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feat(pii): masking for Cassandra & Neo4j (graph nodes + live property read) + MongoDB payload/free-text

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mo
2026-06-27 21:10:16 +00:00
parent e2ac114863
commit cdc8aa4bf7
2 changed files with 40 additions and 6 deletions
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api/dataflow.py
+12 -4
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@@ -34,9 +34,11 @@ NODES: list[dict[str, Any]] = [
{"id": "generator", "label": "Data Generator", "sub": "Airflow DAGs", "kind": "generator", "x": 9, "y": 34},
{"id": "hdfs", "label": "Hadoop HDFS", "sub": "historical_sales", "kind": "hadoop", "x": 9, "y": 80},
# col 1 — source databases
{"id": "postgres", "label": "PostgreSQL", "sub": "sales_orders", "kind": "source", "x": 28, "y": 16},
{"id": "mysql", "label": "MySQL", "sub": "employee_events", "kind": "source", "x": 28, "y": 38},
{"id": "mongodb", "label": "MongoDB", "sub": "events", "kind": "source", "x": 28, "y": 60},
{"id": "postgres", "label": "PostgreSQL", "sub": "sales_orders", "kind": "source", "x": 28, "y": 12},
{"id": "mysql", "label": "MySQL", "sub": "employee_events", "kind": "source", "x": 28, "y": 28},
{"id": "mongodb", "label": "MongoDB", "sub": "events", "kind": "source", "x": 28, "y": 44},
{"id": "cassandra", "label": "Cassandra", "sub": "device_metrics", "kind": "source", "x": 28, "y": 60},
{"id": "neo4j", "label": "Neo4j", "sub": "Product · Supplier graph", "kind": "source", "x": 28, "y": 76},
# col 2 — change data capture
{"id": "kafka", "label": "Kafka · Debezium", "sub": "CDC topics", "kind": "stream", "x": 47, "y": 24},
{"id": "spark", "label": "Apache Spark", "sub": "Streaming · batch", "kind": "compute", "x": 62, "y": 38,
@@ -57,9 +59,13 @@ EDGES: list[dict[str, Any]] = [
{"from": "generator", "to": "postgres", "kind": "generate", "movement_id": "gen_postgres"},
{"from": "generator", "to": "mysql", "kind": "generate", "movement_id": "gen_mysql"},
{"from": "generator", "to": "mongodb", "kind": "generate", "movement_id": "gen_mongodb"},
{"from": "generator", "to": "cassandra", "kind": "generate"},
{"from": "generator", "to": "neo4j", "kind": "generate"},
{"from": "postgres", "to": "kafka", "kind": "cdc"},
{"from": "mysql", "to": "kafka", "kind": "cdc"},
{"from": "mongodb", "to": "kafka", "kind": "cdc"},
{"from": "cassandra", "to": "kafka", "kind": "cdc"},
{"from": "neo4j", "to": "kafka", "kind": "cdc"},
{"from": "kafka", "to": "spark", "kind": "stream"},
{"from": "spark", "to": "iceberg_curated", "kind": "movement", "movement_id": "spark_to_curated"},
{"from": "spark", "to": "s3_cdc", "kind": "movement", "movement_id": "spark_to_s3"},
@@ -77,6 +83,8 @@ EDGES: list[dict[str, Any]] = [
{"from": "postgres", "to": "openmetadata", "kind": "catalog"},
{"from": "mysql", "to": "openmetadata", "kind": "catalog"},
{"from": "mongodb", "to": "openmetadata", "kind": "catalog"},
{"from": "cassandra", "to": "openmetadata", "kind": "catalog"},
{"from": "neo4j", "to": "openmetadata", "kind": "catalog"},
{"from": "trino", "to": "openmetadata", "kind": "catalog"},
