
     340    while parent_scope.is_union:
     341        parent_scope = parent_scope.parent
     342
     343    # We shouldn't expand aliases if they match the recursive CTE's columns
     344    if parent_scope.is_cte:
     345        cte = parent_scope.expression.parent
     346        if cte.find_ancestor(exp.With).recursive:
     347            for recursive_cte_column in cte.args["alias"].columns or cte.this.selects:
     348                alias_to_expression.pop(recursive_cte_column.output_name, None)
     349
     350    replace_columns(expression.args.get("where"))
     351    replace_columns(expression.args.get("group"), literal_index=True)
     352    replace_columns(expression.args.get("having"), resolve_table=True)
     353    replace_columns(expression.args.get("qualify"), resolve_table=True)
     354
     355    # Snowflake allows alias expansion in the JOIN ... ON clause (and almost everywhere else)
     356    # https://docs.snowflake.com/en/sql-reference/sql/select#usage-notes
     357    if dialect == "snowflake":
     358        for join in expression.args.get("joins") or []:
     359            replace_columns(join)
     360
     361    scope.clear_cache()
     362
     363
     364def _expand_group_by(scope: Scope, dialect: DialectType) -> None:
     365    expression = scope.expression
     366    group = expression.args.get("group")
     367    if not group:
     368        return
     369
     370    group.set("expressions", _expand_positional_references(scope, group.expressions, dialect))
     371    expression.set("group", group)
     372
     373
     374def _expand_order_by_and_distinct_on(scope: Scope, resolver: Resolver) -> None:
     375    for modifier_key in ("order", "distinct"):
     376        modifier = scope.expression.args.get(modifier_key)
     377        if isinstance(modifier, exp.Distinct):
     378            modifier = modifier.args.get("on")
     379
     380        if not isinstance(modifier, exp.Expression):
     381            continue
     382
     383        modifier_expressions = modifier.expressions
     384        if modifier_key == "order":
     385            modifier_expressions = [ordered.this for ordered in modifier_expressions]
     386
     387        for original, expanded in zip(
     388            modifier_expressions,
     389            _expand_positional_references(
     390                scope, modifier_expressions, resolver.schema.dialect, alias=True
     391            ),
     392        ):
     393            for agg in original.find_all(exp.AggFunc):
     394                for col in agg.find_all(exp.Column):
     395                    if not col.table:
     396                        col.set("table", resolver.get_table(col.name))
     397
     398            original.replace(expanded)
     399
     400        if scope.expression.args.get("group"):
     401            selects = {s.this: exp.column(s.alias_or_name) for s in scope.expression.selects}
     402
     403            for expression in modifier_expressions:
     404                expression.replace(
     405                    exp.to_identifier(_select_by_pos(scope, expression).alias)
     406                    if expression.is_int
     407                    else selects.get(expression, expression)
     408                )
     409
     410
     411def _expand_positional_references(
     412    scope: Scope, expressions: t.Iterable[exp.Expression], dialect: DialectType, alias: bool = False
     413) -> t.List[exp.Expression]:
     414    new_nodes: t.List[exp.Expression] = []
     415    ambiguous_projections = None
     416
     417    for node in expressions:
     418        if node.is_int:
     419            select = _select_by_pos(scope, t.cast(exp.Literal, node))
     420
     421            if alias:
     422                new_nodes.append(exp.column(select.args["alias"].copy()))
     423            else:
     424                select = select.this
     425
     426                if dialect == "bigquery":
     427                    if ambiguous_projections is None:
     428                        # When a projection name is also a source name and it is referenced in the
     429                        # GROUP BY clause, BQ can't understand what the identifier corresponds to
     430                        ambiguous_projections = {
     431                            s.alias_or_name
     432                            for s in scope.expression.selects
     433                            if s.alias_or_name in scope.selected_sources
     434                        }
     435
     436                    ambiguous = any(
     437                        column.parts[0].name in ambiguous_projections
     438                        for column in select.find_all(exp.Column)
     439                    )
     440                else:
     441                    ambiguous = False
     442
     443                if (
     444                    isinstance(select, exp.CONSTANTS)
     445                    or select.find(exp.Explode, exp.Unnest)
     446                    or ambiguous
     447                ):
     448                    new_nodes.append(node)
     449                else:
     450                    new_nodes.append(select.copy())
     451        else:
     452            new_nodes.append(node)
     453
     454    return new_nodes
     455
     456
     457def _select_by_pos(scope: Scope, node: exp.Literal) -> exp.Alias:
     458    try:
     459        return scope.expression.selects[int(node.this) - 1].assert_is(exp.Alias)
     460    except IndexError:
     461        raise OptimizeError(f"Unknown output column: {node.name}")
     462
     463
     464def _convert_columns_to_dots(scope: Scope, resolver: Resolver) -> None:
     465    """
     466    Converts `Column` instances that represent struct field lookup into chained `Dots`.
     467
     468    Struct field lookups look like columns (e.g. "struct"."field"), but they need to be
     469    qualified separately and represented as Dot(Dot(...(<table>.<column>, field1), field2, ...)).
     470    """
     471    converted = False
     472    for column in itertools.chain(scope.columns, scope.stars):
     473        if isinstance(column, exp.Dot):
     474            continue
     475
     476        column_table: t.Optional[str | exp.Identifier] = column.table
     477        if (
     478            column_table
     479            and column_table not in scope.sources
     480            and (
     481                not scope.parent
     482                or column_table not in scope.parent.sources
     483                or not scope.is_correlated_subquery
     484            )
     485        ):
     486            root, *parts = column.parts
     487
     488            if root.name in scope.sources:
     489                # The struct is already qualified, but we still need to change the AST
     490                column_table = root
     491                root, *parts = parts
     492            else:
     493                column_table = resolver.get_table(root.name)
     494
     495            if column_table:
     496                converted = True
     497                column.replace(exp.Dot.build([exp.column(root, table=column_table), *parts]))
     498
     499    if converted:
     500        # We want to re-aggregate the converted columns, otherwise they'd be skipped in
     501        # a `for column in scope.columns` iteration, even though they shouldn't be
     502        scope.clear_cache()
     503
     504
     505def _qualify_columns(scope: Scope, resolver: Resolver, allow_partial_qualification: bool) -> None:
     506    """Disambiguate columns, ensuring each column specifies a source"""
     507    for column in scope.columns:
     508        column_table = column.table
     509        column_name = column.name
     510
     511        if column_table and column_table in scope.sources:
     512            source_columns = resolver.get_source_columns(column_table)
