423 lines
15 KiB
Python
423 lines
15 KiB
Python
from __future__ import annotations
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import json
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import logging
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import typing as t
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from dataclasses import dataclass, field
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from sqlglot import Schema, exp, maybe_parse
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from sqlglot.errors import SqlglotError
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from sqlglot.optimizer import Scope, build_scope, find_all_in_scope, normalize_identifiers, qualify
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from sqlglot.optimizer.scope import ScopeType
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if t.TYPE_CHECKING:
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from sqlglot.dialects.dialect import DialectType
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logger = logging.getLogger("sqlglot")
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@dataclass(frozen=True)
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class Node:
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name: str
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expression: exp.Expression
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source: exp.Expression
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downstream: t.List[Node] = field(default_factory=list)
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source_name: str = ""
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reference_node_name: str = ""
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def walk(self) -> t.Iterator[Node]:
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yield self
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for d in self.downstream:
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yield from d.walk()
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def to_html(self, dialect: DialectType = None, **opts) -> GraphHTML:
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nodes = {}
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edges = []
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for node in self.walk():
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if isinstance(node.expression, exp.Table):
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label = f"FROM {node.expression.this}"
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title = f"<pre>SELECT {node.name} FROM {node.expression.this}</pre>"
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group = 1
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else:
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label = node.expression.sql(pretty=True, dialect=dialect)
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source = node.source.transform(
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lambda n: (
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exp.Tag(this=n, prefix="<b>", postfix="</b>") if n is node.expression else n
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),
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copy=False,
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).sql(pretty=True, dialect=dialect)
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title = f"<pre>{source}</pre>"
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group = 0
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node_id = id(node)
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nodes[node_id] = {
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"id": node_id,
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"label": label,
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"title": title,
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"group": group,
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}
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for d in node.downstream:
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edges.append({"from": node_id, "to": id(d)})
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return GraphHTML(nodes, edges, **opts)
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def lineage(
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column: str | exp.Column,
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sql: str | exp.Expression,
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schema: t.Optional[t.Dict | Schema] = None,
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sources: t.Optional[t.Mapping[str, str | exp.Query]] = None,
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dialect: DialectType = None,
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scope: t.Optional[Scope] = None,
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trim_selects: bool = True,
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**kwargs,
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) -> Node:
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"""Build the lineage graph for a column of a SQL query.
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Args:
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column: The column to build the lineage for.
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sql: The SQL string or expression.
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schema: The schema of tables.
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sources: A mapping of queries which will be used to continue building lineage.
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dialect: The dialect of input SQL.
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scope: A pre-created scope to use instead.
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trim_selects: Whether or not to clean up selects by trimming to only relevant columns.
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**kwargs: Qualification optimizer kwargs.
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Returns:
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A lineage node.
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"""
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expression = maybe_parse(sql, dialect=dialect)
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column = normalize_identifiers.normalize_identifiers(column, dialect=dialect).name
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if sources:
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expression = exp.expand(
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expression,
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{k: t.cast(exp.Query, maybe_parse(v, dialect=dialect)) for k, v in sources.items()},
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dialect=dialect,
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)
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if not scope:
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expression = qualify.qualify(
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expression,
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dialect=dialect,
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schema=schema,
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**{"validate_qualify_columns": False, "identify": False, **kwargs}, # type: ignore
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)
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scope = build_scope(expression)
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if not scope:
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raise SqlglotError("Cannot build lineage, sql must be SELECT")
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if not any(select.alias_or_name == column for select in scope.expression.selects):
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raise SqlglotError(f"Cannot find column '{column}' in query.")
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return to_node(column, scope, dialect, trim_selects=trim_selects)
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def to_node(
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column: str | int,
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scope: Scope,
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dialect: DialectType,
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scope_name: t.Optional[str] = None,
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upstream: t.Optional[Node] = None,
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source_name: t.Optional[str] = None,
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reference_node_name: t.Optional[str] = None,
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trim_selects: bool = True,
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) -> Node:
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# Find the specific select clause that is the source of the column we want.
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# This can either be a specific, named select or a generic `*` clause.