]
@@ -165,7 +173,7 @@ async def _build() -> dict[str, Any]:
used = spark.get("cores_used") or 0
metric = f"{spark.get('alive_workers', 0)} workers · {used}/{cores} cores · {apps} apps"
node["level"] = "ok" if spark.get("ui_ok") and (spark.get("status") or "").upper() == "ALIVE" else "warn"
elif n["id"] in ("postgres", "mysql", "mongodb"):
elif n["id"] in ("postgres", "mysql", "mongodb", "cassandra", "neo4j"):
metric = f"{cdc.get('by_source', {}).get(n['id'], 0)} CDC/15m"
elif n["id"] == "iceberg_hadoop":
c = _iceberg_hadoop_count()
api/pii_catalog.py
+28 -2
View File
@@ -62,6 +62,14 @@ DATASETS = [
"table": "iceberg.hadoop.historical_sales_hdfs", "table_name": "historical_sales_hdfs", "catalog": "iceberg",
"schema": "hadoop",
"om_fqn": "atc_trino.iceberg.hadoop.historical_sales_hdfs"},
{"key": "cassandra", "node_id": "cassandra", "label": "Cassandra device_metrics",
"table": "cassandra_telemetry.telemetry.device_metrics", "table_name": "device_metrics",
"catalog": "cassandra_telemetry", "schema": "telemetry",
"om_fqn": "atc_trino.cassandra_telemetry.telemetry.device_metrics",
"native": {"engine": "cassandra"}},
{"key": "neo4j", "node_id": "neo4j", "label": "Neo4j Product/Supplier graph",
"table": "neo4j_graph", "table_name": "graph", "catalog": "neo4j",
"native": {"engine": "neo4j"}},
]
KEY_BY_NODE = {ds["node_id"]: ds["key"] for ds in DATASETS}
@@ -112,7 +120,8 @@ PII_RULES: list[tuple[str, str]] = [
(r"address|street|city|zip|postal|postcode", "ADDRESS"),
(r"dob|birth|date_of_birth", "DOB"),
(r"ip_addr|ip_address|_ip$|customer_ip|client_ip", "IP"),
(r"customer_id|client_id|user_id|account_id|member_id|device_id|subscriber_id|employee_id|guest_id|person_id", "IDENTIFIER"),
(r"customer_id|client_id|user_id|account_id|member_id|device_id|subscriber_id|employee_id|guest_id|person_id|supplier_id", "IDENTIFIER"),
(r"^payload$|payload|^notes$|^note$|free_text|freeform|raw_json|description", "FREEFORM"),
]
_cache: dict[str, Any] = {"ts": 0.0, "data": None}
@@ -182,13 +191,30 @@ def _trino_columns(catalog: str, schema: str | None, table_name: str) -> list[st
return []
def _neo4j_property_keys() -> list[str]:
"""Property keys across the Neo4j graph, used as the 'columns' for PII tagging."""
try:
from neo4j import GraphDatabase
uri = os.getenv("NEO4J_URI", f"bolt://{os.getenv('DB_HOST', '10.0.21.51')}:7687")
drv = GraphDatabase.driver(uri, auth=(os.getenv("NEO4J_USER", "neo4j"), os.getenv("NEO4J_PASSWORD", "testpwd")))
with drv.session() as s:
keys = [r["propertyKey"] for r in s.run("CALL db.propertyKeys() YIELD propertyKey RETURN propertyKey")]
drv.close()
return keys
except Exception:
return []
def _build() -> dict[str, Any]:
datasets_out = []
total_pii = 0
total_masked = 0
om_used = False
for ds in DATASETS:
cols = _trino_columns(ds["catalog"], ds.get("schema"), ds["table_name"])
if (ds.get("native") or {}).get("engine") == "neo4j":
cols = _neo4j_property_keys()
else:
cols = _trino_columns(ds["catalog"], ds.get("schema"), ds["table_name"])
om_tags = _om_column_tags(ds["om_fqn"]) if ds.get("om_fqn") else {}
if om_tags:
om_used = True