     513            if (
     514                not allow_partial_qualification
     515                and source_columns
     516                and column_name not in source_columns
     517                and "*" not in source_columns
     518            ):
     519                raise OptimizeError(f"Unknown column: {column_name}")
     520
     521        if not column_table:
     522            if scope.pivots and not column.find_ancestor(exp.Pivot):
     523                # If the column is under the Pivot expression, we need to qualify it
     524                # using the name of the pivoted source instead of the pivot's alias
     525                column.set("table", exp.to_identifier(scope.pivots[0].alias))
     526                continue
     527
     528            # column_table can be a '' because bigquery unnest has no table alias
     529            column_table = resolver.get_table(column_name)
     530            if column_table:
     531                column.set("table", column_table)
     532
     533    for pivot in scope.pivots:
     534        for column in pivot.find_all(exp.Column):
     535            if not column.table and column.name in resolver.all_columns:
     536                column_table = resolver.get_table(column.name)
     537                if column_table:
     538                    column.set("table", column_table)
     539
     540
     541def _expand_struct_stars(
     542    expression: exp.Dot,
     543) -> t.List[exp.Alias]:
     544    """[BigQuery] Expand/Flatten foo.bar.* where bar is a struct column"""
     545
     546    dot_column = t.cast(exp.Column, expression.find(exp.Column))
     547    if not dot_column.is_type(exp.DataType.Type.STRUCT):
     548        return []
     549
     550    # All nested struct values are ColumnDefs, so normalize the first exp.Column in one
     551    dot_column = dot_column.copy()
     552    starting_struct = exp.ColumnDef(this=dot_column.this, kind=dot_column.type)
     553
     554    # First part is the table name and last part is the star so they can be dropped
     555    dot_parts = expression.parts[1:-1]
     556
     557    # If we're expanding a nested struct eg. t.c.f1.f2.* find the last struct (f2 in this case)
     558    for part in dot_parts[1:]:
     559        for field in t.cast(exp.DataType, starting_struct.kind).expressions:
     560            # Unable to expand star unless all fields are named
     561            if not isinstance(field.this, exp.Identifier):
     562                return []
     563
     564            if field.name == part.name and field.kind.is_type(exp.DataType.Type.STRUCT):
     565                starting_struct = field
     566                break
     567        else:
     568            # There is no matching field in the struct
     569            return []
     570
     571    taken_names = set()
     572    new_selections = []
     573
     574    for field in t.cast(exp.DataType, starting_struct.kind).expressions:
     575        name = field.name
     576
     577        # Ambiguous or anonymous fields can't be expanded
     578        if name in taken_names or not isinstance(field.this, exp.Identifier):
     579            return []
     580
     581        taken_names.add(name)
     582
     583        this = field.this.copy()
     584        root, *parts = [part.copy() for part in itertools.chain(dot_parts, [this])]
     585        new_column = exp.column(
     586            t.cast(exp.Identifier, root),
     587            table=dot_column.args.get("table"),
     588            fields=t.cast(t.List[exp.Identifier], parts),
     589        )
     590        new_selections.append(alias(new_column, this, copy=False))
     591
     592    return new_selections
     593
     594
     595def _expand_stars(
     596    scope: Scope,
     597    resolver: Resolver,
     598    using_column_tables: t.Dict[str, t.Any],
     599    pseudocolumns: t.Set[str],
     600    annotator: TypeAnnotator,
     601) -> None:
     602    """Expand stars to lists of column selections"""
     603
     604    new_selections: t.List[exp.Expression] = []
     605    except_columns: t.Dict[int, t.Set[str]] = {}
     606    replace_columns: t.Dict[int, t.Dict[str, exp.Alias]] = {}
     607    rename_columns: t.Dict[int, t.Dict[str, str]] = {}
     608
     609    coalesced_columns = set()
     610    dialect = resolver.schema.dialect
     611
     612    pivot_output_columns = None
     613    pivot_exclude_columns: t.Set[str] = set()
     614
     615    pivot = t.cast(t.Optional[exp.Pivot], seq_get(scope.pivots, 0))
     616    if isinstance(pivot, exp.Pivot) and not pivot.alias_column_names:
     617        if pivot.unpivot:
     618            pivot_output_columns = [c.output_name for c in _unpivot_columns(pivot)]
     619
     620            for field in pivot.fields:
     621                if isinstance(field, exp.In):
     622                    pivot_exclude_columns.update(
     623                        c.output_name for e in field.expressions for c in e.find_all(exp.Column)
     624                    )
     625
     626        else:
     627            pivot_exclude_columns = set(c.output_name for c in pivot.find_all(exp.Column))
     628
     629            pivot_output_columns = [c.output_name for c in pivot.args.get("columns", [])]
     630            if not pivot_output_columns:
     631                pivot_output_columns = [c.alias_or_name for c in pivot.expressions]
     632
     633    is_bigquery = dialect == "bigquery"
     634    if is_bigquery and any(isinstance(col, exp.Dot) for col in scope.stars):
     635        # Found struct expansion, annotate scope ahead of time
     636        annotator.annotate_scope(scope)
     637
     638    for expression in scope.expression.selects:
     639        tables = []
     640        if isinstance(expression, exp.Star):
     641            tables.extend(scope.selected_sources)
     642            _add_except_columns(expression, tables, except_columns)
     643            _add_replace_columns(expression, tables, replace_columns)
     644            _add_rename_columns(expression, tables, rename_columns)
     645        elif expression.is_star:
     646            if not isinstance(expression, exp.Dot):
     647                tables.append(expression.table)
     648                _add_except_columns(expression.this, tables, except_columns)
     649                _add_replace_columns(expression.this, tables, replace_columns)
     650                _add_rename_columns(expression.this, tables, rename_columns)
     651            elif is_bigquery:
     652                struct_fields = _expand_struct_stars(expression)
     653                if struct_fields:
     654                    new_selections.extend(struct_fields)
     655                    continue
     656
     657        if not tables:
     658            new_selections.append(expression)
     659            continue
     660
     661        for table in tables:
     662            if table not in scope.sources:
     663                raise OptimizeError(f"Unknown table: {table}")
     664
     665            columns = resolver.get_source_columns(table, only_visible=True)
     666            columns = columns or scope.outer_columns
     667
     668            if pseudocolumns:
     669                columns = [name for name in columns if name.upper() not in pseudocolumns]
     670
     671            if not columns or "*" in columns:
     672                return
     673
     674            table_id = id(table)
     675            columns_to_exclude = except_columns.get(table_id) or set()
     676            renamed_columns = rename_columns.get(table_id, {})
     677            replaced_columns = replace_columns.get(table_id, {})
     678
     679            if pivot:
     680                if pivot_output_columns and pivot_exclude_columns:
     681                    pivot_columns = [c for c in columns if c not in pivot_exclude_columns]
