Files

218 lines
8.6 KiB
Python

import logging
from dataclasses import dataclass
from sqlalchemy import Engine, text
from tht.config import ExamplesConfig, LshConfig
from tht.execute import require_positive_int
from tht.mschema.models import Annotations, PhysicalSchema
from tht.ports.dwh import DistinctValues
logger = logging.getLogger(__name__)
TEXT_TYPE_PREFIXES = ("text", "varchar", "character", "char")
DEFAULT_DISTINCT_VALUES_LIMIT = 1000
def _quoted_top_values_query(engine: Engine, schema: str, table: str, column: str):
quote = engine.dialect.identifier_preparer.quote
identifier = quote(column)
return text(
f"SELECT {identifier} AS value FROM {quote(schema)}.{quote(table)} "
f"WHERE {identifier} IS NOT NULL GROUP BY {identifier} "
f"ORDER BY count(*) DESC, {identifier} LIMIT :lim"
)
def sample_column(
engine: Engine, schema: str, table: str, column: str, *, limit: int
) -> list[object]:
limit = require_positive_int(limit, name="limit")
query = _quoted_top_values_query(engine, schema, table, column)
with engine.connect() as conn:
rows = conn.execute(query, {"lim": limit}).fetchall()
return [row[0] for row in rows]
def sample_column_rest(
client, schema: str, table: str, column: str, *, limit: int
) -> list[object]:
limit = require_positive_int(limit, name="limit")
rows = client.top_values(schema, table, column, limit)
return [row["value"] for row in rows if row.get("value") is not None]
def distinct_values(
engine: Engine,
schema: str,
table: str,
column: str,
*,
max_values: int = DEFAULT_DISTINCT_VALUES_LIMIT,
) -> DistinctValues:
max_values = require_positive_int(max_values, name="max_values")
values = sample_column(engine, schema, table, column, limit=max_values + 1)
return DistinctValues(values=values[:max_values], truncated=len(values) > max_values)
def distinct_values_rest(
client,
schema: str,
table: str,
column: str,
*,
max_values: int = DEFAULT_DISTINCT_VALUES_LIMIT,
) -> DistinctValues:
max_values = require_positive_int(max_values, name="max_values")
values = sample_column_rest(client, schema, table, column, limit=max_values + 1)
return DistinctValues(values=values[:max_values], truncated=len(values) > max_values)
def is_text_type(pg_type: str) -> bool:
return pg_type.lower().startswith(TEXT_TYPE_PREFIXES)
def add_examples(engine: Engine, physical: PhysicalSchema, cfg: ExamplesConfig) -> None:
"""Campiona i valori distinti piu' frequenti delle colonne testuali (in-place)."""
schema = physical.db_schema
with engine.connect() as conn:
for table_name, table in physical.tables.items():
for column_name, column in table.columns.items():
if not is_text_type(column.type):
continue
q = text(f'''
SELECT "{column_name}" FROM (
SELECT "{column_name}", count(*) AS _freq
FROM "{schema}"."{table_name}"
WHERE "{column_name}" IS NOT NULL AND length("{column_name}") > 0
GROUP BY "{column_name}"
ORDER BY _freq DESC
LIMIT :lim
) AS sub
''')
try:
rows = conn.execute(q, {"lim": cfg.max_per_column}).fetchall()
except Exception as e: # noqa: BLE001 - skip any unreadable DWH column
logger.warning("Campionamento saltato per %s.%s: %s", table_name, column_name, e)
continue
column.examples = [str(r[0]) for r in rows]
def add_examples_rest(client, physical: PhysicalSchema, cfg: ExamplesConfig) -> None:
"""Variante REST di add_examples: valori più frequenti via rpc `top_values`."""
schema = physical.db_schema
for table_name, table in physical.tables.items():
for column_name, column in table.columns.items():
if not is_text_type(column.type):
continue
rows = client.top_values(schema, table_name, column_name, cfg.max_per_column)
column.examples = [str(r["value"]) for r in rows if r["value"] not in (None, "")]
@dataclass
class SkippedColumn:
table: str
column: str
reason: str
@dataclass
class TruncatedColumn:
table: str
column: str
indexed: int # quanti valori (i più frequenti) sono stati indicizzati
def unique_values_for_lsh(
engine: Engine,
physical: PhysicalSchema,
cfg: LshConfig,
annotations: Annotations | None = None,
) -> tuple[dict[str, dict[str, list[str]]], list[SkippedColumn], list[TruncatedColumn]]:
"""Valori delle colonne testuali *eligible* per l'indice LSH.
