sqlglot.optimizer.qualify_columns API documentation

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# sqlglot.optimizer.qualify_columns

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

     99def validate_qualify_columns(expression: E) -> E:
    100    """Raise an `OptimizeError` if any columns aren't qualified"""
    101    all_unqualified_columns = []
    102    for scope in traverse_scope(expression):
    103        if isinstance(scope.expression, exp.Select):
    104            unqualified_columns = scope.unqualified_columns
    105
    106            if scope.external_columns and not scope.is_correlated_subquery and not scope.pivots:
    107                column = scope.external_columns[0]
    108                for_table = f" for table: '{column.table}'" if column.table else ""
    109                raise OptimizeError(f"Column '{column}' could not be resolved{for_table}")
    110
    111            if unqualified_columns and scope.pivots and scope.pivots[0].unpivot:
    112                # New columns produced by the UNPIVOT can't be qualified, but there may be columns
    113                # under the UNPIVOT's IN clause that can and should be qualified. We recompute
    114                # this list here to ensure those in the former category will be excluded.
    115                unpivot_columns = set(_unpivot_columns(scope.pivots[0]))
    116                unqualified_columns = [c for c in unqualified_columns if c not in unpivot_columns]
    117
    118            all_unqualified_columns.extend(unqualified_columns)
    119
    120    if all_unqualified_columns:
    121        raise OptimizeError(f"Ambiguous columns: {all_unqualified_columns}")
    122
    123    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

    700def qualify_outputs(scope_or_expression: Scope | exp.Expression) -> None:
    701    """Ensure all output columns are aliased"""
    702    if isinstance(scope_or_expression, exp.Expression):
    703        scope = build_scope(scope_or_expression)
    704        if not isinstance(scope, Scope):
    705            return
    706    else:
    707        scope = scope_or_expression
    708
    709    new_selections = []
    710    for i, (selection, aliased_column) in enumerate(
    711        itertools.zip_longest(scope.expression.selects, scope.outer_columns)
    712    ):
    713        if selection is None:
    714            break
    715
    716        if isinstance(selection, exp.Subquery):
    717            if not selection.output_name:
    718                selection.set("alias", exp.TableAlias(this=exp.to_identifier(f"_col_{i}")))
    719        elif not isinstance(selection, exp.Alias) and not selection.is_star:
    720            selection = alias(
    721                selection,
    722                alias=selection.output_name or f"_col_{i}",
    723                copy=False,
    724            )
    725        if aliased_column:
    726            selection.set("alias", exp.to_identifier(aliased_column))
    727
    728        new_selections.append(selection)
    729
    730    if isinstance(scope.expression, exp.Select):
    731        scope.expression.set("expressions", new_selections)

Ensure all output columns are aliased

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

    734def quote_identifiers(expression: E, dialect: DialectType = None, identify: bool = True) -> E:
    735    """Makes sure all identifiers that need to be quoted are quoted."""
    736    return expression.transform(
    737        Dialect.get_or_raise(dialect).quote_identifier, identify=identify, copy=False
    738    )  # 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

    741def pushdown_cte_alias_columns(expression: exp.Expression) -> exp.Expression:
    742    """
    743    Pushes down the CTE alias columns into the projection,
    744
    745    This step is useful in Snowflake where the CTE alias columns can be referenced in the HAVING.
    746
    747    Example:
    748        >>> import sqlglot
    749        >>> expression = sqlglot.parse_one("WITH y (c) AS (SELECT SUM(a) FROM ( SELECT 1 a ) AS x HAVING c > 0) SELECT c FROM y")
    750        >>> pushdown_cte_alias_columns(expression).sql()
    751        'WITH y(c) AS (SELECT SUM(a) AS c FROM (SELECT 1 AS a) AS x HAVING c > 0) SELECT c FROM y'
    752
    753    Args:
    754        expression: Expression to pushdown.
    755
    756    Returns:
    757        The expression with the CTE aliases pushed down into the projection.
    758    """
    759    for cte in expression.find_all(exp.CTE):
    760        if cte.alias_column_names:
    761            new_expressions = []
    762            for _alias, projection in zip(cte.alias_column_names, cte.this.expressions):
    763                if isinstance(projection, exp.Alias):
    764                    projection.set("alias", _alias)
    765                else:
    766                    projection = alias(projection, alias=_alias)
    767                new_expressions.append(projection)
    768            cte.this.set("expressions", new_expressions)
    769
    770    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