     682                    pivot_columns.extend(pivot_output_columns)
     683                else:
     684                    pivot_columns = pivot.alias_column_names
     685
     686                if pivot_columns:
     687                    new_selections.extend(
     688                        alias(exp.column(name, table=pivot.alias), name, copy=False)
     689                        for name in pivot_columns
     690                        if name not in columns_to_exclude
     691                    )
     692                    continue
     693
     694            for name in columns:
     695                if name in columns_to_exclude or name in coalesced_columns:
     696                    continue
     697                if name in using_column_tables and table in using_column_tables[name]:
     698                    coalesced_columns.add(name)
     699                    tables = using_column_tables[name]
     700                    coalesce_args = [exp.column(name, table=table) for table in tables]
     701
     702                    new_selections.append(
     703                        alias(exp.func("coalesce", *coalesce_args), alias=name, copy=False)
     704                    )
     705                else:
     706                    alias_ = renamed_columns.get(name, name)
     707                    selection_expr = replaced_columns.get(name) or exp.column(name, table=table)
     708                    new_selections.append(
     709                        alias(selection_expr, alias_, copy=False)
     710                        if alias_ != name
     711                        else selection_expr
     712                    )
     713
     714    # Ensures we don't overwrite the initial selections with an empty list
     715    if new_selections and isinstance(scope.expression, exp.Select):
     716        scope.expression.set("expressions", new_selections)
     717
     718
     719def _add_except_columns(
     720    expression: exp.Expression, tables, except_columns: t.Dict[int, t.Set[str]]
     721) -> None:
     722    except_ = expression.args.get("except")
     723
     724    if not except_:
     725        return
     726
     727    columns = {e.name for e in except_}
     728
     729    for table in tables:
     730        except_columns[id(table)] = columns
     731
     732
     733def _add_rename_columns(
     734    expression: exp.Expression, tables, rename_columns: t.Dict[int, t.Dict[str, str]]
     735) -> None:
     736    rename = expression.args.get("rename")
     737
     738    if not rename:
     739        return
     740
     741    columns = {e.this.name: e.alias for e in rename}
     742
     743    for table in tables:
     744        rename_columns[id(table)] = columns
     745
     746
     747def _add_replace_columns(
     748    expression: exp.Expression, tables, replace_columns: t.Dict[int, t.Dict[str, exp.Alias]]
     749) -> None:
     750    replace = expression.args.get("replace")
     751
     752    if not replace:
     753        return
     754
     755    columns = {e.alias: e for e in replace}
     756
     757    for table in tables:
     758        replace_columns[id(table)] = columns
     759
     760
     761def qualify_outputs(scope_or_expression: Scope | exp.Expression) -> None:
     762    """Ensure all output columns are aliased"""
     763    if isinstance(scope_or_expression, exp.Expression):
     764        scope = build_scope(scope_or_expression)
     765        if not isinstance(scope, Scope):
     766            return
     767    else:
     768        scope = scope_or_expression
     769
     770    new_selections = []
     771    for i, (selection, aliased_column) in enumerate(
     772        itertools.zip_longest(scope.expression.selects, scope.outer_columns)
     773    ):
     774        if selection is None or isinstance(selection, exp.QueryTransform):
     775            break
     776
     777        if isinstance(selection, exp.Subquery):
     778            if not selection.output_name:
     779                selection.set("alias", exp.TableAlias(this=exp.to_identifier(f"_col_{i}")))
     780        elif not isinstance(selection, exp.Alias) and not selection.is_star:
     781            selection = alias(
     782                selection,
     783                alias=selection.output_name or f"_col_{i}",
     784                copy=False,
     785            )
     786        if aliased_column:
     787            selection.set("alias", exp.to_identifier(aliased_column))
     788
     789        new_selections.append(selection)
     790
     791    if new_selections and isinstance(scope.expression, exp.Select):
     792        scope.expression.set("expressions", new_selections)
     793
     794
     795def quote_identifiers(expression: E, dialect: DialectType = None, identify: bool = True) -> E:
     796    """Makes sure all identifiers that need to be quoted are quoted."""
     797    return expression.transform(
     798        Dialect.get_or_raise(dialect).quote_identifier, identify=identify, copy=False
     799    )  # type: ignore
     800
     801
     802def pushdown_cte_alias_columns(expression: exp.Expression) -> exp.Expression:
     803    """
     804    Pushes down the CTE alias columns into the projection,
     805
     806    This step is useful in Snowflake where the CTE alias columns can be referenced in the HAVING.
     807
     808    Example:
     809        >>> import sqlglot
     810        >>> expression = sqlglot.parse_one("WITH y (c) AS (SELECT SUM(a) FROM ( SELECT 1 a ) AS x HAVING c > 0) SELECT c FROM y")
     811        >>> pushdown_cte_alias_columns(expression).sql()
     812        'WITH y(c) AS (SELECT SUM(a) AS c FROM (SELECT 1 AS a) AS x HAVING c > 0) SELECT c FROM y'
     813
     814    Args:
     815        expression: Expression to pushdown.
     816
     817    Returns:
     818        The expression with the CTE aliases pushed down into the projection.
     819    """
     820    for cte in expression.find_all(exp.CTE):
     821        if cte.alias_column_names:
     822            new_expressions = []
     823            for _alias, projection in zip(cte.alias_column_names, cte.this.expressions):
     824                if isinstance(projection, exp.Alias):
     825                    projection.set("alias", _alias)
     826                else:
     827                    projection = alias(projection, alias=_alias)
     828                new_expressions.append(projection)
     829            cte.this.set("expressions", new_expressions)
     830
     831    return expression
     832
     833
     834class Resolver:
     835    """
     836    Helper for resolving columns.
     837
     838    This is a class so we can lazily load some things and easily share them across functions.
     839    """
     840
     841    def __init__(self, scope: Scope, schema: Schema, infer_schema: bool = True):
     842        self.scope = scope
     843        self.schema = schema
     844        self._source_columns: t.Optional[t.Dict[str, t.Sequence[str]]] = None
     845        self._unambiguous_columns: t.Optional[t.Mapping[str, str]] = None
     846        self._all_columns: t.Optional[t.Set[str]] = None
     847        self._infer_schema = infer_schema
     848        self._get_source_columns_cache: t.Dict[t.Tuple[str, bool], t.Sequence[str]] = {}
     849
     850    def get_table(self, column_name: str) -> t.Optional[exp.Identifier]:
     851        """
     852        Get the table for a column name.
     853
     854        Args:
     855            column_name: The column name to find the table for.
     856        Returns:
     857            The table name if it can be found/inferred.
     858        """
     859        if self._unambiguous_columns is None:
     860            self._unambiguous_columns = self._get_unambiguous_columns(
     861                self._get_all_source_columns()
     862            )
     863
     864        table_name = self._unambiguous_columns.get(column_name)
