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