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select = (
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scope.expression.selects[column]
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if isinstance(column, int)
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else next(
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(select for select in scope.expression.selects if select.alias_or_name == column),
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exp.Star() if scope.expression.is_star else scope.expression,
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)
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)
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if isinstance(scope.expression, exp.Subquery):
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for source in scope.subquery_scopes:
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return to_node(
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column,
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scope=source,
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dialect=dialect,
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upstream=upstream,
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source_name=source_name,
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reference_node_name=reference_node_name,
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trim_selects=trim_selects,
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)
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if isinstance(scope.expression, exp.SetOperation):
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name = type(scope.expression).__name__.upper()
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upstream = upstream or Node(name=name, source=scope.expression, expression=select)
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index = (
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column
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if isinstance(column, int)
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else next(
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(
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i
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for i, select in enumerate(scope.expression.selects)
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if select.alias_or_name == column or select.is_star
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),
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-1, # mypy will not allow a None here, but a negative index should never be returned
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)
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)
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if index == -1:
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raise ValueError(f"Could not find {column} in {scope.expression}")
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for s in scope.union_scopes:
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to_node(
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index,
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scope=s,
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dialect=dialect,
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upstream=upstream,
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source_name=source_name,
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reference_node_name=reference_node_name,
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trim_selects=trim_selects,
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)
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return upstream
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if trim_selects and isinstance(scope.expression, exp.Select):
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# For better ergonomics in our node labels, replace the full select with
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# a version that has only the column we care about.
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# "x", SELECT x, y FROM foo
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# => "x", SELECT x FROM foo
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source = t.cast(exp.Expression, scope.expression.select(select, append=False))
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else:
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source = scope.expression
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# Create the node for this step in the lineage chain, and attach it to the previous one.
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node = Node(
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name=f"{scope_name}.{column}" if scope_name else str(column),
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source=source,
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expression=select,
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source_name=source_name or "",
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reference_node_name=reference_node_name or "",
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)
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if upstream:
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upstream.downstream.append(node)
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subquery_scopes = {
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id(subquery_scope.expression): subquery_scope for subquery_scope in scope.subquery_scopes
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}
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for subquery in find_all_in_scope(select, exp.UNWRAPPED_QUERIES):
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subquery_scope = subquery_scopes.get(id(subquery))
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if not subquery_scope:
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logger.warning(f"Unknown subquery scope: {subquery.sql(dialect=dialect)}")
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continue
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for name in subquery.named_selects:
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to_node(
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name,
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scope=subquery_scope,
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dialect=dialect,
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upstream=node,
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trim_selects=trim_selects,
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)
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# if the select is a star add all scope sources as downstreams
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if select.is_star:
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for source in scope.sources.values():
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if isinstance(source, Scope):
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source = source.expression
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node.downstream.append(
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Node(name=select.sql(comments=False), source=source, expression=source)
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)
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# Find all columns that went into creating this one to list their lineage nodes.
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source_columns = set(find_all_in_scope(select, exp.Column))
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# If the source is a UDTF find columns used in the UTDF to generate the table
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if isinstance(source, exp.UDTF):
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source_columns |= set(source.find_all(exp.Column))
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derived_tables = [
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source.expression.parent
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for source in scope.sources.values()
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if isinstance(source, Scope) and source.is_derived_table
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]
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else:
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derived_tables = scope.derived_tables
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source_names = {
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dt.alias: dt.comments[0].split()[1]
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for dt in derived_tables
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if dt.comments and dt.comments[0].startswith("source: ")
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}
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pivots = scope.pivots
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pivot = pivots[0] if len(pivots) == 1 and not pivots[0].unpivot else None
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if pivot:
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# For each aggregation function, the pivot creates a new column for each field in category
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# combined with the aggfunc. So the columns parsed have this order: cat_a_value_sum, cat_a,
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# b_value_sum, b. Because of this step wise manner the aggfunc 'sum(value) as value_sum'
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# belongs to the column indices 0, 2, and the aggfunc 'max(price)' without an alias belongs
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# to the column indices 1, 3. Here, only the columns used in the aggregations are of interest
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# in the lineage, so lookup the pivot column name by index and map that with the columns used
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# in the aggregation.