     865
     866        if not table_name and self._infer_schema:
     867            sources_without_schema = tuple(
     868                source
     869                for source, columns in self._get_all_source_columns().items()
     870                if not columns or "*" in columns
     871            )
     872            if len(sources_without_schema) == 1:
     873                table_name = sources_without_schema[0]
     874
     875        if table_name not in self.scope.selected_sources:
     876            return exp.to_identifier(table_name)
     877
     878        node, _ = self.scope.selected_sources.get(table_name)
     879
     880        if isinstance(node, exp.Query):
     881            while node and node.alias != table_name:
     882                node = node.parent
     883
     884        node_alias = node.args.get("alias")
     885        if node_alias:
     886            return exp.to_identifier(node_alias.this)
     887
     888        return exp.to_identifier(table_name)
     889
     890    @property
     891    def all_columns(self) -> t.Set[str]:
     892        """All available columns of all sources in this scope"""
     893        if self._all_columns is None:
     894            self._all_columns = {
     895                column for columns in self._get_all_source_columns().values() for column in columns
     896            }
     897        return self._all_columns
     898
     899    def get_source_columns(self, name: str, only_visible: bool = False) -> t.Sequence[str]:
     900        """Resolve the source columns for a given source `name`."""
     901        cache_key = (name, only_visible)
     902        if cache_key not in self._get_source_columns_cache:
     903            if name not in self.scope.sources:
     904                raise OptimizeError(f"Unknown table: {name}")
     905
     906            source = self.scope.sources[name]
     907
     908            if isinstance(source, exp.Table):
     909                columns = self.schema.column_names(source, only_visible)
     910            elif isinstance(source, Scope) and isinstance(
     911                source.expression, (exp.Values, exp.Unnest)
     912            ):
     913                columns = source.expression.named_selects
     914
     915                # in bigquery, unnest structs are automatically scoped as tables, so you can
     916                # directly select a struct field in a query.
     917                # this handles the case where the unnest is statically defined.
     918                if self.schema.dialect == "bigquery":
     919                    if source.expression.is_type(exp.DataType.Type.STRUCT):
     920                        for k in source.expression.type.expressions:  # type: ignore
     921                            columns.append(k.name)
     922            elif isinstance(source, Scope) and isinstance(source.expression, exp.SetOperation):
     923                set_op = source.expression
     924
     925                # BigQuery specific set operations modifiers, e.g INNER UNION ALL BY NAME
     926                on_column_list = set_op.args.get("on")
     927
     928                if on_column_list:
     929                    # The resulting columns are the columns in the ON clause:
     930                    # {INNER | LEFT | FULL} UNION ALL BY NAME ON (col1, col2, ...)
     931                    columns = [col.name for col in on_column_list]
     932                elif set_op.side or set_op.kind:
     933                    side = set_op.side
     934                    kind = set_op.kind
     935
     936                    left = set_op.left.named_selects
     937                    right = set_op.right.named_selects
     938
     939                    # We use dict.fromkeys to deduplicate keys and maintain insertion order
     940                    if side == "LEFT":
     941                        columns = left
     942                    elif side == "FULL":
     943                        columns = list(dict.fromkeys(left + right))
     944                    elif kind == "INNER":
     945                        columns = list(dict.fromkeys(left).keys() & dict.fromkeys(right).keys())
     946                else:
     947                    columns = set_op.named_selects
     948            else:
     949                select = seq_get(source.expression.selects, 0)
     950
     951                if isinstance(select, exp.QueryTransform):
     952                    # https://spark.apache.org/docs/3.5.1/sql-ref-syntax-qry-select-transform.html
     953                    schema = select.args.get("schema")
     954                    columns = [c.name for c in schema.expressions] if schema else ["key", "value"]
     955                else:
     956                    columns = source.expression.named_selects
     957
     958            node, _ = self.scope.selected_sources.get(name) or (None, None)
     959            if isinstance(node, Scope):
     960                column_aliases = node.expression.alias_column_names
     961            elif isinstance(node, exp.Expression):
     962                column_aliases = node.alias_column_names
     963            else:
     964                column_aliases = []
     965
     966            if column_aliases:
     967                # If the source's columns are aliased, their aliases shadow the corresponding column names.
     968                # This can be expensive if there are lots of columns, so only do this if column_aliases exist.
     969                columns = [
     970                    alias or name
     971                    for (name, alias) in itertools.zip_longest(columns, column_aliases)
     972                ]
     973
     974            self._get_source_columns_cache[cache_key] = columns
     975
     976        return self._get_source_columns_cache[cache_key]
     977
     978    def _get_all_source_columns(self) -> t.Dict[str, t.Sequence[str]]:
     979        if self._source_columns is None:
     980            self._source_columns = {
     981                source_name: self.get_source_columns(source_name)
     982                for source_name, source in itertools.chain(
     983                    self.scope.selected_sources.items(), self.scope.lateral_sources.items()
     984                )
     985            }
     986        return self._source_columns
     987
     988    def _get_unambiguous_columns(
     989        self, source_columns: t.Dict[str, t.Sequence[str]]
     990    ) -> t.Mapping[str, str]:
     991        """
     992        Find all the unambiguous columns in sources.
     993
     994        Args:
     995            source_columns: Mapping of names to source columns.
     996
     997        Returns:
     998            Mapping of column name to source name.
     999        """
    1000        if not source_columns:
    1001            return {}
    1002
    1003        source_columns_pairs = list(source_columns.items())
    1004
    1005        first_table, first_columns = source_columns_pairs[0]
    1006
    1007        if len(source_columns_pairs) == 1:
    1008            # Performance optimization - avoid copying first_columns if there is only one table.
    1009            return SingleValuedMapping(first_columns, first_table)
    1010
    1011        unambiguous_columns = {col: first_table for col in first_columns}
    1012        all_columns = set(unambiguous_columns)
    1013
    1014        for table, columns in source_columns_pairs[1:]:
    1015            unique = set(columns)
    1016            ambiguous = all_columns.intersection(unique)
    1017            all_columns.update(columns)
    1018
    1019            for column in ambiguous:
    1020                unambiguous_columns.pop(column, None)
    1021            for column in unique.difference(ambiguous):
    1022                unambiguous_columns[column] = table
    1023
    1024        return unambiguous_columns