    773class Resolver:
    774    """
    775    Helper for resolving columns.
    776
    777    This is a class so we can lazily load some things and easily share them across functions.
    778    """
    779
    780    def __init__(self, scope: Scope, schema: Schema, infer_schema: bool = True):
    781        self.scope = scope
    782        self.schema = schema
    783        self._source_columns: t.Optional[t.Dict[str, t.Sequence[str]]] = None
    784        self._unambiguous_columns: t.Optional[t.Mapping[str, str]] = None
    785        self._all_columns: t.Optional[t.Set[str]] = None
    786        self._infer_schema = infer_schema
    787        self._get_source_columns_cache: t.Dict[t.Tuple[str, bool], t.Sequence[str]] = {}
    788
    789    def get_table(self, column_name: str) -> t.Optional[exp.Identifier]:
    790        """
    791        Get the table for a column name.
    792
    793        Args:
    794            column_name: The column name to find the table for.
    795        Returns:
    796            The table name if it can be found/inferred.
    797        """
    798        if self._unambiguous_columns is None:
    799            self._unambiguous_columns = self._get_unambiguous_columns(
    800                self._get_all_source_columns()
    801            )
    802
    803        table_name = self._unambiguous_columns.get(column_name)
    804
    805        if not table_name and self._infer_schema:
    806            sources_without_schema = tuple(
    807                source
    808                for source, columns in self._get_all_source_columns().items()
    809                if not columns or "*" in columns
    810            )
    811            if len(sources_without_schema) == 1:
    812                table_name = sources_without_schema[0]
    813
    814        if table_name not in self.scope.selected_sources:
    815            return exp.to_identifier(table_name)
    816
    817        node, _ = self.scope.selected_sources.get(table_name)
    818
    819        if isinstance(node, exp.Query):
    820            while node and node.alias != table_name:
    821                node = node.parent
    822
    823        node_alias = node.args.get("alias")
    824        if node_alias:
    825            return exp.to_identifier(node_alias.this)
    826
    827        return exp.to_identifier(table_name)
    828
    829    @property
    830    def all_columns(self) -> t.Set[str]:
    831        """All available columns of all sources in this scope"""
    832        if self._all_columns is None:
    833            self._all_columns = {
    834                column for columns in self._get_all_source_columns().values() for column in columns
    835            }
    836        return self._all_columns
    837
    838    def get_source_columns(self, name: str, only_visible: bool = False) -> t.Sequence[str]:
    839        """Resolve the source columns for a given source `name`."""
    840        cache_key = (name, only_visible)
    841        if cache_key not in self._get_source_columns_cache:
    842            if name not in self.scope.sources:
    843                raise OptimizeError(f"Unknown table: {name}")
    844
    845            source = self.scope.sources[name]
    846
    847            if isinstance(source, exp.Table):
    848                columns = self.schema.column_names(source, only_visible)
    849            elif isinstance(source, Scope) and isinstance(
    850                source.expression, (exp.Values, exp.Unnest)
    851            ):
    852                columns = source.expression.named_selects
    853
    854                # in bigquery, unnest structs are automatically scoped as tables, so you can
    855                # directly select a struct field in a query.
    856                # this handles the case where the unnest is statically defined.
    857                if self.schema.dialect == "bigquery":
    858                    if source.expression.is_type(exp.DataType.Type.STRUCT):
    859                        for k in source.expression.type.expressions:  # type: ignore
    860                            columns.append(k.name)
    861            else:
    862                columns = source.expression.named_selects
    863
    864            node, _ = self.scope.selected_sources.get(name) or (None, None)
    865            if isinstance(node, Scope):
    866                column_aliases = node.expression.alias_column_names
    867            elif isinstance(node, exp.Expression):
    868                column_aliases = node.alias_column_names
    869            else:
    870                column_aliases = []
    871
    872            if column_aliases:
    873                # If the source's columns are aliased, their aliases shadow the corresponding column names.
    874                # This can be expensive if there are lots of columns, so only do this if column_aliases exist.
    875                columns = [
    876                    alias or name
    877                    for (name, alias) in itertools.zip_longest(columns, column_aliases)
    878                ]
    879
    880            self._get_source_columns_cache[cache_key] = columns
    881
    882        return self._get_source_columns_cache[cache_key]
    883
    884    def _get_all_source_columns(self) -> t.Dict[str, t.Sequence[str]]:
    885        if self._source_columns is None:
    886            self._source_columns = {
    887                source_name: self.get_source_columns(source_name)
    888                for source_name, source in itertools.chain(
    889                    self.scope.selected_sources.items(), self.scope.lateral_sources.items()
    890                )
    891            }
    892        return self._source_columns
    893
    894    def _get_unambiguous_columns(
    895        self, source_columns: t.Dict[str, t.Sequence[str]]
    896    ) -> t.Mapping[str, str]:
    897        """
    898        Find all the unambiguous columns in sources.
    899
    900        Args:
    901            source_columns: Mapping of names to source columns.
    902
    903        Returns:
    904            Mapping of column name to source name.
    905        """
    906        if not source_columns:
    907            return {}
    908
    909        source_columns_pairs = list(source_columns.items())
    910
    911        first_table, first_columns = source_columns_pairs[0]
    912
    913        if len(source_columns_pairs) == 1:
    914            # Performance optimization - avoid copying first_columns if there is only one table.
    915            return SingleValuedMapping(first_columns, first_table)
    916
    917        unambiguous_columns = {col: first_table for col in first_columns}
    918        all_columns = set(unambiguous_columns)
    919
    920        for table, columns in source_columns_pairs[1:]:
    921            unique = set(columns)
    922            ambiguous = all_columns.intersection(unique)
    923            all_columns.update(columns)
    924
    925            for column in ambiguous:
    926                unambiguous_columns.pop(column, None)
    927            for column in unique.difference(ambiguous):
    928                unambiguous_columns[column] = table
    929
    930        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