Indicizza solo colonne con eligibilità effettiva True (le `wide_text` sono escluse:
vedi principio di column eligibility). Estrae i valori distinti *più frequenti*
(ORDER BY frequenza); se superano `max_values_per_column` la colonna è troncata e
segnalata (mai tagliata in silenzio).
"""
from tht.mschema.eligibility import effective_eligibility
annotations = annotations or Annotations()
schema = physical.db_schema
values: dict[str, dict[str, list[str]]] = {}
skipped: list[SkippedColumn] = []
truncated: list[TruncatedColumn] = []
with engine.connect() as conn:
for table_name, table in physical.tables.items():
table_ann = annotations.tables.get(table_name)
for column_name, column in table.columns.items():
if not is_text_type(column.type):
continue
ann_col = table_ann.columns.get(column_name) if table_ann else None
if not effective_eligibility(column, ann_col)[0]:
continue
q = text(f'''
SELECT "{column_name}" FROM (
SELECT "{column_name}", count(*) AS _freq
FROM "{schema}"."{table_name}"
WHERE "{column_name}" IS NOT NULL AND length("{column_name}") > 0
GROUP BY "{column_name}"
ORDER BY _freq DESC, "{column_name}"
LIMIT :lim
) AS sub
''')
try:
rows = conn.execute(q, {"lim": cfg.max_values_per_column}).fetchall()
except Exception as e: # noqa: BLE001 - skip any unreadable DWH column
skipped.append(SkippedColumn(table_name, column_name, f"errore: {e}"))
continue
vals = [str(r[0]) for r in rows]
if not vals:
continue
values.setdefault(table_name, {})[column_name] = vals
if len(vals) >= cfg.max_values_per_column:
truncated.append(TruncatedColumn(table_name, column_name, len(vals)))
return values, skipped, truncated
def unique_values_for_lsh_rest(
client,
physical: PhysicalSchema,
cfg: LshConfig,
annotations: Annotations | None = None,
) -> tuple[dict[str, dict[str, list[str]]], list[SkippedColumn], list[TruncatedColumn]]:
"""Variante REST di unique_values_for_lsh: valori più frequenti via rpc `top_values`.
Stessa logica di eligibility e di segnalazione del troncamento del transport diretto.
"""
from tht.mschema.eligibility import effective_eligibility
annotations = annotations or Annotations()
schema = physical.db_schema
values: dict[str, dict[str, list[str]]] = {}
skipped: list[SkippedColumn] = []
truncated: list[TruncatedColumn] = []
for table_name, table in physical.tables.items():
table_ann = annotations.tables.get(table_name)
for column_name, column in table.columns.items():
if not is_text_type(column.type):
continue
ann_col = table_ann.columns.get(column_name) if table_ann else None
if not effective_eligibility(column, ann_col)[0]:
continue
try:
rows = client.top_values(
schema, table_name, column_name, cfg.max_values_per_column
)
except Exception as e: # noqa: BLE001 - skip any unreadable REST column
skipped.append(SkippedColumn(table_name, column_name, f"errore: {e}"))
continue
vals = [str(r["value"]) for r in rows if r["value"] not in (None, "")]
if not vals:
continue
values.setdefault(table_name, {})[column_name] = vals
if len(vals) >= cfg.max_values_per_column:
truncated.append(TruncatedColumn(table_name, column_name, len(vals)))
return values, skipped, truncated