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#
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# Example: PIVOT (SUM(value) AS value_sum, MAX(price)) FOR category IN ('a' AS cat_a, 'b')
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pivot_columns = pivot.args["columns"]
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pivot_aggs_count = len(pivot.expressions)
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pivot_column_mapping = {}
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for i, agg in enumerate(pivot.expressions):
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agg_cols = list(agg.find_all(exp.Column))
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for col_index in range(i, len(pivot_columns), pivot_aggs_count):
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pivot_column_mapping[pivot_columns[col_index].name] = agg_cols
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for c in source_columns:
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table = c.table
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source = scope.sources.get(table)
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if isinstance(source, Scope):
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reference_node_name = None
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if source.scope_type == ScopeType.DERIVED_TABLE and table not in source_names:
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reference_node_name = table
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elif source.scope_type == ScopeType.CTE:
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selected_node, _ = scope.selected_sources.get(table, (None, None))
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reference_node_name = selected_node.name if selected_node else None
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# The table itself came from a more specific scope. Recurse into that one using the unaliased column name.
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to_node(
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c.name,
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scope=source,
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dialect=dialect,
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scope_name=table,
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upstream=node,
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source_name=source_names.get(table) or source_name,
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reference_node_name=reference_node_name,
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trim_selects=trim_selects,
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)
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elif pivot and pivot.alias_or_name == c.table:
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downstream_columns = []
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column_name = c.name
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if any(column_name == pivot_column.name for pivot_column in pivot_columns):
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downstream_columns.extend(pivot_column_mapping[column_name])
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else:
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# The column is not in the pivot, so it must be an implicit column of the
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# pivoted source -- adapt column to be from the implicit pivoted source.
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downstream_columns.append(exp.column(c.this, table=pivot.parent.this))
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for downstream_column in downstream_columns:
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table = downstream_column.table
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source = scope.sources.get(table)
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if isinstance(source, Scope):
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to_node(
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downstream_column.name,
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scope=source,
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scope_name=table,
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dialect=dialect,
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upstream=node,
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source_name=source_names.get(table) or source_name,
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reference_node_name=reference_node_name,
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trim_selects=trim_selects,
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)
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else:
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source = source or exp.Placeholder()
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node.downstream.append(
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Node(
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name=downstream_column.sql(comments=False),
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source=source,
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expression=source,
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)
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)
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else:
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# The source is not a scope and the column is not in any pivot - we've reached the end
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# of the line. At this point, if a source is not found it means this column's lineage
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# is unknown. This can happen if the definition of a source used in a query is not
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# passed into the `sources` map.
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source = source or exp.Placeholder()
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node.downstream.append(
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Node(name=c.sql(comments=False), source=source, expression=source)
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)
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return node
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class GraphHTML:
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"""Node to HTML generator using vis.js.
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https://visjs.github.io/vis-network/docs/network/
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"""
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def __init__(
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self, nodes: t.Dict, edges: t.List, imports: bool = True, options: t.Optional[t.Dict] = None
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):
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self.imports = imports
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self.options = {
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"height": "500px",
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"width": "100%",
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"layout": {
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"hierarchical": {
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"enabled": True,
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"nodeSpacing": 200,
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"sortMethod": "directed",
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},
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},
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"interaction": {
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"dragNodes": False,
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"selectable": False,
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},
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"physics": {
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"enabled": False,
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},
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"edges": {
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"arrows": "to",
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},
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"nodes": {
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"font": "20px monaco",
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"shape": "box",
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"widthConstraint": {
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"maximum": 300,
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},
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},
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**(options or {}),
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}
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self.nodes = nodes
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self.edges = edges
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def __str__(self):
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nodes = json.dumps(list(self.nodes.values()))
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edges = json.dumps(self.edges)
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options = json.dumps(self.options)
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imports = (
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"""<script type="text/javascript" src="https://unpkg.com/vis-data@latest/peer/umd/vis-data.min.js"></script>
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<script type="text/javascript" src="https://unpkg.com/vis-network@latest/peer/umd/vis-network.min.js"></script>
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<link rel="stylesheet" type="text/css" href="https://unpkg.com/vis-network/styles/vis-network.min.css" />"""
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if self.imports
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else ""
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)
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return f"""<div>
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<div id="sqlglot-lineage"></div>
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{imports}
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<script type="text/javascript">
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var nodes = new vis.DataSet({nodes})
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nodes.forEach(row => row["title"] = new DOMParser().parseFromString(row["title"], "text/html").body.childNodes[0])
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new vis.Network(
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document.getElementById("sqlglot-lineage"),
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{{
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nodes: nodes,
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edges: new vis.DataSet({edges})
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}},
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{options},
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)
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</script>
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</div>"""
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def _repr_html_(self) -> str:
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return self.__str__()
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