    780    def __init__(self, scope: Scope, schema: Schema, infer_schema: bool = True):
    781        self.scope = scope
    782        self.schema = schema
    783        self._source_columns: t.Optional[t.Dict[str, t.Sequence[str]]] = None
    784        self._unambiguous_columns: t.Optional[t.Mapping[str, str]] = None
    785        self._all_columns: t.Optional[t.Set[str]] = None
    786        self._infer_schema = infer_schema
    787        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

    789    def get_table(self, column_name: str) -> t.Optional[exp.Identifier]:
    790        """
    791        Get the table for a column name.
    792
    793        Args:
    794            column_name: The column name to find the table for.
    795        Returns:
    796            The table name if it can be found/inferred.
    797        """
    798        if self._unambiguous_columns is None:
    799            self._unambiguous_columns = self._get_unambiguous_columns(
    800                self._get_all_source_columns()
    801            )
    802
    803        table_name = self._unambiguous_columns.get(column_name)
    804
    805        if not table_name and self._infer_schema:
    806            sources_without_schema = tuple(
    807                source
    808                for source, columns in self._get_all_source_columns().items()
    809                if not columns or "*" in columns
    810            )
    811            if len(sources_without_schema) == 1:
    812                table_name = sources_without_schema[0]
    813
    814        if table_name not in self.scope.selected_sources:
    815            return exp.to_identifier(table_name)
    816
    817        node, _ = self.scope.selected_sources.get(table_name)
    818
    819        if isinstance(node, exp.Query):
    820            while node and node.alias != table_name:
    821                node = node.parent
    822
    823        node_alias = node.args.get("alias")
    824        if node_alias:
    825            return exp.to_identifier(node_alias.this)
    826
    827        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

    829    @property
    830    def all_columns(self) -> t.Set[str]:
    831        """All available columns of all sources in this scope"""
    832        if self._all_columns is None:
    833            self._all_columns = {
    834                column for columns in self._get_all_source_columns().values() for column in columns
    835            }
    836        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

    838    def get_source_columns(self, name: str, only_visible: bool = False) -> t.Sequence[str]:
    839        """Resolve the source columns for a given source `name`."""
    840        cache_key = (name, only_visible)
    841        if cache_key not in self._get_source_columns_cache:
    842            if name not in self.scope.sources:
    843                raise OptimizeError(f"Unknown table: {name}")
    844
    845            source = self.scope.sources[name]
    846
    847            if isinstance(source, exp.Table):
    848                columns = self.schema.column_names(source, only_visible)
    849            elif isinstance(source, Scope) and isinstance(
    850                source.expression, (exp.Values, exp.Unnest)
    851            ):
    852                columns = source.expression.named_selects
    853
    854                # in bigquery, unnest structs are automatically scoped as tables, so you can
    855                # directly select a struct field in a query.
    856                # this handles the case where the unnest is statically defined.
    857                if self.schema.dialect == "bigquery":
    858                    if source.expression.is_type(exp.DataType.Type.STRUCT):
    859                        for k in source.expression.type.expressions:  # type: ignore
    860                            columns.append(k.name)
    861            else:
    862                columns = source.expression.named_selects
    863
    864            node, _ = self.scope.selected_sources.get(name) or (None, None)
    865            if isinstance(node, Scope):
    866                column_aliases = node.expression.alias_column_names
    867            elif isinstance(node, exp.Expression):
    868                column_aliases = node.alias_column_names
    869            else:
    870                column_aliases = []
    871
    872            if column_aliases:
    873                # If the source's columns are aliased, their aliases shadow the corresponding column names.
    874                # This can be expensive if there are lots of columns, so only do this if column_aliases exist.
    875                columns = [
    876                    alias or name
    877                    for (name, alias) in itertools.zip_longest(columns, column_aliases)
    878                ]
    879
    880            self._get_source_columns_cache[cache_key] = columns
    881
    882        return self._get_source_columns_cache[cache_key]

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