def qualify_columns( expression: sqlglot.expressions.Expression, schema: Union[Dict, sqlglot.schema.Schema ], expand_alias_refs: bool = True, expand_stars: bool = True, infer_schema: Optional[bool] = None, allow_partial_qualification: bool = False, dialect: Union[str, sqlglot.dialects.Dialect , Type[ sqlglot.dialects.Dialect ], NoneType] = None) -> sqlglot.expressions.Expression: View Source

     20def qualify_columns(
     21    expression: exp.Expression,
     22    schema: t.Dict | Schema,
     23    expand_alias_refs: bool = True,
     24    expand_stars: bool = True,
     25    infer_schema: t.Optional[bool] = None,
     26    allow_partial_qualification: bool = False,
     27    dialect: DialectType = None,
     28) -> exp.Expression:
     29    """
     30    Rewrite sqlglot AST to have fully qualified columns.
     31
     32    Example:
     33        >>> import sqlglot
     34        >>> schema = {"tbl": {"col": "INT"}}
     35        >>> expression = sqlglot.parse_one("SELECT col FROM tbl")
     36        >>> qualify_columns(expression, schema).sql()
     37        'SELECT tbl.col AS col FROM tbl'
     38
     39    Args:
     40        expression: Expression to qualify.
     41        schema: Database schema.
     42        expand_alias_refs: Whether to expand references to aliases.
     43        expand_stars: Whether to expand star queries. This is a necessary step
     44            for most of the optimizer's rules to work; do not set to False unless you
     45            know what you're doing!
     46        infer_schema: Whether to infer the schema if missing.
     47        allow_partial_qualification: Whether to allow partial qualification.
     48
     49    Returns:
     50        The qualified expression.
     51
     52    Notes:
     53        - Currently only handles a single PIVOT or UNPIVOT operator
     54    """
     55    schema = ensure_schema(schema, dialect=dialect)
     56    annotator = TypeAnnotator(schema)
     57    infer_schema = schema.empty if infer_schema is None else infer_schema
     58    dialect = Dialect.get_or_raise(schema.dialect)
     59    pseudocolumns = dialect.PSEUDOCOLUMNS
     60    bigquery = dialect == "bigquery"
     61
     62    for scope in traverse_scope(expression):
     63        scope_expression = scope.expression
     64        is_select = isinstance(scope_expression, exp.Select)
     65
     66        if is_select and scope_expression.args.get("connect"):
     67            # In Snowflake / Oracle queries that have a CONNECT BY clause, one can use the LEVEL
     68            # pseudocolumn, which doesn't belong to a table, so we change it into an identifier
     69            scope_expression.transform(
     70                lambda n: n.this if isinstance(n, exp.Column) and n.name == "LEVEL" else n,
     71                copy=False,
     72            )
     73            scope.clear_cache()
     74
     75        resolver = Resolver(scope, schema, infer_schema=infer_schema)
     76        _pop_table_column_aliases(scope.ctes)
     77        _pop_table_column_aliases(scope.derived_tables)
     78        using_column_tables = _expand_using(scope, resolver)
     79
     80        if (schema.empty or dialect.FORCE_EARLY_ALIAS_REF_EXPANSION) and expand_alias_refs:
     81            _expand_alias_refs(
     82                scope,
     83                resolver,
     84                dialect,
     85                expand_only_groupby=bigquery,
     86            )
     87
     88        _convert_columns_to_dots(scope, resolver)
     89        _qualify_columns(scope, resolver, allow_partial_qualification=allow_partial_qualification)
     90
     91        if not schema.empty and expand_alias_refs:
     92            _expand_alias_refs(scope, resolver, dialect)
     93
     94        if is_select:
     95            if expand_stars:
     96                _expand_stars(
     97                    scope,
     98                    resolver,
     99                    using_column_tables,
    100                    pseudocolumns,
    101                    annotator,
    102                )
    103            qualify_outputs(scope)
    104
    105        _expand_group_by(scope, dialect)
    106
    107        # DISTINCT ON and ORDER BY follow the same rules (tested in DuckDB, Postgres, ClickHouse)
    108        # https://www.postgresql.org/docs/current/sql-select.html#SQL-DISTINCT
    109        _expand_order_by_and_distinct_on(scope, resolver)
    110
    111        if bigquery:
    112            annotator.annotate_scope(scope)
    113
    114    return expression

Rewrite sqlglot AST to have fully qualified columns.

###### Example:

>     >>> import sqlglot
>     >>> schema = {"tbl": {"col": "INT"}}
>     >>> expression = sqlglot.parse_one("SELECT col FROM tbl")
>     >>> qualify_columns(expression, schema).sql()
>     'SELECT tbl.col AS col FROM tbl'

###### Arguments:

- expression: Expression to qualify.
- schema: Database schema.
- expand_alias_refs: Whether to expand references to aliases.
- expand_stars: Whether to expand star queries. This is a necessary step for most of the optimizer's rules to work; do not set to False unless you know what you're doing!
- infer_schema: Whether to infer the schema if missing.
- allow_partial_qualification: Whether to allow partial qualification.

###### Returns:

> The qualified expression.

###### Notes:

> - Currently only handles a single PIVOT or UNPIVOT operator

def validate_qualify_columns(expression: ~E) -> ~E: View Source

    117def validate_qualify_columns(expression: E) -> E:
    118    """Raise an `OptimizeError` if any columns aren't qualified"""
    119    all_unqualified_columns = []
    120    for scope in traverse_scope(expression):
    121        if isinstance(scope.expression, exp.Select):
    122            unqualified_columns = scope.unqualified_columns
    123
    124            if scope.external_columns and not scope.is_correlated_subquery and not scope.pivots:
    125                column = scope.external_columns[0]
    126                for_table = f" for table: '{column.table}'" if column.table else ""
    127                raise OptimizeError(f"Column '{column}' could not be resolved{for_table}")
    128
    129            if unqualified_columns and scope.pivots and scope.pivots[0].unpivot:
    130                # New columns produced by the UNPIVOT can't be qualified, but there may be columns
    131                # under the UNPIVOT's IN clause that can and should be qualified. We recompute
    132                # this list here to ensure those in the former category will be excluded.
    133                unpivot_columns = set(_unpivot_columns(scope.pivots[0]))
    134                unqualified_columns = [c for c in unqualified_columns if c not in unpivot_columns]
    135
    136            all_unqualified_columns.extend(unqualified_columns)
    137
    138    if all_unqualified_columns:
    139        raise OptimizeError(f"Ambiguous columns: {all_unqualified_columns}")
    140
    141    return expression

Raise an `OptimizeError` if any columns aren't qualified

def qualify_outputs( scope_or_expression: sqlglot.optimizer.scope.Scope | sqlglot.expressions.Expression ) -> None: View Source

    762def qualify_outputs(scope_or_expression: Scope | exp.Expression) -> None:
    763    """Ensure all output columns are aliased"""
    764    if isinstance(scope_or_expression, exp.Expression):
    765        scope = build_scope(scope_or_expression)
    766        if not isinstance(scope, Scope):
    767            return
    768    else:
    769        scope = scope_or_expression
    770
    771    new_selections = []
    772    for i, (selection, aliased_column) in enumerate(
    773        itertools.zip_longest(scope.expression.selects, scope.outer_columns)
    774    ):
    775        if selection is None or isinstance(selection, exp.QueryTransform):
    776            break
    777
    778        if isinstance(selection, exp.Subquery):
    779            if not selection.output_name:
    780                selection.set("alias", exp.TableAlias(this=exp.to_identifier(f"_col_{i}")))
    781        elif not isinstance(selection, exp.Alias) and not selection.is_star:
    782            selection = alias(
    783                selection,
    784                alias=selection.output_name or f"_col_{i}",
    785                copy=False,
    786            )
    787        if aliased_column:
    788            selection.set("alias", exp.to_identifier(aliased_column))
    789
    790        new_selections.append(selection)
    791
    792    if new_selections and isinstance(scope.expression, exp.Select):
    793        scope.expression.set("expressions", new_selections)

Ensure all output columns are aliased

def quote_identifiers( expression: ~E, dialect: Union[str, sqlglot.dialects.Dialect , Type[ sqlglot.dialects.Dialect ], NoneType] = None, identify: bool = True) -> ~E: View Source

    796def quote_identifiers(expression: E, dialect: DialectType = None, identify: bool = True) -> E:
    797    """Makes sure all identifiers that need to be quoted are quoted."""
    798    return expression.transform(
    799        Dialect.get_or_raise(dialect).quote_identifier, identify=identify, copy=False
    800    )  # type: ignore

Makes sure all identifiers that need to be quoted are quoted.

def pushdown_cte_alias_columns( expression: sqlglot.expressions.Expression ) -> sqlglot.expressions.Expression: View Source

    803def pushdown_cte_alias_columns(expression: exp.Expression) -> exp.Expression:
    804    """
    805    Pushes down the CTE alias columns into the projection,
    806
    807    This step is useful in Snowflake where the CTE alias columns can be referenced in the HAVING.
    808
    809    Example:
    810        >>> import sqlglot
    811        >>> expression = sqlglot.parse_one("WITH y (c) AS (SELECT SUM(a) FROM ( SELECT 1 a ) AS x HAVING c > 0) SELECT c FROM y")
    812        >>> pushdown_cte_alias_columns(expression).sql()
    813        'WITH y(c) AS (SELECT SUM(a) AS c FROM (SELECT 1 AS a) AS x HAVING c > 0) SELECT c FROM y'
    814
    815    Args:
    816        expression: Expression to pushdown.
    817
    818    Returns:
    819        The expression with the CTE aliases pushed down into the projection.
    820    """
    821    for cte in expression.find_all(exp.CTE):
    822        if cte.alias_column_names:
    823            new_expressions = []
    824            for _alias, projection in zip(cte.alias_column_names, cte.this.expressions):
    825                if isinstance(projection, exp.Alias):
    826                    projection.set("alias", _alias)
    827                else:
    828                    projection = alias(projection, alias=_alias)
    829                new_expressions.append(projection)
    830            cte.this.set("expressions", new_expressions)
    831
    832    return expression

Pushes down the CTE alias columns into the projection,

This step is useful in Snowflake where the CTE alias columns can be referenced in the HAVING.

###### Example:

>     >>> import sqlglot
>     >>> expression = sqlglot.parse_one("WITH y (c) AS (SELECT SUM(a) FROM ( SELECT 1 a ) AS x HAVING c > 0) SELECT c FROM y")
>     >>> pushdown_cte_alias_columns(expression).sql()
>     'WITH y(c) AS (SELECT SUM(a) AS c FROM (SELECT 1 AS a) AS x HAVING c > 0) SELECT c FROM y'

###### Arguments:

- expression: Expression to pushdown.

###### Returns:

> The expression with the CTE aliases pushed down into the projection.

class Resolver: View Source

     835class Resolver:
     836    """
     837    Helper for resolving columns.
     838
     839    This is a class so we can lazily load some things and easily share them across functions.
     840    """
     841
     842    def __init__(self, scope: Scope, schema: Schema, infer_schema: bool = True):
     843        self.scope = scope
     844        self.schema = schema
     845        self._source_columns: t.Optional[t.Dict[str, t.Sequence[str]]] = None
     846        self._unambiguous_columns: t.Optional[t.Mapping[str, str]] = None
     847        self._all_columns: t.Optional[t.Set[str]] = None
     848        self._infer_schema = infer_schema
     849        self._get_source_columns_cache: t.Dict[t.Tuple[str, bool], t.Sequence[str]] = {}
     850
     851    def get_table(self, column_name: str) -> t.Optional[exp.Identifier]:
     852        """
     853        Get the table for a column name.
     854
     855        Args:
     856            column_name: The column name to find the table for.
     857        Returns:
     858            The table name if it can be found/inferred.
     859        """
     860        if self._unambiguous_columns is None:
     861            self._unambiguous_columns = self._get_unambiguous_columns(
     862                self._get_all_source_columns()
     863            )
     864
     865        table_name = self._unambiguous_columns.get(column_name)
     866
     867        if not table_name and self._infer_schema:
     868            sources_without_schema = tuple(
     869                source
     870                for source, columns in self._get_all_source_columns().items()
     871                if not columns or "*" in columns
     872            )
     873            if len(sources_without_schema) == 1:
     874                table_name = sources_without_schema[0]
     875
     876        if table_name not in self.scope.selected_sources:
     877            return exp.to_identifier(table_name)
     878
     879        node, _ = self.scope.selected_sources.get(table_name)
     880
     881        if isinstance(node, exp.Query):
     882            while node and node.alias != table_name:
     883                node = node.parent
     884
     885        node_alias = node.args.get("alias")
     886        if node_alias:
     887            return exp.to_identifier(node_alias.this)
     888
     889        return exp.to_identifier(table_name)
     890
     891    @property
     892    def all_columns(self) -> t.Set[str]:
     893        """All available columns of all sources in this scope"""
     894        if self._all_columns is None:
     895            self._all_columns = {
     896                column for columns in self._get_all_source_columns().values() for column in columns
     897            }
     898        return self._all_columns
     899
     900    def get_source_columns(self, name: str, only_visible: bool = False) -> t.Sequence[str]:
     901        """Resolve the source columns for a given source `name`."""
     902        cache_key = (name, only_visible)
     903        if cache_key not in self._get_source_columns_cache:
     904            if name not in self.scope.sources:
     905                raise OptimizeError(f"Unknown table: {name}")
     906
     907            source = self.scope.sources[name]
     908
     909            if isinstance(source, exp.Table):
     910                columns = self.schema.column_names(source, only_visible)
     911            elif isinstance(source, Scope) and isinstance(
     912                source.expression, (exp.Values, exp.Unnest)
     913            ):
     914                columns = source.expression.named_selects
     915
     916                # in bigquery, unnest structs are automatically scoped as tables, so you can
     917                # directly select a struct field in a query.
     918                # this handles the case where the unnest is statically defined.
     919                if self.schema.dialect == "bigquery":
     920                    if source.expression.is_type(exp.DataType.Type.STRUCT):
     921                        for k in source.expression.type.expressions:  # type: ignore
     922                            columns.append(k.name)
     923            elif isinstance(source, Scope) and isinstance(source.expression, exp.SetOperation):
     924                set_op = source.expression
     925
     926                # BigQuery specific set operations modifiers, e.g INNER UNION ALL BY NAME
     927                on_column_list = set_op.args.get("on")
     928
     929                if on_column_list:
     930                    # The resulting columns are the columns in the ON clause:
     931                    # {INNER | LEFT | FULL} UNION ALL BY NAME ON (col1, col2, ...)
     932                    columns = [col.name for col in on_column_list]
     933                elif set_op.side or set_op.kind:
     934                    side = set_op.side
     935                    kind = set_op.kind
     936
     937                    left = set_op.left.named_selects
     938                    right = set_op.right.named_selects
     939
     940                    # We use dict.fromkeys to deduplicate keys and maintain insertion order
     941                    if side == "LEFT":
     942                        columns = left
     943                    elif side == "FULL":
     944                        columns = list(dict.fromkeys(left + right))
     945                    elif kind == "INNER":
     946                        columns = list(dict.fromkeys(left).keys() & dict.fromkeys(right).keys())
     947                else:
     948                    columns = set_op.named_selects
     949            else:
     950                select = seq_get(source.expression.selects, 0)
     951
     952                if isinstance(select, exp.QueryTransform):
     953                    # https://spark.apache.org/docs/3.5.1/sql-ref-syntax-qry-select-transform.html
     954                    schema = select.args.get("schema")
     955                    columns = [c.name for c in schema.expressions] if schema else ["key", "value"]
     956                else:
     957                    columns = source.expression.named_selects
     958
     959            node, _ = self.scope.selected_sources.get(name) or (None, None)
     960            if isinstance(node, Scope):
     961                column_aliases = node.expression.alias_column_names
     962            elif isinstance(node, exp.Expression):
     963                column_aliases = node.alias_column_names
     964            else:
     965                column_aliases = []
     966
     967            if column_aliases:
     968                # If the source's columns are aliased, their aliases shadow the corresponding column names.
     969                # This can be expensive if there are lots of columns, so only do this if column_aliases exist.
     970                columns = [
     971                    alias or name
     972                    for (name, alias) in itertools.zip_longest(columns, column_aliases)
     973                ]
     974
     975            self._get_source_columns_cache[cache_key] = columns
     976
     977        return self._get_source_columns_cache[cache_key]
     978
     979    def _get_all_source_columns(self) -> t.Dict[str, t.Sequence[str]]:
     980        if self._source_columns is None:
     981            self._source_columns = {
     982                source_name: self.get_source_columns(source_name)
     983                for source_name, source in itertools.chain(
     984                    self.scope.selected_sources.items(), self.scope.lateral_sources.items()
     985                )
     986            }
     987        return self._source_columns
     988
     989    def _get_unambiguous_columns(
     990        self, source_columns: t.Dict[str, t.Sequence[str]]
     991    ) -> t.Mapping[str, str]:
     992        """
     993        Find all the unambiguous columns in sources.
     994
     995        Args:
     996            source_columns: Mapping of names to source columns.
     997
     998        Returns:
     999            Mapping of column name to source name.
    1000        """
    1001        if not source_columns:
    1002            return {}
    1003
    1004        source_columns_pairs = list(source_columns.items())
    1005
    1006        first_table, first_columns = source_columns_pairs[0]
    1007
    1008        if len(source_columns_pairs) == 1:
    1009            # Performance optimization - avoid copying first_columns if there is only one table.
    1010            return SingleValuedMapping(first_columns, first_table)
    1011
    1012        unambiguous_columns = {col: first_table for col in first_columns}
    1013        all_columns = set(unambiguous_columns)
    1014
    1015        for table, columns in source_columns_pairs[1:]:
    1016            unique = set(columns)
    1017            ambiguous = all_columns.intersection(unique)
    1018            all_columns.update(columns)
    1019
    1020            for column in ambiguous:
    1021                unambiguous_columns.pop(column, None)
    1022            for column in unique.difference(ambiguous):
    1023                unambiguous_columns[column] = table
    1024
    1025        return unambiguous_columns

Helper for resolving columns.

This is a class so we can lazily load some things and easily share them across functions.

Resolver( scope: sqlglot.optimizer.scope.Scope, schema: sqlglot.schema.Schema, infer_schema: bool = True) View Source

    842    def __init__(self, scope: Scope, schema: Schema, infer_schema: bool = True):
    843        self.scope = scope
    844        self.schema = schema
    845        self._source_columns: t.Optional[t.Dict[str, t.Sequence[str]]] = None
    846        self._unambiguous_columns: t.Optional[t.Mapping[str, str]] = None
    847        self._all_columns: t.Optional[t.Set[str]] = None
    848        self._infer_schema = infer_schema
    849        self._get_source_columns_cache: t.Dict[t.Tuple[str, bool], t.Sequence[str]] = {}

scope
schema
def get_table(self, column_name: str) -> Optional[ sqlglot.expressions.Identifier ]: View Source

    851    def get_table(self, column_name: str) -> t.Optional[exp.Identifier]:
    852        """
    853        Get the table for a column name.
    854
    855        Args:
    856            column_name: The column name to find the table for.
    857        Returns:
    858            The table name if it can be found/inferred.
    859        """
    860        if self._unambiguous_columns is None:
    861            self._unambiguous_columns = self._get_unambiguous_columns(
    862                self._get_all_source_columns()
    863            )
    864
    865        table_name = self._unambiguous_columns.get(column_name)
    866
    867        if not table_name and self._infer_schema:
    868            sources_without_schema = tuple(
    869                source
    870                for source, columns in self._get_all_source_columns().items()
    871                if not columns or "*" in columns
    872            )
    873            if len(sources_without_schema) == 1:
    874                table_name = sources_without_schema[0]
    875
    876        if table_name not in self.scope.selected_sources:
    877            return exp.to_identifier(table_name)
    878
    879        node, _ = self.scope.selected_sources.get(table_name)
    880
    881        if isinstance(node, exp.Query):
    882            while node and node.alias != table_name:
    883                node = node.parent
    884
    885        node_alias = node.args.get("alias")
    886        if node_alias:
    887            return exp.to_identifier(node_alias.this)
    888
    889        return exp.to_identifier(table_name)

Get the table for a column name.

###### Arguments:

- column_name: The column name to find the table for.

###### Returns:

> The table name if it can be found/inferred.

all_columns: Set[str] View Source

    891    @property
    892    def all_columns(self) -> t.Set[str]:
    893        """All available columns of all sources in this scope"""
    894        if self._all_columns is None:
    895            self._all_columns = {
    896                column for columns in self._get_all_source_columns().values() for column in columns
    897            }
    898        return self._all_columns

All available columns of all sources in this scope

def get_source_columns(self, name: str, only_visible: bool = False) -> Sequence[str]: View Source

    900    def get_source_columns(self, name: str, only_visible: bool = False) -> t.Sequence[str]:
    901        """Resolve the source columns for a given source `name`."""
    902        cache_key = (name, only_visible)
    903        if cache_key not in self._get_source_columns_cache:
    904            if name not in self.scope.sources:
    905                raise OptimizeError(f"Unknown table: {name}")
    906
    907            source = self.scope.sources[name]
    908
    909            if isinstance(source, exp.Table):
    910                columns = self.schema.column_names(source, only_visible)
    911            elif isinstance(source, Scope) and isinstance(
    912                source.expression, (exp.Values, exp.Unnest)
    913            ):
    914                columns = source.expression.named_selects
    915
    916                # in bigquery, unnest structs are automatically scoped as tables, so you can
    917                # directly select a struct field in a query.
    918                # this handles the case where the unnest is statically defined.
    919                if self.schema.dialect == "bigquery":
    920                    if source.expression.is_type(exp.DataType.Type.STRUCT):
    921                        for k in source.expression.type.expressions:  # type: ignore
    922                            columns.append(k.name)
    923            elif isinstance(source, Scope) and isinstance(source.expression, exp.SetOperation):
    924                set_op = source.expression
    925
    926                # BigQuery specific set operations modifiers, e.g INNER UNION ALL BY NAME
    927                on_column_list = set_op.args.get("on")
    928
    929                if on_column_list:
    930                    # The resulting columns are the columns in the ON clause:
    931                    # {INNER | LEFT | FULL} UNION ALL BY NAME ON (col1, col2, ...)
    932                    columns = [col.name for col in on_column_list]
    933                elif set_op.side or set_op.kind:
    934                    side = set_op.side
    935                    kind = set_op.kind
    936
    937                    left = set_op.left.named_selects
    938                    right = set_op.right.named_selects
    939
    940                    # We use dict.fromkeys to deduplicate keys and maintain insertion order
    941                    if side == "LEFT":
    942                        columns = left
    943                    elif side == "FULL":
    944                        columns = list(dict.fromkeys(left + right))
    945                    elif kind == "INNER":
    946                        columns = list(dict.fromkeys(left).keys() & dict.fromkeys(right).keys())
    947                else:
    948                    columns = set_op.named_selects
    949            else:
    950                select = seq_get(source.expression.selects, 0)
    951
    952                if isinstance(select, exp.QueryTransform):
    953                    # https://spark.apache.org/docs/3.5.1/sql-ref-syntax-qry-select-transform.html
    954                    schema = select.args.get("schema")
    955                    columns = [c.name for c in schema.expressions] if schema else ["key", "value"]
    956                else:
    957                    columns = source.expression.named_selects
    958
    959            node, _ = self.scope.selected_sources.get(name) or (None, None)
    960            if isinstance(node, Scope):
    961                column_aliases = node.expression.alias_column_names
    962            elif isinstance(node, exp.Expression):
    963                column_aliases = node.alias_column_names
    964            else:
    965                column_aliases = []
    966
    967            if column_aliases:
    968                # If the source's columns are aliased, their aliases shadow the corresponding column names.
    969                # This can be expensive if there are lots of columns, so only do this if column_aliases exist.
    970                columns = [
    971                    alias or name
    972                    for (name, alias) in itertools.zip_longest(columns, column_aliases)
    973                ]
    974
    975            self._get_source_columns_cache[cache_key] = columns
    976
    977        return self._get_source_columns_cache[cache_key]

Resolve the source columns for a given source `name`.